start small, think big · children with growth disorders like zita – from referral, diagnostic...

Start Small, Think Big Growth monitoring, genetic

analysis, treatment and

quality of life in children

with growth disorders

Susanne E. Stalman

ISBN 978 94 6169 962 6

© 2016 Susanne Stalman, Amsterdam

All rights reserved

Cover design: Marieke Veere Vonk en Susanne Stalman

Drawings: Marieke Veere Vonk (www.mariekeveere.com)

Tekstcorrectie: Margreet de Broekert

Electronic version: http://www.epubs.nl/?epub=s.stalman

Layout and printing: Optima Grafische Communicatie, Rotterdam, The Netherlands

Publication of this thesis was financially supported by: Tergooi Hospitals and AMR

Medical Research

The sponsors, who are all gratefully acknowledged, had no involvement in any stage of

the study design, data collection, data-analysis, interpretation of the data or the deci-

sion to publish study results

Start Small, Think Big Growth monitoring, genetic analysis, treatment and

quality of life in children with growth disorders

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor

aan de Universiteit van Amsterdam

op gezag van de Rector Magnificus

prof. dr. ir. K.I.J. Maex

ten overstaan van een door het College voor Promoties ingestelde commissie,

in het openbaar te verdedigen in de Agnietenkapel

op dinsdag 8 november 2016, te 12:00 uur

door Susanne Elisabeth Stalman

geboren te Amsterdam

Promotiecommissie

Promotor prof. dr. R.C.M. Hennekam

Universiteit van Amsterdam

Co-promotores dr. F.B. Plötz

Tergooiziekenhuizen

dr. G.A. Kamp

Tergooiziekenhuizen

Overige leden prof. dr. M.A. Grootenhuis


prof. dr. H.S.A. Heymans


prof. dr. M.M.A.M. Mannens


dr. A.S.P. van Trotsenburg


prof. dr. A.C.S. Hokken-Koelega

Erasmus Universiteit Rotterdam

dr. W. Oostdijk

Universiteit Leiden

dr. M.M. van Weissenbruch

Vrije Universiteit Amsterdam

Faculteit der Geneeskunde

Table of contents

Chapter 1 General Introduction and Thesis Outline 9

Part 1 Growth monitoring 19

Chapter 2 Application of the Dutch, Finnish and British Screening

Guidelines in a Cohort of Children with Growth Failure.

Hormone Research in Paediatrics 2015;84(6):376-82

21

Chapter 3 Growth Failure in Adolescents: Etiology, the Role of Pubertal

Timing and Most Useful Criteria for Diagnostic Workup.

Journal of Pediatric Endocrinology and Metabolism 2016;29(4):465-73

35

Chapter 4 Diagnostic Work-up and Follow-up in Children with Tall

Stature: A Simplified Algorithm for Clinical Practice.

Journal of Clinical Research in Pediatric Endocrinology 2015;7(4):260-7

53

Part II Genetic Analysis 73

Chapter 5 Genetic Analysis in Small for Gestational Age Newborns

[Submitted]

Part III Treatment 103

Chapter 6 Positive Effect of Growth Hormone Treatment in Maternal

Uniparental Disomy Chromosome 14.

Clinical Endocrinology (Oxf ). 2015;83(5):671-6

105

Part IV Quality of Life 121

Chapter 7 Psychometric Performance of the Quality of Life in Short Stature

Youth (QoLISSY) Questionnaire in the Netherlands.

European Journal of Pediatrics 2016;175(3):347-54

123

Chapter 8 Summary and General Discussion 141

Chapter 9 Samenvatting (Summary, in Dutch) 157

Appendices Curriculum Vitae 169

List of Co-Authors 171

PhD Portfolio 175

Dankwoord (Acknowledgements, in Dutch) 179

Supplements Supplemental Materials (Chapter 5) 187

chapter 1General Introduction

and Thesis Outline

11

1

General Introduction and Thesis Outline

A Short Girl

Zita1 is a 10-year old girl with growth failure. After an uncomplicated pregnancy, she

was born at 38 weeks of gestation and weighed only 2340 grams, well below the aver-

age. At one year she was still small, and her parents found the tone in her muscles

low. Zita was not sitting yet and was also not babbling. So, her parents consulted their

general practitioner (GP): Why is she smaller than other children? Why is she developing slowly?

Could both be related and could Zita have an underlying disease? Their young GP did not yet

have much experience with growth disorders and wondered: Should I refer her to a special-

ist? Are there any criteria or guidelines available for this?

The GP first decided to wait a bit longer. At two years, Zita’s growth was still below

all centiles on the growth chart, her development was also still slow, and the parents

had noticed she looked a bit different compared to the family. So the GP referred her

to a paediatrician. The paediatrician had a specific interest in children with growth

disturbances, and knew about the guidelines that she could follow in her work-up. She

thought that all signs and symptoms in Zita likely constituted a syndrome, and asked

a clinical geneticist for help. The genetic evaluations showed Zita to have a known

syndrome: she had received two chromosomes 14 from her mother instead of one from

her mother and one from her dad. It explained her development, her growth pattern,

and the way she looked. The parents were informed, and the paediatrician took over

the further care.

At 7 years of age, Zita was 11 centimetres shorter than on average her peers were, while

her parents were in fact quite tall. She had developed some overweight, something that

was known to occur in this syndrome. Zita had difficulties with her short stature, it

hindered her to participate in certain activities. She and her class mates would go to a

theme park, and Zita wondered: Will I be tall enough to enter the attractions? Can the doctors

make me taller?

Treatment with growth hormone to increase her height and improve her body composi-

tion was considered by her paediatrician. She wondered: Is there any evidence available that

in this syndrome growth hormone would increase Zita’s height and improve her body proportions?

What could be the physical and psychological benefits of any treatment?

In this thesis, I aim to focus on each of these questions that arise when dealing with

children with growth disorders like Zita – from referral, diagnostic workup and genetic

analysis to diagnosis, treatment and quality of life.

1 The name, meaning “little girl” in Tuscan Italian, and some identifying details are fictional.

12

1


Human Growth

The process of human growth starts at conception and ends when adult height has

been reached. Every fetus has a genetically determined growth potential and its growth

is further influenced by fetal, maternal and placental factors [1]. Fetal growth is defined

as the increase in mass that occurs towards the end of the first trimester and birth [2].

From the third trimester of pregnancy, increase in body size is among other things

achieved by linear growth, determined by the rate of growth plate chondrogenesis, and

by increase of essential body stores, resulting in a nearly 20% increase in fat mass

[2, 3]. Growth plate chondrogenesis plays an important role in height gain from the

end of pregnancy to adolescence: decreased chondrogenesis causes short stature and

increased chondrogenesis results in tall stature. Many factors, such as nutritional,

genetic, paracrine and endocrine factors, regulate this process [3]. Furthermore,

other disorders of the bone, like abnormal breakdown or remodelling of bone tissue,

bone malformations and deformations can contribute to disturbed growth. For short

stature, growth disorders include clinically defined syndromes, small for gestational

age (SGA) with failure to catch-up growth, skeletal dysplasias, malnutrition, disorders

in organ systems, growth hormone deficiency and other disorders of the growth

hormone-IGF axis, endocrine- and metabolic disorders, psychosocial and iatrogenic

causes and idiopathic short stature [4]. Regarding tall stature, disorders consist of

dysmorphic syndromes, growth hormone overproduction, hyperinsulinism, familial

glucocorticoid deficiency, hyperthyroidism, other endocrine disorders and idiopathic

tall stature [4]. For some of these disorders, including certain dysmorphic syndromes

and idiopathic short and tall stature, the mechanism for dysregulation of the growth

plate remains unknown [3].

Growth Monitoring

Growth failure, which includes short stature, growth retardation or short stature in

comparison to target height, is considered an early sign of various underlying pathologi-

cal conditions and forms a common reason for referral to specialist paediatric care [5].

The incidence of pathological causes of growth failure in children aged below 10 years

varies between 3 and 9.5% [6-9]. For adolescents with growth failure, the incidence of

detectable disorders has been reported markedly lower, 1.3% [10]. Overgrowth or tall

13

1


stature on the other hand is a less common reason for referral and underlying pathol-

ogy is seen in this group of patients as well, but is very rare [11]. However, it remains

important to rule out pathology in tall patients. The most common genetic causes of

overgrowth, such as Fragile X syndrome, Marfan syndrome, Klinefelter syndrome and

Sotos syndrome show incidences of <<0.1% [12-17].

In order to detect pathological causes of disturbed growth in children, an efficient sys-

tem for growth monitoring and a diagnostic workup with a high sensitivity and speci-

ficity is essential. Despite similarities in clinical presentation and etiology of growth

disorders, national guidelines for screening and diagnostic workup in children and

adolescents with growth failure or overgrowth vary widely [7, 18-23]. In Part 1 of the

thesis we evaluate various national guidelines for growth monitoring and diagnostic

workup in children and adolescents with growth failure and overgrowth. Chapter 2

describes a study evaluating the Dutch, Finnish and British screening guidelines in a

cohort of children with growth failure. In Chapter 3 we present a study investigating

the etiology, the role of puberty and the most useful criteria for diagnostic workup in a

cohort of adolescents with growth failure. The study in Chapter 4 explores diagnostic

workup and follow-up in children with tall stature and we present a simplified diagnos-

tic algorithm for use in clinical practice.

Genetic Analysis

Part of the diagnostic workup in growth disorders includes genetic analysis. Genome-

wide association studies (GWAS) have shown hundreds of genes involved in growth.

Although over 400 loci showed to contribute to variation of normal stature, effect sizes

per loci are small and these studies have provided limited insight into pathological

causes of growth failure [24]. With respect to sequence variants, rare genetic variants

with a large impact on growth cannot be found in GWAS.

The technical abilities to examine genetic disorders have increased dramatically in the

past few years. Array-comparative genomic hybridization (array-CGH) and microarrays

were introduced for the detection of copy number variants (CNVs) and the arrival of

whole-exome sequencing (WES) enabled clinicians and researchers to detect muta-

tions in virtually all exons of the genome, instead of testing each locus separately [25].

For children with growth disorders it has become clear that this genetic technology

may greatly improve and accelerate the diagnostic process, at a lower cost. In the past

14

1


few years several genetic growth disorders have been discovered by WES, for example

caused by CUL7, IGSF1, FGFR3, ACAN, PAPPA2 and XRCC2 mutations [26-31]. Further-

more, epigenetic changes such as DNA methylation disturbances play a critical role in

the development of disease. Genome-wide methylation arrays allowed assessment of

methylation patterns across the entire genome [32].

Presumably, 30-50% of the variation in weight at birth can be explained by genetic

causes, which includes chromosome imbalances, sequence variants and epigenetic

disturbances. The London Dysmorphology Database contains over 400 entities associ-

ated with prenatal growth failure [33] and GWAS have disclosed a number of variants

associated with fetal growth [34]. Furthermore, numerous studies on epigenetic

influences, especially methylation disturbances, have been performed [35-42]. Despite

this, the (dys)regulation of prenatal growth is still only understood to a limited extent.

The study in Chapter 5 shows a unique combination of genetic studies in a cohort of

small for gestational age (SGA) newborns, using array-CGH, WES and a genome-wide

methylation array.

Treatment

Several growth disorders, such as Turner syndrome, SHOX gene haploinsufficiency,

Noonan syndrome, growth hormone deficiency (GHD) and Prader-Willi syndrome,

are approved indications for growth hormone treatment (GH-T) in children and ado-

lescents [43]. Besides increasing growth and final height, treatment can be beneficial

for psychosocial and cognitive functioning, body composition and muscle strength. In

addition to these disorders, other disorders in which GH-T has not been investigated

yet, could benefit from this treatment. Chapter 6 describes a therapeutic study in pa-

tients with maternal Uniparental Disomy 14 (matUPD(14)), a syndrome that resembles

Prader-Willi syndrome (PWS) and is characterized by short stature, truncal obesity

and precocious puberty. Treatment with GH has not been reported in detail for this

syndrome before. Therefore, we observed the effect of GH-T in matUPD(14) patients on

growth and body composition during a 2-year follow-up period.

15

1


Quality of life

Literature suggests that a child develops a certain attitude towards short and tall stature

from an early age. Tall stature is considered a positive phenomenon in contrast to short

stature, even in very young children [44]. Negative stereotypes regarding short stature

constitute a potential source of psychosocial stress for the affected child. Therefore, an

important aim of growth hormone therapy besides increasing height, is psychological

improvement of short individuals [45]. Regarding growth hormone therapy, on average

10-14 cm height gain can be expected after treatment in children with in growth hor-

mone deficiency (GHD) [46], 5-8 cm in Turner syndrome [47] and 3-6 cm in idiopathic

short stature (ISS) [48, 49]. Nevertheless, it is questionable whether GH-T, in the form

of subcutaneous injections for many years, actually improves the child’s quality of life

when only a few centimetres in height can be gained, especially in otherwise ‘healthy’

ISS children.

To subjectively investigate in what way children experience the burden of being small

as well as the quality of life outcome of GH-T, the European Quality of Life in Short

Stature Youth was developed and psychometrically tested [50]. In the study presented

in Chapter 7, the original European QoLISSY questionnaire, as developed for young

patients with GHD and ISS, was translated to Dutch and psychometrically tested in

GHD and ISS patients and their parents in the Netherlands.

16

1


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14. Simm, P.J. & Werther, G.A. Child and adolescent growth disorders--an overview. Aust Fam Physician 2005;34:731-37.

15. Tatton-Brown, K. & Rahman, N. Sotos syndrome. Eur J Hum Genet 2007;15:264-71.

16. Thorburn, M.J., Wright, E.S., Miller, C.G. & Smith-Read, E.H. Exomphalos-macroglossia-gigantism syndrome in Jamaican infants. Am J Dis Child 1970;119:316-21.

17. Coffee, B. et al. Incidence of fragile X syndrome by newborn screening for methylated FMR1 DNA. Am J Hum Genet 2009;85:503-14.

18. Davies, J.H. & Cheetham, T. Investigation and management of tall stature. Arch Dis Child 2014;99;772-77.

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23. Visser, R., Kant, S.G., Wit, J.M. & Breuning, M.H. Overgrowth syndromes: from classical to new. Pediatr Endocrinol Rev 2009;6:375-94.

24. Wood, A.R. et al. Defining the role of common variation in the genomic and biological architecture of adult human height. Nat Genet 2014;46:1173-86.

25. Pasche, B. & Absher, D. Whole-genome sequencing: a step closer to personalized medicine. JAMA 2011;305:1596-7.

26. Quintos, J.B., Guo, M.H. & Dauber, A. Idiopathic short stature due to novel heterozygous mutation of the aggrecan gene. J Pediatr Endocrinol Metab 2015;28:927-32.

27. Sun, Y. et al. Loss-of-function mutations in IGSF1 cause an X-linked syndrome of central hypothy-roidism and testicular enlargement. Nat Genet 2012;44:1375-81.

28. Dauber, A. et al. Mutations in pregnancy-associated plasma protein A2 cause short stature due to low IGF-I availability. EMBO Mol Med 2016;8(4):363-74.

29. de Bruin, C. et al. An XRCC4 splice mutation associ-ated with severe short stature, gonadal failure, and early-onset metabolic syndrome. J Clin Endocrinol Metab 2015;100:E789-98.

30. Kant, S.G. et al. A novel variant of FGFR3 causes

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proportionate short stature. Eur J Endocrinol 2015;172:763-70.

31. Dauber, A., Rosenfeld, R.G. & Hirschhorn, J.N. Genetic evaluation of short stature. J Clin Endocrinol Metab 2014;99:3080-92.

32. Dedeurwaerder, S. et al. Evaluation of the Infinium Methylation 450K technology. Epigenomics 2011;3:771-84.

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34. Freathy, R.M. et al. Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight. Nat Genet 2010;42:430-5.

35. Bourque, D.K., Avila, L., Penaherrera, M., von Dadelszen, P. & Robinson, W.P. Decreased placental methylation at the H19/IGF2 imprinting control region is associated with normotensive intrauterine growth restriction but not preeclampsia. Placenta 2010;31:197-202.

36. Bouwland-Both, M.I. et al. DNA methylation of IGF2DMR and H19 is associated with fetal and infant growth: the generation R study. PLoS One 2013;8:e81731.

37. Cordeiro, A., Neto, A.P., Carvalho, F., Ramalho, C. & Doria, S. Relevance of genomic imprinting in intrauterine human growth expression of CDKN1C, H19, IGF2, KCNQ1 and PHLDA2 imprinted genes. J Assist Reprod Genet 2014;31:1361-8.

38. Hillman, S.L. et al. Novel DNA methylation profiles associated with key gene regulation and transcription pathways in blood and placenta of growth-restricted neonates. Epigenetics 2015;10:50-61.

39. Lambertini, L. et al. Diffeential methylation of imprinted genes in growth-restricted placentas. Reprod Sci 2011;18:1111-7.

40. Leeuwerke, M. et al. DNA Methylation and Expres-sion Patterns of Selected Genes in First-Trimester Placental Tissue from Pregnancies with Small-for-Gestational-Age Infants at Birth. Biol Reprod 2016;94:37.

41. Moore, G.E. et al. The role and interaction of imprinted genes in human fetal growth. Philos Trans R Soc Lond B Biol Sci 2015;370:20140074.

42. Tobi, E.W. et al. DNA methylation of IGF2, GNASAS, INSIGF and LEP and being born small for gestational age. Epigenetics 2011;6:171-6.

43. Richmond, E. & Rogol, A.D. Current indications for growth hormone therapy for children and adolescents. Endocr Dev 2010;18:92-108.

44. Clopper, R. Height and children’s stereotypes, (Chapel Hill Press, University of North Carolina, 1994).

45. Sandberg, D.E. & Voss, L.D. The psychosocial consequences of short stature: a review of the evidence. Best Pract Res Clin Endocrinol Metab 2002;16:449-63.

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part iGrowth Monitoring

chapter 2Application of the Dutch,

Finnish and British Screening Guidelines in a Cohort of

Children with Growth Failure

Susanne E. Stalman, Ilse Hellinga, Paula van Dommelen,

Raoul C.M. Hennekam, Antti Saari, Ulla Sankilampi, Leo Dunkel,

Jan M. Wit, Gerdine A. Kamp, Frans B. Plötz


22 Part I

2

Abstract

Aims

To evaluate three guidelines for selecting short children for diagnostic workup in a

general pediatric clinic.

Methods

All patients (n = 131) aged 3.00-9.99 years who were referred for growth failure to a gen-

eral pediatric clinic were evaluated for their medical history and growth and examined.

All of them underwent the same standardized diagnostic workup. Retrospectively, the

criteria for the diagnostic workup from three guidelines (proposed in the Netherlands,

Finland and the UK) were applied, and their sensitivity was assessed. A Dutch reference

sample (n = 958) was used for calculating population specificity.

Results

In 23 patients (17.6%), a pathological cause of their growth failure was found. The sen-

sitivity of the original Dutch, Finnish and British guidelines was 73.9, 78.3 and 56.5%

and their specificity 98.5, 83.7 and 95.8%, respectively. When adding recent growth

deflection to the Dutch guideline, sensitivity increased to 87%, but specificity decreased

markedly (to 87%).

Conclusion

The proposed cutoff values for height standard deviation score and distance to target

height/mid-parental height, as used in the Netherlands and Finland, are effective for

population growth monitoring, and superior to the monitoring algorithm in the UK.

Growth deflection irrespective of height is an important sign of acquired growth disor-

ders, but its specificity is too low for population screening.

Screening Guidelines in Children with Growth Failure 23

2

Introduction

Short stature or growth retardation is considered a relatively early sign of underlying

pathology in children. In several countries, a system of growth monitoring is estab-

lished in primary health care, with referral to secondary and/or tertiary care of patients

suspected for a pathological cause [1]. Criteria for growth monitoring and diagnostic

workup should ideally have a high sensitivity and specificity.

Despite similarities in the clinical presentation and etiology of growth failure in various

parts of the world, national guidelines for the screening and diagnostic approach vary

considerably [2,3]. Indeed, even in countries using a similar set of growth indicators

[i.e. height standard deviation score (HSDS), distance to target height and growth

rate], such as the Netherlands, Finland and England, different cutoff limits are used.

The Dutch guideline is based on a set of 4 criteria which show a high sensitivity (76-

86%) for detecting pathological causes of growth failure in children aged 3.00-9.99

years [4]. It has subsequently been suggested to add 2 additional criteria in primary

health care [5]. A similar set of auxological criteria was reported by a Finnish group,

showing a sensitivity of 97% in screening for Turner syndrome [6]. In the UK, height

and weight are measured at the age of 4-5 and 10-11 years [7,8], and recommendations

are provided for criteria for further assessment based on growth rate and distance to

mid-parental height [9-11].

The aim of our study was to analyze the sensitivity and specificity of these three guide-

lines in a pediatric clinic examining children that were referred for growth failure.

Methods

Study Population

All children between 3.00 and 9.99 years of Dutch, North African or Southeastern Eu-

ropean ethnicity referred to our pediatric endocrine outpatient growth clinic for growth

failure (Growth Clinic, Tergooi Hospitals, Hilversum, The Netherlands) between Janu-

ary 2010 and June 2013 were included. Excluded were (1) adopted children, (2) children

of other ethnicities and (3) children with missing medical records.

24 Part I

2

Diagnostic Workup

At our growth clinic, all referred patients underwent a standardized diagnostic workup

which includes an evaluation of the medical and family history, detailed auxological

measurements, bone age assessment and a physical examination with special atten-

tion to dysmorphisms and body disproportions. A pediatrician with special training in

endocrinology and growth disorders decided whether a further diagnostic workup was

indicated, which included (if indicated) further referral to a pediatric endocrinologist

or clinical geneticist. If insufficient indications for disturbed growth were found, pa-

tients were discharged from further follow-up, or the pediatrician decided on watchful

waiting. On patients with indications for disturbed growth, further investigations were

carried out. If an immediate indication for a specific diagnosis was present, targeted

further investigations of this disease were conducted. If no specific clues were found,

full laboratory assessments of blood and urine were performed. In case of abnormal

IGF-1 levels (<-1.0 SDS), a growth hormone provocation test was performed with cloni-

dine; if necessary, a second test was performed using arginine, after priming with tes-

tosterone esters in boys and ethinyl estradiol in girls. In case of abnormal IGF-1 (<-1.0

SDS), a peak growth hormone value of >6.7 ng/ml was considered a normal response;

in case of an IGF-1 level <-2.0 SDS, a peak growth hormone value of >10 ng/ml was con-

sidered a normal response. In addition, in case of disproportion, defined as a sitting

height/height ratio >+2.0 SDS [12] and/or a low arm span for height (<96.5%) [13], a

radiographic evaluation of the skeleton was performed. Screening for a short stature

homeobox (SHOX)-containing gene defect was planned in case of a Rappold score >4

[13]. In case a girl showed an HSDS >2.0 below the target height SDS (THSDS), genetic

testing for Turner syndrome was performed, except if additional clinical or laboratory

findings made such a diagnosis unlikely (e.g. low follicle-stimulating hormone levels

and no dysmorphisms). In case of an abnormal phenotype, the patient was referred to

a clinical geneticist for evaluation, and, if indicated, genetic testing was performed.

Diagnoses and Definitions

Growth failure in our population included short stature and/or abnormally low height

velocity [14] and/or large distance to target height. Short stature was defined as an

HSDS below -2.0 according to the ESPE Classification [14]. Patients with pathological

causes of short stature were classified as having primary or secondary growth disorders.

The remaining children with an HSDS <-2.0 were classified as having idiopathic short


2

stature [14]. The children were further subclassified into either familial or nonfamilial

cases [15,16]. Children with an HSDS ≥-2.0 were classified as ‘non-short’.

Criteria according to the Dutch, Finnish and British Guidelines

The three guidelines for growth monitoring contain various criteria which were as-

sessed both separately and as a set to allow for calculating the sensitivity and specificity

of both the individual criteria and the full guidelines. These guidelines were tested on

the children referred for growth failure to establish if the sensitivity of the guidelines

for detecting pathological causes of growth failure was sufficient. We also tested them

on a Dutch reference sample (n = 958) for calculating population specificity.

According to the Dutch guideline for children aged 3.00-9.99 years with short stature

[4], an additional workup would be indicated if any of the following criteria applied: (1)

HSDS <-2.5; (2) HSDS <-2.0 and dysmorphic features or disproportion; (3) HSDS <-2.0

and HSDS >1.6 SD below THSDS (the original cutoff of 2.0 SD below the THSDS was

changed when a new formula of target height was used [16] and the secular change in

height had stopped [17]), or (4) HSDS <-2.0 and height deflection (>1.0 SD). Two addi-

tional consensus-based criteria have been suggested for primary health care: (5) HSDS

>2.5 SD below THSDS and (6) growth deflection irrespective of HSDS [5]. We evaluated

the suitability of the set of 4 criteria and the set of 6 criteria separately. In the absence

of a definition of a recent ‘growth deflection’, we used the following cutoff values: >0.5

SD/1 year, >0.7 SD/2 years or >1.0 SD/undefined time, irrespective of height, in contrast

to criterion 4.

Screening parameters according to the Finnish guideline include HSDS, distance

between HSDS and THSDS (THSDSDEV) and HSDS change over time (ΔHSDS), and

optimal cutoff points were defined at maximum sensitivity and specificity values [6].

Regarding THSDSDEV, the cutoff limit is variable: the cutoff value is multiplied by an

age- and gender-specific reference value (SD) for target height [6]. This results in the

following criteria: (1) HSDS ≤-2.2414; (2) THSDSDEV ≤-2.2414 × SD, and (3) ΔHSDS

≤-2.2414. In order to apply the Finnish criteria to our population, Dutch reference data

for calculating HSDS and THSDS were used [4].

In the UK, an HSDS below the 0.4th centile (<-2.67 SD) at the age of 4-5 years is used

as a referral cutoff [8,10,11]; also at 10-11 years, height and weight are measured. Ad-

ditional rules are specified in the current UK growth charts: a height centile more than

3 centile spaces (>2.0 SD) below the mid-parental height centile and a drop in height

26 Part I

2

of more than 2 centile spaces (>1.33 SD) [10,11]. Also for the evaluation of the British

criteria, Dutch reference data were used for calculating SDS [4].

Statistical Analysis

All data were collected from case records and analyzed in SPSS version 21. Descriptive

statistics were used to quantify the incidence of pathological causes of growth failure

and to determine whether the various criteria according to the three guidelines were

met. The formulas used for the Finnish criteria for THSDSDEV and ΔHSDS differ from

the Dutch and British, since they can only be determined by computerized calculation

instead of interpreting the growth data directly.

For ΔHSDS, the following formula is used: (HSDS2 - HSDS1)/SD, where SD = sqrt(2 ×

(1 - r)), where r = (exp(2 × z) - 1)/(exp (2 × z) + 1), where z is calculated according to

age- and gender-specific formulas using the age distance (age2 - age1) and the mean

age (age2 + age1)/2 between two height measurements, where age2 is the age at the

visit at our clinic, and age1 the age at which the patient’s growth rate changed. For

the calculation of height- for-age SDS deviation from the THSDS, age-specific SD for

THSDSDEV were used. Sensitivity, specificity and likelihood ratios were calculated for

all criteria, using MedCalc for Windows version 12.7.8 (MedCalc Software, Belgium).

Ethics Approval

Approval for the study was obtained by the Scientific Review Committee of Tergooi

Hospitals (reference No. kv/15.04).


2

Results

Study Population

A total of 131 patients between 3.00 and 9.99 years referred for growth failure were even-

tually included for analysis (fig. 1), and all underwent the same standardized diagnostic

workup followed by additional investigations based on the pediatrician’s judgement. Pa-

thology was found in 23 patients with growth failure (17.6%): a primary growth disorder

in 8 children and a secondary growth disorder in 15 (Table 1; Fig. 1). Five of the 23 patients

presented with an HSDS ≥-2.0. Among the 69 patients with an HSDS <-2.0, no specific

diagnosis could be made in 51 patients (73.9%), and they were thus classified as having

idiopathic short stature. The majority had nonfamilial short stature (n = 35) (Fig. 1).

Criteria according to the Dutch, Finnish and British Guidelines

The auxological characteristics of the children with pathological diagnoses according

to the criteria of the Dutch, Finnish and British guidelines are shown in Table 1.

Excluded n = 14 Adopted children (n = 3), childrenwith another ethnicity than Dutch,

North African or SoutheasternEuropean (n = 4) and children with

missing data (n = 7)

Patients referred for short stature 3.00–9.99 years

n = 145

Patients included for analyses n = 131

Boysn = 76

Girlsn = 55

Non-shortn = 37

Idiopathicn = 29

Primaryn = 4

Secondaryn = 6

Non-shortn = 20

Idiopathicn = 22

Primaryn = 4

Secondaryn = 9

Familialn = 9

Non-familialn = 20

Familialn = 7

Non-familialn = 15

Figure 1. Overview of the study population. The majority of the children referred for growth failure showed

an HSDS ≥-2.0 or were diagnosed with idiopathic short stature. A few children with an HSDS ≥-2.0 at pre-

sentation had a previous HSDS <-2.0, and in a number of children, the HSDS was >1.6 SD below the THSDS.

Among the children with idiopathic short stature, the majority had nonfamilial short stature and was prepu-

bertal. Ten boys and 13 girls were diagnosed with a pathological cause of their growth failure, further classi-

fied into primary and secondary growth disorders.

28 Part I

2

Tabl

e 1.

Gro

wth

cha

ract

eris

tics

of t

he c

hild

ren

wit

h pa

thol

ogy

(n =

23)

Cas

ePa

thol

ogic

dia

gnos

isa

Age

, yea

rs; M

/F

Dut

ch

guid

elin

e b

Fin

nis

h gu

idel

ine

b

Bri

tish

gu

idel

ine

bIn

dica

tion

for

diag

nos

tic

wor

kup

1)

2)3)

4)5)

6)1)

2)

3)1)

2)

3)D

utch

–

4 cr

iter

iaD

utch

–

6 cr

iter

iaFi

nn

ish

Bri

tish

1SG

A4.

6, M

+-

+-

--

++

-+

--

++

++

2SG

A4.

4, M

+-

+-

--

++

-+

+-

++

++

3SG

A5,

7, M

+-

++

+-

++

-+

+-

++

++

4SG

A7.

7, M

--

+-

+-

++

+-

+-

++

++

5SG

A6.

6, F

--

--

--

+-

--

--

--

+-

6K

now

n ca

rdia

c di

sord

er

8.8,

M-

-+

--

-+

--

+-

-+

++

+

7Ps

ycho

soci

al7.

0, M

--

+-

--

-+

--

+-

++

++

8M

ethy

lphe

nida

te9.

3, M

--

--

--

--

--

--

--

--

9M

ethy

lphe

nida

te9.

8, M

+-

+-

--

+-

--

--

++

+-

10Tu

rner

syn

drom

e6.

1, F

--

+-

+-

++

--

+-

++

++

11SH

OX

defi

cien

cy

6.4,

F+

++

--

-+

+-

+-

-+

++

+

12SH

OX

defi

cien

cy9.

6, F

-+

+-

+-

++

--

--

++

+-

13M

ucop

olys

acch

arid

osis

3.

3, M

--

--

-+

--

-*

-+

-+

-+

14M

ucop

olys

acch

arid

osis

3.3,

M-

--

--

+-

--

*-

--

+-

-

15C

elia

c di

seas

e5.

1, M

--

--

-+

--

--

--

-+

--

16C

elia

c di

seas

e5.

2, F

+-

+-

+-

++

-+

+-

++

++

17C

elia

c di

seas

e5.

7, F

+-

--

--

++

--

--

++

+-

18C

elia

c di

seas

e5.

8, F

+-

+-

--

++

--

+-

++

++

19G

itel

man

syn

drom

e8.

4, F

--

+-

--

+-

--

--

++

+-

20Pa

rtia

l GH

defi

cien

cy3.

5, F

+-

+-

+-

++

-*

+-

++

++

21A

cqui

red

GH

defi

cien

cy d

ue to

m

enin

giti

s4.

8, F

++

+-

++

++

++

+-

++

++

22IG

F-I r

esis

tanc

e3.

5, F

++

+-

-+

++

-*

--

++

+-

23H

ypot

hyro

idis

m9.

2, F

--

--

--

--

--

--

--

--

Num

ber

fulfi

llin

g cr

iter

ion

114

161

75

1714

27

91

1720

1813

SGA

=sm

all f

or g

esta

tion

al a

ge; G

H=

grow

th h

orm

one;

IGF-

I=in

sulin

like

gro

wth

fact

or I.

* A

ge b

elow

4 y

ears

.a ac

cord

ing

to E

SPE

Cla

ssifi

cati

on o

f Pae

diat

ric

Endo

crin

e D

iagn

oses

[14

]; b fo

r cr

iter

ia a

nd n

umbe

ring

, see

tabl

e 2.


2

Sensitivity, Specificity and Likelihood Ratios

The sensitivity, as well as the estimated population specificity and positive likelihood

ratios for the various elements of the three guidelines, are shown in Table 2. For the

Dutch guideline, the population specificity could not be calculated for HSDS <-2.0 +

dysmorphisms/disproportions, since dysmorphisms and disproportions were not

recorded for the reference population [4]. The addition of 1 of the 2 consensus-based

criteria (recent growth deflection irrespective of the HSDS) to the Dutch guideline led to

the detection of 3 more patients, increasing the sensitivity to 87%, but at the expense of

a lower specificity (87%). No additional patients were detected with criterion 3 (ΔHSDS

≤-2.2414) of the Finnish guideline, but the specificity of this guideline decreased to

Table 2. Sensitivity, specificity and likelihood ratios

Sensitivity – pathology (n = 23)

Specificity – Dutch reference sample (n = 958)

Positivelikelihood ratio

Dutch guidelines

(1) HSDS <–2.5 48 (27–69) 99.1 (98.2–99.6) 50.91

(2) HSDS <–2.0 + dysmorphisms/disproportions 17 (5–39) – –

(3) HSDS <–2.0 + HSDS >1.6 below THSDS 70 (47–87) 99.1 (98.2–99.6) 74.05

(4) HSDS <–2.0 + height deflection >1.0 SD 4 (0–22) 99.9 (99.4–100) 41.61

Any of the 4 growth criteria positivea 74 (52–90) 98.5 (97.6–99.2) 50.58

(5) HSDS >2.5 below THSDS 30 (13–53) 99.8 (99.3–100) 145.78

(6) Recent growth deflectionb 22 (7–44) 87.6 (85.2–89.7) 1.75

Any of the 6 growth criteria positivec 87 (66–97) 87.0 (84.7–89.0) 6.66

Finnish guidelines

(1) HSDS ≤–2.2414 74 (52–90) 98.4 (97.4–99.1) 47.21

(2) THSDSDEV ≤–2.2414 × SD 61 (39–80) 94.4 (92.7–95.7) 10.80

(3) ΔHSDS/SD ≤–2.2414 9 (1–28) 88.0 (85.7–90.1) 0.73

Any of the 3 criteria positive 78 (56–93) 83.7 (81.2–86.0) 4.81

British guidelines

(1) HSDS <–2.67 at 4–5 years 30 (13–53) 99.4 (98.7–99.8) 52.41

(2) HSDS >2.0 below MPHSDS 39 (20–61) 99.0 (98.1–99.5) 37.49

(3) Height deflection >1.33 SD 4 (0–22) 97.1 (95.8–98.1) 1.49

Any of the 3 criteria positive 57 (34–77) 95.8 (94.4–97.0) 13.54

Values are percentages (95% confidence intervals) or ratios. MPHSDS = Mid-parental HSDS.a For the specificity of the Dutch reference sample: any of criteria (1), (3) and (4). b Defined as >0.5 SD/1 year,

>0.7 SD/2 years or >1 SD/undefined time. c For the specificity of the Dutch reference sample: any of criteria

(1), (3), (4), (5) and (6).

30 Part I

2

83.7% when applying this rule. The criterion for height deflection according to the

British guideline led to the detection of 1 more patient, and also reduced the specificity.

Discussion

We investigated the sensitivity of the criteria for diagnostic workup presently used in

three countries in a cohort of children referred for growth failure to a general pediatric

clinic. With the Dutch [4] and the Finnish guidelines [6], a sensitivity of 74 and 78%

was reached at a specificity of 98.5 and 83.7%, respectively. The sensitivity of the UK

criteria was considerably lower (57%). Growth deflection (irrespective of the HSDS), as

included in the Finnish and British guidelines and added to the original Dutch guide-

line, led to a decrease in specificity of all guidelines below an acceptable level (>98%)

for population screening.

The present sensitivity of the Dutch guideline (74%) is in line with the sensitivity (76-

86%) in the original studies [4]. The sensitivity of the Finnish guideline (78%) is lower

than reported for screening in Turner syndrome (97%) [6], but still within the same

range as that reported for the original Dutch guideline. The similar sensitivities of these

two guidelines can be explained by their use of the combination of HSDS and distance

to target height, with comparable cutoff values varying for these screening criteria.

Cases that did not conform to any of the proposed Dutch or Finnish criteria included 1

with SGA (Table 1, case 5), 1 with methylphenidate use (case 8), 2 with mucopolysac-

charidosis (cases 13 and 14), 1 with celiac disease (case 15) and 1 with hypothyroidism

(case 23). The main reason for this was that 5 of those patients (cases 8, 13-15 and 23)

were in fact not short (HSDS ≥-2.0). This emphasizes the limitation of the Dutch guide-

line in particular, in which the first 4 criteria are based on an HSDS of at least <-2.0.

Furthermore, this study also shows that despite carefully designed referral criteria, their

diligent application would still not identify 25% of children with a pathological cause

of their growth failure. This underlines that a detailed medical history and physical

examination, followed by proper medical judgement, cannot be replaced by just strictly

following growth-related guidelines. The present study also demonstrates that growth

failure-related disorders may occur in children who are not (yet) short but show other

parameters of disturbed growth; the diagnoses of the present cases that did not con-

form to the Dutch or Finnish criteria were made based on the medical history (cases 5

and 8), observation of dysmorphisms (cases 13 and 14), growth deflection (case 15) and


2

clinical suspicion of hypothyroidism (case 23). For the British guideline, several cases

with diagnoses requiring medical attention, which would only be found by abnormal

growth, would have been missed (cases 12, 14, 15, 17, 19 and 22). The lower sensitivity

of the UK guideline is due to the stricter cutoff values used for HSDS and height deflec-

tion. The sensitivity of all guidelines can be improved by adding the parameter of recent

growth deflection (>0.5 SD/1 year, >0.7 SD/2 years, >1.0 SD/undefined time), but the

low specificity does not allow this parameter to be added routinely. Growth deflection

can occur relatively commonly during the prepubertal period, and during this prepu-

bertal growth dip, the response of growth hormone secretion to the stimulation tests

mimics that of growth hormone deficiency. Still, recent growth deflection should be

considered a red flag in primary health care, and any abnormal symptom or sign should

lead to referral to a specialist clinic.

Our cohort may be considered a representative sample for various causes of pathology

among children with growth failure in a general population. First, the prevalence of

pathological causes among all the children of this cohort is comparable to most previ-

ous observations in children with growth failure, reporting an incidence between 1.3

and 19.8% [3, 18,19,20,21,22,23]. In none of these studies was a complete detailed rou-

tine diagnostic workup performed. In a recent North American study, a lower incidence

(1.3%) of pathology in short children was reported [23]. This may be explained by the

exclusion of children with low height velocity and/or abnormal symptoms, a higher

average age compared to our population and a high percentage of missing medical

growth records. Second, we identified patients with pathology even though they did not

conform to any of the criteria of the guidelines, again emphasizing the importance of

clinical judgement besides strictly following standardized criteria.

We acknowledge that there are also several limitations. First, this is a cohort originat-

ing from a single general pediatric center. It may well be that the diagnostic yield may

be different from an academic center. Second, the number of participants is still small;

thus, our analyses are limited to descriptive statistics, and the 95% confidence intervals

have a wide range. Third, use in the past of existing Dutch guidelines by the pediatri-

cians as well as referring doctors from primary care may have led to a biased approach,

resulting in the relatively high sensitivity of the criteria used in the Dutch guideline.

In conclusion, this study demonstrates that the proposed cutoff values for HSDS and

distance to target height/mid-parental height, as used in the Netherlands and Finland,

can be effectively used for growth monitoring. Both the Dutch and the Finnish guide-

32 Part I

2

lines show a good sensitivity for detecting pathological causes of growth failure, with

recent growth deflection as an important warning sign.

Acknowledgements

We are grateful to Dr. Charlotte Wright for providing information about the British

guideline. We wish to thank Liselotte de Kloet for her contributions and Bea Jansen van

‘t Land, Desirée Paap, Lidi Schilperoort, Irene Bergsma and Ingrid van de Woude for

taking good care of the patients at the growth clinic and for performing accurate auxo-

logical measurements. Funding for data collection was provided by Tergooi Hospitals,

Blaricum, The Netherlands. The sponsor had no involvement in the study.

Disclosure Statement

The authors indicate that they have no financial relationships relevant to this paper or

potential conflicts of interest to disclose.


2

References

1. Scherdel P, Salaün JF, Robberecht-Riquet MN, Reali L, Páll G, Jäger-Roman E, Crespo MP, Moretto M, Seher-Zupancic M, Agustsson S, Chalumeau M: Growth monitoring: a survey of current practices of primary care paediatricians in Europe. PLoS One 2013;8:e70871.

2. Fayter D, Nixon J, Hartley S, Rithalia A, Butler G, Rudolf M, Glasziou P, Bland M, Stirk L, Westwood M: Effectiveness and cost-effectiveness of height-screening programmes during the primary school years: a systematic review. Arch Dis Child 2008;93:278-84.

3. Grote FK, Oostdijk W, de Muinck Keizer-Schrama SM, van Dommelen P, van Buuren S, Dekker FW, Ketel AG, Moll HA, Wit JM: The diagnostic work up of growth failure in secondary health care; an evaluation of consensus guidelines. BMC Pediatr 2008;8:21.

4. Grote FK, van Dommelen P, Oostdijk W, de Muinck Keizer-Schrama SM, Verkerk PH, Wit JM, van Buuren S: Developing evidence-based guidelines for referral for short stature. Arch Dis Child 2008;93:212-17.

5. Oostdijk W, Grote F, Wit JM, et al: NVK guideline short stature. 2008. http://www.nvk.nl/Portals/0/richtlijnen/kleine%20lengte/kleinelengte.pdf (accessed November 24, 2014).

6. Saari A, Sankilampi U, Hannila ML, Saha MT, Mäkitie O, Dunkel L: Screening of Turner syndrome with novel auxological criteria facilitates early diagnosis. J Clin Endocrinol Metab 2012;97:E2125-32.

7. Health and Social Care Information Centre: National Child Measurement Programme (NCMP). http://www.hscic.gov.uk/ncmp (accessed April 29, 2015).

8. Hall DM: Growth monitoring. Arch Dis Child 2000;82:10-5.

9. Freeman JV, Cole TJ, Chinn S, Jones PRM, White EM, Preece MA: Cross sectional stature and weight reference curves for the UK. Arch Dis Child 1995;73:17-24.

10. Royal College of Paediatrics and Child Health: UK growth chart girls 2012. http://www.rcpch.ac.uk/system/files/protected/page/NEW%20Girls%202-18yrs(4TH%20JAN%202012).pdf (accessed April 29, 2015).

11. Royal College of Paediatrics and Child Health: UK growth chart boys 2012. http://www.rcpch.ac.uk/system/files/protected/page/NEW%20Boys%202-18yrs%20(4TH%20JAN%202013).pdf (accessed April 29, 2015).

12. Fredriks AM, van Buuren S, van Heel WJ, Dijkman-Neerincx RH, Verloove-Vanhorick SP, Wit JM: Nationwide age references for sitting height, leg length, and sitting height/height ratio, and their diagnostic value for disproportionate growth disorders. Arch Dis Child 2005;90:807-12.

13. Rappold G, Blum WF, Shavrikova EP, Crowe BJ, Roeth R, Quigley CA, Ross JL, Niesler B: Genotypes and phenotypes in children with short stature: clinical indicators of SHOX haploinsufficiency. J Med Genet 2007;44:306-13.

14. Wit JM, Ranke MB, Kelnar CJH: ESPE Classification of Pediatric Endocrine Diagnoses. Horm Res Paediatr 2007;68:1-119.

15. Hermanussen M, Cole J: The calculation of target height reconsidered. Horm Res 2003;59:180-183.

16. van Dommelen P, Schönbeck Y, van Buuren S: A simple calculation of the target height. Arch Dis Child 2012;97:182.

17. Schönbeck Y, Talma H, van Dommelen P, Bakker B, Buitendijk SE, Hirasing RA, van Buuren S: The world’s tallest nation has stopped growing taller: the height of Dutch children from 1955 to 2009. Pediatr Res 2013;73:371-77.

18. Voss LD, Mulligan J, Betts PR, Wilkin TJ: Poor growth in school entrants as an index of organic disease: the Wessex Growth Study. BMJ 1992;305:1400-2.

19. Ahmed ML, Allen AD, Sharma A, Macfarlane JA, Dunger DB: Evaluation of a district growth screening programme: the Oxford Growth Study. Arch Dis Child 1993;69:361-65.

20. Lindsay R, Feldkamp M, Harris D, Robertson J, Rallison M: Utah Growth Study: growth standards and the prevalence of growth hormone deficiency. J Pediatr 1994;125:29-35.

21. de Muinck Keizer-Schrama SM: Consensus ‘diagnosis of short stature in children’. National Organization for Quality Assurance in Hospitals (in Dutch). Ned Tijdschr Geneeskd 1998;142:2519-25.

22. Sankilampi U, Saari A, Laine T, Miettinen PJ, Dunkel L: Use of electronic health records for automated screening of growth disorders in primary care. JAMA 2013;310:1071-2.

23. Sisley S, Trujillo MV, Khoury J, Backeljauw P: Low incidence of pathology detection and high cost of screening in the evaluation of asymptomatic short children. J Pediatr 2013;163:1045-51.

chapter 3Growth Failure in Adolescents: Etiology, the Role of Pubertal

Timing and Most Useful Criteria for Diagnostic Workup

Susanne E. Stalman, Ilse Hellinga, Jan M. Wit,

Raoul C.M. Hennekam, Gerdine A. Kamp, Frans B. Plötz


36 Part I

3

Abstract

Background

The aim of the study was to evaluate the etiology, the role of pubertal timing and most

useful criteria for diagnostic workup in adolescents with growth failure.

Methods

Adolescents (n=182) aged 10.0–18.0 years underwent a standardized diagnostic pro-

tocol. Constitutional delay of growth and puberty (CDGP) was defined as late pubertal

onset or a Tanner stage less than –2 SDS. Dutch and Finnish criteria for growth moni-

toring were retrospectively assessed.

Results

In 13 children (7.1%) a specific diagnosis could be established. CDGP was diagnosed

in 10% of patients aged ≥13 (girls) or ≥14 years (boys). Sensitivity to detect pathologic

causes was 85% and 62% for, respectively Dutch and Finnish criteria for growth moni-

toring as used in younger children, but specificity was low (55%–59%).

Conclusions

In adolescents, pathological causes for growth failure and pubertal delay are common,

and we recommend a combination of height SDS, distance to THSDS and growth

deflection for deciding on further diagnostic testing.

Growth Failure in Adolescents 37

3

Introduction

Growth failure, including short stature, growth retardation, or short in comparison to

target height, is generally considered a relatively early sign of various pathological con-

ditions. The incidence of detectable causes in children below 10 years varies between

3.0% and 9.5% [1–4]. In two countries evidence-based guidelines have been developed

to assist primary health workers in their decision to refer a child for specialist care: in

the Netherlands validated up to 10.0 years and in Finland up to 18 years. These consist

of a combination of short stature for the population, short for genetic background, and

growth deflection [5–7]. The Finnish guideline [6, 7] contains complicated algorithms

that can only be used if integrated into an electronic health record system and the

change in height SDS (ΔHSDS) can only be calculated up to 12 years of age.

For adolescents with growth failure, the incidence of detectable pathological causes

has been reported as markedly lower (1.3%) than in younger children [8]. This can

be explained in part by assuming that the majority of congenital disorders have been

diagnosed at an earlier age and that acquired disorders causing growth failure in ado-

lescence are rare. In this age group, it is also more difficult to develop guidelines for

referral for specialist care because of the wide variability of the onset and progression

of puberty. For example, in case of delayed pubertal development, growth rate can sub-

stantially decrease, leading to a decreasing height standard deviation score (HSDS) and

increasing distance to target height SDS (THSDS) [9]. Constitutional delay of growth

and puberty (CDGP), the most common cause of delayed puberty [10, 11], is primarily

characterized by delayed puberty (pubertal onset >13 in girls and >14 in boys), but also

associated with slow growth, delayed bone age and a positive family history for delayed

puberty [12–14]. In a recent paper on Danish boys [10], the definition of CDGP for boys

was expanded by including a low Tanner score SDS [15, 16].

Here, our first aim is to evaluate the incidence of causes, including the contribution of

CDGP, of growth failure in adolescents referred to a general pediatric clinic. Our sec-

ond aim is to probe the efficacy of the existing Dutch and Finnish criteria for diagnostic

workup in adolescents.

38 Part I

3

Materials and methods

Participants

The pediatric clinic of the general Tergooi Hospitals serves as a regional referral center

for children and adolescents with suspected disorders of growth and puberty. During

the study period (January 2010–June 2013), 197 patients aged 10.0–18.0 years were

referred for a suspicion of growth failure.

In the Netherlands, growth references are available for Dutch, Turkish and Moroccan

children. Therefore, referred adolescents of Dutch, Turkish (including similar South

Eastern European ethnic backgrounds, e.g. Iranian, Azerbaijani) and Moroccan (in-

cluding similar North African ethnic background, e.g. Algerian, Egyptian) ethnicities,

were included for evaluation of growth failure. Children with another ethnicity than

Dutch, North-African or South-Eastern European, adopted children, and children with

missing files were excluded.


Hospitals (letter reference kv/15.04).

Data collection

Upon the first visit the parents completed a questionnaire regarding demographic

data, perinatal information, medical history, medication use, growth, and physical/

psychological changes or complaints. The family history included pubertal onset,

health status and height of first-degree family members. Specialized nurses completed

the data on the growth history of the patient and performed anthropometry (height,

weight, head circumference, SH, arm span) and assessed blood pressure and heart rate.

Height of both parents was measured, and if the child was disproportionate also pa-

rental arm span, SH and head circumference was measured. The following parameters

were calculated: birth weight and length standard deviation score (SDS) [17]; height

SDS (HSDS, separately for Dutch origin [18] and Moroccan and Turkish origin [19]);

target height (in cm and THSDS) [20]; body mass index (BMI) and BMI SDS [21]; head

circumference SDS [22]; arm span for height ratio [23]; sitting height (SH SDS) and

ratio between SH and height (SH/H SDS) [24]. Pubertal development according to

Tanner [25, 26] was expressed as SDS for age and gender using Dutch reference data

[15, 27]. Bone age in all children was assessed by a single pediatrician (GK) using the

Greulich and Pyle method [28]. Bone age development was defined as bone age minus


3

chronological age. The same strategy for workup was performed in children who did

and those who did not fulfill the criteria for growth failure.

In all patients referred for a suspected growth disorder the questionnaire, anthropo-

metric measurements, medical history, full physical examination with special attention

to dysmorphisms and disproportions, pubertal development and bone age assessment

were evaluated by the pediatrician specifically trained in pediatric endocrinology and

growth disorders. If insufficient clues for a disturbed growth were found, the patient

was discharged from further follow-up or the pediatrician decided on watchful wait-

ing. In patients with clues for disturbed growth, additional further investigations were

performed. If an immediate clue for a specific diagnosis was present, targeted further

investigations for this disease were performed. If no specific clues were found, full

laboratory investigations in blood and urine were performed. In case of abnormal IGF-1

levels (less than –1.0 SD), a GH provocation test was performed with clonidine, and if

necessary a second test was performed using arginine, after priming with a testoster-

one ester (100 mg Sustanon, i.m. 5 days before the test) in boys and estrogen (25 μg

ethinylestradiol p.o. for 5 days) in girls. In case of abnormal IGF-1 less than –1.0 SD a

peak GH value of >6.7 ng/mL was considered a normal response and in case of an IGF-1

less than –2.0 SDS a peak GH value of >10 ng/mL. In addition, in case of disproportion,

defined as SH/H ratio greater than +2.0 SDS [24] and/or a low arm span for height

(<96.5%) [23], a radiographic evaluation of the skeleton was performed. Screening for

a short stature homeobox containing gene (SHOX) defect was planned in case of a Rap-

pold score >4 [23]. In case a girl showed a HSDS >2.0 below THSDS, genetic testing

for Turner syndrome was performed except if additional clinical or laboratory findings

made such diagnosis unlikely (e.g. low FSH levels, no dysmorphisms). In the case of

an abnormal phenotype, the patient was referred to a clinical geneticist for evaluation

and if indicated genetic testing was performed. An overview of this clinical assessment

is shown in Fig. 1.

40 Part I

3

Definitions

Growth and pathology

We defined growth failure if one or more of the following characteristics would apply:

short stature, growth deflection and/or height below target height range. Short stature

was defined as a HSDS below –2.0, in line with general consensus [14, 29]. Growth de-

flection was defined as a negative change in HSDS of >0.5 SD/1 year, >0.7 SD/2 years or

>1.0 SD/undefined time, in line with the definitions used in our recent paper on 3–9.9

year olds [30]. A HSDS >1.6 below THSDS was considered short for target height, in

Assessment by pediatrician

Blood countInfection param. ElectrolytesFSH, LHLiver/ kidney function param.IgA a.b. celiac d.Total IgAThyroid functionIGF-1Urine: Glucose, protein, erythro.

Targeted further investigations4

Referral: growth disorder?

Medical history Physical exam1

Insufficient clues for disturbed growth n = 133 Clues for disturbed growth

Dischargen = 86

Targeted further investigations

No immediate clue for specific diagnosis

Cytogenetic testing31. Skeletal survey2. Rappold score

Clues for specific diagnosis Disproportion

1. Girl2. HSDS >2.0

below THSDS

Abnormal phenotype

Targeted further investigations2

Referral to clinical geneticist

Watchful waitingn = 47

Figure 1. Diagnostic workup in adolescents with growth failure. In all patients clinical characteristics were

evaluated by the pediatrician. If insufficient clues for a disturbed growth were found the patient was dis-

charged or the pediatrician decided on watchful waiting. In case of clues for disturbed growth additional

investigations were performed. Param., Parameters; FSH, follicle-stimulating hormone; LH, luteinizing hor-

mone; IgA a.b. celiac d., immunoglobulin A antibodies for celiac disease; IGF-1, insulin-like growth factor

1; erythro., erythrocytes; GH, growth hormone; SH/H SDS, sitting height/height ratio standard deviation

score; SHOX, short stature homeobox containing gene; HSDS, height standard deviation score; THSDS, tar-

get height standard deviation score. 1Special attention for dysmorphism, disproportion, anthropometrics. 2If

Rappold score >4: SHOX analysis. 3Turner syndrome. 4If IGF-1 abnormal: GH provocation tests.


3

line with results of the most recent Dutch nationwide growth study [20]. Patients who

were diagnosed with a pathological cause of their growth failure after our diagnostic

workup were classified using the European Society for Paediatric Endocrinology (ESPE)

Classification into primary or secondary growth disorders, and the remaining patients

with short stature as idiopathic short stature (ISS) [14]. Children with ISS were subclas-

sified as either familial short stature (FSS) if HSDS was ≥THSDS-1.6, or non-familial

short stature (NFSS), if HSDS was <THSDS-1.6 [20, 31]. Children with HSDS≥–2.0 and

no pathology were classified as non-short.

Pubertal onset

CDGP was defined in a similar fashion as reported by Lawaetz et al. [10]. The first (clas-

sical) type, CDGP type 1, consisted of adolescents with Tanner stage G1 at age ≥14 years

in boys or B1 ≥13 years in girls [14], usually in combination with slow growth, delayed

bone age (>1.0 years) and a positive family history for delayed puberty. Comorbidity

had to be excluded. The second type, CDGP type 2, consisted of adolescents who were

pubertal but at a stage expected for a much younger individual, defined by a Tanner

genital stage less than –2.0 SDS [10, 15, 16].

Although, obviously, in younger prepubertal adolescents (boys <14 years and girls <13

years) CDGP cannot be diagnosed, we tried to obtain an impression on the likelihood

of future development of CDGP by collecting information about pubertal stage SDS,

bone age delay, short stature for TH and the family history of pubertal delay (maternal

menarche ≥15.0; late paternal growth spurt and shaving).

Assessment of criteria for diagnostic workup

In patients with known causes for growth failure we retrospectively assessed both

Dutch and Finnish growth criteria. The Dutch criteria that have been suggested for

3–9.9-year-old children [5, 32] were applied to the teenagers with pathology and

included: 1) HSDS less than –2.5; 2) HSDS less than –2.0 and dysmorphic features

or disproportion; 3) HSDS less than –2.0 and HSDS>1.6 SD below cTHSDS; 4) HSDS

less than –2.0 and height deflection (>1.0 over an undefined time; 5) HSDS >2.5 below

cTHSDS and 6) growth deflection (>0.5 SD/1 year, >0.7 SD/2 years or >1.0 SD/undefined

time) irrespective of height SDS. We also assessed the predictive value of the Finnish

algorithm [6, 7]. The Finnish guideline includes HSDS, distance between HSDS and

THSDS (THSDSDEV) and HSDS change over time (ΔHSDS). This results in the following

criteria 1) HSDS≤–2.2414, 2) THSDSDEV≥2.2414*SD, 3) ΔHSDS≤–2.2414. In order to

42 Part I

3

apply the Finnish criteria to our population, Dutch reference data for calculating HSDS

and THSDS were used [18, 20].

Statistical analyses

All data were collected from case records and analyzed in SPSS, version 21 (IBM Corp.,

Armonk, NY, USA). Descriptive statistics were used to quantify the incidence of patho-

logic causes for growth failure and to classify patients for CDGP. Independent t-tests

for continuous variables and χ2-tests for categorical variables were used to compare

characteristics between short and non-short adolescents. Sensitivity, specificity and

likelihood ratios were calculated for all criteria, using MedCalc for Windows, version

12.7.8 (MedCalc Software, Ostend, Belgium).

Results

Participants

After excluding 15 cases, 182 children (99 boys, 83 girls) were available for analysis

(Fig. 2). At the time of their visit to the growth clinic, 123 children met the characteristics

of growth failure as defined at the time of analysis. Patient characteristics categorized

for short and non-short adolescents are shown in Table 1.

Diagnoses

Known causes of growth failure were detected in 13 adolescents (7.1%) (Table 2), which

were subclassified into three with a primary growth disorder (cases 1, 2 and 7) and ten

with a secondary growth disorder. Seven of them were referred only because of growth

failure (cases 1, 2, 8–12) without any other physical complaints.

The remaining 70 children with a HSDS less than –2.0 were classified as ISS. The num-

ber of NFSS (n=54) was considerably greater than that of FSS (n=16) (Fig. 2). Most of

the 99 adolescents without pathology and a height SDS ≥–2.0 had no previous height

measurement below –2.0 SDS, nor a height SDS more than 1.6 SD below TH.


3

n = 15 excludedAdopted children (n = 5), children with

another ethnicity than Dutch, North-African or Sounth-Eastern European

(n = 3) and missing data (n = 7)

Patients referred for suspicion of growth failure ≥10 years

n = 197

Patients included for analyses n = 182

Boysn = 99

Girlsn = 83

Non-shortn = 44

Idiopathicn = 49

Primaryn = 1

Secondaryn = 5

Non-shortn = 55

Idiopathicn = 21

Primaryn = 2

Secondaryn = 5

PreviousHSDS <-2.0

n= 2

No previousHSDS <-2.0

n= 42

HSDS >1.6 below THSDS n=12HSDS ≤1.6 below THSDS n=32

PreviousHSDS <-2.0

n= 3

No previousHSDS <-2.0

n= 52

HSDS >1.6 below THSDS n=16HSDS ≤1.6 below THSDS n=39

Non-familial short stature

n= 37

Familial short staturen= 12

Non-familial short stature

n= 17

Familial short stature

n= 4

Figure 2. Overview of the participants. One hundred and eighty-two adolescents were included. The majority

were non-short (HSDS ≥–2.0) or were diagnosed as ISS, of whom the majority was non-familial short with

normal pubertal development. Six boys and seven girls were diagnosed with a pathological cause for their

growth failure. ISS, Idiopathic short stature; HSDS, height SDS; CDGP, constitutional delay of growth and

puberty; THSDS, target height SDS.

Table 1. Characteristics of the study group: short vs. non-short

HSDS <-2.0 (n=79) HSDS ≥-2.0 (n=130) Sign

Age at presentation, mean (SD), years 13.3 (1.9) 13.0 (1.7) p=0.198

Age range, years 10.2–18.0 10.3–17.8 –

Gestational age in weeks, mean (SD) 39.2 (2.3) 39.5 (1.9) p=0.334

Birth weight SDS, mean (SD) –0.4 (1.2) –0.1 (1.0) p=0.053

Birth length SDS, mean (SD) –0.5 (1.4) 0.1 (1.4) p=0.013

THSDS, mean (SD) –0.6 (0.5) –0.2 (0.6) p<0.001

HSDS, mean (SD) –2.5 (0.4) –1.4 (0.6) p<0.001

HSDS less than –2.5, no. (%) 32 (40.5) – –

Any of the six criteria positive, no. (%) 67 (84.8) 20 (19.4) p<0.001

BMI SDS at presentation, mean (SD) –0.5 (1.0) –0.1 (1.0) p=0.012

Tanner stage, mean (SD)

G 2.2 (1.0) 2.5 (1.2) p=0.208

B 1.7 (1.1) 2.6 (1.3) p=0.004

Tanner stage SDS, mean (SD)

G –1.1 (0.7) –0.5 (0.7) p<0.001

B –0.7 (0.5) –0.4 (1.0) p=0.119

SD, standard deviation; HSDS, height standard deviation score; THSDS, target height standard deviation

score; BMI, body mass index; G, genitals (male); B, breast (female).

44 Part I

3

Tabl

e 2.

Gro

wth

cha

ract

eris

tics

in c

hild

ren

wit

h gr

owth

failu

re w

ith

know

n ca

use

(n =

13)

Cas

ePa

thol

ogic

dia

gnos

isa

Age

, M/F

HSD

S <

-2.0

Dut

ch g

uide

line b

Fin

nis

h gu

idel

ine b

Indi

cati

on

for

diag

nos

tic

wor

kup

– D

utch

gui

delin

e

Indi

cati

on

for

diag

nos

tic

wor

kup

– Fi

nn

ish

guid

elin

e

1)2)

3)4)

5)

6)

1)2)

3)

1SG

A

11.8

, F+

+-

+-

+- (

-0.4

0/5.

8yr)

++

-+

+

2SG

A

12.8

, M+

+-

+-

-- (

-0.2

0/10

.0yr

)+

+a

++

3K

now

n ca

rdia

c di

sord

er (T

GA

)15

.8, M

--

--

--

+ (-

0.72

/2.0

yr)

--

a+

-

4K

now

n pu

lmon

ary

diso

rder

(sev

ere

asth

ma

wit

h st

eroi

d tr

eatm

ent)

12.6

, M-

--

--

-- (

-0.9

5/9.

5yr)

--

a-

-

5M

ethy

lphe

nida

te c

12.9

, M+

--

--

-- (

-0.5

0/6.

1yr)

--

a-

-

6M

ethy

lphe

nida

te c

12.3

, F-

--

--

-+

(-1.

03/3

.2yr

)-

-a

+-

746

XX

gon

adal

dys

gene

sis

13.6

, F-

--

--

-+

(-1.

73/8

.4yr

)-

-a

+-

8C

elia

c di

seas

e 12

.2, F

++

-+

--

- (-0

.80/

4.5y

r)+

-a

++

9C

elia

c di

seas

e 11

.8, F

+-

-+

+-

- (-1

.26/

8.8y

r)+

--

++

10Is

olat

ed G

H d

efici

ency

12

.4, F

++

+-

+-

- (-2

.60/

6.8y

r)+

-a

++

11IG

F in

sens

itiv

ity

(IGF

1R d

efec

t)

15.3

, M+

++

++

-- (

-1.1

4/4.

8yr)

++

a+

+

12H

ypot

hyro

idis

m (H

ashi

mot

o)15

.7, M

++

-+

++

- (-1

.40/

7.0y

r)+

+a

++

13Ps

ycho

soci

al d

epri

vati

on

10.5

, F+

++

+-

-- (

-0.1

0/4.

3yr)

++

-+

+

Num

ber

fulfi

llin

g cr

iter

ion

9

73

74

23

85

011

8

a Age

> 1

2.0

year

s, s

o Δ

HSD

S/SD

cou

ld n

ot b

e ca

lcul

ated

. b Cla

ssifi

ed b

y ES

PE [

14].

c For

crit

eria

and

num

beri

ng, s

ee T

able

4. d

Gro

wth

rat

e de

crea

sed

afte

r th

e

star

t of

the

rapy

and

incr

ease

d m

arke

dly

afte

r lo

wer

ing

of t

he d

osag

e (c

ase

6) a

nd c

essa

tion

of

med

icat

ion

(cas

e 5)

. M

, M

ale;

F,

fem

ale;

HSD

S, h

eigh

t SD

S;

TH

SDS,

targ

et h

eigh

t SD

S; +

, doe

s co

mpl

y; –

, doe

s no

t com

ply;

SG

A, s

mal

l for

ges

tati

onal

age

; TG

A, t

rans

posi

tion

of t

he g

reat

art

erie

s; G

H, g

row

th h

orm

one;

IGF,

insu

lin-l

ike

grow

th fa

ctor

.


3

Pubertal onset

Of the 70 adolescents with an age above the classical cut-off limit for delayed puberty,

five children (7.1%) were still prepubertal, and thus were labeled as delayed pubertal

development. One of them was diagnosed with gonadal dysgenesis explaining her

delayed puberty. She was the only patient out of the 13 children with a known cause for

growth failure who showed delayed puberty (case 7). The remaining four adolescents

were thus diagnosed as CDGP (type 1), and all were short for TH, had a delayed bone

age (–1.8 to –2.7), and three had a positive family history for delayed puberty (Table 3).

Three of them were short (HSDS –2.7 to –3.2). Three other pubertal adolescents with

an age above the cut-off limit showed a Tanner SDS less than –2.0 and were classified

as CDGP type 2. All had a bone age delay (2.6 – 3.3 years) and two out of these three

were short for TH and had positive family history for delayed puberty. Thus, out of

70 adolescents with an age ≥13.0 (F) or ≥14.0 (M), seven complied with the diagnosis

CDGP (10.0%).

Out of 112 (including nine patients with known causes for their growth failure) prepu-

bertal adolescents with an age below the cut-off limit, many showed at least one clinical

feature compatible with future CDGP. Table 3 shows the numerical data when relatively

mild (and arbitrary) cut-off limits were used.

Table 3. Subcategorization of adolescents referred for growth failure, according to the likelihood of constitu-

tional delay of growth and puberty (CDGP)]

CDGP type 1 a CDGP type 2 b Possible future CDGP c

Boys 4 2 5

Short for TH 4 2 1

Delayed bone age 4 2 3

Positive family history delayed puberty

3 2 3

Girls - 1 15

Short for TH - - 8

Delayed bone age - 1 8

Positive family history delayed puberty

- - 7

Total 4 3 20

aAdolescents with Tanner stage G1 at age > 14 years in boys and/or B1 > 13 years in girls. bPubertal adoles-

cents with pubertal stage SDS less than –2.0. cYounger prepubertal adolescents (boys < 14 years and girls <

13 years) if three out of the following four conditions were met: 1) a pubertal stage SDS for age and sex of less

than –1.0 (as a continuous variable); 2) bone age delay > 1.0 year; 3) short for TH; 4) positive family history of

pubertal delay (maternal menarche ≥ 15.0 years, late paternal growth spurt and shaving).

46 Part I

3

Assessment of criteria for diagnostic workup

Assuming that out of the 182 subjects 13 were “diseased” and 169 “non-diseased”, we

calculated the sensitivity, specificity, and positive likelihood ratios (LR+) of suggested

selection criteria for 3–10-year-old children and adolescents [5, 32] in the Netherlands

for referral to specialist care for diagnostic workup. We also investigated these param-

eters for the Finnish algorithm [6, 7]. The results are shown in Tables 2 and 4.

The highest sensitivity (85%), as is desirable in referred patients, is found for a combi-

nation of the six Dutch criteria.

Table 4. Sensitivity, specificity and positive likelihood ratio

Sensitivity Specificity Positive Likelihood ratio (LR+)

Dutch algorithm

Criterion 1 Current criterion adolescents, HSDS <-2.5

54 (25-81) 85 (79-90) 3.64 (1.96-6.77)

Criterion 2HSDS <-2.0 + dysmorphisms/ disproportions

23 (5-54) 92 (87-96) 3.00 (0.98-9.21)

Criterion 3HSDS <-2.0 + HSDS >1.6 below THSDS

54 (25-81) 68 (60-75) 1.69 (0.97-2.92)

Criterion 4HSDS <-2.0 + height deflection >1.0 SDS

31 (9-61) 86 (80-91) 2.17 (0.88-5.31)

Criterion 5HSDS >2.5 below THSDS

15 (2-45) 93 (88-96) 2.17 (0.54-8.67)

Criterion 6Recent growth deflection, defined as >0.5 SDS/1 year, >0.7 SDS/2year or >1SD/undefined time

23 (5-54) 89 (83-93) 2.05 (0.70-6.04)

Criterion 1 and 2 54 (25-81) 81 (74-87) 2.84 (1.57-5.14)

Criterion 1 and 5 54 (25-81) 82 (76-88) 3.03 (1.67-5.52)

Criterion 1, 2 and 5 54 (25-81) 79 (72-85) 2.53 (1.41-4.52)

Criterion 1, 2, 4 and 5 62 (32-86) 74 (67-80) 2.36 (1.43-3.89)

Any of the 6 growth criteria positive 85 (55-98) 55 (47-63) 1.88 (1.41-2.50)

Finnish algorithm

Criterion 1HSDS ≤ -2.2414

62 (32-86) 72 (65-79) 2.21 (1.35-3.63)

Criterion 2THSDSDEV ≥ 2.2414 * SD

38 (14-68) 76 (69-82) 1.59 (0.76-3.31)

Criterion 3ΔHSDS ≤ -2.2414

0 (0-71) 84 (70-93) 0.00

Any of the 3 growth criteria positive 62 (32-86) 59 (51-67) 1.51 (0.95-2.40)

Values are percent or ratio (95% confidence interval). HSDS, Height SDS; THSDS, target height SDS.


3

Of the single criteria a height SDS less than –2.5 and a height SDS less than –2.0 in

combination with a HSDS >1.6 below TH had the highest sensitivity (both 54%), at

specificities between 68% and 85%. The complete Finnish algorithm gave a lower

outcome (sensitivity 62%). The specificities of both approaches were similar (55% and

59%).

Discussion

The present study evaluated etiology and criteria for diagnostic workup in adolescents

with growth failure in clinical practice. First, our results show that in 13 cases (7%)

a specific diagnosis could be established for their growth failure. Second, CDGP was

found in 10% of the adolescents who were old enough to allow for this diagnosis.

Third, the Dutch evidence-based auxological criteria (for 3.0–9.9-year-old children) for

specialized diagnostic workup showed a high sensitivity (85%), which was higher than

the sensitivity obtained by using the Finnish algorithm (62%). However, the overall

specificities for both guidelines are too low for population screening.

The prevalence of pathologic causes for growth failure in adolescents in our study is

similar to those in previous observations in children up to 10 years, varying between

3.0% and 9.5% [1–4]. This contrasts to a study in an academic setting on 235 children

and adolescents (mean age 10.1 years), which reported an incidence of 1.3 % [8]. This

discrepancy may be explained by exclusion in the latter study of children with low height

velocity and/or abnormal symptoms, and a high percentage of missing data. Thus,

although pathological causes for growth failure are usually uncovered at a younger age,

significant pathology in adolescents can still be found.

Growth disorders which one may expect in adolescents are acquired disorders or

congenital disorders with a relatively mild phenotype. We did not detect individuals

with Turner syndrome or a SHOX defect. Likely, most children with these conditions

have been diagnosed at an earlier age. We detected celiac disease in two adolescents,

illustrating that celiac disease should be ruled out in any child or adolescent with

growth failure [8, 33]. Furthermore, we demonstrate that not all adolescents with a

pathological cause for their growth failure were in fact short (HSDS less than –2.0).

Two cases (case 4 and 7) presented with a HSDS just above –2.0 in combination with

growth deflection. The other two (case 3 and 6) showed growth deflection but their

height was still normal.

48 Part I

3

The term “CDGP” has been used for a condition characterized by delayed pubertal on-

set (≥13 in females or ≥14 years in males), relatively short stature, delayed bone age and

usually a positive family history for delayed puberty. With this classical definition, it has

been difficult to establish the diagnosis in older adolescents who may have entered late

into puberty, but in whom the exact age at pubertal onset is uncertain. The development

of stage line diagrams for Tanner stages (puberty nomograms) [10, 15, 16] has now

made it possible to express Tanner stage as SDS for age, so that a Tanner stage less than

–2.0 SDS can be used as an additional criterion for CDGP (type 2). In our study, 10% of

the patients presenting at an age above the cut-off limits, could be diagnosed as CDGP,

and one patient was diagnosed as gonadal dysgenesis. In younger adolescents at least a

similar percentage would be expected with time.

Our second aim was to probe the efficacy of various referral criteria for diagnostic

workup in adolescents. A retrospective investigation of various criteria for specialized

diagnostic workup showed a high sensitivity (85%) when applying the evidence-based

Dutch criteria as used in younger children, consisting of a combination of HSDS,

height distance to THSDS and growth rate. So, these criteria appear suitable for pa-

tients referred to secondary or tertiary care clinics. However, for population screening

the specificities of the Dutch and Finnish guidelines are too low. Similarly to our find-

ings in 0–3 and 3–9.9 years old children [30], two essential growth criteria are most

important for adolescents: for acquired growth disorders height deflection is the major

criterion, while in congenital growth disorders the distance to target height is most

important [5]. Therefore, physicians are advised to collect data on previous growth

data and parental height for proper analysis of growth at the first visit to the clinic,

Obviously, this should always be combined with taking a proper medical history and

physical examination [34].

The establishment of auxological criteria in adolescents for population screening is

complicated, mainly because growth rate may substantially decrease in adolescents

with a late or relatively late puberty, in contrast with usually stable growth in childhood.

This implies that parameters for growth monitoring used in younger children can be

expected to be less specific in adolescents than in childhood. Indeed, our study shows

that the evidence-based criteria for referral and diagnostic workup in 3.0–9.9 years old

children show low specificities and positive likelihood ratios, rendering these criteria

unsuitable for routine growth monitoring in the general population. However, the

sensitivity for detecting pathology in our cohort of children referred for growth failure

in a secondary hospital setting is 85%. Therefore, we feel that these criteria may still


3

serve as practical guidelines in the diagnostic workup of children referred to secondary

and tertiary care for suspected disorders of growth.

We acknowledge several limitations of this study. First, this is a cohort studied in a re-

gional, general hospital in a well-developed health care system (encompassing primary,

secondary and tertiary health care), and the diagnostic yield and the nature of diagnoses

may be different in academic centers and in different health care systems. Second, the

total number of studied cases is limited, so analyses had to be limited to descriptive

statistics. For similar reasons, the 95% confidence intervals of likelihood ratios for the

elements of growth aberration are wide. Third, we have not been able to investigate the

specificity of the various criteria in a general population, although the low specificity in

the referred cases make it likely that population specificity may be even lower. Fourth,

the lack of routine assessment by a clinical geneticist in the majority of cases might

have led to undiagnosed growth disorders that are associated with only slightly unusual

phenotypes. However, this mirrors the general policy of most general hospitals, in

which patients usually are only referred if the phenotype is clearly abnormal.

In conclusion, pathological causes for growth failure in adolescents were found in 7%

and CDGP in 10%. A combination of height SDS, distance to THSDS and growth deflec-

tion is recommended in adolescents to guide the decision to perform further diagnostic

testing.

Acknowledgments

We wish to thank Antti Saari, Ulla Sankilampi and Leo Dunkel for providing us with

the algorithms of the Finnish referral criteria; and Bea Jansen van ‘t Land, Desirée

Paap, Lidi Schilperoort, Irene Bergsma and Ingrid van de Woude (specialized nurses

of the Tergooi growth clinic, Tergooi Hospitals, Hilversum, The Netherlands) for their

good care of the patients at the growth clinic and for performing accurate auxological

measurements.


The authors declare that they have no conflicts of interest to disclose.

50 Part I

3

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4. Voss LD, Mulligan J, Betts PR, Wilkin TJ. Poor growth in school entrants as an index of organic disease: the Wessex growth study. BMJ 1992;305:1400–2.

5. Grote FK, van Dommelen P, Oostdijk W, de Muinck Keizer-Schrama SM, Verkerk PH, et al. Developing evidence-based guidelines for referral for short stature. Arch Dis Child 2008;93:212–7

6. Saari A, Harju S, Makitie O, Saha MT, Dunkel L, et al. Systematic growth monitoring for the early detection of celiac disease in children. JAMA Pediatr 2015;169:e1525.

7. Saari A, Sankilampi U, Hannila ML, Saha MT, Makitie O, et al. Screening of turner syndrome with novel auxological criteria facilitates early diagnosis. J Clin Endocrinol Metab 2012;97:E2125–32.

8. Sisley S, Trujillo MV, Khoury J, Backeljauw P. Low incidence of pathology detection and high cost of screening in the evaluation of asymptomatic short children. J Pediatr 2013;163:1045–51.

9. Palmert MR, Dunkel L. Clinical practice. Delayed puberty. N Engl J Med 2012;366:443–53.

10. Lawaetz JG, Hagen CP, Mieritz MG, Blomberg Jensen M, Petersen JH, et al. Evaluation of 451 Danish boys with delayed puberty: diagnostic use of a new puberty nomogram and effects of oral testosterone therapy. J Clin Endocrinol Metab 2015;100:1376–85.

11. Sedlmeyer IL, Palmert MR. Delayed puberty: analysis of a large case series from an academic center. J Clin Endocrinol Metab 2002;87:1613–20.

12. Prader A. Delayed adolescence. Clin Endocrinol Metab 1975;4:143–55.

13. Rogol AD, Hayden GF. Etiologies and early diagnosis of short stature and growth failure in children and adolescents. J Pediatr 2014;164(5 Suppl):S1–14.

14. Wit JM, Ranke MB, Kelnar CJ. ESPE classification of

pediatric endocrine diagnoses. Horm Res Paediatr 2007;68:1–120.

15. van Buuren S. Puberty Plot Pro Web Application, TNO Quality of Life. 2008. Available at: http://vps.stefvanbuuren.nl/puberty/.

16. van Buuren S, Ooms JC. Stage line diagram: an age-conditional reference diagram for tracking development. Stat Med 2009;28:1569–79.

17. Niklasson A, Ericson A, Fryer JG, Karlberg J, Lawrence C, et al. An update of the Swedish reference standards for weight, length and head circumference at birth for given gestational age (1977–1981). Acta Paediatr Scand 1991;80:756–62.

18. Schönbeck Y, Talma H, van Dommelen P, Bakker B, Buitendijk SE, et al. The world’s tallest nation has stopped growing taller: the height of Dutch children from 1955 to 2009. Pediatr Res 2013;73:371–7.

19. van Buuren S. TNO Growth Calculator. 2013. Available at: http://groeiweb.pgdata.nl/general.asp/.

20. van Dommelen P, Schönbeck Y, van Buuren S. A simple calculation of the target height. Arch Dis Child 2012;97:182.

21. Cole TJ, Roede MJ. Centiles of body mass index for Dutch children aged 0–20 years in 1980 – a baseline to assess recent trends in obesity. Ann Hum Biol 1999;26:303–8.

22. Fredriks AM, van Buuren S, Burgmeijer RJ, Meulmeester JF, Beuker RJ, et al. Continuing positive secular growth change in The Netherlands 1955–1997. Pediatr Res 2000;47: 316–23.

23. Rappold G, Blum WF, Shavrikova EP, Crowe BJ, Roeth R, et al. Genotypes and phenotypes in children with short stature: clinical indicators of SHOX haploinsufficiency. J Med Genet 2007;44:306–13.

24. Fredriks AM, van Buuren S, van Heel WJ, Dijkman-Neerincx RH, Verloove-Vanhorick SP, et al. Nationwide age references for sitting height, leg length, and sitting height/height ratio, and their diagnostic value for disproportionate growth disorders. Arch Dis Child 2005;90:807–12.

25. Marshall WA, Tanner JM. Variations in pattern of pubertal changes in girls. Arch Dis Child 1969;44:291–303.

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27. Mul D, Fredriks AM, van Buuren S, Oostdijk W, Verloove-Vanhorick SP, et al. Pubertal development


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in The Netherlands 1965–1997. Pediatr Res 2001;50:479–86.

28. Greulich WW, Pyle SI. Radiograph Atlas of Skeletal Development of the Hand and Wrist, 2nd ed. Stanford: Stanford University Press, 1959.

29. Cohen P, Rogol AD, Deal CL, Saenger P, Reiter EO, et al. Consensus statement on the diagnosis and treatment of children with idiopathic short stature: a summary of the Growth Hormone Research Society, the Lawson Wilkins Pediatric Endocrine Society, and the European Society for Paediatric Endocrinology Workshop. J Clin Endocrinol Metab 2008;93:4210–7.

30. Stalman SE, Hellinga I, van Dommelen P, Hennekam RC, Saari A, et al. Application of the Dutch, Finnish and British screening guidelines in a cohort of children with growth failure. Horm Res Pediatr 2015;84:376–82.

31. Hermanussen M, Cole J. The calculation of target height reconsidered. Horm Res 2003;59:180–3.

32. Oostdijk W, Grote F, Wit JM, de Munick Keizer-Schrama SM. [NVK Guideline Short Stature]. Available at: http://www.nvk.nl/Portals/0/richtlijnen/kleine%20lengte/kleinelengte.pdf.

33. van Rijn JC, Grote FK, Oostdijk W, Wit JM. Short stature and the probability of coeliac disease, in the absence of gastrointestinal symptoms. Arch Dis Child 2004;89:882–3.

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chapter 4Diagnostic Work-up and Follow-up in Children with Tall Stature:

A Simplified Algorithm for Clinical Practice

Susanne E. Stalman*, Anke Pons*, Jan M. Wit,

Gerdine A. Kamp, Frans B. Plötz


54 Part I

4

Abstract

Objective

No evidence-based guideline has been published about optimal referral criteria and

diagnostic work-up for tall stature in children. The aim of our study was to describe

auxological and clinical characteristics of a cohort of children referred for tall stature,

to identify potential candidates for adult height reduction, and to use these observa-

tions for developing a simple algorithm for diagnostic work-up and follow-up in clini-

cal practice.

Methods

Data regarding family and medical history, auxological measurements, bone age de-

velopment, physical examination, additional diagnostic work-up, and final diagnosis

were collected from all children referred for tall stature, irrespective of their actual

height standard deviation score (HSDS). Predicted adult height (PAH) was calculated in

children above 10 years. Characteristics of patients with an indication for adult height

reduction were determined.

Results

Hundred thirty-two children (43 boys) with a mean ± SD age of 10.9±3.2 (range 0.5-

16.9) years were included in the study. Fifty percent of the referred children had an

HSDS ≤2.0 (n=66). Two pathological cases (1.5%) were found (HSDS 2.3 and 0.9).

Tall children without pathology were diagnosed as idiopathic tall, further classified as

familial tall stature (80%), constitutional advancement of growth (5%), or unexplained

non-familial tall stature (15%). Of the 74 children in whom PAH was calculated, epi-

physiodesis was considered in six (8%) and performed in four (5%) patients.

Conclusion

The incidence of pathology was very low in children referred for tall stature, and few

children were potential candidates for adult height reduction. We propose a simple

diagnostic algorithm for clinical practice.

55

4

Diagnostic Work-up and Follow-up in Tall Children

Introduction

Tall stature is defined as a height of more than 2.0 standard deviations (SD) above

the corresponding mean height for age and sex as observed in the population [1,2].

Although there are as many children with tall stature as children with short stature, tall

stature is a less common reason for referral from primary health care to specialist care

than short stature [2].

There are two main reasons to refer children with tall stature. First, like in short stat-

ure, it is important to distinguish between normal variation and pathology [3]. There is

some confusion about the nomenclature of non-pathological causes of tall stature. In

the European Society for Paediatric Endocrinology (ESPE) Classification of Paediatric

Endocrine Diagnoses [3], this group was denominated as idiopathic tall stature (ITS)

and further subdivided into genetic (familial) tall stature (or constitutional tall stature)

and non-familial tall stature (NFTS). Later, several authors coined the term “constitu-

tional advancement of growth” (CAG) [1,3,4] for tall children with a height beyond the

target height (TH) range but with coincident bone age (BA) advance, who therefore

would be expected to end up with a normal adult height. The second reason for refer-

ral of tall children is to predict adult height and thus to identify potential candidates

for adult height reduction [5]. Recommendations regarding follow-up of tall children

are lacking, in particular with respect to indications for interventions to reduce adult

height. We have learned from clinical experience that some children with a normal

height can reach very tall adult stature if bone maturation and/or puberty are extremely

delayed. In addition, only few data have been published about the characteristics of

patients who eventually underwent adult height reduction by epiphysiodesis [5,6].

So far, no evidence-based (inter) national guideline has been published about optimal

referral criteria, diagnostic work-up, and follow-up for tall stature. Various expert-

based algorithms have been proposed to identify pathological causes although in

the majority, no pathology can be found [1,4,7]. Here, our first aim was to describe

auxological and clinical characteristics of a cohort of children referred for tall stature to

a general pediatric clinic. Our second aim was to identify potential candidates for adult

height reduction. Based on these observations and published literature, we propose a

simple algorithm for diagnostic work-up and follow-up of children with tall stature

which, we hope, will be prospectively validated in the future.

56 Part I

4

Methods

Study Population

In this study, we included all children referred for tall stature, irrespective of their

actual height standard deviation score (HSDS), to the general (non-academic) pediatric

growth clinic of Tergooi Hospitals in the Netherlands between January 2010 and March

2014. Exclusion criteria were ethnicity other than Dutch (defined as at least one parent

with non-western European ethnicity) and missing medical records.

Data Collection

All patients underwent a four-step diagnostic program. First, the parents completed a

questionnaire regarding perinatal and medical history (with special attention to psy-

chomotor/mental development and behavior), medication use, pubertal signs, growth

and family history regarding height, puberty onset and medical history of first-degree

relatives. Second, BA was assessed by a single pediatrician (G.K.) according to the

method of Greulich and Pyle [8] and BA advance or delay was calculated as BA minus

chronological age (CA). Third, height, weight, head circumference, sitting height

(SH), arm span, blood pressure, and heart rate were measured. Parental height could

be measured in most cases (approximately 95%), the remaining parental height data

were based on reported values. TH was calculated based on father’s height (FH) and

mother’s height (MH) according to two equations, both without secular trend correc-

tion. We used the traditional Tanner formula ((FH+MH)/2+ or -6.5) [9] and conditional

TH (cTH) based on the most recent Dutch growth study reported by van Dommelen et

al [10] (44.5+0.376xFH+0.411xMH for boys and 47.1+0.334xFH+0.364xMH for girls).

SDS of the following items were calculated based on appropriate reference data: height

(HSDS) [11]; TH (in cm and SDS) [9] and cTH (in cm and SDS) [10]; body mass index

(BMI) [12]; head circumference [13]; sitting height/height ratio (SH/H) [14]; and birth

weight, length and head circumference [15]. The HSDS distance to THSDS according

to Tanner as well as to cTHSDS according to van Dommelen et al [10] was calculated,

and we also calculated the difference between the patient’s HSDS and the HSDS of the

tallest parent. Predicted adult height (PAH) was calculated in children above 10 years

according to Bayley and Pinneau [16] and an update of the formula of De Waal et al

[17] based on the change of the TH formula because of the discontinuation of secular

trend in the Netherlands [11]: 267.02+(0.62xheight) + (2.75xcTHSDS) - (10.49xCA)

- (12.98xBA) + (0.72xCAxBA) for boys and 158.42+(0.74xheight) + (1.47xcTHSDS)

57

4


- (5.90xCA) - (7.70xBA) + (0.41xCAxBA) for girls (Wit and van Dommelen, personal

communication). Finally, one pediatrician (G.K.) reviewed the questionnaire, BA, and

the auxological measurements and performed a complete physical and neurological

examination. The physical examination was focused on detecting body disproportion

(defined as SH/H ratio >-2.2 SDS) [14] and specific dysmorphic features rated on

syndrome-specific checklists. Pubertal development was rated according to Tanner

[18,19].

Diagnostic Work-up

Briefly, diagnostic work-up in order to uncover pathologic causes for tall stature was

considered in case of presence of the following features: developmental and/or speech

delay, behavioral problems, dysmorphisms, disproportion, a distance between HSDS

and THSDS >2.0, a recent growth acceleration, pubertal development not appropriate

for age, or indications of other hormonal disorders such as growth hormone excess or

hyperthyroidism.

Definitions

Pathological tall stature was subclassified into two categories: children with a dysmor-

phic syndrome with overgrowth (primary growth disorder) and those with tall stature

caused by endocrine diseases (secondary growth disorder) [3]. Non-pathological tall

stature is considered a normal variant, probably caused by multiple gene variants with

a positive effect on linear growth [20] and maturation. Because the precise etiology

is unknown, this condition is termed ITS in the ESPE Classification of Paediatric En-

docrine Diagnoses [3], and further classified into two subclasses: familial tall stature

(FTS) (explained by gene variants associated with linear growth) and NFTS. In our

study, we further distinguished in the latter group two conditions: CAG (hypothetically

explained by gene variants associated with a fast tempo of growth, “maturation”) and

others unexplained by genetic factors.

Three ways to distinguish FTS from NFTS were used. First, FTS was defined as a HSDS

distance to THSDS <2.0 based on the Tanner equation and TH range of +/- 2.0 SD [9].

Second, we subclassified the children based on the distance to cTHSDS [10], with a

cTH range of +/-1.6 SD (children with a HSDS minus cTHSDS <1.6 were classified as

FTS). Third, we reasoned that tall height can appear as a dominantly inherited condi-

tion, either monogenic (e.g., in Marfan syndrome), or polygenic (if the child inherits

by chance mostly “tall gene variants” from the tallest parent). So, tall children were

58 Part I

4

also denominated as FTS if they were tall (HSDS>+2.0) and their HSDS minus HSDS of

the tallest parent was below +1.6. CAG was defined as NFTS with an advanced BA >2.0

years [8].

Children with a HSDS ≤2.0 were classified as ‘not-tall’. These children were included in

the study because the reason for referral was identical to that of children with a HSDS

>2.0. Characteristics of not-tall and tall children were compared, including their HSDS,

THSDS, HSDS-THSDS, BMI, BA-CA, and PAH data.

Adult Height Reduction

Adult height reduction by epiphysiodesis was considered for a PAH of >205 cm (+3.0

SDS) in boys or >185 cm (+2.3 SDS) in girls [5] with PAH based on the formula of De

Waal et al [17], since this is considered the most accurate for tall stature in the Nether-

lands. These patients were assessed separately to determine the characteristics of this

group. Furthermore, children with a PAH >205 cm (boys) or >185 cm (girls), regard-

less of their HSDS at presentation, were assessed to identify patients with a HSDS ≤2.0

at presentation who might still have an indication for adult height reduction and to

determine their characteristics.

Analysis

All data were collected from hospital files and were analysed in Statistical Package for

the Social Sciences, version 19. Descriptive statistics were used to quantify the preva-

lence of pathologic causes for tall stature and the analysis of the different diagnostic

group characteristics. Independent t-tests for continuous variables and chi-square tests

for categorical variables were used to compare characteristics between boys and girls

and between different diagnostic groups. A value of p<0.05 (two-sided) was considered

statistically significant.

Ethical Approval


Hospitals (letter reference kv/15.05).

59

4


Results

Study Population

During this study period, 139 children were referred for tall stature, of whom seven

children were excluded because of missing data (n=4) or non-Dutch ethnicity (n=3).

Patient characteristics of the 132 children included for analysis are shown in Table 1.

Diagnostic Work-up

The adherence to our initial four-step diagnostic work-up protocol was 100% and ad-

ditional diagnostic work-up was performed in 19 patients (14.4%) based on clinical

judgement using a local protocol and various flow charts [1,4,7]. In 5 children with

dysmorphic features, one of whom showed slight body disproportion (long legs),

genetic testing revealed no specific diagnosis (Marfan syndrome was excluded). In

ten children, the head circumference was >2.0 SDS. Given the low Sotos score on the

checklist [21], no diagnostic work-up was indicated. Thirteen children did not meet any

Table 1. Characteristics of the study population, according to gender

Total n=132 Boys n=43 (32.6%) Girls n=89 (67.4%) Sign.

Age, yrs 10.9 ± 3.2 (0.5 - 16.9) 10.1 ± 3.8 (1.7 - 16.9) 11.2 ± 2.9 (0.5 - 16.6) P=0.10

HSDS 2.0 ± 0.7 (0.1 - 3.7) 2.4 ± 0.7 (0.7 - 3.7) 1.9 ± 0.7 (0.1 - 3.5) P<0.01

THSDS (Tanner) 1.1 ± 0.7 (-0.9 – 2.6) 1.0 ± 0.6 (-0.7 – 2.4) 1.2 ± 0.7 (-0.9 - 2.6) P=0.60

cTH SDS (Van Dommelen) 0.8 ± 0.5 (-0.7 - 1.9) 0.8 ± 0.5 (-0.5 - 1.9) 0.8 ± 0.5 (-0.7 - 1.8) P=0.61

SH/H ratio SDS -0.5 ± 0.7 (-2.2 - 1.1) -0.4 ± 0.8 (-2.2 - 1.0) -0.6 ± 0.7 (-1.9 - 1.1) P<0.05

BA-CA, yrs 0.4 ± 1.3 (-3.9 – 4.3) 0.7 ± 1.3 (-2.4 – 3.5) 0.2 ± 1.3 (-3.9 – 4.3) P=0.02

BL SDS 1.6 ± 1.5 (-3.6 – 4.9) 1.6 ± 1.9 (-3.6 - 4.9) 1.6 ± 1.2 (-0.5 – 4.1) P= 0.98

BW SDS 0.7 ± 1.0 (-2.5 - 3.0) 0.8 ± 1.1 (-2.5 - 2.8) 0.7 ± 1.0 (-1.8 - 3.0) P=0.95

GA, weeks 39.6 ± 1.9 (32,0 - 42,0) 39.4 ± 1.8 (33.4 - 42.0) 39.6 ± 1.9 (32.0 - 42.0) P=0.52

BMI SDS 0.2 ± 1.1 (-2.6 - 3.0) 0.5 ± 1.1 (-1.5 - 3.0) 0.1 ± 1.0 (-2.6 - 2.4) P=0.05

PAH (De Waal)SDS (≥ 10 yrs)*

1.6 ± 0.6 (-0.3 – 2.7) 1.8 ± 0.7 (-0.3 – 2.7) 1.5 ± 0.6 (-0.2 - 2.6) P=0.11

PAH (Bayley and Pinneau) SDS (≥10 yrs)*

1.8 ± 0.9 (-0.3 – 2.7) 2.4 ± 0.7 (0.2 – 4.0) 1.6 ± 0.8 (-0.3 - 3.3) P<0.01

Mean ± SD (range)

HSDS: height SDS, THSDS: target height SDS (according to Tanner), cTH SDS: conditional target height SDS

(according to Van Dommelen), SH/H: sitting height/height, BA-CA: bone age minus calendar age, BL: birth

length, BW: birth weight, GA: gestational age, BMI: body mass index, PAH: predicted adult height

* PAH calculated in 74 patients (18 boys and 56 girls).

60 Part I

4

of the three definitions for FTS (HSDS-THSDS >2.0, HSDS-cTHSDS >1.6, and HSDS-

HSDS of tallest parent >1.6). Three of these children had an advanced BA of >2.0 years

and were classified as CAG. Seven children had an advanced BA of >1.0 year (1.2-1.9

SDS). Additional work-up was performed in two out of these seven children to rule

out secondary growth disorders, which revealed no abnormalities. In the remaining

five, no diagnostic work-up was performed, but during follow-up, no abnormal growth

pattern was observed. In two out of three pre-pubertal patients with a recent growth

acceleration, additional work-up was performed and revealed no specific diagnosis. In

six patients with a pubertal development not appropriate for age, the additional work-

up showed precocious puberty in two patients. Diagnostic work-up to reveal secondary

growth disorders was performed in six children and found negative.

Diagnoses

A pathological cause of tall stature was found in the two patients with precocious pu-

berty (1.5%). In one patient, the diagnosis was made based on clinical features (recent

growth acceleration, HSDS 2.3, an advanced BA development, a reported onset of

puberty of 7.5 years, and Tanner pubertal stage B3/P3 at the age of 9.4 years) [22]. In

the other patient (5.3 years), the diagnosis was based on clinical features (pubertal de-

velopment, Tanner B2/P1, HSDS 0.9) and a positive gonadotropin-releasing hormone

test.

Fig. 1 shows histograms of HSDS minus THSDS (a), HSDS minus cTH (b) and the

child’s HSDS minus HSDS of the tallest parent (c). The mean values are 0.9, 1.2, and

0.4, showing that the child’s height is on average closest to the tallest parent’s height.

The number of idiopathic tall children labelled FTS according to the three definitions

(HSDS-THSDS >2.0, HSDS-cTH >1.6 and HSDS-HSDS of tallest parent >1.6) was 50

(77%), 21 (32%), and 46 (71%), respectively. Fifty-two children complied with at least

one of these definitions (80%) and were labelled FTS. Of the 13 children with NFTS,

3 were labelled CAG. Fig. 2 demonstrates the correlation between HSDS distance to

THSDS (Tanner) and BA development in the 65 children with non-pathological tall

stature, showing a relatively advanced BA development in children who are taller than

THSDS (Pearson correlation 0.45, p<0.01).

Exactly fifty percent of the children referred for tall stature had an HSDS ≤2.0 (n=66),

so were classified as not-tall (Table 2). There was no difference in THSDS between both

groups, but tall children had a significantly more advanced BA development compared

to not-tall. To answer the question why so many not-tall children were indeed referred

61

4


A

HSDS - THSDS (Tanner)

4.003.503.002.502.001.501.00.50.00-.50-1.00-1.50-2.00-2.50-3.00-3.50-4.00

N (n

umbe

r of

pat

ient

s)

30

25

20

15

10

5

0

a.

Page 1

B

HSDS - THSDS (van Dommelen)

4.003.503.002.502.001.501.00.50.00-.50-1.00-1.50-2.00-2.50-3.00-3.50-4.00

N (n

umbe

r of

pat

ient

s)

30

25

20

15

10

5

0

b.

Page 1

C

HSDS - tallest parent HSDS

4.003.503.002.502.001.501.00.50.00-.50-1.00-1.50-2.00-2.50-3.00-3.50-4.00

N (n

umbe

r of

pat

ient

s)

30

25

20

15

10

5

0

c.

Figure 1. Distributions of HSDS distance to THSDS (a), conditional target height standard deviation score (b)

and HSDS distance to tallest parental HSDS (c).

HSDS: height standard deviation score, THSDS: target height standard deviation score.

62 Part I

4

HSDS - THSDS (Tanner)

4.03.02.01.0.0

BA -

CA

4.00

3.00

2.00

1.00

.00

-1.00

-2.00

-3.00

Figure 2. Correlation between HSDS distance to THSDS (according to Tanner) and bone age advancement

HSDS: height standard deviation score.

THSDS: target height standard deviation score, BA: bone age, CA: chronological age.

63

4


Tabl

e 2.

Cha

ract

eris

tics

of n

ot-t

all a

nd ta

ll bo

ys a

nd g

irls

Boy

sG

irls

Not

-tal

l n =

14

Tall

n =

29

Not

-tal

l n =

52

Tall

n =

37

Age

at p

rese

nta

tion

, yea

rs11

.5 ±

3.4

(5.5

– 1

6.7)

9.5

± 3

.8 (1

.7 –

16.

9)11

.4 ±

2.7

(5.3

– 1

5.6)

10.9

± 3

.2 (0

.5 –

16.

6)

HSD

S 1.

6 ±

0.4

(0.7

– 2

.0) *

2.

7 ±

0.4

(2.1

– 3

.7) *

1.4

± 0

.5 (0

.1 –

2.0

) *2.

6 ±

0.4

(2.1

– 3

.5) *

TH

SDS

(Tan

ner

)1.

0 ±

0.7

(-0.

7 –

2.0)

1.0

± 0

.6 (-

0.2

– 2.

4)1.

2 ±

0.7

(-0.

9 –

2.6)

1.2

± 0

.7 (-

0.3

– 2.

6)

HSD

S-T

HSD

S (T

ann

er)

0.6

± 0

.9 (-

0.8

– 2.

8) *

1.7

± 0

.7 (0

.0 –

3.2

) *0.

2 ±

0.9

(-2.

1 –

2.9)

*1.

4 ±

0.7

(0.1

– 2

.6) *

BM

I SD

S 0.

4 ±

0.9

(-1.

0 –

2.0)

0.5

± 1

.1 (-

1.5

– 2.

7)0.

0 ±

1.0

(-2.

6 –

1.8)

0.2

± 1

.1 (-

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4)

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0.

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*-0

.1 ±

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(-2.

7 –

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*0.

7 ±

1.2

(-2.

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4.3)

*

PAH

(De

Waa

l)

SDS

(≥ 1

0 yr

s)**

1.6

± 0

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0.3

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4)

2.0

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(B&

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05 c

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cm

in g

irls

n =

2n

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l)

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m in

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irls

n =

0n

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n =

1n

= 5

Mea

n ±

SD

(ran

ge).

HSD

S: h

eigh

t SD

S, T

HSD

S: ta

rget

hei

ght S

DS

(acc

ordi

ng to

Tan

ner)

, BM

I: b

ody

mas

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dex,

BA

-CA

: bon

e ag

e m

inus

cal

enda

r ag

e, P

AH

: pre

dict

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t hei

ght,

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ayle

y &

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.

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ted

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and

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64 Part I

4

with “a fear to become too tall”, we evaluated their family history regarding parental

height and parental pubertal development, showing that in 33 out of 66 (50%) not-tall

children, at least one parent had a HSDS >2.0 or had a delayed puberty, compared to 29

out of 66 (44%) tall children (p=0.49).

Adult Height Reduction

In all 74 children above 10 years of age, PAH was calculated (Table 1). PAH based on

Bayley and Pinneau [16] resulted in five boys with a prediction >205 cm and 13 girls

with a prediction >185 cm. Of these patients, two boys and two girls had a HSDS ≤2.0.

Both girls had a delay in puberty. Using the De Waal method, we found that none of the

boys had a PAH >205 cm, while six girls had a PAH >185 cm. One of these girls was not

tall, but she had pubertal delay. Four patients (3.0%) wished to be referred for adult

height reduction by epiphysiodesis (Table 3). One girl who underwent epiphysiodesis

did not meet the criteria for treatment at the first presentation, but did so on return two

years later.

Discussion

In our population referred for tall stature, 50% had indeed a height >2.0 SDS. Two pa-

tients were diagnosed with precocious puberty (1.5%); one of them had a HSDS of 0.9,

but a recent growth acceleration. Of the idiopathic tall children, 80% were diagnosed

as FTS, 5% as CAG and 15% remained unexplained. In all children older than 10 years

Table 3. Characteristics of 4 patients who underwent epiphysiodesis

Sex Male Female Female Female

Age at presentation, yrs 15.8 10.5 12.5 13.0 14.9

HSDS 2.4 2.7 2.6 2.6 2.0

THSDS 1.2 2.6 2.5 2.3 0.5

BA-CA, yrs -1.83 0.74 -0.28 -0.53 -2.68

PAH SDS (cm)(de Waal)

2.7 (203.1) 1.9 (182.8) 2.4 (185.8) 2.5 (186.5) 2.3 (185.1)

PAH SDS (cm)(Bayley and Pinneau)

4.0 (211.9) 1.7 (181.1) 2.3 (185.2) 3.0 (189.7) 3.3 (191.7)

HSDS: height SDS, THSDS: target height SDS (according to Tanner), BA-CA: bone age minus calendar age,

PAH: predicted adult height.

65

4


(n=74) PAH was calculated, and in only six (8%), epiphysiodesis was considered and

eventually performed in four (5%) patients.

Although the incidence of pathology in children referred for tall stature is very low, it

remains important to rule out chromosomal, genetic, or endocrine disorders. A careful

history, in particular developmental delay and behavioral problems, may be suggestive

for chromosomal disorders, whereas specific findings on examination, like dysmor-

phisms and macrocephaly, may be suggestive for specific genetic syndromes. The most

common genetic causes of tall stature are Klinefelter syndrome, Marfan syndrome,

Sotos syndrome, and Beckwith-Wiedemann syndrome (BWS) [23], with an incidence

of 1.1-1.7 per 1000 [24], 2-3 per 10.000 [25], 1 per 15.000 [26], and 1 per 13.700 [27]

individuals, respectively. Precocious puberty is the most common endocrine cause

of accelerated growth. Based on these numbers, it is not unexpected that no primary

growth disorders and only two secondary growth disorders have been diagnosed in our

population.

To determine whether tall stature is familial or not, the usual approach has been to

compare the child’s height with the height of both parents. Conventionally, accord-

ing to Tanner et al [9], this has been expressed as the midparental height (TH) with a

range of +/- 2.0 SD. In theory, however, the cTH [10,28], with additional corrections

for parent-parent and parent-offspring correlations, with a range of +/-1.6 would be

expected to be superior. Our results suggest that the cTH range (+/-1.6 SD) may be too

strict for defining FTS compared to the Tanner TH range (+/-2.0 SD). This is supported

by a previous study showing that only 10% of healthy children show a HSDS outside

their TH range (defined as +/-1.5 SD) [29] and by estimates that 50-90% of the height

variation is accounted for by genetic factors [30].

An alternative approach is to compare the child’s HSDS with the HSDS of the tallest

parent. In theory, this would better accommodate genetic influences of dominant

inheritance, inheritance of predominantly “tall” gene variants in case of discrepancy

between parental heights [1,20,29]. However, no experimental data have been col-

lected about the expected range around the difference between the child’s HSDS minus

the HSDS of the tallest parent. For the detection of pathological causes of tall stature,

this approach appears as not suitable, because one of the most important disorders to

diagnose (Marfan syndrome) is transmitted in a dominant fashion.

Most children with non-FTS show an advanced BA and can be labeled CAG. We have

shown that their PAH is not different from that of children with FTS, confirming previ-

66 Part I

4

ous observations [1,31]. In our opinion, BA assessment remains an important tool in

the differential diagnosis of tall stature.

Assessment of height velocity, expressed as a positive change of HSDS, is part of the

diagnostic work-up, since increased height velocity may be associated with several

rare hormonal causes of tall stature (secondary growth disorders such as precocious

puberty, hyperthyroidism and GH excess) [1]. We believe that the criterion of a change

in HSDS >1.0, over an undefined period of time, may be a too strict rule in children over

the age of 10 years [32], since an acceleration in height velocity is a normal phenom-

enon related to the pubertal stage. Therefore, we propose to first interpret the height

velocity [1] in relation to pubertal development prior to performing additional work-up

to exclude hormonal pathology. In case of doubt, a follow-up visit in three months’

time to reconfirm normal pubertal growth and development may prevent unnecessary

additional tests and costs. Pubertal development should be interpreted in relation to

CA. Both precocious puberty and delayed puberty may be the result of underlying pa-

thology. Precocious puberty causes increased height velocity and thus tall stature during

childhood but a reduced adult height. In contrast, children with a delayed puberty may

present with a normal stature during childhood but may reach a tall adult height [3].

A major reason for referral is to predict adult height and eventually consider adult

height reduction. The present attitude of many pediatric endocrinologists is that inter-

ventions to reduce adult height are to be discouraged. Treating tall girls with estrogen

preparations is considered obsolete by many, because of its association with fertility

disorders in adulthood [33,34]. Treatment of tall boys with high-dose androgens is

rather frequently associated with side effects, and its effect on adult height is limited

[35]. At present, only epiphysiodesis can be offered, which is associated with few com-

plications in experienced hands [6]. Our analysis showed that there is a large difference

in numbers of patients with an indication for epiphysiodesis depending on which

prediction method is used. Indeed, we demonstrated an overestimation of adult height

according to Bayley and Pinneau [16], particularly in boys, compared to De Waal et al

[17], as has been shown in previous studies. Therefore, we advise to use the method of

De Waal et al [17] to calculate PAH, to avoid unnecessary referrals. If a BA is determined

before girls have reached a height of 170 cm and boys 185 cm, there is sufficient time to

discuss the pros and cons of the intervention [5,6].

It is noteworthy that out of the four children in whom epiphysiodesis was performed,

one patient had a HSDS ≤2.0 at first presentation. We therefore suggest that even in

children who are not tall at first presentation, a second referral at height 170 cm before

67

4


Tall stature (height >+2.0 SD)

or Tall for target height (H-TH >+2.0 SD)

Positive family history of delayed puberty?

Marfan suspected? Dysmorphism? Dysproportion? Macrocephaly? Developmental delay? Behavioral problems?

Consultation clinical geneticist, consider: 1) Marfan, homocystinuria etc. 2) XXY, XYY, XXX, Fragile X 3) Sotos, Beckwith-Wiedemann, Weaver etc.

No further follow up

Increased height velocity before puberty? or Exaggerated height velocity during puberty?

Pubertal development appropriate for age?

Tall stature?

Consultation pediatric endocrinologist, consider: 1) Obesity related 2) Hyperthyroidism 3) GH hormone excess 4) (pseudo) precocious puberty

Constitutional delayed puberty or Consultation pediatric endocrinologist, consider: gonadotrophin deficiency etc.

Tall for target height (H-TH >+2.0 SD) or

Tall for tallest parental height (H-pH >+1.6 SD)

Familial tall stature

Non-familial tall stature Advanced bone age?

Consider second referral at height 170 cm in girls and 185 cm in boys for adult height

prediction

Unexplained non-familial tall stature

Constitutional advancement of growth

Advanced

Delayed

Figure 3. Proposed flow chart for the diagnostic work-up of tall children aged 0-17.99 years. The flow chart

consists of two main pathways. Initially, height standard deviation score and distance to target height (Tan-

ner) are calculated. In case of a height standard deviation score ≤2.0 or height standard deviation score -tar-

get height standard deviation score ≤2.0, the child is classified as not-tall or not-tall for target height. We

suggest that a second referral at height 170 cm before the age of 12.5 years in girls and 185 cm before the

age of 14 years in boys for adult height prediction should be considered if a positive family history of delayed

puberty is present. In case of a height standard deviation score >2.0 or height standard deviation score-target

height standard deviation score >2.0, each subsequent step is aimed at excluding pathologic causes requiring

further investigation and possibly treatment. The final step is to determine whether the tall child is familial

tall or non-familial tall.

68 Part I

4

the age of 12.5 years in girls and 185 cm before the age of 14 years in boys for adult

height prediction should be considered if a positive family history of delayed puberty

is present.

Based on our results and review of the literature, we propose a new diagnostic flow chart

(Fig. 3). This flow chart uses a simple step by step strategy and suggests recommenda-

tions for follow-up. Initially, HSDS and distance to TH are calculated. Each subsequent

step is aimed at discovering clues for pathologic causes with severe consequences (e.g.

Marfan syndrome) or pathological causes requiring further investigation and possibly

treatment (e.g. precocious puberty, hyperthyroidism, and growth hormone excess).

The final steps are aimed at classifying children without any established pathology and

providing recommendations for follow-up. We suggest a follow-up visit for children

with unexplained NFTS and others who may be at risk for attaining an extreme tall

stature at a time when they are expected to reach a height of 170 and 185 for girls and

boys, respectively.

We acknowledge there are several limitations of this study. First, it is a retrospective

study performed in a single centre in a general hospital; it is possible that our study

population differs from that in other clinics, particularly academic clinics. Second, our

study population contains a limited number of patients, and only few pathologic causes

of tall stature were found, so only descriptive statistics could be performed. Third, it

cannot be excluded that diagnoses may have been missed in the diagnostic work-up.

In conclusion, we found a low incidence of pathology in children referred for tall stat-

ure to a general paediatric clinic, and adult height reduction was seldom indicated. We

suggest that the diagnostic work-up and follow-up can be minimal in most children,

and propose a diagnostic algorithm for clinical practice.

Acknowledgments

We thank Dr. Wilma Oostdijk and Dr. Sabine Hannema for helpful comments on a pre-

vious version of the manuscript. We wish to thank Bea Jansen van‘t Land, Desirée Paap,

Irene Bergsma, Lidi Schilperoort and Ingrid van de Woude for the good care for the

patients at the growth clinic and for performing accurate auxological measurements.


None declared.

69

4


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2. Drop SL, De Waal WJ. Sex steroid treatment of con-stitutionally tall stature. Endocr Rev 1998;19:540–58.

3. Wit JM, Ranke MB, Kelnar CJH. ESPE Classification of Pediatric Endocrine Diagnoses. Horm Res Paediatr 2007;68:1–120.

4. Visser R, Kant SG, Wit JM, Breuning MH. Overgrowth syndromes. from classical to new. Pediatr Endocrinol Rev 2009;6:375–94.

5. Odink RJ, Gerver WJ, Heeg M, Rouwe CW, Waarde WM, van, Sauer PJ. Reduction of excessive height in boys by bilateral percutaneous epiphysiodesis around the knee. Eur J Pediatr 2006;165:50–4.

6. Benyi E, Berner M, Bjernekull I, Boman A, Chrysis D, Nilsson O, Waehre A, Wehtje H, Savendahl L. Efficacy and safety of percutaneous epiphysiodesis operation around the knee to reduce adult height in extremely tall adolescent girls and boys. Int J Pediatr Endocrinol 2010;2010:740629.

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10. Van Dommelen P, Schönbeck Y, Buuren S., van A simple calculation of the target height. Arch Dis Child 2012;97:182.

11. Schönbeck Y, Talma H, Dommelen P, van, Bakker B, Buitendijk SE, HiraSing RA, Buuren S., van The world’s tallest nation has stopped growing taller: the height of Dutch children from 1955 to 2009. Pediatr Res 2013;73:371–7.

12. Cole TJ, Roede MJ. Centiles of body mass index for Dutch children aged 0-20 years in 1980--a baseline to assess recent trends in obesity. Ann Hum Biol 1999;26:303–8.

13. Fredriks AM, Buuren S, van, Burgmeijer RJ, Meulmeester JF, Beuker RJ, Brugman E, Roede MJ, Verloove-Vanhorick SP, Wit JM. Continuing positive secular growth change in The Netherlands 1955-1997. Pediatr Res 2000;47:316–23.

14. Fredriks AM, Buuren S, van, Heel WJ, van, Dijkman-Neerincx RH, Verloove-Vanhorick SP, Wit JM. Nationwide age references for sitting height,

leg length, and sitting height/height ratio, and their diagnostic value for disproportionate growth disorders. Arch Dis Child 2005;90:807–12.

15. Niklasson A, Ericson A, Fryer JG, Karlberg J, Lawrence C, Karlberg P. An update of the Swedish reference standards for weight, length and head circumference at birth for given gestational age (1977-1981) Acta Paediatr Scand 1991;80:756–62.

16. Bayley N, Pinneau SR. Tables for predicting adult height from skeletal age: revised for use with the Greulich-Pyle hand standards. J Pediatr 1952;40:423–41.

17. De Waal WJ, Stijnen T, Lucas IS, Gurp E, van, Drop SL. A new model to predict final height in constitu-tionally tall children. Acta Paediatr 1996;85:889–93.

18. Marshall WA, Tanner JM. Variations in pattern of pubertal changes in girls. Arch Dis Child 1969;44:291–303.

19. Marshall WA, Tanner JM. Variations in the pattern of pubertal changes in boys. Arch Dis Child 1970;45:13–23.

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21. Boer L, Kant SG, Karperien M, Beers L, van, Tjon J, Vink GR, Tol D, van, Dauwerse H, le Cessie S, Beemer FA, Hamel BC, Hennekam RC, Kuhnle U, Mathijssen IB, Veenstra-Knol HE, Stumpel CT, Breuning MH, Wit JM. Genotype-phenotype correla-tion in patients suspected of having Sotos syndrome. Horm Res 2004;62:197–207.

22. Van Buuren S. Puberty Plot Pro Web Application. [Internet] Available at: http://vps.stefvanbuuren.nl/puberty/

23. Simm PJ, Werther GA. Child and adolescent growth disorders--an overview. Aust Fam Physician. 2005;34:731–37.

24. Morris JK, Alberman E, Scott C, Jacobs P. Is the prevalence of Klinefelter syndrome increasing? Eur J Hum Genet 2008;16:163–70.

25. Ramirez F, Dietz HC. Marfan syndrome: from molecular pathogenesis to clinical treatment. Curr Opin Genet Dev 2007;17:252–8.

26. Tatton-Brown K, Rahman N. Sotos syndrome. Eur J Hum Genet 2007;15:264–71.

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Exomphalos-macroglossia-gigantism syndrome in Jamaican infants. Am J Dis Child 1970;119:316–21.

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29. Wright CM, Cheetham TD. The strengths and limitations of parental heights as a predictor of attained height. Arch Dis Child 1999;81:257–60.

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31. Papadimitriou A, Kanakis G, Douros K, Papadimi-triou DT, Boutsiadis AH, Nicolaidou P, Fretzayas A. Constitutional advancement of growth is associated with early puberty in girls. Horm Res Paediatr 2011;76:273–7.

32. Drop SL, Greggio N, Cappa M. Current concepts in tall stature and overgrowth syndromes. J Pediatr Endocrinol Metab 2001;14(Suppl 2):975–84.

33. Hendriks AE, Drop SL, Laven JS, Boot AM. Fertility of tall girls treated with high-dose estrogen, a dose-response relationship. J Clin Endocrinol Metab 2012;97:3107–14.

34. Venn A, Bruinsma F, Werther G, Pyett P, Baird D, Jones P, Rayner J, Lumley J. Oestrogen treatment to reduce the adult height of tall girls: long-term effects on fertility. Lancet 2004;364:1513–18.

35. Hendriks AE, Boellaard WP, Casteren NJ, van, Romijn JC, Jong FH, de, Boot AM, Drop SL. Fatherhood in tall men treated with high-dose sex steroids during adolescence. J Clin Endocrinol Metab 2010;95:5233–40.

part iiGenetic Analysis

chapter 5Genetic Analysis in Small for Gestational Age Newborns

Susanne E. Stalman, Nita Solanky, Miho Ishida,

Cristina Alemán-Charlet, Sayeda Abu-Amero, Marielle Alders,

Lucas Alvizi, William Baird, Charalambos Demetriou,

Peter Henneman, Chela T James, Lia C. Knegt, Lydia J. Leon,

Marcel M.A.M. Mannens, Adri Mul, Nicole A. Nibbering,

Emma Peskett, Joris A.M. van der Post, Faisal I. Rezwan,

Carrie Ris-Stalpers, Gerdine A. Kamp, Frans B. Plötz, Jan M. Wit,

Philip Stanier, Gudrun E. Moore, Raoul C. Hennekam

[Submitted]

76 Part II

5

Abstract

Small for gestational age (SGA), defined as a birth weight below the 10th centile, can

be a result of fetal growth restriction, associated with perinatal morbidity and mor-

tality. Mechanisms that control prenatal growth are poorly understood. The aim of

the present study is to gain more insight into prenatal growth failure and determine

whether a combination of genomic analyses forms an effective diagnostic approach in

SGA newborns. Array comparative genomic hybridization, genome-wide methylation

studies and exome sequencing in 21 SGA newborns with a mean birthweight below the

1st centile demonstrated three CNVs, one systematically disturbed methylation pattern

and one sequence variant explaining the SGA. Additional methylation disturbances

and sequence variants that potentially contributed to SGA were present 20 patients. In

19 patients, multiple abnormalities were found. Our results confirm the influence of a

large number of mechanisms explaining dysregulation of fetal growth.

Genetic Analysis in SGA Newborns 77

5

Introduction

The process of human fetal growth starts towards the end of the first trimester at 13

weeks of gestation and is steered by a combination of fetal and maternal genetic fac-

tors that affect intrauterine environment to ensure effective nutrient exchange between

mother and fetus via the placenta. In affluent countries, 5% to 6% of pregnancies result

in small for gestational age (SGA) newborns [1-4]. SGA has been defined either as being

<10th centile for weight at a given gestational age or as having a birth length or weight

standard deviation score (SDS) of <-2.0 (equivalent to <2.3rd centile) [5]. SGA can be

a result of fetal growth restriction (FGR), which is defined as a fetus being unable to

reach its individual growth potential [6]. FGR is associated with significant perinatal

morbidity and mortality, [7, 8] and babies with FGR can be predisposed to metabolic

diseases later in life, including type 2 diabetes, obesity and cardiovascular disease [9].

Thirty to fifty percent of the variation in weight at birth can be explained by genetic or

epigenetic causes [10, 11], which include chromosome imbalances, sequence variants

and independent epigenetic disturbances. The London Dysmorphology Database con-

tains over 400 entities associated with prenatal growth failure [12] and Genome-Wide

Association Studies have disclosed less than ten variants associated with fetal growth

[13]. Numerous studies on epigenetic influences, especially DNA methylation distur-

bances, have also been performed [1, 3, 14-19]. Despite this research the mechanisms

behind prenatal growth failure are only poorly understood, at least in part due to the

heterogeneous nature of growth disturbances.

Consequently, an appropriate diagnostic workup for SGA newborns is not well es-

tablished, and questions remain what the extent is of the genetic contribution, which

genes are important, what the optimal care pathway is for the child, and how we provide

adequate counselling to parents.

The aim of the present study is to gain further insight into prenatal growth failure and

determine whether a combination of different genomic analyses can yield an effective

diagnostic approach for SGA newborns. We used array comparative genomic hybridiza-

tion (array-CGH) to detect copy number variations (CNVs), genome-wide methylation

studies to uncover methylation disturbances, and “whole” exome sequencing (WES)

to detect sequence variants in a cohort of SGA newborns. We hypothesized that one or

more CNVs explaining the SGA may be found, disturbed methylation may be present,

in a set of genes known to be aberrantly methylated in low birth weight newborns,

78 Part II

5

and that sequence variants may be present in genes targeted because of their known

association with SGA.

Methods

Patients

We selected 21 small for gestational age (SGA) newborns and their parents from the

Baby Bio Bank (BBB) and Moore Cohort (Institute of Child Health, London, UK). The

BBB contains biological samples from 2,515 undisturbed and complicated pregnan-

cies, and clinical data from babies and their parents, collected between 2000 and 2014

to be used in research on four main pregnancy complications: growth restriction, pre-

eclampsia, recurrent miscarriages and prematurity [20]. The Moore cohort consists of

319 trio samples collected from newborns and their parents between 1991 and 1994,

including a small FGR cohort to investigate genetic causes of intrauterine growth

disturbances.

Inclusion criteria for this study included: a weight at birth at or below the 3.4th centile,

availability of parental samples and absence of major structural malformations. No

pre-eclampsia/HELLP syndrome, systemic disease (e.g. diabetes mellitus), medica-

tion use during pregnancy or maternal smoking was present in the mothers, except

for one mother (SGA4) who was a moderate smoker during pregnancy and one other

mother (SGA3) who had pre-existing essential hypertension at conception for which

she received treatment.

A control cohort of appropriate for gestational age (AGA) newborns (n = 24) was

selected from the Preeclampsia And Non-preeclampsia Database (PANDA) Biobank

(Academic Medical Center, Amsterdam, The Netherlands) based on birth weight for GA

closest to the 50th centile and an equal distribution of mode of delivery and gestational

age in relation to the SGA cases. The PANDA Biobank collected placental biopsies,

umbilical cord blood samples and maternal blood samples of 400 women with either

preeclampsia or normotensive pregnancies, between 2006 and 2010.

The SDS of the weight at birth were calculated using the 1990 British growth references

[21] for the British cases and the 1991 reference data by Niklasson et al. for the Dutch

controls [22], both based on the LMS method [23]. Descriptive statistics for analysing

demographic data was performed in IBM SPSS Statistics, version 22.


5

Ethical approval for all studies was obtained (BBB Research Ethics Committee refer-

ences: 09/H0405/30 and 09/h0405/30+5, Moore cohort reference: 2001/6029, PANDA

Biobank AMC2005_133).

Targeted genes

We performed three literature searches on respectively previously reported (1) genes

known to be aberrantly methylated in low birthweight newborns (2) genes known to be

involved in (regulation of ) DNA methylation and (3) genes in which sequence variants

are associated with disorders with a low birthweight as part of the phenotype. Those

genes will be referred to as ‘targeted genes’.

A list of genes known to be aberrantly methylated in low birthweight newborns was

generated as shown in Supplemental Table 1. We searched in PubMed using as search

terms: “Birth Weight/genetics”[Mesh], “Infant, Small for Gestational Age”[Mesh],

“Infant, Low Birth Weight”[Mesh], “Fetal Growth Retardation/genetics”[Mesh], “DNA

Methylation”[Mesh], “DNA Methylation/genetics”[Mesh], “Genomic Imprinting”[Mesh].

Additional articles were selected by hand searching reference lists.

Genes known to be involved in (regulation of ) DNA methylation were also listed

(Supplemental Table 2). We searched the UniProt resource (Universal Protein Resource,

uniprot.org) and Ensembl database (ensebml.org). The search strategy in UniProt was:

[go:”dna methylation” AND reviewed:yes AND organism:”Homo sapiens (Human)

[9606]”] and [go:”dna demethylation” AND reviewed:yes AND organism:”Homo sapi-

ens (Human) [9606]”]. The GO term “DNA methylation” includes the GO-terms “DNA

methylation”, “regulation of DNA methylation”, “DNA methylation on cytosine”, DNA

methylation on cytosine within a CG sequence” and “DNA methylation involved in

embryo development”. The search term in Ensembl was “DNA methylation” and we

used as filters “only Human” and “only Genes”. Several additional genes were derived

from the literature.

Regarding exome sequencing, we determined genes in which sequence variants

are associated with disorders with a low birthweight as part of the phenotype

(Supplemental Table 3). We searched in two recent reviews [24, 25] and in the London

Dysmorphology Database (LDDB, Oxford University Press, Oxford, UK). Search crite-

ria in LDDB were “birth weight <3rd centile” and/or “short stature, prenatal onset”.

Syndromes of which the causative gene was unknown, with intrauterine lethality and

with markedly abnormal morphology or visible malformations were excluded. In case

80 Part II

5

the severity of dysmorphisms or malformations at birth remained uncertain due to its

variability, a syndrome was included.

DNA isolation

DNA from the cases was obtained from biopsies from placenta tissue from the fetal side

of the placenta near the umbilical cord insertion. DNA from parental blood samples

and the cases were extracted using DNEasy Blood and Tissue Kit (Qiagen, CA, USA).

DNA from the control samples was biopsied from the maternal site of the placenta and

extracted according to the Gentra protocol (Qiagen, CA, USA). To minimize the risk

of maternal blood contamination, the placenta biopsies were washed in phosphate-

buffered saline and stored in RNAlater. To verify whether no maternal DNA contami-

nation occurred, clustering of male samples and female samples was investigated by

principal component analysis.

Array CGH

The array comparative genomic hybridization (array-CGH) analysis was performed

using the Agilent 180K oligo-array (Amadid 023363) (Agilent Technologies, Inc., Palo

Alto, CA), with 13kb overall median probe spacing and the GRCh37/hg19 browser.

Standard methods were used for the labelling and hybridization. The samples were hy-

bridized against a pool of 40 healthy sex-matched human reference samples. Data were

analysed with the Genomic Workbench 6.5 (Agilent, Santa Clara, CA and Cartagenia

(BENCHlab CNV v5.0 (r6643)).

Genome-wide methylation array

Bisulfite conversion of genomic DNA for the genome-wide methylation array was

performed using the EZ DNA Methylation Kit (Zymo Research, CA, USA). The con-

verted DNA samples were randomized across one batch and hybridized on the Infinium

Human Methylation 450K BeadChip array (Illumina, Inc., CA, USA), carried out by a

certified Illumina service provider (ServiceXS, Leiden, the Netherlands). The 450K

BeadChip applies both the Infinium I and II assays for optimal coverage and exam-

ines >450.000 CpG sites across the whole genome. Due to the bisulfite conversion,

unmethylated cytosines are converted to uracil, whereas methylated cystosines remain

unchanged. The array recognizes these chemically differentiated loci and expresses the

degree of methylation in β-values. The β-values correspond to the methylation score

for each analysed probe and ranges from 0 (fully unmethylated) to 1 (fully methylated).


5

Quality control of the Illumina 450k assay was performed using MethylAid [26]. Raw

data were provided by ServiceXS and used for further statistical analysis. A file contain-

ing the β-value methylation data including annotation was produced by GenomeStudio.

The methylation data from GenomeStudio and sample phenotype data were exported

to the R statistical analysis environment (R version 2.15.2) (http://www.r-project.org),

where a single sample analysis [27] was performed. This method allows analysis of

genome-wide methylation data in small sample sizes, where each case is individually

compared to a control cohort. A sample size of ≥20 controls is recommended for this

analysis. The method combines the Illumina Methylation Analyzer (IMA) package

(version 3.2.1) [28] and the Crawford-Howell t-test [29]. The IMA package performs

a basic quality control and pre-processes the methylation data. Any CpG sites with

missing values as well as samples with at least 75% CpG sites having a p-value >0.05,

CpG sites where >75% samples have detection p-value >1e-5, probes on the X and Y

chromosomes and probes containing SNP(s) were removed. The β-values were con-

verted to M-values by logit transformation [30]. Quantile normalization was used to

reduce unwanted technical variation across samples. Peak correction [31] was applied

to correct differences between Infinium I and Infinium II type assays. As all cases and

controls were hybridized on the same batch, no batch correction was required. The dif-

ferences between the pre-processed M-values of all single cases and the controls were

determined using the Crawford-Howell t-test.

Given the large number of significantly differentially methylated probes in our patients

resulting from the single sample analysis, a script in Python (version 2.7) (https://www.

python.org/) was used for further filtering of this data. Probes with a β value difference

of at least 20%, adjusted p-value <0.05 and a minimum of three differentially methyl-

ated probes within 2000 base pairs, allowing for reduction of false positive findings,

were selected for hypermethylated and hypomethylated probes, respectively. Probes

without a gene annotation were removed from further analysis.

Genes found to be hypermethylated and hypomethylated at the same time in the same

patient were removed. First, the genome-wide methylation pattern in SGA newborns in

the context of the previously reported literature (Supplemental Table 1), was analysed.

Second, other genes that were differentially methylated in >5 patients were selected.

Exome sequencing

“Whole” Exome Sequencing (WES) was performed by BGI (Hong Kong). A total of 41

samples were analysed using Agilent SureSelect Human All Exon V5 (50M) kit and high

82 Part II

5

throughput sequencing technology of Complete Genomics, at a 100x coverage. The 41

samples consist of 10 trio samples from the babies with the lowest birth weights and

their parents (SGA1, SGA3, SGA6, SGA15 – SGA21) and 11 singletons of the remaining

newborns. For each sample submitted, BGI analysed and provided: reads, results of

mappings, and basic bioinformatics analysis (including alignment and assessment,

SNP and InDel calling, basic annotation and statistics, SNP validation). At our institu-

tion, the data were further annotated, including pathogenicity prediction data, allow-

ing for subsequent filtering of variants. Variants were kept for further examination if:

mutation types (SO terms) with “high” and “moderate” impact (Ensembl Variation

- Predicted data, ensemble.org), 1K genome minor allele frequency (MAF) <0.05,

ExAC allele frequency <0.05, read depth ≥30, quality score ≥30. Variants with known

non-pathogenic clinical significance and a combined SIFT and PolyPhen prediction of

“tolerated” and “benign” were discarded.

Subsequently, we checked the variants in targeted genes known to cause a low birth

weight in the context of the previously reported literature (Supplemental Table 3), and

determined the likelihood of pathogenicity. At this stage ethnicity-specific MAF were

obtained from the 1000 Genome, ExAC and GO-ESP databases. Second, potential de

novo variants were selected and verified in IGV (Integrative Genomics Viewer, Broad

Institute) in the 10 patients of whom sequencing results from both the newborn and

parents were available. Lastly, homozygous and compound heterozygous mutations

were analysed. All variants in genes discussed in Results and Discussion have been

validated by Sanger sequencing.

Results

Patients

All 21 SGA cases (SGA1 – SGA21) had a birth weight (BW) for gestational age (GA) be-

low the 3.4th centile, 19 were below the 2.3nd centile and 14 patients below the 1st centile.

Table 1 shows other demographics of the study group and the control samples. Sepa-

rate clustering of male cases and control samples from female samples was confirmed,

indicating that no maternal DNA contamination was measured (Supplemental Fig. 1).


5

Array CGH

The array-CGH yielded abnormalities in three patients. Patient SGA1 showed a mosaic

trisomy of chromosome 16 in 70% of the cells (arr[19] 16p13.3q24(64,381-90,163,114)

x2~3). Another mosaic imbalance, mosaic Turner syndrome, was seen in patient

SGA11

Table 1. Demographics of 21 SGA Newborns and 24 Controls Appropriate for Gestational Age

Patient ID Gender GA (weeks)BW

(grams) BW (centile) BW (SDS) Ethnicity Mode of delivery

Cases

SGA1 Female 33.00 1220 0.41 -2.64 Caucasian Caesarean section

SGA2 Female 38.00 1980 0.51 -2.57 African Vaginal

SGA3 Female 33.71 640 4.7E-5 -4.91 South American

Caesarean section

SGA4 Female 39.00 2435 3.36 -1.83 Caribbean Caesarean section

SGA5 Female 34.00 1350 0.59 -2.52 Asian Caesarean section

SGA6 Female 39.57 2120 0.22 -2.85 Caucasian Vaginal

SGA7 Male 38.00 2080 0.69 -2.46 South American

Vaginal

SGA8 Male 38.00 2140 1.04 -2.31 Caucasian Vaginal

SGA9 Male 34.43 1543 1.04 -2.31 Caucasian Caesarean section


SGA11 Female 38.57 2180 1.10 -2.29 African Caesarean section

SGA12 Female 39.00 2385 2.56 -1.95 African Caesarean section

SGA13 Male 38.57 2280 1.36 -2.21 Asian Caesarean section

SGA14 Female 37.14 2017 1.83 -2.09 Caribbean Vaginal

SGA15 Female 31.71 474 3.14E-4 -4.52 Caucasian Caesarean section

SGA16 Male 39.00 2090 0.24 -2.82 African Caesarean section

SGA17 Male 22.00 236 0.13 -3.00 Caucasian Termination of pregnancy





Mean ± SD - 36.49 ± 4.14 1760 ± 640 0.78 ± 0.88 -2.76 ± 0.77 - -

Controls

Mean ± SD - 37.48 ± 4.10 2953 ± 926 53.83 ± 15.51 0.10 ± 0.42 - -

GA=gestational age; BW=birth weight; SDS=standard deviation score

84 Part II

5

(arr Xp22.33q28(61,091-155,009,479)x1~2). Patient SGA17 had a deletion of 11p13-

p14.1 (arr[h19] 11p14.1p13(29,663,942-33,400,789)x1) causing WAGR syndrome

(Wilms tumour, Aniridia, Genital anomalies and mental Retardation).

Genome-wide methylation

Quality control of the Illumina 450k assay showed no failed samples for bisulphite

conversion, hybridization and overall methylation threshold. Table 2 shows methyla-

tion changes in genes known to be aberrantly methylated in low birth weight newborns

which we targeted first (see Methods and Supplemental Table 1). Differential methyla-

tion was seen in 12 patients of which nine had differential methylation in more than

one gene. As patient SGA3 shows an extensively aberrant methylation profile (Fig. 1),

the results for this patient are presented separately. Subsequently, all genes found in an

untargeted study to be differentially methylated in five or more patients, were analysed

(Table 3), showing 28 hypermethylated genes and 6 hypomethylated genes.

Table 2. Differential Methylation in Genes Known to Be Aberrantly Methylated in Low Birthweight Newborns

Patient ID

Gene Chromosome (MapInfo)

Control β-value(mean)

Case β-value(mean)

No. of probes

Main gene function(s) and influence(s) on fetal growtha

Hypermethylation

SGA11SGA15

CDKN1C 11 (2905931-2907008)11 (2906667-2907073)

0.140.21

0.410.48

54

Imprinted gene in 11p15.5 region, highly expressed in placenta. Upregulation associated with IUGR placentas, loss of function associated with Beckwith-Wiedemann syndrome, gain of function with Silver-Russel syndrome

SGA4 FGF14 13 (103052362-103052943)

0.16 0.44 3 Hypomethylation associated with SGA or FGR

SGA13 GNAS; GNASAS 20 (57414162-57414539)

0.62 0.83 3 Hypomethylation of GNASAS associated with SGA. Decreased expression of GNAS observed in IUGR placentas

SGA1SGA7

FOXP1 3 (71631050-71631744)3 (71631050-71631744)

0.090.09

0.450.46

44

Increased methylation associated with FGR

SGA14 SGA20

NPR3 5 (32710614-32711429)5 (32710231-32711517)

0.240.12

0.490.39

46

Hypermethylation associated with FGR

SGA14 NR3C1 5 (142784522-142785258)

0.22 0.47 3 Differential methylation in this glucocorticoid receptor in placenta correlated with birth weight


5

Table 2. Differential Methylation in Genes Known to Be Aberrantly Methylated in Low Birthweight New-

borns (continued)

Patient ID

Gene Chromosome (MapInfo)

Control β-value(mean)

Case β-value(mean)

No. of probes


SGA11SGA14SGA15SGA17SGA20SGA21

TBX15 1 (119530600-119530702)1 (119530600-119531093)1 (119530600-119530702)1 (119530048-119530932)1 (119530600-119530702)1 (119530600-119531093)

0.280.310.280.350.280.30

0.580.550.640.580.570.61

333434

Promotor hypomethylation leads to TBX15 decrease in FGR placentas

SGA7SGA11SGA13SGA16

WNT2 7 (116963193-116963502)7 (116962950-116964012)7 (116962950-116963502)7 (116962950-116963502)

0.180.190.170.17

0.520.510.480.48

5766

WNT2 promoter methylation in placenta is associated with low birthweight

SGA10SGA15SGA21

ZIC1;ZIC4

3 (147125714-147127662)3 (147125712-147126206)3 (147126763-147127662)

0.300.430.21

0.580.660.57

566

Decreased methylation associated with SGA or FGR

Hypomethylation

SGA17 IGF2AS; INS-IGF2; IGF2

11 (2162406-2162616) 0.44 0.17 5 IGF2 is imprinted and highly expressed in placenta, hypomethylation of H19/IGF2 control region is associated with FGR. INS-IGF2 involved in growth and metabolism. IGF2AS is imprinted and expressed in antisense to IGF2

SGA13 KCNQ1; KCNQ1OT1

11 (2721207-2721383) 0.49 0.24 4 Upregulated KCNQ1 and loss of KCNQ1OT1 associated with IUGR; genetic variants of KCNQ1 associated with Beckwith-Wiedemann syndrome

SGA1 TBX15 1 (119526060-119527377)

0.68 0.42 4 Promotor hypomethylation leads to TBX15 decrease in FGR placentas

SGA17 WNT2 7 (116964012-116964802)

0.35 0.11 4 WNT2 promoter methylation in placenta is associated with low birthweight

a For references see Supplemental Table 1

86 Part II

5

Patient IDSGA21SGA20SGA19SGA18SGA17SGA16SGA15SGA14SGA13SGA11SGA10SGA8SGA7SGA6SGA4SGA3SGA2SGA1

Tota

l diff

eren

tially

met

hyla

ted

prob

es

8000

7500

7000

6500

6000

5500

5000

4500

4000

3500

3000

2500

2000

1500

1000

500

0

Hypomethylated probesHypermethylated probes

Figure 1. Total number of differentially methylated probes per patient out of 485,577 interrogated probes,

after single case analysis and further probe fi ltering (see Methods). An extensively disturbed methylation

profi le is evident in patient SGA3, and patient SGA15 has an increased number of hypermethylated probes in

comparison to the other patients.

Table 3. Differentially Methylated Genes Present in >5 Patients

Gene Chrom. N Main gene function(s)

Hypermethylation

B3GNT3 19 11 Involved in in L-selectin ligand biosynthesis, lymphocyte homing and lymphocyte traffi cking (ncbi.nlm.nih.gov/gene)

PIK3R1 5 11 Associated with insulin resistance and SHORT syndrome [40, 41] Homozygous mutations in mice cause embryonic growth retardation [42]

PURA 5 11 Implicated in control of DNA replication and transcription (ncbi.nlm.nih.gov/gene)

HSPA1A 6 10 Stabilizes proteins against aggregation, mediates folding of proteins, involved in ubiquitination (ncbi.nlm.nih.gov/gene)

TTC23 15 10 Tetratricopeptide repeat domain 23 (ncbi.nlm.nih.gov/gene)

CMSS1 3 8 Cms1 ribosomal small subunit homolog (ncbi.nlm.nih.gov/gene)

CBR1 21 8 A short-chain reductase, functions as oxidoreductases (ncbi.nlm.nih.gov/gene)

HSPA1L 6 8 Stabilizes proteins against aggregation, mediates protein folding (ncbi.nlm.nih.gov/gene)

ACSS3 12 7 Activates acetate allowing use for lipid synthesis or for energy generation (uniprot.org)

ANKMY1 2 7 Ankyrin repeat and MYND domain-containing protein 1 (ncbi.nlm.nih.gov/gene)

DDX60L 4 7 Probable ATP-dependent RNA helicase DDX60-like (uniprot.org)

DIXDC1 11 7 Regulator of Wnt signalling pathway (uniprot.org) [43]

ECE1 1 7 Endothelin converting enzyme, associated with M. Hirschsprung, cardiac defects and autonomic dysfunction (ncbi.nlm.nih.gov/gene)

ESRRG 1 7 Involved in intrauterine growth restriction and preeclampsia [44]


5

SGA3 showed differential methylation in 26 targeted genes known to be aberrantly

methylated in low birth weight newborns (Supplemental Table 4). A possible explana-

tion for this extensively disturbed methylation pattern in SGA3 would be an alteration in

a gene known to be involved in (the regulation of ) DNA-methylation (see Methods and

Supplemental Table 2). Of these, four were hypermethylated and 11 hypomethylated

(Supplemental Table 5). Additionally, WES data were checked for sequence variants

in genes involved in regulating DNA-methylation (Supplemental Table 5), showing a

Table 3. Differentially Methylated Genes Present in >5 Patients (continued)

Gene Chrom. N Main gene function(s)

GPR135 14 7 Probable G-protein coupled receptor 135 (uniprot.org)

MECOM 3 7 Transcriptional regulator and oncoprotein involved amongst others in cell differentiation and proliferation (ncbi.nlm.nih.gov/gene)

MOSC2 1 7 Component of the benzamidoxime prodrug-converting complex (uniprot.org)

PRKCDBP 11 7 Possible tumour suppressor function (ncbi.nlm.nih.gov/gene)

TBX15a 1 6 Methylation correlates with weight and stature of newborn[45]

[45]FAM221A 7 6 Family with sequence similarity 221 member A (ncbi.nlm.nih.gov/gene)

GGT1 22 6 Associated with growth retardation in mice [46]

HLA-F 6 6 Belongs to HLA class I heavy chain paralogues (ncbi.nlm.nih.gov/gene)

MICA 6 6 Associated with susceptibility to psoriasis 1 and psoriatic arthritis (ncbi.nlm.nih.gov/gene)

MT1E 16 6 Binds various heavy metals (uniprot.org)

NAT15 16 6 Uncharacterized LOC100609520 (ncbi.nlm.nih.gov/gene)

NOL3 16 6 Anti-apoptotic protein, regulates enzyme activities of caspase 2, caspase 8 and p53 (ncbi.nlm.nih.gov/gene)

PAK6 15 6 Expression linked to prostate cancer (ncbi.nlm.nih.gov/gene)

PPP1R2P1 6 6 Inhibitor of protein-phosphatase 1 (uniprot.org)

Hypomethylation

NAPRT1 4 9 Catalyses conversion of nicotinic acid to NA mononucleotide (uniprot.org)

GUCY1B3 4 8 Receptor for ligands such as nitric oxide, oxygen and nitrovasodilator drugs (ncbi.nlm.nih.gov/gene)

SDHAP3 5 7 Succinate dehydrogenase complex fl avoprotein subunit A pseudogene 3 (ncbi.nlm.nih.gov/gene)

C11orf87 11 6 Uncharacterized protein C11orf87 (uniprot.org)

FGF8 10 6 Involved in regulation of embryonic development, cell proliferation, cell differentiation and cell migration (uniprot.org)

GDA 9 6 May play a role in microtubule assembly (ncbi.nlm.nih.gov/gene)

aTBX15 is the only targeted gene differentially methylated in >5 patients

88 Part II

5

heterozygous missense mutation in MPHOSPH8 (p.Asp460Tyr). The same variant, with

a known minor allele frequency (MAF) of 2-3% (rs75390100), was found in two other

patients (SGA2 and SGA15).

Due to an administrative error, three samples (SGA5, SGA9 and SGA12) could not be

included in the genome-wide methylation analysis.

Exome sequencing

Exome sequencing without filtering yielded over 70,000 single nucleotide variants and

~5.000 InDel variants in the 21 patients studied. After filtering (see Methods) we first

evaluated sequence variants in genes that if mutated are known to be associated with

disorders in which a low birthweight is part of the phenotype (Supplemental Table 3).

This targeted analysis yielded potentially pathogenic heterozygous variants in 32 genes,

one homozygous variant and two compound heterozygous variants (Table 4). In this

targeted gene panel, no de novo variants were identified in newborns of whom sequenc-

ing data of the parents were available. In patients in which no WES was performed in

their parents, variants were sequenced by Sanger in parents and showed inheritance of

all variants from one or both parents.

Second, de novo variants in untargeted genes were analysed in silico (see Methods). Two

de novo single nucleotide variants were predicted to be potentially pathogenic (Table 4).

Third, we analysed all WES data for homozygous variants in untargeted genes, and

found three homozygous missense mutations of potential interest (Table 4). Lastly,

we evaluated data for compound heterozygous mutations in untargeted genes and

found one compound heterozygous variant (Table 4). All variants described have been

validated by Sanger sequencing.

Discussion

In the present study we investigated 21 SGA newborns using a combination of array-

CGH, genome wide methylation array and exome sequencing. In four patients (19%),

we found a genetic abnormality that likely contributes to their low birth weight. In

these and 16 other patients (95%), abnormalities were found that potentially can influ-

ence fetal growth but require further functional analyses. There were three CNVs (in 3

patients), 37 variants (in 18 patients) in targeted genes known to be associated with a

low birthweight, and disturbed methylation in 30 targeted genes (in 13 patients) known


5

Tabl

e 4.

Seq

uenc

e Va

rian

ts in

Tar

gete

d an

d U

ntar

gete

d G

enes

Pati

ent I

DG

ene

Posi

tion

Alt

.A

ssoc

iate

d di

sord

er

(in

heri

tan

ce)a

MA

FSN

P ID

SIFT

Poly

Phen

2

Targ

eted

gen

es

Mis

sen

se v

aria

nts

SGA

1/ M

COL2

A112

:483

6926

8G

>A

SED

Con

geni

ta;

Hyp

ocho

ndro

gene

sis;

A

chon

drog

enes

is ty

pe

2 (A

D)

6.0e

-5-1

.1e-

4rs

3740

8276

2D

elet

erio

usU

nkno

wn

SGA

2PC

NT

21:4

7801

666

C>

TSe

ckel

syn

drom

e (A

R)

--

Del

eter

ious

Prob

ably

dam

agin

g

SGA

3/ M

TUBG

CP6

22:5

0664

782

C>

TM

icro

ceph

aly

+

chor

iore

tino

path

y (A

R)

--

Del

eter

ious

Prob

ably

dam

agin

g

SGA

4GH

R5:

4269

9970

G>

TG

H in

sens

itiv

ity

(Lar

on

synd

rom

e) (A

R)

none

rs64

1348

4D

elet

erio

usB

enig

n*

SGA

5CL

CNK

A1:

1635

9674

C>

TB

artt

er s

yndr

ome

(AR

)0-

0.00

9-

Del

eter

ious

Ben

ign

SGA

5ID

UA

4:99

5634

G>

TH

urle

r sy

ndro

me

(AR

)0-

0.00

5-

Del

eter

ious

Prob

ably

dam

agin

g

SGA

6/ M

ANK

RD

1116

:893

4737

2G

>A

KB

G s

yndr

ome

(AD

)0.

001

rs14

4516

367

Tole

rate

dPr

obab

ly d

amag

ing

SGA

6/M

LEM

D3

12:6

5564

283

G>

TC

hrom

osom

e 12

q14

mic

rode

leti

onno

ne-0

.001

rs35

2215

58D

elet

erio

usPr

obab

ly d

amag

ing

SGA

7SL

C26A

25:

1493

6072

3G

>A

De

la C

hape

lle s

yndr

ome

(neo

nata

l oss

eous

dy

spla

sia)

(AR

)

--

Tole

rate

dPo

ssib

ly d

amag

ing

SGA

8LM

NA

1:15

6108

510

C>

TH

utch

inso

n-G

ilfor

d Pr

oger

ia (A

D)

0.00

1-0.

002

rs14

2000

963

Del

eter

ious

Poss

ibly

dam

agin

g

SGA

9CO

L1A1

17:4

8270

172

G>

TO

steo

gene

sis

impe

rfec

ta

(AD

)3.

01e-

5-

Del

eter

ious

Unk

now

n

SGA

9ER

CC4

16:1

4028

081

C>

TX

erod

erm

a pi

gmen

tosu

m/C

ocka

yne

synd

rom

e (A

R)

0.00

5-0.

007

rs17

9980

2D

elet

erio

usPr

obab

ly d

amag

ing

SGA

9IN

PPL1

11:7

1943

374

C>

TO

psis

mod

yspl

asia

(AR

)0.

001

rs14

1305

290

Del

eter

ious

Prob

ably

dam

agin

g

90 Part II

5

Tabl

e 4.

Seq

uenc

e Va

rian

ts in

Tar

gete

d an

d U

ntar

gete

d G

enes

(con

tinu

ed)

Pati

ent I

DG

ene

Posi

tion

Alt

.A

ssoc

iate

d di

sord

er

(in

heri

tan

ce)a

MA

FSN

P ID

SIFT

Poly

Phen

2

SGA

10N

F117

:295

4608

3G

>A

Neu

rofi

brom

atos

is

(-N

oona

n) s

yndr

ome

(AD

)

9.4e

-5-2

.2e -4

rs14

5191

978

Del

eter

ious

Prob

ably

dam

agin

g

SGA

11FG

FR1

8:38

2758

43G

>A

Palli

ster

–Hal

l syn

drom

e;

Pfei

ffer

syn

drom

e (A

D)

none

b-

Del

eter

ious

Prob

ably

dam

agin

g

SGA

11GH

R5:

4268

9094

G>

TG

H in

sens

itiv

ity

(Lar

on

synd

rom

e) (A

R)

0.00

3-0.

004

rs11

4025

919

Del

eter

ious

Prob

ably

dam

agin

g

SGA

11K

MT2

D12

:494

3492

5G

>A

Kab

uki s

yndr

ome

1 (A

D)

--

-B

enig

n

SGA

11LE

MD

312

:656

3392

5G

>A

Chr

omos

ome

12q1

4 –

mic

rode

leti

on9.

6e-5

Tole

rate

dPr

obab

ly d

amag

ing

SGA

12AC

AN15

:894

0069

2C

>T

Spon

dylo

epim

etap

hyse

al

dysp

lasi

a ty

pe a

ggre

can;

SE

D ty

pe K

imbe

rley

(A

R, A

D)

2.0e

-4-

Del

eter

ious

Prob

ably

dam

agin

g

SGA

12CT

C117

:813

8569

C>

GR

eves

z (C

oats

plu

s)

synd

rom

e (A

R)

0.00

2-0.

005

rs62

6249

78To

lera

ted

Prob

ably

dam

agin

g

SGA

13GN

PTAB

12:1

0216

4255

T>

GM

ucol

ipid

osis

II a

lpha

/be

ta (I

-cel

l dis

ease

) (A

R)

none

-1.2

e-4

rs79

5870

9D

elet

erio

usPr

obab

ly

dam

agin

g*

SGA

13O

RC1

1:52

8618

99T

>G

Mei

er-G

orlin

syn

drom

e (A

R)

none

6.06

E-05

b

rs30

8748

2To

lera

ted

Poss

ibly

dam

agin

g

SGA

14ER

CC6

10:5

0667

229

C>

TC

ocka

yne

synd

rom

e ty

pe

B (A

R)

0.00

5rs

4253

227

Del

eter

ious

Prob

ably

dam

agin

g

SGA

15/ M

WN

T41:

2244

6860

G>

ASE

RK

AL

synd

rom

e (A

R)

7.

5e-5

-2.3

e-4

rs14

0080

433

Del

eter

ious

Poss

ibly

dam

agin

g

SGA

17/ P

CBL

11:1

1917

0384

C>

AN

oona

n-lik

e sy

ndro

me

(AD

)1.

5e-5

-D

elet

erio

usPo

ssib

ly d

amag

ing

SGA

17/ M

IHH

2:21

9920

120

C>

TA

croc

apit

ofem

oral

dy

spla

sial

(AR

)4.

6e-5

-D

elet

erio

usPr

obab

ly d

amag

ing


5

Tabl

e 4.

Seq

uenc

e Va

rian

ts in

Tar

gete

d an

d U

ntar

gete

d G

enes

(con

tinu

ed)

Pati

ent I

DG

ene

Posi

tion

Alt

.A

ssoc

iate

d di

sord

er

(in

heri

tan

ce)a

MA

FSN

P ID

SIFT

Poly

Phen

2

SGA

18SY

NPR

3:63

2643

92C

>T

Chr

omos

ome

3p14

.3

mic

rode

leti

on0.

003-

0.00

4rs

2018

8023

3D

elet

erio

usPr

obab

ly d

amag

ing

SGA

21/ P

ERCC

85:

6019

5517

C>

GC

ocka

yne

synd

rom

e ty

pe

A (A

R)

0.00

2-0.

004

rs15

0727

525

Del

eter

ious

Ben

ign

Mis

sen

se v

aria

nt &

spl

ice

regi

on v

aria

nt

SGA

15/ M

COL9

A320

:614

4892

0G

>C

Mul

tipl

e ep

iphy

seal

dys

plas

ia

3 (A

D)

--

Tole

rate

dU

nkno

wn

Stop

gai

ned

var

ian

t

SGA

21/ M

MCP

H1

8:63

0194

1C

>A

Prim

ary

mic

roce

phal

y 1(

AR

)-

--

-

Splic

e do

nor

var

ian

t

SGA

14SM

ARCA

419

:110

9768

1T

>C

Cof

fin-

Siri

s sy

ndro

me

(AD

)-

--

-

Splic

e ac

cept

or v

aria

nt

SGA

3/F

SOS1

2: 3

9216

456

C>

TN

oona

n sy

ndro

me

(AD

)8.

98e-

5rs

1415

6523

4-

-

Hom

ozyg

ous

vari

ant

SGA

8EM

G112

:708

0187

C>

GB

owen

-Con

radi

syn

drom

e (A

R)

0.04

rs11

0644

80-

-

Com

poun

d he

tero

zygo

us v

aria

nts

SGA

3TR

PV4

12:1

1023

0568

G>

CSp

ondy

lom

etap

hyse

al

dysp

lasi

a –

type

Mar

otea

ux

(AD

)

0.08

rs18

5933

892

Tole

rate

dPo

ssib

ly d

amag

ing

12:1

1024

0859

C>

A0.

07rs

1878

6472

7To

lera

ted

Prob

ably

dam

agin

g

SGA

4KC

NJ1

111

:174

0962

2C

>T

Tran

sien

t neo

nata

l dia

bete

s m

ellit

us ty

pe 3

(AD

)-

--

-

11:1

7409

055

C>

Tno

ners

5217

Del

eter

ious

Ben

ign

Un

targ

eted

gen

es

De

nov

o m

isse

nse

var

ian

ts

92 Part II

5

Tabl

e 4.

Seq

uenc

e Va

rian

ts in

Tar

gete

d an

d U

ntar

gete

d G

enes

(con

tinu

ed)

Pati

ent I

DG

ene

Posi

tion

Alt

.A

ssoc

iate

d di

sord

er

(in

heri

tan

ce)a

MA

FSN

P ID

SIFT

Poly

Phen

2

SGA

15M

TUS1

8:17

5036

28G

>T

Coo

pera

tes

wit

h A

GT

R2

to

inhi

bit E

RK

2 ac

tiva

tion

and

ce

ll pr

olif

erat

ion

(uni

prot

.org

)-

-D

elet

erio

usPr

obab

ly d

amag

ing

SGA

20LZ

TS2

10:1

0276

6749

C>

TN

egat

ive

regu

lati

on o

f ce

ll pr

olif

erat

ion;

pos

itiv

e re

gula

tion

of c

ell d

eath

(u

nipr

ot.o

rg)

--

Del

eter

ious

Prob

ably

dam

agin

g

Hom

ozyg

ous

vari

ants

SGA

2IG

SF21

1:18

7033

28C

>T

App

ears

to p

lay

a ro

le in

cel

l re

cogn

itio

n an

d re

gula

tion

of

cell

beha

viou

r (o

mim

.org

)

0.09

-0.

12rs

1207

6815

Del

eter

ious

Prob

ably

dam

agin

g

SGA

11FG

F612

:454

3487

T>

AFi

brob

last

gro

wth

fact

or,

invo

lved

in e

mbr

yoni

c de

velo

pmen

t and

cel

l gro

wth

(u

nipr

ot.o

rg)

0.16

-0.

19rs

7961

645

Tole

rate

dPo

ssib

ly d

amag

ing

SGA

12M

THFD

114

:648

9253

9T

>C

Play

s a

role

in fo

late

m

etab

olis

m[6

3] a

nd m

ay

be a

ssoc

iate

d w

ith

feta

l hy

potr

ophy

[64]

--

Del

eter

ious

Ben

ign

Com

poun

d he

tero

zygo

us v

aria

nts

SGA

11PH

LDA1

12:7

6425

137

C>

GPH

LDA1

may

pla

y an

impo

rtan

t ro

le in

the

anti

-apo

ptot

ic

effe

cts

of in

sulin

-lik

e gr

owth

fa

ctor

-1[1

4]

--

--

12:7

6424

368

T>

G0.

001-

0.00

2rs

1470

4923

7To

lera

ted

Unk

now

n

a For

refe

renc

es o

f ta

rget

ed g

enes

see

Sup

plem

enta

l Tab

le 3

. Alt

.=A

lter

atio

n; M

=m

ater

nal;

P=pa

tern

al; A

D=

auto

som

al d

omin

ant;

AR

=au

toso

mal

rec

essi

ve;

MA

F=m

inor

alle

le fr

eque

ncy

(100

0 G

enom

e, E

xAC

and

GO

-ESP

).


5

to be aberrantly methylated in low birth weight newborns. In evaluating the probability

of pathogenicity of present findings we reasoned that the likelihood increased if an

abnormality was present in a targeted gene, so a gene of which we had determined

in advance that a low birthweight is part of the phenotype. In addition, homozygous,

compound heterozygous and de novo variants were detected in other, untargeted genes,

that did not result from our literature search, as well as abnormally methylated genes,

present in more than five patients, that were not included in the targeted analyses.

Three CNVs (14%) were detected in the present cohort, a relatively higher number com-

pared to previous reports in patients with SGA or short stature [32-35]. Mosaic trisomy

16 is known to lead to a high risk of prenatal abnormalities [36], frequently including

SGA, and can thus be considered a valid explanation for SGA in patient SGA1. Patient

SGA11 showed mosaicism for monosomy X. About 50% of individuals with Turner

syndrome have a mosaic karyotype [37], and it typically includes a low birth weight.

In patient SGA17 an 11p14.1-p13 deletion, as seen in WAGR syndrome, was identified.

This syndrome features reduced intrauterine growth as a known phenotype [38, 39].

As hypothesized in advance, methylation disturbances in several genes known to be

aberrantly methylated in low birth weight newborns, were found. In general, more

hypermethylation than hypomethylation was found in the present cohort. A methyla-

tion abnormality potentially involved in SGA was detected in 13 patients, of which five

showed differential methylation in several imprinted genes from the 11p15.5 imprinted

region associated with fetal growth restriction, including CDKN1C, KCNQ1, IGF2AS, INS

and IGF2 [14].

Methylation disturbances in untargeted genes were considered if the disturbance was

present in at least 5 patients, and these were detected in 34 genes. Seven of these genes

(PIK3R1, DIXDC1, ESRRG, TBX15, GGT1 and FGF8) appeared to be of specific interest, in

view of their gene functions. PIK3R1 plays a role in the metabolism of insulin and is

associated with SHORT syndrome [40, 41] and embryonic growth retardation in mice

[42]. DIXDC1 is involved in the Wnt signalling pathway, which plays a major role in

regulating embryonic development [43]. ESRRG is known to be involved in intrauterine

growth restriction and preeclampsia [44]. Differential methylation of TBX15 in placenta

is associated with variation in neonatal weight and stature [45]. GGT1 is associated with

growth retardation in mice [46] and FGF8 is a member of the fibroblast growth fac-

tors, which play an important role in the regulation of embryonic development, cell

proliferation, cell differentiation [47] and bone formation [48, 49].

94 Part II

5

Although promoter methylation is generally associated with reduced gene expression

and methylation of a gene itself typically with increased gene expression [50, 51], DNA

methylation differs pre- and postnatally both quantitatively and in terms of CpG versus

non-CpG methylation in utero. RNA samples are not available in the present series, but

RNA expression studies in similar studies should provide insight in the consequences

of the hyper- and hypomethylation detected in the present candidate genes.

In contrast to the generally more frequent hypermethylation profile in the present co-

hort, patient SGA3 showed a predominant hypomethylation pattern and an extensively

disturbed methylation profile. First, an external epigenetic influence, such as tobacco

smoke or infectious pathogens, could be the cause of this observation [52]. The essen-

tial hypertension of SGA3’s mother may be of importance in this respect [53]. Second,

a mutation in genes regulating DNA methylation, such as the DNMTs and TETs [54-

57], could theoretically cause widespread DNA methylation disturbances. In SGA3,

a heterozygous mutation in MPHOSPH8 was found, a gene important in mediating

epigenetic control. However, the relatively high minor allele frequency (MAF) argues

against such role. Also maternal mutations in so called ‘maternal-effect genes’ such

as NLRP5, NLRP7 I and KHDC3L [58] can cause multi-locus imprinting disturbances in

their offspring, usually resulting in hypomethylation at multiple loci and seen primar-

ily in female offspring [59]. Even though SGA3 had a predominant hypomethylation

pattern and is a female, we were unable to detect such mutation. Lastly, disturbed

methylation of 15 genes known to be involved in (regulation of ) DNA methylation

was present in SGA3. Especially the abnormal methylation of DNMT1, DNMT3B, TET1,

UHRF1 and ZFP57 may be of interest as abnormal methylation of one of these may have

had a subsequent more extensive effect.

The evaluation of exome sequencing, targeted for genes associated with disorders in

which a low birthweight is part of the phenotype, uncovered 37 sequence variants in 35

genes. Each may be considered as being potentially pathogenic and, if mutated, these

genes can cause malformation syndromes, skeletal dysplasias and endocrine disorders.

Our analyses showed a splice acceptor variant in SOS1 (c.3347-1G>A), a variant that is

described previously in patients with Noonan-syndrome [60], and in combination with

the low reported MAF considered pathogenic. Seven other missense variants in tar-

geted genes (ACAN, CBL, COL1A1, COL2A1, FGFR1, GRH, NF1) may well be pathogenic, given

their associated disorders and inheritance patterns, low MAF and prediction programs

indicating the variant as being pathogenic and additional features in several variants

as described below. Our analyses uncovered a c.484G>T variant of GHR (rs6413484)


5

in FGF4. The same rsID is assigned to a G>A change at this position (c.484G>A), and

this specific heterozygote variant has been associated with short stature [61]. However,

the fact that most patients with growth hormone deficiency and insensitivity are born

with a normal weight and length casts doubt on its role in SGA. The other heterozygous

variants in targeted genes are less likely to be causative due to their function, because

of their association with recessive disorders, high MAF, and all prediction programs

indicating the variant as likely to be benign or tolerated.

We found de novo mutations in two untargeted genes. MTUS1 is a tumour suppressor

gene controlling cell proliferation, however no function interfering with fetal growth

is known [62] so the meaning of this variant remains uncertain. The protein encoded

by LZTS2 acts as a tumour suppressor and is involved in regulating embryonic develop-

ment by the Wnt signalling pathway [43].

Homozygous mutations were found in four genes. For three of these (EMG1, FGF6,

IGSF21) the ethnicity-specific MAFs of the patients are between 4.5% and 17% and high

numbers of homozygotes are reported in the Exome Aggregation Consortium (ExAC).

Therefore, we consider these to be non-pathogenic variants. One patient was homozy-

gous for the p.Val316Ala variant in MTHFD1. MTHFD1 is important for folate metabolism

[63] and embryonic development and a mutation in this gene has been associated with

fetal hypotrophy [64]. Given the function of the gene, the type of mutation, and because

the variant is not a known polymorphism, this variant may be pathogenic. Compound

heterozygous variants of interest were found in two targeted genes and one untargeted

gene. Two variants in TRPV4 show a high MAF therefore are considered unlikely patho-

genic. The variants in KCNJ11, associated with transient neonatal diabetes and a low

birth weight [65], is considered a likely pathogenic variant. PHLDA1 is suggested to be

involved in the anti-apoptotic effects of insulin-like growth factor-1 and associated with

embryo developmental competence [66, 67] and may contribute to the SGA phenotype.

Our results do not indicate the presence of a single, unifying theme explaining the

dysregulation of fetal growth, and confirms previous findings that growth in utero

is influenced by a large number of genes [68, 69]. We demonstrate that there is no

predominant type of genetic abnormality present in SGA newborns: copy number

variations, methylation disturbances and sequence variants may all contribute in part

to the phenotype. In 19 patients, combinations of a CNV, (multiple) sequence variants

and (multiple) methylation disturbances are present. Table 5 shows an overview of the

genetic abnormalities detected in each patient, classified into the probability of their

contribution to SGA. The polygenic nature of SGA indicates interactions between the

96 Part II

5

Table 5. Overview of Genetic Abnormalities Classified into the Probability of their Contribution to SGA

Sample ID

Finding(s)

Likely contributing Probably contributing Possibly contributing

SGA1 70% trisomy 16 mosaicism COL2A1 variant FOXP1 hypermethylation; PIK3R1 hypermethylation; ESRRG hypermethylation; GGT1 hypermethylation

SGA2 PIK3R1 hypermethylation; DIXDC1 hypermethylation; ESRRG hypermethylation; GGT1 hypermethylation

SGA3 Extensively disturbed methylation pattern; SOS1 variant

SGA4 KCNJ11 variant PIK3R1 hypermethylation; FGF14 hypermethylation; GGT1 hypermethylation; GHR variant

SGA5

SGA6 PIK3R1 hypermethylation; DIXDC1 hypermethylation

SGA7 FOXP1 hypermethylation; WNT2 hypermethylation; PIK3R1 hypermethylation; GGT1 hypermethylation

SGA8 PIK3R1 hypermethylation; GGT1 hypermethylation

SGA9 COL1A1 variant

SGA10 NF1 variant DIXDC1 hypermethylation; FGF8 hypomethylation; ZIC1 hypermethylation

SGA11 46% monosomy X mosaicism

FGFR1 variant; CDKN1C hypermethylation; PHLDA1 variant

TBX15 hypermethylation; WNT2 hypermethylation

SGA12 ACAN variant; MTHFD1 compound heterozygote variant

SGA13 KCNQ1/KCNQ10T1 hypomethylation

GNAS/GNASAS hypermethylation; WNT2 hypermethylation

SGA14 NPR3 hypermethylation; NR3C1 hypermethylation; ESRRG hypermethylation; TBX15 hypermethylation; GGT1 hypermethylation; FGF8 hypomethylation

SGA15 CDKN1C hypermethylation PIK3R1 hypermethylation; DIXDC1 hypermethylation; ESRRG hypermethylation; TBX15 hypermethylation; FGF8 hypomethylation; MTUS1 de novo variant; ZIC1 hypermethylation

SGA16 WNT2 hypermethylation; PIK3R1 hypermethylation; DIXDC1 hypermethylation; ESRRG hypermethylation

SGA17 11p14.1-p13 deletion CBL variant; IGF2AS/INS-IGF2/IGF2 hypomethylation

DIXDC1 hypermethylation; ESRRG hypermethylation; TBX15 hypermethylation


5

various genetic abnormalities, and the pathogenic mechanisms explaining this are

likely extremely complex. A separate study in each patient will be needed to evaluate

this in detail. Our results mirror a similar study in children with postnatal growth

failure [70], using a similar approach in evaluating variants in genes known to be as-

sociated with short stature as well as studying variants in other, untargeted genes [70].

The latter authors highlight the multitude of genetic causes for short stature and the

complexity of interpretation of variants and their pathogenicity, which resembles the

observations in the present study.

We acknowledge limitations of the present study. The size of our cohort is small and

the power to draw general conclusions is limited. The genetic heterogeneity within the

present cohort also appears high. We therefore used an individual-based data analysis

approach to enable suitable data analysis. Using filtering strategies based on popula-

tion allele frequencies as in the present study limits the ability to determine the patho-

genicity of WES variants, since such data lack individual phenotypic data. Furthermore,

we had no access to clinical follow-up data of the presently studied cohort. The large

number of potentially pathogenic variants inhibits investigating each individual variant

extensively; ideally, each variant would require a separate, detailed study.

We conclude that copy number variations, methylation disturbances and sequence

variants all contribute to prenatal growth failure. Such genetic workup can be an ef-

fective diagnostic approach in SGA newborns. The results of such studies in individual

patients may have important consequences for patient care and counselling of patients

and their families.

Table 5. Overview of Genetic Abnormalities Classified into the Probability of their Contribution to SGA

(continued)

Sample ID

Finding(s)

Likely contributing Probably contributing Possibly contributing

SGA18 PIK3R1 hypermethylation; DIXDC1 hypermethylation

SGA19 PIK3R1 hypermethylation; FGF8 hypomethylation

SGA20 NPR3 hypermethylation; PIK3R1 hypermethylation; ESRRG hypermethylation; TBX15 hypermethylation; FGF8 hypomethylation; LZTS2 de novo variant

SGA21 TBX15 hypermethylation; FGF8 hypomethylation; ZIC1 hypermethylation

98 Part II

5

Acknowledgments

We would like to thank Jessica Glebbeek, Patricia Schmidt, Sander de Jong, Femke van

Sinderen and Jet Bliek for their help in the laboratory. The present study has been made

possible by grants of the following institutions: Tergooi Grant for Support of Scientific

Research, KNAW Ter Meulen Fund, Jo Kolk Study Fund, ZonMW Rare Disease Network

Grant, the Baby Bio Bank, Wellbeing of Women and Biomedical Research Center Grant.

All sponsors are gratefully acknowledged. Sponsors had no involvement in any stage of

the study design, data collection, data analyses or interpretation of the data or decision

to publish study results.


5

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part iiiTreatment

chapter 6Positive Effect of Growth Hormone Treatment in

Maternal Uniparental Disomy Chromosome 14

Susanne E. Stalman, Gerdine A. Kamp, Yvonne M. Hendriks,

Raoul C.M. Hennekam, Joost Rotteveel

Clinical Endocrinology (Oxf ) 2015;83(5):671-6

106 Part III

6

Abstract

Objective

Maternal uniparental disomy of chromosome 14 (matUPD(14)) resembles Prader–Willi

syndrome (PWS). As positive effects of growth hormone (GH) are observed in individu-

als with PWS, treatment with GH may be useful in individuals with matUPD(14) as well.

The aim of this study was to investigate the effect of GH treatment on growth and body

composition in children with matUPD(14).

Design

This is a prospective observational study of GH treatment in two girls with matUPD(14)

during 2 years, and spontaneous growth in another matUPD(14) girl of similar age.

Patients

Three girls (patient A, B and C, aged 8·9, 11·4 and 12·7 years, respectively) with

matUPD(14) were included in this study.

Measurements

Patients A and B were treated with GH during 2 years. Patient C was not treated with

GH, as she was diagnosed at an age at which she attained near-final height. Main out-

come measures included height, weight, body proportions, IGF-1, bone age, and DXA

scan for body composition.

Results

In both treated girls, a considerable increase in height (from –2·3SD and –1·2SD to

–1·2SD and –0·6SD, respectively) and IGF-1 levels (from +0·1SD and –1·4SD to +1·3SD

and +0·9SD, respectively) and, in patient A, a decrease in weight (+1·2 SD to –0·7SD),

and improved body composition (fat percentage from 51·5% to 45·4%) were found.

Both experienced improved muscle strength.

Conclusions

GH treatment in matUPD(14) cases can show beneficial effects on growth and body

composition if started in time. Larger, international studies to determine detailed ef-

fectivity and side effects are suggested.

Growth Hormone Treatment in matUPD(14) 107

6

Introduction

Uniparental disomy (UPD) is the inheritance of both homologues of a chromosome

pair from the same parent. The phenotype of patients with UPD depends on the chro-

mosome or chromosome segment involved, the parent of origin and whether abnormal

variants are located on the chromosome (segment). Maternal uniparental disomy 14

(matUPD(14); Temple syndrome) is an infrequently described entity, first reported in

1991 [1],characterized by prenatal and postnatal growth retardation, hypotonia, feed-

ing difficulties, small hands and feet, unusual face, truncal obesity, advanced bone age,

early puberty and, in some, mild-to-moderate intellectual disability [2, 3]. The majority

(70–80%) of individuals with matUPD(14) inherit two maternal chromosomes 14. In

the remaining individuals, the phenotype is caused by a normal (biparental) disomy but

loss of function of the paternal allel due to a methylation disturbance [2].

The phenotype of matUPD(14) and, especially, the short stature and truncal obesity

are similar to the phenotype in Prader–Willi syndrome (PWS) (Table 1) [4]. Growth

Table 1. Clinical features of matUPD(14) [2, 4, 10, 11, 13, 25] compared to those in Prader–Willi syndrome

[26-29]

Clinical feature matUPD(14) Prader–Willi syndrome

Neonatal features

Prematurity + –

Low birth weight + –

Feeding difficulties + +

Hypotonia + +

Growth

Short stature + +

Truncal obesity + +

Face

Supra-orbital fullness + –

Unusual forehead + (prominent) + (narrow)

Almond-shaped eyes + +

Low-set ears + –

Up-turned nose + –

Thin upper vermillion – +

Short philtrum + –

High-arched palate + +

108 Part III

6

hormone (GH) treatment in children with PWS has been shown to improve growth,

body composition and muscle strength [2, 5], and possibly has a positive effect on

cognition [6]. Consensus guidelines for GH therapy in PWS have been proposed [7].

The comparable combination of short stature and early puberty in individuals with

matUPD(14) suggested treatment with GH can be useful in this entity as well. If early

puberty is present, gonadotropin-releasing hormone analogue (GnRHa) could be given

in addition to the GH treatment [2, 8].

We hypothesized that GH can have a beneficial effect on height and body composi-

tion in individuals with matUPD(14). This treatment has not been reported in detail in

matUPD(14) before. We describe the effect of GH treatment during a 2-year follow-up

period in two girls with matUPD(14) on growth and body composition, and compare

these to a third matUPD(14) girl who could not be treated anymore.

Table 1. Clinical features of matUPD(14) [2, 4, 10, 11, 13, 25] compared to those in Prader–Willi syndrome

[26-29] (continued)

Clinical feature matUPD(14) Prader–Willi syndrome

Downturned corners of the mouth + +

Micrognathia + +

Muscoskeletal features

Small hands and feet + +

Clinodactyly + –

Hypotonia + +

Hypermobile joints + +

Kyphosis or scoliosis + +

Advanced bone age + –

Endocrine features

Precocious puberty + –

Cryptorchidism + +

Cognition/Behaviour

Motor developmental delay + +

Speech developmental delay + +

Intellectual disability ± +

Behavioural problems – +

Other

Recurrent otitis media + –


6

Materials and Methods

Patients

Patient A is an 8·9-year-old Dutch girl, born at 38 weeks of gestation to nonconsan-

guineous parents, with a birth weight of 2340 g (–2·1 SD); length at birth is unknown.

Father’s height is 188 cm and mother’s height 174 cm, resulting in a target height (TH)

of 173·6 cm (+0·5 SD). At 1 year of age, she was evidently hypotonic. Motor develop-

ment was delayed, and she was able to walk at 23 months. Speech development was

delayed as well, possibly related to recurrent ear infections. At 7·0 years, her physical

appearance was characterized by short stature (113·9 cm; –2·1 SD), truncal obesity,

supraorbital fullness, square and low-set ears, a small up-turned nose, open-mouth

appearance and loose hand joints. She was prepubertal. Her social behaviour is nor-

mal. Genetic evaluations at 2·8 years of age showed a maternal uniparental disomy of

chromosome 14. In some cells, a paternal chromosome 14 was also present (trisomy

14 mosaicism). The clinical features were characteristic for matUPD(14) and did not

match those of a trisomy 14 mosaicism [9].

Patient B is an 11·4-year-old Dutch girl, born to nonconsanguineous parents at 40

weeks of gestation, with a birth weight of 2300 g (–2·9 SD); length at birth is unknown.

TH is 170·0 cm (–0·1 SD), father’s height is 185 cm, and mother’s height is 168 cm.

During pregnancy, oligohydramnios and intra-uterine growth retardation (IUGR) had

been observed. In the neonatal period, hypotonia and feeding difficulties were pres-

ent. Motor development and speech were delayed. She had recurrent ear infections.

At 9·3 years, physical examination showed height within the normal range (131·8 cm;

–1·2 SD), truncal obesity, a high forehead, supraorbital fullness, low-set ears, a small

up-turned nose, mandibular prognathism, hypermobile joints and bilateral simian

flexion creases. She is diagnosed with an autism spectrum disorder. She has followed

an early pubertal development, with Tanner breast stage B2 present at the age of 8·5

years, after which GnRHa treatment (triptoreline 3·75 mg/4 weeks) had been started.

Genetic evaluation at the age of 5 showed maternal uniparental disomy of chromosome

14 (matUPD(14)).

Patient C is a 12·7-year-old girl, born at 41 weeks of gestation to nonconsanguineous

parents, with a birth weight of 2880 g (–1·8 SD) and birth length of 48 cm (–1·6 SD).

Father’s height is 166 cm and mother’s height 169 cm, and TH is 164·1 cm (–1·1 SD).

During infancy, no feeding difficulties or hypotonia were seen. She was able to walk

at age 1·5, and speech development was delayed. She was seen by a paediatrician

110 Part III

6

elsewhere from birth until the age of four. In that period, a specific diagnosis was not

revealed. At the age of 11·5, she presented at our clinic with short stature (135 cm, –2·8

SD), generalized obesity, an up-turned nose, a narrow palate, crowding of the tooth,

downturned corners of the mouth, small hand and feet and short metacarpals four and

five. At the age of 11·65, she had her menarche and showed an advanced bone age (13·75

years). Clinical genetic analyses allowed the diagnosis of matUPD(14). GH treatment

was considered to be of little use for height gain due to her age and early maturation.

Predicted adult height was 138·4 cm (–5·1 SD).

Treatment

Treatment with GH was started at the age of 6·9 (patient A) and 9·3 (patient B), respec-

tively. Before treatment anthropometrics, endocrine status and body composition by

dual-energy X-ray absorptiometry (DXA) scan (Table 2) were determined. Both patients

had decreased IGF-1 levels and increased fat mass before GH treatment. In all patients,

anthropometrics were recorded as well as laboratory findings at baseline. In patients A

and B, endocrine status and body composition were determined after respectively one

and 2 years of treatment, and additionally, muscle strength was evaluated anamnesti-

cally.

Both patients were treated with somatropin (recombinant human growth hormone),

initially with 0·48 mg/m2 per day in patient A and 0·34 mg/m2 per day in patient B. In

patient A, the dosage was increased to 0·53 mg/m2 per day after 1 year.


6

Tabl

e 2.

Pat

ient

cha

ract

eris

tics

: bas

elin

e an

d at

follo

w-u

p

Bas

elin

e1-

year

follo

w-u

p2-

year

follo

w-u

p

Pati

ent A

Pati

ent B

Pati

ent C

Pati

ent A

Pati

ent B

Pati

ent C

Pati

ent A

Pati

ent B

Gro

wth

an

d pu

bert

y

Hei

ght,

cm

(SD

S)10

8·8

(–2·

3)12

8·8

(–1·

2)12

7·0

(–3·

1)12

1·7

(–1·

6)14

1·9

(–0·

4)13

5·8

(–3·

0)12

8·8

(–1·

2)14

7·7

(–0·

6)

Targ

et h

eigh

t, c

m (S

DS)

173·

6 (+

0·5)

170·

0 (–

0·1)

163·

7 (–

1·1)

––

––

–

Wei

ght,

kg

(wei

ght f

or

heig

ht S

DS)

20·6

(+1·

2)36

·2 (+

2·4)

34·0

(+2·

3)24

·1 (+

0·5)

51·8

(+2·

5)49

·5 (+

3·0)

27·1

(–0·

7)55

·8 (+

2·3)

BM

I, k

g/m

2 (S

DS)

17·4

(+1·

4)21

·8 (+

2·4)

21·1

(+1·

7)16

·3 (+

0·5)

25·7

(+2·

8)26

·8 (+

2·6)

16·3

(+0·

3)25

·6 (+

2·6)

Tann

er B

, sta

ge1

22

12

–2

2

Labo

rato

ry a

nd

radi

ogra

phic

inve

stig

atio

ns

IGF-

1, n

mol

/l (S

DS)

20 (+

0·1)

16·0

(–1·

4)44

·5 (+

0·8)

30 (+

0·7)

38 (+

0·7)

–43

(+1·

3)47

(+0·

9)

TSH

, mU

/l3·

62·

94·

92·

42·

3–

2·6

3·5

fT4,

pm

ol/l

13·4

17·0

12·0

12·3

14·4

–11

·614

·3

Bon

e ag

e ad

vanc

emen

t,

year

s0·

0+

1·8

+2·

1+

0·1

+1·

4–

+2·

5+

1·1

Bod

y co

mpo

siti

on

Tota

l mas

s, k

g22

·139

·3–

––

–27

·456

·5

Lean

mas

s, k

g10

·119

·0–

––

–14

·226

·4

Fat m

ass,

kg

11·4

19·4

––

––

12·5

28·9

Fat p

erce

ntag

e, %

, (SD

S)51

·5*

49·5

(+2·

1)–

––

–45

·4 (+

1·7)

51·2

(+2·

3)

Mea

n B

MD

, g/c

m2

(z-s

core

)0·

59*

0·82

(+0·

5)–

––

–0·

65 (–

2·0)

0·84

(–0·

7)

BM

D,

bone

min

eral

den

sity

; B

MI,

bod

y m

ass

inde

x; f

T4,

fre

e th

yrox

ine;

IG

F-1,

ins

ulin

-lik

e gr

owth

fac

tor

1; S

DS,

sta

ndar

d de

viat

ion

scor

e; T

SH,

thyr

oid-

stim

ulat

ing

horm

one.

* Too

youn

g fo

r ca

lcul

atin

g SD

S or

z-s

core

[30

].

112 Part III

6

Ethical approval

This observational study did not fall under the Medical Research Involving Human

Subjects Act, and therefore, informed consent was not required. In both patients, treat-

ment with GH was approved by the forum of the National Registration GH treatment

in the Netherlands. Written approval was given by the parents for the use of the ano-

nymized medical records and the anonymized test results of their child for teaching,

research and/or publication in a medical journal by the participating departments of VU

University Medical Center, Amsterdam and Tergooi Hospitals, Blaricum.

Results

The results in both patients during the follow-up during 2 years are summarized in

Table 2 and Fig. 1 (Patient A: a-c, Patient B: d-f ), showing a considerable increased

growth and IGF-1 levels in both patients since GH treatment was initiated and a decrease

in weight and improvement of body composition in patient A. In patient B, weight

and body composition remained stable. In Fig. 1 (g–i), patient C is demonstrated, in

which height SDS (HSDS) further decreased below –3·0 SD and weight for height and

BMI increased above +3·0 and +2·5 SD, respectively. Anamnestically, muscle strength

in patients A and B improved after the initiation of GH treatment, both experienced

increased muscle strength during exercise.


6

Mean

Target height

Child

Age (years)

Hei

ght (

cm)

Mean

Wei

ght (

kg)

Height (cm) Age (years)

Child

BMI (

kg/m

²)

Obesity Overweight Normal weight Underweight Extreme underweight Child

Start GH

Start GH

Start GH

Age (years) Height (cm) Age (years)

a b

Age (years)

Hei

ght (

cm)

Wei

ght (

kg)


BMI (

kg/m

²)

Mean

Target height

Child

Mean

Child


Start GH

Start GH

Start GH

Age (years) Height (cm) Age (years)

d e

Age (years)

Hei

ght (

cm)

Wei

ght (

kg)


BMI (

kg/m

²)

Mean

Target height

Child

Mean

Child


g h

c

f

i

Figure 1. An overview of height for age, weight for height and BMI for age in patient A (fi gure a, b and c),

patient B (fi gure d, e and f ) and patient C (fi gure g, h and i). The start of GH treatment is indicated with the

arrows. Abbreviations: BMI=body mass index; GH=growth hormone.

114 Part III

6

Discussion

We provide here the first detailed report including a 2-year follow-up of GH treatment

in matUPD(14). The literature data on the spontaneous course of growth and body com-

position in matUPD(14) have been analysed using 51 published cases[10]. The majority

of patients had a HSDS below –1·0 (mean height at 0–7 year –2·0SD and at 7–16 year

–1·6SD), and the median adult height was –2·04 SDS (range –2·0 to –4·0 SDS). After

the initial failure to thrive, obesity was present in 49 of the matUPD(14) patients[10].

Others [2] reported obesity in 60% of cases, without the compulsory eating habits as

seen in PWS. Two reports [11, 12] have mentioned the effect of GH treatment on height

gain in matUPD(14), and in both patients, this was reported as ‘effective’: in one, no

further information was provided [12]; in the other, HSDS increased from –2·5 at the

age of 6 to HSDS –1·5 SD at the age of 12 [11]. No data on GH and IGF-1 levels, body

composition or side effects were provided.

In the present patients treated with GH, HSDS changed from –2·3 and –1·2 to –1·2 and

–0·6 in 2 years’ time, respectively. The IGF-1 levels increased from +0·1 and –1·4 to

+1·3 and +0·9 in that same period. Regarding body composition, the results were less

consistent among the two patients. In patient A, a decrease in weight for height SDS

was seen, from +1·2 to –0·7, and the fat percentage decreased from 51·5% to 45·4%.

In patient B, weight for height SDS remained stable (+2·4 to +2·3) as well as her fat

percentage (49·5% to 51·2%). In patient C, who did not receive treatment, HSDS further

decreased and weight increased.

The resemblance in phenotypes of matUPD(14) and PWS has been evaluated in a

series of four patients with matUPD(14), referred because of a suspicion for the pres-

ence of Prader–Willi syndrome [13]. All had been referred in infancy, suggesting that

matUPD(14) and PWS resemble each other significantly at least during this period.

Features that in general were present in matUPD(14) and not in PWS, included less-

specific facial characteristics (frontal bossing, highly arched palate and micrognathia),

prenatal growth failure, on average a higher level of cognitive development and pre-

cocious puberty (Table 1). The combination of age-dependent failure to thrive, short

stature and precocious puberty was considered to be the best clinical diagnostic handle

for matUPD(14). As these become more evident with age, distinction from PWS will

become more easy with increasing age. Other reports also describe this variable, age-

dependent phenotype of matUPD(14) [2, 11]. There are several other disorders sharing

major manifestation with matUPD(14) such as congenital hypothyroidism [14], the


6

PWS-like phenotype in fragile X syndrome [15], 2qter subtelomeric microdeletion [16],

Bardet–Biedl syndrome, Cohen syndrome and Alström syndrome [17], but in each,

other major manifestations allow relatively easy differentiation.

Short stature, obesity and reduced muscle strength are typically present in children

with severe congenital (isolated) GH deficiency (GHD). It is uncertain whether these

features in PWS can be explained by the impaired GH secretion in PWS [18-22]. The

plasma levels of IGF-I are reduced in most children with PWS [19-21]. In matUPD(14),

children deficient GH secretion has been described in matUPD(14) [11], but data

on IGF-I levels are lacking. In our patients, IGF-1 levels at baseline were within the

normal range. Following PWS guidelines, growth hormone stimulation tests were not

performed.

In both presently treated patients, GH treatment was started at a low dosage (0·34–0·48

mg/m2) to evaluate the effect and, after a year, slightly increased to 0·53 mg/m2 in pa-

tient A. The guidelines for GH treatment in PWS advice infants and children with PWS

to start with 0·5 mg/m2 per day, with adjustments towards 1·0 mg/m2 per day [7]. In

the presently described matUPD(14) patients, growth and IGF-1 levels rapidly increased

after the start of GH treatment, and also a decrease in weight occurred in one patient

(Fig. 1b and c). IGF-1 levels were kept below 2·0 SD because IGF-1 levels above 2·0 SD

are associated with a slightly increased risk for developing malignancies [23] .Using

the present schedule, both treated patients remained euthyroid during treatment and

no side effects were evident. Based on this (limited) experience, we recommend to ini-

tially start with a low dosage and determine adjustment of the dosage guided by IGF-1

levels, whilst monitoring effect parameters height, weight and DXA results.

The average age of diagnosing matUPD(14) reported in literature is late, at 9 years,

mainly explained by the age-dependent manifestations of the entity [11]. For optimal

clinical management of matUPD(14), it would be advantageous to diagnosis the entity

at an earlier age. Precocious puberty can best be treated in an early phase, and mean

menarche in matUPD(14) is at 10 years [2, 10]. The same may hold for the treatment

of obesity: in PWS, GH treatment is advised to start before the onset of obesity, which

is typically at 2 years [7]. Following this reasoning, GH treatment in matUPD(14)

should start before 3 years as obesity typically arises at that time [2]. This is supported

by the fact that that body composition of patient B, in which treatment was started at

age 9·3, did not improve. In addition, in patient B, a decrease in bone mineral density

(BMD) was seen (+0·5 to –0·7 SD). Although conflicting results have been reported, the

combination of decreasing BMD and a negative effect on body composition could pos-

116 Part III

6

sibly also be caused by GnRHa treatment in this patient [24]. Still, body composition

remained stable in this patient in contrast to the untreated patient in which increasing

obesity is seen. Lastly, early diagnosis of matUPD(14) allows timely genetic counselling

of the family. Therefore, we suggest to perform diagnostic studies for matUPD(14) in

patients suspected to have PWS in whom methylation testing for PWS is found nega-

tive. If precocious puberty is present in someone who is suspected to have PWS, we

suggest testing for matUPD(14) even before testing for PWS.

We realize we describe GH treatment in only two matUPD(14) patients, and have data

on follow-up of 2 years only. Long-term follow-up in a larger cohort will be needed to

allow for more firm conclusions with respect to optimal GH dosage schemes, determi-

nation of any side effects, objective measurements of muscle strength and assessment

of cognitive functioning. As matUPD(14) is an orphan disorder, this likely will need an

international collaborative study.

We conclude that this report of GH treatment in two matUPD(14) cases provides a good

indication that GH treatment shows beneficial effects particularly if started at an early

age, and suggest a larger, international study to determine effects and side effects in

detail.

Acknowledgements

We are very grateful to the patients and their parents, for their generous collaboration.

This work was funded by the Department of Pediatrics, Tergooi Hospitals, Blaricum,

The Netherlands.


The authors have nothing to declare.


6

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2. Hoffmann, K. & Heller, R. Uniparental disomies 7 and 14. Best Pract Res Clin Endocrinol Metab 2011;1:77–100.

3. Hosoki, K., Ogata, T., Kagami, M. et al. Epimutation (hypomethylation) affecting the chromosome 14q32.2 imprinted region in a girl with upd(14)mat-like phenotype. Eur J Hum Genet 2008;16:1019–23.

4. Falk, M.J., Curtis, C.A., Bass, N.E. et al. Maternal uniparental disomy chromosome 14: case report and literature review. Pediatr Neurol 2005;32:116–20.

5. Carrel, A.L., Myers, S.E., Whitman, B.Y. et al. Growth hormone improves body composition, fat utilization, physical strength and agility, and growth in Prader-Willi syndrome: a controlled study. J Pediatr 1999;134, 215–221.

6. Siemensma, E.P., T-dLvW, R.F., Festen, D.A. et al. Beneficial effects of growth hormone treatment on cognition in children with Prader-Willi syndrome: a randomized controlled trial and longitudinal study. J Clin Endocrinol Metab 2012;97:2307–14.

7. Deal, C.L., Tony, M., Hoybye, C. et al. Growth-Hormone Research Society workshop summary: consensus guidelines for recombinant human growth hormone therapy in Prader-Willi syndrome. J Clin Endocrinol Metab 2013;98:E1072–87.

8. Takahashi, I., Takahashi, T., Utsunomiya, M. et al. Long-acting gonadotropin-releasing hormone analogue treatment for central precocious puberty in maternal uniparental disomy chromosome 14. Tohoku J Exp Med 2005;207:333–338.

9. von Sneidern, E. & Lacassie, Y. Is trisomy 14 mosaic a clinically recognizable syndrome?–case report and review. Am J Med Genet A 2008;146A:1609–13.

10. Ioannides, Y., Lokulo-Sodipe, K., Mackay, D.J. et al. Temple syndrome: improving the recognition of an underdiagnosed chromosome 14 imprinting disorder: an analysis of 51 published cases. J Med Gen 2014;51;495–501.

11. Mitter, D., Buiting, K., von Eggeling, F. et al. Is there a higher incidence of maternal uniparental disomy 14 [upd(14)mat]? Detection of 10 new patients by methylation-specific PCR. Am J Med Genet A 2006;140:2039–49.

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disomy of chromosome 14. Am J of Med Genet A 2011;155A:2584–8.

13. Hosoki, K., Kagami, M., Tanaka, T. et al. Maternal uniparental disomy 14 syndrome demonstrates prader-willi syndrome-like phenotype. J Pediatr 2009;155;900–3.

14. Sher, C., Bistritzer, T., Reisler, G. et al. Congenital hypothyroidism with Prader-Willi syndrome. J Ped Endocrinol and Metab 2002;15:105–7.

15. de Vries, B.B., Fryns, J.P., Butler, M.G. et al. Clinical and molecular studies in fragile X patients with a Prader-Willi-like phenotype. Journal of Medical Genetics 1993;30:761–6.

16. Falk, R.E. & Casas, K.A. Chromosome 2q37 deletion: clinical and molecular aspects. Am J Med Genet C Semin Med Genet 2007;145C:357–71.

17. Gillessen-Kaesbach, G., Gross, S., Kaya-Westerloh, S. et al. DNA methylation based testing of 450 patients suspected of having Prader-Willi syndrome. J Med Genet 1995;32:88–92.

18. Thacker, M.J., Hainline, B., St Dennis-Feezle, L. et al. (1998) Growth failure in Prader-Willi syndrome is secondary to growth hormone deficiency. Horm Res 1998;49:216–20.

19. Eiholzer, U., Stutz, K., Weinmann, C. et al. Low insulin, IGF-I and IGFBP-3 levels in children with Prader-Labhart-Willi syndrome. Eur J Pediatr 1998;157:890–3.

20. Tauber, M., Barbeau, C., Jouret, B. et al. Auxological and endocrine evolution of 28 children with Prader-Willi syndrome: effect of GH therapy in 14 children. Horm Res 2000;53:279–87.

21. Corrias, A., Bellone, J., Beccaria, L. et al. GH/IGF-I axis in Prader-Willi syndrome: evaluation of IGF-I levels and of the somatotroph responsiveness to various provocative stimuli. Genetic Obesity Study Group of Italian Society of Pediatric Endocrinology and Diabetology. J Endocrinol Invest 2000;23:84–9.

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23. Clayton, P.E., Banerjee, I., Murray, P.G. et al. Growth hormone, the insulin-like growth factor axis, insulin and cancer risk. Nat Rev Endocrinol 2011;7:11–24.

24. Willemsen, R.H., Elleri, D., Williams, R.M. et al. Pros and cons of GnRHa treatment for early puberty in girls. Nat Rev Endocrinol 2014;10:352–63.

118 Part III

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25. Eggermann, T., Mergenthaler, S., Eggermann, K. et al. Identification of interstitial maternal uniparental disomy (UPD) (14) and complete maternal UPD(20) in a cohort of growth retarded patients. J Med Genet 2001;38:86–9.

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27. de Souza, M.A., McAllister, C., Suttie, M. et al. Growth hormone, gender and face shape in Prader-Willi syndrome. Am J Med Genet A 2013;161A:2453–63.

28. Gunay-Aygun, M., Schwartz, S., Heeger, S. et al. The changing purpose of Prader-Willi syndrome clinical diagnostic criteria and proposed revised criteria. Pediatr 2001;108:E92.

29. Oiglane-Shlik, E., Zordania, R., Varendi, H. et al. The neonatal phenotype of Prader-Willi syndrome. Am J Med Genet A 2006;140:1241–44.

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part ivQuality of Life

chapter 7Psychometric Performance of the

Quality of Life in Short Stature Youth (QoLISSY) Questionnaire

in the Netherlands

Anja C. Rohenkohl, Susanne E. Stalman, Gerdine A. Kamp,

Monika Bullinger, Julia H. Quitmann


124 Part IV

7

Abstract

The European Quality of Life in Short Stature Youth (QoLISSY) questionnaire is a

disease-specific instrument assessing quality of life (QoL) in children with short stature

from the child and parent perspectives. In order to use the QoLISSY in Dutch samples, a

translation process and psychometric testing is needed. Children diagnosed with short

stature (8 to 18 years) and their parents were recruited from a Dutch growth clinic.

Reliability was assessed using Cronbach’s α and intraclass correlation coefficients

(ICCs). Pearsons’ correlations with the generic KIDSCREEN and a confirmatory factor

analysis (CFA) were performed to test validity. Scales showed good internal consistency

with α ranging from 0.80 to 0.94 (child report) and from 0.85 to 0.95 (parent report).

Test–retest reliability (ICC) ranged from 0.15 to 0.91 (child report) and from 0.14 to

0.83 (parent report). Correlations with the KIDSCREEN in the mean range indicated

criterion validity. The models’ goodness of fit was confirmed by CFA results in the

Dutch and in comparison with the European sample.

Conclusion

The Dutch QoLISSY is a psychometrically reliable and valid short stature-specific QoL

measure. It is now available for use in clinical research and practice to evaluate well-

being and possible effects of growth hormone treatment and psychological interven-

tions in the Netherlands.

Psychometric Performance of the QoLISSY Questionnaire 125

7

Introduction

Short stature, clinically defined as a height below –2 standard deviation scores (SDS), is

a common reason for referral to pediatric endocrinologists for an evaluation of growth-

inhibiting disorders [2, 21]. In addition to growth hormone deficiency (GHD) and

idiopathic short stature (ISS), many other growth-related conditions are seen at growth

clinics such as the Turner syndrome, skeletal dysplasia, oncological and neurological

conditions impacting on growth, familiar short stature, and constitutional growth

delay. We concentrated on GHD as secondary growth disorder which is treated with

growth hormone replacement therapy (GH-T) as well as on ISS for which such treat-

ment is optional. Because of an interest in the burden of disease and the QoL outcome

of GH-T in these conditions, the original QoLISSY questionnaire was developed for

young patients with GHD and ISS and was consequently tested in this group also in the

Netherlands. Children with GHD lack growth hormone and have a low growth velocity

for age or pubertal stage. The clinical approach is to accelerate growth and improve

their final height through GH-T, and the majority of children who have been diagnosed

with GHD are therefore treated with GH.

ISS is defined as a condition in which the height of an individual is more than 2 SDS

below the mean height for age and gender in the population, without evidence of sys-

temic, endocrine, nutritional, or chromosomal abnormalities [8]. Specifically, children

with ISS have normal birth weight and are GH sufficient. While clinical effectiveness of

GH treatment in ISS has been documented, the use of growth hormone for treatment

of ISS has only been approved in the USA in children whose height is more than 2.25

SDS (1.2nd percentile) below the mean for age and sex [7]. The clinical effectiveness

of GH treatment in ISS is well documented [1, 11, 17]. In contrast to the USA, treat-

ment of ISS with GH is not approved by the European Medicines Agency [3], although

the impact of short stature and its treatment on children’s and adolescents’ mental

health and behavioral functioning has been documented. The effects on quality of life

(QoL) have only recently been investigated. QoL is defined as the person’s subjective

evaluation of their health in terms of physical, psychological and social well-being [4].

It can be measured via generic and condition-specific instruments. There is however

a lack of internationally available short stature-specific instruments that reflect the

child and parent perspectives. Therefore, the aim of the European Quality of Life in

Short Stature Youth (QoLISSY) Study Group was to develop and psychometrically test a

disease-specific questionnaire for short statured children and adolescents.

126 Part IV

7

The original QoLISSY project utilized a simultaneous approach to cross-cultural QoL

assessment with a common conceptual development of the instrument across different

European countries and languages. The international guidelines for the development of

quality of life measures including focus groups, pilot testing with cognitive debriefing,

and field and retesting were followed resulting in a cross-culturally valid instrument

[6].

The aim of the original European QoLISSY study was to construct a psychometrically

sound and cross culturally valid tool to assess the impacts of short stature on QoL in

children and adolescents from their own perspective with the added perspective of their

parents. This development and psychometric testing of the original QoLISSY instrument

was described in previous papers [5]. The QoLISSY questionnaire was also validated in

Flemish in Belgium [13]. The current paper describes the translation, adaptation and

validation of a Dutch language version based on the Flemish language version for use in

children/adolescents with short stature and their parents in the Netherlands.

Subjects and Methods

Study Design

The validation of the QoLISSY questionnaire in a Dutch population of clinically referred

children and adolescents included a forward and backward translation of the existing

Flemish version into Dutch, followed by a cognitive debriefing and a pilot test and

finally a field test together with a retest.

The Dutch QoLISSY questionnaire was used in a pilot test and sent out to the families

with a short statured child via mail together with a prepaid return envelope. Partici-

pants of the study were asked to fill out the questionnaire and for cognitive debriefing

purposes, give a feedback on the questionnaire in terms of understanding, interpreta-

tion, and relevance of items. They were also asked whether any aspects related to their

experience with short stature were missing and should be added.

After receiving and evaluating the feedback of the families, the QoLISSY questionnaire

was adapted according to their responses. A number of 13 short statured children/

adolescents from 8 to 18 years as well as at least one parent and parents of younger

children (4–7 years) participated in the Dutch cognitive debriefing and pilot test phase.

As a result, some items were changed in wording, where the Dutch differs from the

Flemish language, but in general items were judged as applicable, important, and clear


7

by the participating Dutch families. No additional themes emerged to be added to the

questionnaire. Quantitative results show low floor and ceiling effects below 10 % and

mean scale scores (possible range between 0 and 100) of 41.80 to 72.60 with standard

deviations ranging from 9.03 to 22.35.

For the field test, the adapted questionnaires for short statured children and parents

in the Netherlands were distributed via mail along with a prepaid return envelope. For

validation purposes, participants were asked to fill out the QoLISSY questionnaire as

well as the generic KIDSCREEN questionnaire [20]. Fifty children/adolescents and 56

parents (including the children/parents from the cognitive debriefing) were invited to

participate in the field test. Test–retest was to be performed with a minimum of three

patients per age group and gender.

Recruitment of Participating Families

Patients with diagnosed short stature (ISS or GHD) aged between 8 and 18 years and

their parents were asked to participate in the Dutch QoLISSY validation study. The study

was conducted in the Tergooi Hospital, a general, nonacademic hospital with a special

growth clinic which is consulted by about 200 new patients per year who have ques-

tions about their height (too short or too tall) and pubertal development (too early or

too late). Exclusion criteria were other medical conditions (e.g., diabetes and asthma)

or a multiple hormone deficiency as well as severe physical or mental conditions

making participation difficult as judged by the investigators. In addition, parents of

younger children (aged 4 to 7 years) were asked to participate. An informed consent

(for parents) and assent (for children) was a requirement to participate in the study. The

study had been approved by the local medical ethics committee of Tergooi Hospitals in

Blaricum and Hilversum (kv/12.012).

Measures

Participating families completed the disease-specific QoLISSY questionnaire with a

total of 53 items for children/adolescents and 66 items for parents. Three core scales

constitute the total QoL score of the QoLISSY, namely Physical: six items—physical

limitations that the child can experience in everyday life due to short stature; Social:

eight items—refers to the way short stature interferes with the child’s social life; and

Emotional: eight items—refers to the child’s feelings and emotions with regards to

his short stature. These domains are supplemented by three additional scales cover-

ing Coping aspects (ten items—referring to the way the child copes with negative

128 Part IV

7

feelings or experiences due to his short stature), experiences with GH Treatment (14

items—referring to the child’s experiences linked to growth hormone treatment), and

general Beliefs about height (with four items—referring to the child’s beliefs about

stature). The parent-reported version reflects the child version in item content and is

used to obtain observer report as well as to compare the QoL between child and parent

perspectives. The parent report additionally includes aspects of the child’s Future (five

items—referring to the parent’s worries about the future of their child in relation to his

short stature) and Effects of the child’s short stature on the parents (11 items—refer-

ring to the impact the child’s growth problem has on his parent’s feelings). Responses

are coded on a standard five-point Likert scale ranging from “not at all/never” to “ex-

tremely/always.” Missing values were substituted by the scales mean score if at least

80 % of the items per scale were completed. Within the original QoLISSY Study [18],

Cronbach’s alpha ranged between 0.82 (Coping) and 0.92 (total QoL score) for the

child self-report and between 0.86 (Physical) and 0.95 (total QoL score) for the parent

report [5, 12]. The generic KIDSCREEN questionnaire with 52 items provides detailed

information on ten QoL dimensions (The KIDSCREEN Group Europe, 2006). These are

Physical Well-being, Psychological Well-being, Moods & Emotions, Self-Perception,

Autonomy, Parent Relation & Home Life, Financial Resources, Social Support & Peers,

School Environment, and Social Acceptance (Bullying). Questions were answered via a

similar five-point Likert scale (never to always). The KIDSCREEN was used to examine

the convergent validity of the QoLISSY. Sociodemographic and clinical data on height

(cm), diagnosis, treatment status, gender, and age were collected as well.

Data analysis

In the first step of the validation process, an overview of the scale distributional charac-

teristics (mean, standard deviation, floor and ceiling effects) was obtained. Reliability

analysis was performed using Cronbach’s alpha as in indicator of internal consistency

for each scale (α > 0.70 can be considered as acceptable [9]). Intraclass correlation co-

efficients (ICCs) were calculated to examine test–retest reliability and to reflect congru-

ency in the child–parent dyads. Differences in mean scale scores between subgroups

regarding age, gender, and SDS height (> –2 SDS, ≤ –2 SDS) were analyzed via t tests.

To test for convergent validity, Pearson’s correlations between the generic KIDSCREEN

scale scores and the disease-specific QoLISSY subscales were inspected. Correlations

in the mean range of r = 0.40 to 0.60 were expected to indicate measurement of the

same but not the identical content [8].


7

Known groups validity in terms of differences between height (> –2 SDS vs ≤ –2 SDS)

was assessed by comparing scale mean scores via the Student’s t tests. These were

used to analyze differences in the QoLISSY according age and gender as well. Since

only eight children received GH treatment, group comparison across treatment status

(treated vs untreated) was not performed. The level of significance was reported at two

thresholds, 0.05 and 0.01.

Construct validity was examined via a confirmatory factor analysis (CFA). Given the

small sample size (N = 49 Dutch children), indices of fit (comparative fit index (CFI),

root mean square error of approximation (RMSEA), χ 2/df ) were compared in a

multigroup analysis investigating differences between the existing European dataset

(including data from Spain, France, the UK, Sweden, and Germany; N = 268 children

and N = 317 parents) and the Dutch data. This procedure named “TOCO approach”

(take one country out) has previously been used in the cross-cultural analysis of the

QoLISSY across languages and indicated cross-cultural equivalence in psychometric

performance [6].

Reference values were taken from Hu and Bentler [10] indicating a good model with

χ 2/df <2 and acceptable with <3. The CFI should be >0.90 and the RMSEA should be

<10.0 to be acceptable.

Results

Sociodemographic and clinical characteristics

A total of 49 children/adolescents between 8 and 18 years and 49 parents plus 8 parents

of younger children between 4 and 7 years were included in this validation study. Pa-

tients’ mean age was 11.82 ± 3.18 years. A total of 23 children (age 8–12 years) as well as

26 adolescents (age 13–18 years) were included. The majority of children/adolescents

were diagnosed with ISS (80.7 %), and 3 out of 49 children currently received GH treat-

ment. About 60 % of the patients had reached normal height (> –2 SDS) at time of

assessment while about 40 % were short statured (see Table 1). A total of 13 families

filled in the questionnaire again about 2 weeks later (retest).

Psychometric testing of the Dutch QoLISSY version

Data quality in terms of missing values for children/adolescents and their parents was

acceptable. QoLISSY scale scores were calculated by mean substitution if missing values

130 Part IV

7

were present in less than 20 % of the items per scale. Missing data were present in five

patient-reported cases and six parent reports only in the additional Coping subscale.

Distributional characteristics and reliability (test–retest and internal consistency) of

the QoLISSY scales are shown in Table 2. Mean scale scores (M) from the child report

and the parent report were in the mid to upper range of the 0–100 scores. The cor-

responding standard deviations were high. Almost no floor and ceiling effects were

present for the QoLISSY scale scores—except for the Beliefs scale (ceiling children 24.5

%, parents 28.1 %) and Future scale (ceiling 39.3 %). Internal consistency coefficients

ranged between r = 0.80 (Physical/Beliefs) and r = 0.94 (Treatment/total QoL score) for

children/adolescents and between r = 0.84 (Beliefs) and r = 0.95 (total QoL Score) for

parents, indicating high reliability. Parent–child agreement was analyzed with the ICC.

Concordance between child and parent dyads ranged from r = 0.34 (Physical) to r = 0.61

(Coping).

Test–retest concordance was tested with an intraclass correlation as well. The coeffi-

cient for the QoLISSY questionnaire in almost all scales ranged from r = 0.15 (Physical)

to r = 0.91 (Beliefs) in the child self-report and similarly in the parent report (r = 0.14

(Physical) to r = 0.83 (Future)).

Table 1. Characteristics of the Dutch patient sample

4–7 yearsa 8–12 years 13–18 years Total

n % n % n % n %

Sex

Girl 3 37.5 12 52.2 10 38.5 25 43.9

Boy 5 62.5 11 47.8 16 61.5 32 56.1

Condition

GHD 3 37.5 4 17.4 4 15.4 11 19.3

ISS 5 62.5 19 82.6 22 84.6 46 80.7

Treatment

Untreated 5 62.,5 18 78.3 23 88.5 46 80.7

Treated 3 37.5 5 21.7 3 11.5 11 19.3

Height (SDS)b

> –2.0 5 71.4 11 47.8 18 69.2 34 60.7

≤ –2.0 2 28.6 12 52.2 8 30.8 22 39.3

GHD growth hormone deficiency, ISS idiopathic short stature. aOnly parents filled in the questionnaire. bActual height is missing in some cases


7

Tabl

e 2.

Dis

trib

utio

nal c

hara

cter

isti

cs o

f the

pat

ient

and

the

pare

nt v

ersi

on o

f the

Dut

ch Q

oLIS

SY s

cale

s in

the

fiel

d te

st

QoL

ISSY

Sca

les

Tota

l Sam

ple,

NM

ean

(M)*

SD%

Flo

or%

Cei

ling

Cro

nba

ch’s

Alp

haIC

CPa

ren

t–ch

ild

NR

etes

tIC

C

Children

Parents

Children

Parents

Children

Parents

Children

Parents

Children

Parents

Children

Parents

Children

Parents

Children

Parents

Phys

ical

4956

80,3

777

.32

16.0

217

.51

2.0

1.8

6.1

8.9

0.80

0.85

0.34

1113

0.15

0.14

Soci

al49

5778

.71

75.0

718

.32

17.8

62.

01.

86.

17.

00.

880.

880.

5310

130.

690.

64

Emot

ion

al49

5779

.83

73.6

918

.29

17.8

22.

01.

814

.38.

80.

880.

870.

3811

130.

830.

55

Cop

ing

4451

40.4

641

.47

22.3

220

.03

2.3

3.9

2.3

2.0

0.86

0.89

0.61

1012

0.80

0.23

Bel

iefs

4957

80.2

378

.87

19.6

120

.85

2.0

1.8

24.5

28.1

0.80

0.84

0.52

1113

0.91

0.74

Trea

tmen

t8

955

.13

67.1

428

.99

18,1

212

.511

.112

.511

.10.

940.

890.

34--

----

----

----

----

----

--

Futu

re**

----

--56

----

--87

,05

----

--17

.76

----

--1.

8--

----

39.3

----

--0.

90--

----

----

--12

----

--0.

83

Effe

cts

on P

aren

ts**

----

--56

----

--83

.24

----

--15

.16

----

--1.

8--

----

5.4

----

--0.

90--

----

----

--13

----

--0.

64

QoL

tota

l Sco

re49

5679

.64

75.3

415

.56

16.4

32.

01.

82.

01.

80.

940.

950.

4310

130.

560.

50

ICC

intr

acla

ss c

orre

lati

on c

oeffi

cien

t.a R

ange

0–1

00.

b Onl

y in

par

ents

’ ver

sion

.

132 Part IV

7

Differences according to sociodemographic characteristics were inspected for informa-

tion about the potential effects of age and gender on scale scores to be taken into con-

sideration regarding scoring and clinical interpretation in future studies. Differences in

mean scale scores between age groups (8–12 and 13–18 years) were only present in the

Physical scale of the child self-report (t(47) = –2.55, p = 0.014, α = 0.05). Younger chil-

dren (M = 74.49 ± 17.84) reported more limitations in their perceived physical QoL than

adolescents (M = 85.58 ± 15.57). Regarding differences between gender, results showed

higher scores for emotional aspects of QoL for boys (M = 85.75 ± 15.80) than for girls

(M = 72.56 ± 18.85; t(47) = –2.66, p = 0.11). In the parent report, significant differences

Table 3. Differences QoLISSY scales according to height below and above –2 SDS (at time of recruitment)

Scales

>-2SDS ≤-2SDS

t df PM SD M SD

Physical

Children 85.37 11.75 73.13 18.75 2.81 47 0.007

Parents 79.70 19.44 72.92 13.47 1.42 53 0.161

Social

Children 83.74 12.64 71.41 22.75 2.43 47 0.019

Parents 77.95 18.75 70.19 15.98 1.60 54 0.115

Emotional

Children 81.59 15.14 77.28 22.26 0.80 47 0.423

Parents 73.53 18.74 73.46 17.02 0.01 54 0.990

Coping

Children 33.69 20.66 48.60 21.99 -2.32 42 0.026

Parents 36.45 20.43 48.72 18.00 -2.20 48 0.033

Beliefs

Children 80.39 19.82 80.00 19.83 0.07 47 0.947

Parents 80.51 21.80 75.38 19.34 0.90 54 0.373

Future

Parents 90.30 16.77 81.59 18.48 1.81 53 0.076

Effects on Parents

Parents 83.86 16.95 81.66 12.31 0.522 53 0.604

Total score

Children 83.57 10.47 73.94 19.80 2.22 47 0.032

Parents 77.04 18.01 72.19 13.77 1.07 53 0.289

aThe scales “Future” and “Effects on parents” only exist in the parents’ version.


7

between boys and girls were present in the three QoL subscales as well as in the total

QoL score (t(54) = –2.23, p = 0.030). Parents of boys (M = 79.58 ± 14.84) reported their

children to have a significantly better QoL than parents from girls (M = 70.07 ± 17.06).

Shorter children with a height ≤ –2 SDS reported a lower QoL in the Physical (p = 0.007),

Social (p = 0.019), and Coping (p = 0.026) scales of the QoLISSY questionnaire (see

Table 3). Parents of shorter children only rated their children in aspects of Coping

lower in comparison to parents of taller children (p = 0.033).

Significant correlations (r = 0.40–0.60) between the generic KIDSCREEN and the short

stature-specific QoLISSY questionnaire were present in QoLISSY core scales (Physical,

Social, and Emotional) reflecting the child’s QoL and Moods & Emotions, Self-Percep-

tion, as well as Autonomy (KIDSCREEN). The highest correlation was found between

Treatment (QoLISSY) and Autonomy (KIDSCREEN) in the child self-report (r = 0.76).

In the parent report, significant correlations were present between Self Perception

(KIDSCREEN) and nearly all parent-related QoLISSY scales except Coping and Treat-

ment. The correlation was highest between Emotional (QoLISSY) and Self-Perception

in the parent report (r = 0.72), see Table 4.

To analyze the factorial structure of the QoLISSY questionnaire in the Dutch dataset, the

TOCO approach was used as published recently [6]. This means to add the Dutch data

to the original field test data and compare results with and without the Netherlands. In

the model, the three core scales were represented by their items and are constituted as

three independent dimensions of the latent construct QoL.

Table 5 shows the results of the multigroup analyses to test for differences between

model fit in the European sample with and without the Netherlands samples. No sig-

nificant difference was found, confirming the measurement and structural invariance

of the structural model across the two subsamples (with and without the Dutch data)

for the child self-report as well as for the parent report. The indices (χ 2/df, CFI, and

RMSEA) show an overall acceptable fit to the dimensional structure of the QoLISSY

questionnaire within the dataset.

134 Part IV

7

Tabl

e 4.

Cor

rela

tion

coe

ffici

ents

(Pea

rson

r) f

or th

e Q

oLIS

SY s

cale

s w

ith

subs

cale

s of

KID

SCR

EEN

-52

(chi

ld–p

aren

t)

KID

SCR

EEN

-52

Phys

ical

wel

l-be

ing

Psyc

holo

gica

l

wel

l-be

ing

Moo

d &

Emot

ions

Self

-Per

cept

ion

Aut

onom

yPa

rent

sFi

nanc

ial

Soci

alSc

hool

ing

Bul

lyin

g

QoLISSY

Phys

ical

-0.0

16/ -

0.03

10.

020/

-0.1

100.

505*

*/ 0

.134

0.26

3/ 0

.496

**0.

271/

0.1

080.

123/

0.02

00.

143/

0.2

110.

002/

-0.0

430.

181/

0.1

760.

476*

*/ 0

.216

Soci

al0.

158/

-0.0

610.

290/

-0.0

100.

535*

*/ 0

.144

0.60

0**/

0.5

81**

0.42

1**/

0.1

290.

350*

/ 0.0

530.

202/

0.0

740.

226/

0.1

060.

312*

/ 0.3

29*

0.36

0*/ 0

.217

Emot

iona

l0.

209/

0.0

620.

334*

/ 0.0

430.

529*

*/ 0

.123

0.56

2**/

0.7

17**

0.44

5**/

0.1

200.

307*

/ 0.1

220.

123/

0.0

330.

137/

0.2

300.

300*

/ 0.2

72*

0.29

5*/ 0

.152

Cop

ing

0.43

0**/

0.2

820.

217/

0.3

08*

-0.0

12/ 0

.142

0.06

5/ 0

.001

0.22

2/ 0

.115

0.37

6*/ 0

.154

0.14

1/ 0

.474

**0.

117/

0.2

210.

317*

/ 0.3

61*

0.26

1/ 0

.203

Bel

iefs

0.09

4/ -0

.123

0.17

6/ -0

.052

0.29

2/ 0

.038

0.61

3**/

0.4

52**

0.30

9*/ -

0.09

70.

163/

-0.0

170.

141/

-0.1

450.

117/

0.2

500.

317*

/ 0.2

61-0

.091

/ 0.0

36

Trea

tmen

t0.

529/

0.0

900.

432/

0.7

29*

-0.0

34/ 0

.525

-0.0

86/ 0

.320

0.76

4**/

0.1

650.

646/

0.6

670.

513/

0.1

320.

380/

0.2

490.

607/

0.6

250.

295/

0.2

98

Futu

rea

-0.1

52-0

.130

0.16

20.

495*

*0.

072

0.02

80.

057

0.02

00.

263

0.28

8*

Effe

cts

on

Pare

ntsa

0.11

1-0

.116

0.12

90.

491*

*0.

074

0.03

30.

260

0.04

70.

136

0.34

0*

QoL

ISSY

tota

l

scor

e

0.13

8/ -0

.010

0.25

1/ -0

.027

0.59

2**/

0.1

470.

432*

*/ 0

.654

**0.

300*

/ 0.1

30-1

0.0/

0.0

730.

181/

0.1

180.

142/

0.1

120.

303*

/ 0.2

82*

0.41

9**/

0.2

29

*Sig

nifi

cant

at p

< 0

.05;

**s

igni

fica

nt a

t p <

0.0

1a O

nly

pare

nt’s

sca

le


7

Discussion

This validation study focused on the assessment of QoL in Dutch children with GHD/

ISS from the child and parent perspectives. Pediatric endocrinologists who treat short

statured children are aware of the impact the disease might have on the affected fami-

lies: restrictions in physical activities especially sports, regular appointments with the

clinician and problems with the GH-T.

QoL was assessed in this study with the disease-specific QoLISSY questionnaire for

self-report in children aged 8–18 years and report from parents of children aged 4–18

years.

The results demonstrate that the Dutch version of the QoLISSY questionnaire is a

valid and reliable instrument for the assessment of QoL in children with GHD/ISS. It

shows acceptable correlations with the well-validated generic KIDSCREEN question-

naire [19] as well as good internal consistency in terms of Cronbach’s alpha >0.80 and

test–retest reliability (r ≥ 0.50 for the total QoL score). Confirmation of the factorial

structure examined via CFA and the TOCO approach indicated construct validity in the

child self-report and in the parent’s report. Results showed no differences in factorial

structure between the Dutch sample and that of the original European QoLISSY study.

It is important to note that this does not imply comparability of the QoLISSY mean

score between countries. The Dutch population is considered the tallest population in

Table 5. Comparison of the factorial structure in the European sample without (original model) and with the

Netherlands (plus NL)

n

Model’s goodness of fit Model comparison

Measurement invariance

Structural invariance

χ2; p χ2/df CFI RMSEA Δχ2 Δdf p Δχ2 Δdf p

Chi

ldre

n

Original Model 263 615.35; 0.05

2.99 0.88 0.087 1.515 19 1.00 0.147 2 0.929

Original Model PLUS the Netherlands

312 1023.3; <0.001

2.52 0.91 0.051

Pare

nts

Original Model 259 718.81; <0.05

3.49 0.87 0.098 5.588 19 0.999 0.036 2 0.982

Original Model PLUS the Netherlands

315 1150,36; <0.001

2.85 0.91 0.057

136 Part IV

7

the world [16]. If tested in a representative sample, short stature could be expected to

result in lower QoL in comparison to Dutch peers or in higher QoL as compared with

non-Dutch populations. Because of composition and potential selection effects, QoL of

the clinical samples cannot be compared in our study [16].

High ICCs indicate agreement between child and parent judgments. Differences be-

tween smaller and taller children in physical and social aspects of QoL show that the

QoLISSY is able to detect height-related differences in perceived QoL. Shorter children

report a lower QoL on these subscales of the QoLISSY than taller children.

According to Wiklund et al. [20], it is well known that differences in perceived QoL ex-

ist between boys and girls. Current findings of age and gender effects on QoLISSY scale

scores suggest their inclusion as covariates in the statistical analysis plans of future

studies. The main limitation of this study is the monocentric design and a limited num-

ber of study participants, especially the low number of GH-treated patients enrolled,

which makes subgroup analysis difficult. A related limitation is the low number of

parents of younger children aged 4–7 years, which might be due to parental reluctance

to health services consultation or due to a recruitment bias. Further studies should use

a controlled design (ideally a randomized clinical trial) to investigate the impact of rGH

treatment on the QoL of patients with GHD or ISS. The explanation of this may be

found in the fact that parents of younger children tend to wait for catch-up growth

before they introduce their children to endocrinologists [20].

Although this study presents a psychometric analysis of the QoLISSY questionnaire,

results identify specific problems from the children and the parent perspectives. Physi-

cal, social, and coping difficulties were found from the child perspective and problems

concerning the child’s future according to the parents. Given that coping is a problem,

it is possible to intervene with a psychosocial group intervention to encourage coping

strategies (such as with the program “op Koers” in the Netherlands [14, 15]) which

could be offered to children and results might be compared with GH treatment alone

or in combination, e.g., in a randomized controlled trial. Questions regarding efficacy

and effectiveness of psychological versus pharmacological interventions alone or in

combination with psychological intervention could thus be answered in the future.

The results of this study are encouraging that adaptation of the QoLISSY questionnaire

for use in other populations is possible in that the concepts of quality of life impacts

appear to be applicable to a broad range of children across cultures and languages.

Additional validation studies are currently ongoing in Greece, Italy, and the USA.


7

In conclusion, the QoLISSY can be used as a treatment outcome indicator in research

but also in clinical management to make treatment choices, understand patient and

parent needs, and to enhance the well-being and functioning of children and adoles-

cents with diagnosed short stature.

138 Part IV

7

References

1. Albertsson-Wikland K, Aronson AS, Gustafsson J, Hagenas L, Ivarsson SA, Jonsson B, Kristrom B, Marcus C, Nilsson KO, Ritzen EM, Tuvemo T, Westphal O, Ãman J. Dose-dependent effect of growth hormone on final height in children with short stature without growth hormone deficiency. J Clin Endocrinol Metab 2008;93:4342–50.

2. Allen DB, Cuttler L. Clinical practice. Short stature in childhood - challenges and choices. New Engl J Med 2013;368:1220–8.

3. Bryant J, Cave C, Milne R. Recombinant growth hormone for idiopathic short stature in children and adolescents. Cochrane Database Syst Rev 2007:CD004440.

4. Bullinger M, Hasford J. Evaluating quality-of-life measures for clinical trials in Germany. Control Clin Trials 1991;12:91–105.

5. Bullinger M, Quitmann J, Power M, Herdman M, Mimoun E, Debusk K, Feigerlova E, Lunde C, Dellenmark-Blom M, Sanz D, Rohenkohl A, Pleil A, Wollmann H, Chaplin JE. Assessing the quality of life of health-referred children and adolescents with short stature: development and psychometric testing of the QoLISSY instrument. Health Qual Life Outcomes 2013;11:76.

6. Bullinger M, Quitmann J, Silva N, Rohenkohl A, Chaplin J, DeBusk K, Mimoun E, Feigerlova E, Herdman M, Sanz D, Wollmann H, Pleil A, Power M. Cross-cultural equivalence of the patient- and parent-reported Quality of Life in Short Stature Youth Questionnaire. Horm Res Paediatr 2014;82:18–30.

7. Cohen LE. Idiopathic Short Stature A Clinical Review. J Amer Med Assoc 2014;311:1787–96.

8. Cohen P, Rogol AD, Deal CL, Saenger P, Reiter EO, Ross JL, Chernausek SD, Savage MO, Wit JM, I. S. S. Consensus Workshop participants. Consensus state-ment on the diagnosis and treatment of children with idiopathic short stature: a summary of the Growth Hormone Research Society, the Lawson Wilkins Pediatric Endocrine Society, and the European Society for Paediatric Endocrinology Workshop. J Clin Endocr Metab 2008;93:4210–7.

9. Cronbach LJ. Coefficient alpha and the internal structure of tests. Psychometrica 1951;16:297–334.

10. Hu L, Bentler PM. Cutoff criteria for fit in-dexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model 1999;6:1–55.

11. Mehta A, Hindmarsh PC. The use of somatropin

(recombinant growth hormone) in children of short stature. Paediatr Drugs 2002;4:37–47.

12. Quitmann J, Rohenkohl A, Bullinger M, Chaplin J, Herdman M, Dolores S, Mimoun E, Feigerlova E, DeBusk K, Power M, Wollmann H, Pleil A. Parental perception of health-related quality of life in children and adolescents with short stature: Literature review and introduction of the parent-reported QoLISSY instrument. Pediatr Endocrinol Rev 2013;11:147–160.

13. Rohenkohl A, De Schepper J, Vanderfaeillie J, Fricke K, Hendrickx S, Lagrou K, Bullinger M, Quitmann J, QoLISSY Study Group. Validation of the Flemish version of the Quality of Life in Short Stature Youth (QoLISSY) questionnaire. Acta Clin Belg 2014;69:177–182.

14. Scholten L, Willemen AM, Grootenhuis MA, Maurice-Stam H, Schuengel C, Last BF. A cognitive behavioral based group intervention for children with a chronic illness and their parents: a multicentre randomized controlled trial. BMC Pediatr 2011;11:65.

15. Scholten L, Willemen AM, Last B, Maurice-Stam H, van Dijk EM, Ensink E, Zandbelt N, van der Hoop-Mooij A, Schuengel C, Grootenhuis MA. Efficacy of psychosocial group intervention for children with chronic illness and their parents. Pediatrics 2013;131:1196–1203.

16. Schönbeck Y, Talma H, van Dommelen P, Bakker B, Buitendijk SE, HiraSing RA, van Buuren S. The world’s tallest nation has stopped growing taller: the height of Dutch children from 1955 to 2009. Pediatr Res 2013;73:371–7.

17. Tanaka T, Cohen P, Clayton PE, Laron Z, Hintz RL, Sizonenko PC. Diagnosis and management of growth hormone deficiency in childhood and adolescence--part 2: growth hormone treatment in growth hormone deficient children. Growth Horm IGF Res 2002;12:323–41.

18. The European QoLISSY Group. Quality of Life in Short Stature Youth. The QoLISSY Questionnaire – User’s Manual. (Pabst Science Publishers, Lengerich, 2013).

19. The KIDSCREEN Group Europe. The KIDSCREEN questionnaires: Quality of life for children and adolescents - Handbook. (Pabst Science Publishers, Lengerich, 2006).

20. Wiklund I, Erling A, Albertsson - Wikland K. Critical review of measurement issues in quality of life assessment for children with growth problems. In: Drotar D (ed) Measuring health-related quality of life


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in children and adolescents. (Lauwrence Erlbaum Associates, Mahwah, 1998).

21. Wit JM, Ranke MB, Kelnar CJH. ESPE classification of paediatric endocrine diagnosis. Short stature. Horm Res 2007;86:1–5.

chapter 8Summary and

General Discussion

Summary and General Discussion 143

8

The aim of this thesis is to focus on issues that arise when dealing with children with

growth disorders – from growth monitoring and genetic analysis to treatment effects

on growth and quality of life. This chapter summarizes and discusses the main out-

comes of the various studies described in this thesis and presents implications and

perspectives for future research.

Growth Monitoring

The first part of this thesis focuses on guidelines for diagnostic workup of children

with growth disorders, including either growth failure or overgrowth. Little is known

about the optimal criteria for referral and diagnostic workup of children with growth

disorders in order to uncover underlying pathology. Since the shape of a child’s growth

curve is influenced by the etiology of the growth disorder (for example, congenital or

acquired underlying disorders), genetic factors, pubertal development, environmental

and in some cases even psychological factors, it has proven difficult to define cut-off

criteria. Still, various studies have attempted to develop an efficient set of criteria and a

number of consensus-based criteria as well as various evidence-based guidelines have

been established [1-5]. However, evaluation and validation of such guidelines has sel-

dom been performed and consensus on the most efficient criteria and their cut-offs has

not been established. In Part 1 of this thesis we investigate the incidence of pathology in

children with suspected growth disorders and evaluate existing guidelines for growth

monitoring.

First, we retrospectively investigated the sensitivity and specificity of guidelines for

diagnostic workup currently used in the Netherlands, Finland and the UK in a Dutch

cohort of children aged 3 to 10 years with growth failure (Chapter 2). These children

were referred for suspected disorders of growth to our general paediatric outpatient

clinic. In 18% of these children a pathological condition was found explaining their

144

8

Summary and General Discussion

growth failure. The Dutch [2] and Finnish guidelines [4], consisting of criteria for

height standard deviation score (HSDS), distance to target height (i.e. the gender-

adjusted mid-parental height) and a decreased growth rate were proven to be effective

for use in growth monitoring, using similar cut-off values. Both guidelines showed

a good sensitivity and specificity for detecting pathological causes of growth failure,

with recent growth deflection as an important warning sign. The sensitivity of the UK

guideline was considerably lower.

Second, in Chapter 3 we performed a similar study in adolescents, taking into account

the influence of puberty on growth. In 7% of the adolescents a specific diagnosis could

be established, so significant pathology at an adolescent age can still be found. Con-

stitutional delay of growth and puberty was diagnosed in 10% of adolescents. A high

sensitivity for detecting pathology was found when applying all Dutch criteria as used in

children aged 3 to 10 years, whereas the sensitivity of the current Dutch recommenda-

tion for adolescents (only a HSDS <-2.5) was considerably lower. This implicates that

although establishment of auxological criteria in adolescents is complicated due to the

influence of delayed pubertal onset on growth, all main growth criteria are important

for growth monitoring in adolescents.

Third, we investigated the diagnostic workup and follow-up in children with tall stature

(Chapter 4). We found a very low incidence of pathology (1.5%) in children referred for

tall stature. Most children were classified as idiopathic tall or had constitutional ad-

vancement of growth, and 50% of the patients referred for tall stature were not tall ac-

cording to its definition (their HSDS was <+2.0). Furthermore, we observed that in only

a few patients adult height reduction by epiphysiodesis was indicated and performed

and that adult height prediction by Bayley and Pinneau (BP) results in overestimation

of adult height. Based on our results and review of the literature we propose a new

diagnostic flow chart, focussing on excluding pathology and giving suggestions for

follow-up.

The similar sensitivities between the Dutch and the Finnish guidelines for growth

failure can be explained by the comparable criteria and cut-off values for HSDS and

distance to target height (TH). Regarding adolescents, not only height SDS should be

used as an indication for pathological growth, but the other main growth criteria are

equally important for the detection of pathology. Optimal criteria based on the Dutch

and Finnish cut-off values could therefore be considered for future use, both in younger

children and adolescents. Regarding the Finnish guideline, a complicating factor in its


8

use is that calculation of certain criteria is complicated and can only be analysed by a

computer.

Since the Dutch referral criteria are relatively simple, and do not need computer-

ized algorithms, they are now generally used in preventive child health care. When

user-friendly software algorithms become available, we recommend to investigate

the diagnostic yield of both sets of criteria in a prospective study, and explore possible

improvements. One of the main limitations of the Dutch guideline is that an HSDS of

less than -2.0 is an obligate criterion. This limits the sensitivity to detect pathology,

because some forms of growth failure, particularly if acquired and if occurring in a

child with tall parents, can be associated with a HSDS within the normal range, at least

for several years. Hence, we investigated whether adding a recent growth deflection

irrespective of HSDS as a criterion to the Dutch guideline would improve its sensitivity.

Sensitivity indeed increased, but as expected specificity decreased below an acceptable

level for population screening.

In general, when using criteria for growth monitoring some children with pathology

will not be detected, emphasising the fact that at all times a detailed medical history

and physical examination, followed by proper medical judgement, cannot be replaced

by growth monitoring guidelines. We also advise every doctor evaluating a growth

curve to always take the parental height into consideration in relation to the child’s

height (irrespective of the actual HSDS) and pay attention to the course of the growth

curve to detect any growth deflection.

In the future, we aim to collaborate with the Finnish group to investigate how frequently

pathology was found in patients with a normal growth pattern according to their cri-

teria. Furthermore, we aim to establish a modification of the current evidence-based

guideline for children aged 3 to 10 years and develop a new guideline for 10 to 18 year

olds. These novel guidelines will focus on the utility of performing additional investiga-

tions in children referred because of a suspected growth disorder but without specific

clues at medical examination. A prospective study in a large cohort will allow us to

answer whether it is recommended to perform radiologic and laboratory investigations

in such children in comparison to not performing additional investigations.

Although the incidence of pathology in children referred for tall stature is low and

much lower than in short children, it remains important to uncover pathological causes

of overgrowth given the sometimes serious underling conditions [1]. These include

Marfan and Klinefelter syndrome, but also other genetic or endocrine disorders. In

Marfan syndrome, serious cardiovascular anomalies such as aortic dilatation are seen

146

8


[6] and thus early diagnosis and treatment of this disorder is important. Therefore,

an adequate guideline for diagnostic workup in tall patients to uncover pathologies is

necessary. In addition, as in children with growth failure, careful clinical assessment

besides following guidelines is crucial, with special attention to developmental and

behavioural problems that could be suggestive for a genetic disorder. Regarding the

prediction of adult height, we and others [7] have observed an overestimation of adult

height prediction by using the BP method and advise to use the De Waal method [8].

The incidence of pathological disorders in tall children is low, but current guidelines

tend to focus on finding pathology, and give little attention to idiopathic forms of tall

stature and recommendations for follow up [1, 3, 5]. We therefore developed a simple

diagnostic algorithm. This algorithm focuses on excluding pathology and provides

recommendations for follow-up. However, additional investigations are necessary in

order to further develop an efficient guideline. Hence, our future aim is to perform a

systematic literature study as well as a further analysis of tall children from our out-

patient clinic and other clinics. Given the low incidence of pathology, large cohorts

are needed to detect more patients with pathology. We hope that this would enable

us to develop a more evidence-based guideline. In line with the intended research in

children with growth failure, we will try to answer the question whether an additional

diagnostic workup for Marfan and Klinefelter syndrome would be indicated in a large

cohort of children with suspected overgrowth disorders without any clues for a specific

diagnosis, compared to only assessing the child’s bone age, in addition to a proper

medical history and physical examination.

Recently, a working group, consisting of paediatricians and paediatric endocrinolo-

gists, researchers, public health care workers and representatives of patient associa-

tions, has been composed, which submitted a grant proposal to carry out the above

mentioned research in children with suspected growth disorders in the near future.

Genetic Analysis

In the second part of this thesis we performed genetic analyses in small for gestational

age (SGA) newborns. In Chapter 5 we present our study investigating SGA newborns,

using a combination of array-CGH, genome wide methylation array and whole exome

sequencing (WES). In four patients we found a genetic abnormality that is likely to

contribute to their restricted growth. These included three copy number variations


8

(CNVs), a sequence variant in SOS1 (associated with Noonan syndrome [9]) and a widely

disturbed methylation pattern in one patient. In most of the remaining patients, abnor-

malities were found that could potentially influence fetal growth, including sequence

variants and methylation disturbances, but its causality remains to be investigated

further. Our results confirm that intrauterine growth is influenced by the function of

a large number of genes and different genetic mechanisms [10, 11]. Furthermore, it

shows the absence of a unifying theme explaining the dysregulation of fetal growth.

We also show that there is no predominant type of genetic abnormality present in SGA

newborns, since many patients show a combination of a CNV, sequence variant and

methylation disturbances.

Based on our findings, several implications for clinical practice arise. Our first obser-

vation is that array-CGH uncovers a fairly high number of CNVs, all with a plausible

causality in comparison to the more uncertain meaning of the methylation and exome

results. For other indications, like intellectual disability, chromosomal microarrays are

the first line diagnostic tool [12]. Therefore, we propose to initially perform array-CGH

to uncover CNVs in the genetic diagnostic workup of SGA newborns, before performing

more expensive forms of genome wide analyses. In the future, it is expected that genome

sequencing will be able to uncover CNVs, and in combination with the expectation that

it will become far less expensive, so that it may develop into a first line diagnostic tool.

Furthermore, a thorough analysis of the patients’ family and their genetic variants and

phenotypes as well as follow-up data could give more direction towards the possible

underlying condition and could narrow down the diagnostic workup. Another, more

complex issue is the implementation of epigenetic diagnostic strategies, for example

with genome-wide methylation arrays. At this stage, our opinion is that its analysis and

interpretation is too complex for clinical applications. Furthermore, we would need

expression data to interpret the meaning of epigenetic alterations at gene expression

level. It will remain a challenge in the future to functionally study all these genetic and

epigenetic findings and to study their interactions. For now, diagnostic testing in a

clinical setting for epigenetic disorders should be limited to known disorders with a

characteristic phenotype, such as Silver-Russel syndrome.

Some limitations of our study form starting points for further research. First, we did

not use a large appropriate for gestational age (AGA) cohort as a reference genome col-

lection for the analysis of the whole exome data. Population allele frequency databases

do not provide phenotypic data of individuals and thus limit the ability to determine

whether a WES variant is causal, since some individuals could have been growth re-

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stricted at birth. Furthermore, we had no access to clinical follow-up data and were

unable to evaluate the patients and their parents at a later age to confirm the phenotype.

Therefore, for future purposes we aim to collect a well-defined large AGA cohort and

perform exome sequencing in these individuals. In addition, we aim to repeat and

confirm our results in a larger SGA cohort, potentially yielding similar variants and

probably revealing many other variants as well as well as collecting follow-up data.

One could consider performing whole genome sequencing instead of WES to uncover

additional sequence variants in non-coding regions of the DNA. However, since our

exome analyses already resulted in many potential variants explaining the patient’s

low birthweight, we reason to first focus on WES. Based on our results and previous

research, it is known that regulation of fetal growth is polygenic in most patients and

can be explained by an interaction between the various genetic abnormalities. Such

pathogenic mechanisms are extremely complex [13, 14] and separate studies in each

patient to evaluate this in detail should be part future research. Additionally, functional

analyses are required and will be conducted to prove the role of the observed variants

in fetal growth.

Treatment

As pointed out in the introduction of this thesis, several growth disorders are approved

indications for growth hormone treatment (GH-T) in children and adolescents [15].

Given the known positive effects of GH-T regarding growth, psychosocial and cognitive

functioning, body composition and muscle strength, many children with other causes

of short stature could benefit from treatment. However, many disorders in which short

stature is part of the phenotype, have not been accepted as an indication for GH-T,

usually because either the effects of treatment were considered insufficient, but also

because the low incidence of the growth disorders did not allow proper evaluation. We

investigated the effect of GH-T in patients with maternal uniparental disomy of chro-

mosome 14 (matUPD(14)) in Chapter 6. MatUPD(14) resembles Prader-Willi syndrome

(PWS); both syndromes are characterized by short stature, truncal obesity and hypoto-

nia. In PWS, GH-T has shown to have a positive effect on growth and body composition

[16, 17]. Our prospective observational study describes GH treatment in two girls with

matUPD(14) during 2 years, and shows growth and weight parameters in another

matUPD(14) girl in which pubertal and bone age development were too advanced to


8

benefit from GH-T. In both treated girls, a considerable increase in height and IGF-1

levels was observed. In one patient in which treatment was started at an early age, also

a decrease in weight and improved body composition was found. Furthermore, both

treated girls experienced improved muscle strength, and no side-effects were reported.

In the patient that could not be treated, growth remained far below average with an

expected adult height of 135 cm, while weight continuously increased.

Based on our results we conclude that GH-T in matUPD(14) cases can show beneficial

effects on growth, body composition and muscle strength. We advise treating ma-

tUPD(14) patients with GH-T and to start at a young age, preferably before the average

onset of obesity in matUPD(14) at 3 years [17, 18]. Similar to GH-T in PWS, the dosage

can initially be started at 0.3-0.5mg/m2 per day and adjusted towards 1.0 mg/m2 [18],

guided by the IGF-I levels, which should be kept below 2.0 SDS given the potentially

increased risk of developing neoplasms under high IGF-1 levels [19]. Besides treatment

with GH, it is important to (simultaneously) inhibit the precocious puberty which is

typically seen in matUPD(14) patients, causing early maturation and closure of growth

plates, and thus early cessation of growth.It is unclear how many children are known

with matUPD(14), and probably patients are misdiagnosed with either PWS or are

not being tested for a maternal disomy of chromosome 14. Therefore, we would rec-

ommend always testing for matUPD(14) in patients with a PWS phenotype. In older

children with a PWS-like phenotype and the presence of precocious puberty, we would

recommend testing for matUPD(14) first.

Given that matUPD(14) is a rare disease, only a large international collaboration would

allow to collect sufficient patients and children of different ages and pubertal stages.

We would like to prospectively document the effects of growth hormone treatment in

such larger cohort and evaluate treatment in patients that are currently treated or have

been treated previously. By performing a larger, international study we will be able to

determine detailed effectivity, the optimal age to start treatment, most appropriate dos-

age and possible side-effects.

Quality of Life

Being short can cause psychosocial problems, and previous research has shown that

these problems occur more frequently in medically referred short children [20]. Little

is known about self-perceived psychosocial functioning of short children and few in-

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8


struments are available assessing perceptions of being short according to children and

their parents [20]. Therefore, a valid tool to evaluate the quality of life (QoL) of short

children, from both the child’s and parents’ perspectives is needed. The European

Quality of Life in Short Stature Youth (QoLISSY) questionnaire was developed to evalu-

ate the health-related QoL in short children [21], assessing QoL from the perspective of

the child as well as the parents. It focuses of the following items: physical, emotional,

coping, treatment, beliefs, future and the effects on the parents. In order to use the

QoLISSY in Dutch patients, a translation process and psychometric testing of the

original questionnaire was required as described in Chapter 7. The study describes

the psychometric performance of the Dutch QoLISSY in children with idiopathic short

stature and growth hormone deficiency and their parents. Our results show a good

reliability based on its internal consistency, consistency between the initial test and

re-test and the congruency between children and parents. Furthermore, a good validity

of the QoLISSY based on the well-validated generic KIDSCREEN [22] and the original

European sample was observed. Therefore, we conclude that the Dutch QoLISSY is a

psychometrically reliable and valid short stature-specific QoL instrument in evaluat-

ing the burden of being short as well as treatment outcomes in clinical practice and

research.

Previous studies regarding QoL in short stature recommended to use a disorder-specific

questionnaire to measure QoL in short children treated with growth hormone [23, 24]

instead of general QoL measures. For example, the TNO-AZL Children’s Quality of

Life Short Stature module (TACQOL-S) was used to asses QoL [25]. To our knowledge,

experience with this questionnaire is limited and the questionnaire was only translated

into three languages, making cross-cultural comparisons difficult [26]. In addition,

the Dutch QoLISSY showed a better internal consistency (α 0.80 – 0.95) compared to

the TACQOL-S (α 0.57 - >0.70). Therefore, the QoLISSY seems a more reliable and

valid tool for evaluating QoL in short stature and we reason that the questionnaire

could be used for various purposes. First, it is an accessible tool for children and their

parents to express thoughts and feelings regarding being short. Additionally, it will

inform the doctor about how short children experience their height and possible as-

sociated problems, enabling him or her to offer appropriate counselling. We would

even urge to focus more on accepting or coping with being short, and the QoLISSY

could well be used to evaluate such psychological interventions. The QoLISSY will soon

be implemented in our outpatient growth clinic for this purpose. Second, the question-

naire could measure the psychological benefits of GH-T. As mentioned earlier in this


8

thesis, GH-T sometimes results in only a few centimetres height gain and therefore it

is questionable whether GH-T in for example idiopathic short patients is worthwhile,

with regard to the burden of daily injections. We believe assessing a child’s QoL should

become part of care before, during and after GH-T.

In line with this, the questionnaire could be used for future research in studies on

GH-T in known or newly treated disorders characterized by short stature. Some studies

have assessed QoL in patients treated with GH [23, 24, 27], showing improvement

of health-related QoL in GH-treated children and adolescents, although a systematic

review considered that the quality of all studies were suboptimal [28]. Furthermore,

it is interesting that some children with short stature develop psychosocial problems

while others don’t, possibly depending on factors like the severity of short stature

and coping strategies [29]. For future research purposes, the QoLISSY questionnaire

could be a valuable measure to gain more insights into the influence and relevance of

those contributing factors. We would be interested in performing a QoL study in short

children treated with growth hormone, compared to children receiving psychological

interventions aimed at accepting and coping with their stature. As mentioned earlier,

we also aim to perform future research on GH-T in matUPD(14), and assessment of the

patients QoL could be measured using this tool. Due to the various translations of the

QoLISSY, it is very useful in larger international studies.

General Conclusion

In this thesis we have discussed various aspects of human growth, including its aetiol-

ogy, growth monitoring, diagnostic workup, treatment and quality of life. We have

taken a step further in expanding the knowledge of growth disorders and treatment

strategies and provide suggestions for future research.

Given the wide variation of shapes of growth curves and the many possible underlying

conditions, pursuing an ideal combination of criteria for growth monitoring might just

be infeasible. We acknowledge and underline the importance of growth monitoring in

public and paediatric healthcare and would recommend to focus on each of the three

main growth indicators (height, distance to target height and height velocity) using

current evidence-based guidelines such as the Finnish and Dutch as a guide, in combi-

nation with a proper medical history and physical examination. The medical profession

needs guidelines that are based on thorough and reliable research, but the clinician

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must never stop thinking for him- or herself: guidelines are made to guide, but the

most valuable guide for an individual medical assessment is the child itself.

Future research should, according to us, therefore focus less on establishing optimal

criteria and more on the utility of performing additional investigations in children

referred because of a suspected growth disorder and without clues for a specific

diagnosis. Given the generally limited knowledge of genetic disorders by primary

health physicians and paediatricians, and the minor role of the clinical geneticist in

this workup, we want to emphasize the importance of genetic diagnostics and its rapid

developments. Maybe one day, the clinician may be able to offer every child with a dis-

turbed growth pattern a whole genome sequence, as well as a genome-wide epigenetic

assay. However, one should always have a keen eye for the ethical issues that always will

go along with this.

To conclude, in this entire diagnostic process, one has to make sure that severe dis-

orders and disorders that require treatment are uncovered, but at the same time one

should attempt to prevent medicalisation or stigmatisation of every short or tall child.

What would our world look like if everybody had the same height, the same eye colour,

or the same face shape? We believe that this variation, within certain limits, is what

makes every human being unique and interesting. By accepting and valuing this and

by passing this belief on to the next generation, quality of life of children with non-

pathogenic short and tall stature could be increased without the interference of growth

hormone treatment or height reduction surgery.

“It is an old saying, abundantly justified, that where sciences meet, there growth occurs” –

Sir Frederick Gowland Hopkins


8

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2. Grote FK, van Dommelen P, Oostdijk W, de Muinck Keizer-Schrama SMPF, Verkerk PH, Wit JM, et al. Developing evidence-based guidelines for referral for short stature. Arch Dis Child 2008;93(3):212-7.

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5. Visser R, Kant SG, Wit JM, Breuning MH. Overgrowth syndromes: from classical to new. Pediatr Endocrinol Rev 2009;6(3):375-94.

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7. de Waal WJ, Greyn-Fokker MH, Stijnen T, van Gurp EA, Toolens AM, de Munick Keizer-Schrama SM, et al. Accuracy of final height prediction and effect of growth-reductive therapy in 362 constitutionally tall children. J Clin Endocrinol Metab 1996;81(3):1206-16.

8. De Waal WJ, Stijnen T, Lucas IS, van GE, de MK-S, Drop SL. A new model to predict final height in constitutionally tall children. Acta Paediatr 1996;85(8):889-93.

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10. Roberts DF. The genetics of human fetal growth. Postgrad Med J. 1978;54 Suppl 1:107-16.

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12. Miller DT, Adam MP, Aradhya S, Biesecker LG, Brothman AR, Carter NP, et al. Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet 2010;86(5):749-64.

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Functional Context of PCOS Loci and Identifies Genetic and Molecular Mechanisms of Disease Heterogeneity. PLoS Genet 2015;11(8):e1005455.

14. Rushton MD, Reynard LN, Young DA, Shepherd C, Aubourg G, Gee F, et al. Methylation quantitative trait locus analysis of osteoarthritis links epigenetics with genetic risk. Hum Mol Genet 2015;24(25):7432-44.

15. Richmond E, Rogol AD. Current indications for growth hormone therapy for children and adolescents. Endocr Dev 2010;18:92-108.

16. Carrel AL, Myers SE, Whitman BY, Allen DB. Growth hormone improves body composition, fat utilization, physical strength and agility, and growth in Prader-Willi syndrome: A controlled study. J Pediatr 1999;134(2):215-21.

17. Hoffmann K, Heller R. Uniparental disomies 7 and 14. Best Pract Res Clin Endocrinol Metab 2011;1:77-100.

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19. Clayton PE, Banerjee I, Murray PG, Renehan AG. Growth hormone, the insulin-like growth factor axis, insulin and cancer risk. Nat Rev Endocrinol 2011;7(1):11-24.

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21. Bullinger M, Quitmann J, Power M, Herdman M, Mimoun E, DeBusk K, et al. Assessing the quality of life of health-referred children and adolescents with short stature: development and psychometric testing of the QoLISSY instrument. Health Qual Life Outcomes 2013;11:76.

22. Europe TKG. The KIDSCREEN questionnaires: Qual-ity of life for children and adolescents. (Lengerich, Pabst Science Publishers: 2006).

23. Lem AJ, Jobse I, van der Kaay DC, de Ridder MA, Raat H, Hokken-Koelega AC. Health-related quality of life in short children born small for gestational age: effects of growth hormone treatment and postponement of puberty. Horm Res Paediatr 2012;77(3):170-9.

24. Bannink EM, van Pareren YK, Theunissen NC, Raat

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H, Mulder PG, Hokken-Koelega AC. Quality of life in adolescents born small for gestational age: does growth hormone make a difference? Horm Res 2005;64(4):166-74.

25. Vogels T, Verrips GH, Verloove-Vanhorick SP, Fekkes M, Kamphuis RP, Koopman HM, et al. Measuring health-related quality of life in children: the development of the TACQOL parent form. Qual Life Res 1998;7(5):457-65.

26. Brutt AL, Sandberg DE, Chaplin J, Wollmann H, Noeker M, Koltowska-Haggstrom M, et al. Assess-ment of health-related quality of life and patient satisfaction in children and adolescents with growth hormone deficiency or idiopathic short stature - part 1: a critical evaluation of available tools. Horm Res 2009;72(2):65-73.

27. Geisler A, Lass N, Reinsch N, Uysal Y, Singer V, Ravens-Sieberer U, et al. Quality of life in children and adolescents with growth hormone deficiency: association with growth hormone treatment. Horm Res Paediatr 2012;78(2):94-9.

28. Gardner M, Boshart ML, Yeguez CE, Desai KM, Sandberg DE. Coming Up Short: Risks of Bias in Assessing Psychological Outcomes in Growth Hormone Therapy for Short Stature. J Clin Endocrinol Metab 2016;101(1):23-30.

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chapter 9Samenvatting

(Summary, in Dutch)

Samenvatting (Summary, in Dutch) 159

9

De studies in dit proefschrift focussen zich op verschillende aspecten, die zich voor-

doen omtrent kinderen met een groeistoornis: van verwijzing, diagnostisch onderzoek

en genetische analyse tot diagnose, behandeling en kwaliteit van leven.

Groeimonitoring

Het eerste deel van dit proefschrift richt zich op richtlijnen voor verwijzing en diag-

nostisch onderzoek van kinderen met groeistoornissen, voor zowel kinderen met een

kleine als een grote lengte.

Er is weinig bekend over de optimale criteria voor verwijzing en diagnostisch onderzoek

om de onderliggende aandoening (pathologie) te ontdekken bij kinderen met een ver-

denking van een groeistoornis. Het is moeilijk gebleken afkapwaarden voor die criteria

te definiëren aangezien de vorm van de groeicurve van een kind wordt beïnvloed door

de etiologie van de onderliggende groeistoornis (bijvoorbeeld aangeboren of verworven

aandoeningen), genetische factoren, puberteitsontwikkeling, omgevingsfactoren en in

sommige gevallen zelfs psychologische factoren. Verschillende onderzoekers hebben

geprobeerd om een efficiënte set criteria te ontwikkelen en er zijn naast een aantal op

consensus gebaseerde criteria verschillende evidence-based richtlijnen ontwikkeld.

Echter, evaluatie en validatie van dergelijke richtlijnen worden zelden uitgevoerd en

consensus over de meest efficiënte criteria en hun afkapwaarden is niet bereikt. In

deel I van dit proefschrift onderzoeken we de incidentie van pathologie bij kinderen,

die verwezen werden met een vermoedelijke groeistoornis, en evalueren we bestaande

richtlijnen voor groeimonitoring bij kinderen.

Ten eerste, hebben we onderzoek gedaan naar de sensitiviteit (hoeveel kinderen met

een pathologische aandoening vind je daadwerkelijk met de richtlijn) en specificiteit

(hoeveel kinderen zonder pathologische aandoening scoren daadwerkelijk negatief

op de criteria van de richtlijn) van de richtlijnen voor verwijzing en diagnostisch on-

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Samenvatting (Summary, in Dutch)

derzoek, zoals die momenteel worden gebruikt in Nederland, Finland en het Verenigd

Koninkrijk. We onderzochten dit in een Nederlands cohort van kinderen van drie tot

tien jaar met een kleine lengte of achterblijvende groei (Hoofdstuk 2). Deze kinderen

werden vanwege een verdenking van een groeistoornis verwezen naar de groeipoli

van polikliniek Kindergeneeskunde van Tergooi. Bij 18% van deze kinderen werd een

pathologische oorzaak gevonden, die hun afwijkende groei kon verklaren. De Ne-

derlandse en Finse richtlijnen, bestaande uit criteria voor de lengte van het kind ten

opzichte van leeftijdgenoten van hetzelfde geslacht en afkomst (de standaarddeviatie

van de lengte), de afstand tot de lengte die op basis van de lengtes van ouders verwacht

wordt (afstand tot de ‘target height’) en een afbuiging in de groei waarbij vergelijkbare

afkappunten van de criteria werden gehanteerd, bleken effectief voor groeimonitoring.

Beide richtlijnen lieten een hoge sensitiviteit voor het opsporen van pathologische

oorzaken van de groeiachterstand zien, evenals een hoge specificiteit. Een recente

afbuiging in de groei bleek een belangrijk alarmsignaal. De sensitiviteit van de Britse

richtlijn was aanzienlijk lager.

Ten tweede, in Hoofstuk 3, hebben we een soortgelijke studie verricht bij adolescenten,

waarbij we speciale aandacht hadden voor de invloed van de puberteit op de groei.

Met name een late puberteitsontwikkeling kan samengaan met een vertraging van de

groei, de zogeheten ‘constitutionele vertraging van groei en puberteit’. Bij 7% van de

adolescenten werd een specifieke diagnose gevonden, waaruit we concluderen dat ook

bij adolescenten nog significante pathologie gevonden kan worden. Constitutionele

vertraging van groei en puberteit werd vastgesteld bij 10% van de adolescenten met een

kleine lengte of achterblijvende groei. Een hoge sensitiviteit voor het vaststellen van

pathologische aandoeningen werd gevonden bij de toepassing van alle Nederlandse

criteria zoals die gebruikt worden bij kinderen van drie tot tien jaar, terwijl de sensitivi-

teit van de huidige Nederlandse aanbeveling voor adolescenten (een standaarddeviatie

van de lengte kleiner dan -2.5 als enig criterium) aanzienlijk lager was. Dit geeft aan

dat, alhoewel het opstellen van criteria voor groeiafwijkingen bij adolescenten bemoei-

lijkt wordt door de invloed van de puberteit, de drie belangrijke groeiprincipes (lengte,

afstand tot ‘target height’ en een groeiafbuiging) van belang zijn voor groeimonitoring

in adolescenten.

Ten derde, hebben we het diagnostisch onderzoek en de follow-up van kinderen met

een grote lengte onderzocht (Hoofdstuk 4). We vonden een zeer lage incidentie van

pathologie (1.5%) bij kinderen, die verwezen waren in verband met een grote lengte.

De meeste kinderen werden geclassificeerd als idiopathisch lang, deze kinderen waren


9

lang, maar een onderliggende aandoening kon niet aangetoond worden. Andere kin-

deren hadden een ‘constitutioneel vooruitlopende groei’, de tegenhanger van de eerder

beschreven ‘constitutionele vertraging van groei en puberteit’. De helft van de patiënten

die verwezen werd in verband met een grote lengte, bleek niet groot volgens de defi-

nitie, ze hadden een lengte kleiner dan 2.0 standaarddeviaties boven het gemiddelde.

Verder hebben we geconstateerd dat bij slechts een paar patiënten een indicatie bestond

voor het remmen van de lengtegroei door middel van epifysiodese, een chirurgische

methode om de groei vanuit de groeischrijven in de knieën te remmen.

Tenslotte, bevestigden we een eerdere constatering dat voorspelling van de eindlengte

met de methode van Bayley en Pinneau resulteert in een overschatting van de eind-

lengte, en dat beter de methode Van de Waal gebruikt kan worden. Op basis van onze

resultaten en literatuuronderzoek stellen we een nieuw diagnostisch stroomschema

voor, gericht op het uitsluiten van pathologie, waarin we tevens suggesties geven voor

de follow-up van de patiënt.

Genetische Analyse

In het tweede deel van dit proefschrift hebben we genetische analyses verricht bij

pasgeborenen met een laag geboortegewicht, dit gecorrigeerd voor het aantal weken

zwangerschap (‘small for gestational age’ (SGA)). In Hoofdstuk 5 presenteren we

het onderzoek naar SGA bij pasgeborenen, waarbij we drie verschillende genetische

onderzoeken verrichtten:

(1) Met een ‘array comparative genomic hybridization’ (array-CGH) onderzochten we

of delen van het DNA van een chromosoom ontbreken (deleties) of teveel aanwezig zijn

(duplicaties), ook wel ‘copy number variations’ (CNVs) genoemd.

(2) Met het ‘genome-wide methylation assay’ onderzochten we niet de DNA-code zelf,

maar een zogenoemd epigenetisch fenomeen dat genen aan of uit kan zetten.

(3) Met behulp van ‘whole exome sequencing’ (WES) bekeken we de DNA-code (de se-

quentie) van delen van het DNA, die afgelezen worden en eiwitten vormen en daardoor

ziektes kunnen veroorzaken (de exomen).

Bij 4 van de 21 patiënten vonden we een genetische afwijking, die zeer waarschijnlijk

bijdraagt aan het lage geboortegewicht. Deze omvatten drie CNVs, een sequentieva-

riant in het SOS1 gen (gerelateerd aan het Noonan syndroom) en een breed gestoord

methylatie-patroon bij één patiënt. Bij 19 van de 21 patiënten werden andere afwijkingen

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gevonden die mogelijk van invloed zijn op foetale groei, inclusief sequentievarianten

en methylatiestoornissen, maar de causaliteit hiervan moet nog nader worden onder-

zocht. Onze resultaten bevestigen dat groei in de baarmoeder wordt beïnvloed door

de functie van een groot aantal genen en genetische mechanismen en, zoals verwacht,

vinden we geen eenduidige oorzaak van de ontregeling van foetale groei. We tonen ook

aan dat er geen specifiek type genetische abnormaliteit overheersend aanwezig is in

SGA bij pasgeborenen, maar dat veel patiënten een combinatie vertonen van een CNV,

methylatie-stoornis en sequentievariant.

Behandeling

Zoals in de inleiding van dit proefschrift genoemd wordt, vormen verschillende groei-

stoornissen bij kinderen en adolescenten indicaties voor behandeling met groeihor-

moon (GH).

Gezien de bekende positieve effecten van GH op lentegroei, psychosociaal en cognitief

functioneren, lichaamssamenstelling en spierkracht, zouden kinderen met andere

oorzaken van een kleine lengte ook kunnen profiteren van deze behandeling. Veel aan-

doeningen waarbij kinderen klein zijn worden niet geaccepteerd als indicatie voor

GH, omdat ofwel de effecten van de behandeling onvoldoende worden geacht, ofwel

omdat de lage incidentie van deze groeistoornissen goede evaluatie van het effect niet

mogelijk maakt.

Wij onderzochten in Hoofdstuk 6 het effect van GH-behandeling bij patiënten met

maternale uniparentale disomie van chromosoom 14 (matUPD(14)). Bij matUPD(14)

ontvangt een kind in plaats van één chromosoom 14 van vader en één van moeder twee

chromosomen 14 van de moeder, dan wel één van vader en één van moeder, waarbij

het van vader afkomstige chromosoom ‘uit’ staat. MatUPD(14) lijkt op het Prader-

Willi-syndroom (PWS); beide syndromen worden gekenmerkt door een kleine lengte,

obesitas en een verminderde spierspanning. Bij PWS is aangetoond dat GH een positief

effect heeft op de lengtegroei en de lichaamssamenstelling.

Onze prospectieve observationele studie beschrijft GH-behandeling bij twee meisjes

met matUPD(14) gedurende 2 jaar, en toont de groei en het gewichtsverloop bij een

andere matUPD(14) patiënt, waarbij de puberteit en botontwikkeling te ver gevorderd

waren om te kunnen profiteren van GH-behandeling. Bij beide behandelde meisjes

werd een aanzienlijke toename waargenomen van IGF-1 levels, een groeifactor die


9

wordt gereguleerd door menselijk groeihormoon. Bij één van hen, waarbij al op jonge

leeftijd met de behandeling was begonnen, werd een evidente gewichtsafname en ver-

beterde lichaamssamenstelling geconstateerd. Bovendien ervoeren beide behandelde

meisjes een verbeterde spierkracht en werden geen bijwerkingen gerapporteerd. Bij de

patiënt die niet kon worden behandeld, bleef de groei ver onder het gemiddelde, met

een verwachte eindlengte van 135 cm, en werd een blijvende toename in gewicht gezien.

Kwaliteit van Leven

Klein zijn kan psychosociale problemen veroorzaken en uit eerder onderzoek is geble-

ken dat deze problemen vaker voorkomen bij kinderen die in verband met hun lengte

verwezen worden naar een arts. Er is weinig bekend over het zelf-ervaren psychosociaal

functioneren bij kleine kinderen, en er zijnweinig instrumenten beschikbaar om de

ervaring van klein zijn te beoordelen vanuit het perspectief van het kind en zijn of haar

ouders. Daarom is een valide instrument nodig om de kwaliteit van leven (quality of

life, QoL) van kleine kinderen, zowel vanuit het perspectief van het kind als de ouders,

te evalueren.

De Europese Quality of Life in Short Stature Youth (QoLISSY)-vragenlijst is ontwikkeld

om de gezondheidsgerelateerde kwaliteit van leven bij kinderen met een kleine lengte

vanuit het perspectief van het kind en de ouders te evalueren. De vragenlijst richt zich

op de volgende items: fysiek, emotioneel, coping, behandeling, opvattingen, toekomst

en de effecten op de ouders. Om de QoLISSY te kunnen gebruiken bij Nederlandse

patiënten waren een vertaalproces en het psychometrisch testen van de oorspronkelijke

vragenlijst vereist, zoals beschreven in Hoofdstuk 7. De studie beschrijft de psychome-

trische prestaties van de Nederlandse QoLISSY bij kinderen met idiopathisch kleine

lengte, kinderen met een groeihormoondeficiëntie, en hun ouders. Onze resultaten

tonen een goede betrouwbaarheid aan op basis van de interne consistentie, de samen-

hang tussen de eerste test en re-test en de congruentie tussen kinderen en ouders.

Bovendien werd een goede validiteit van de QoLISSY waargenomen op basis van de

goed gevalideerde generieke KIDSCREEN en de oorspronkelijke Europese studie. We

concluderen dat de Nederlandse QoLISSY een psychometrisch betrouwbaar en valide

kleine lengte-specifiek QoL-instrument is voor het in kaart brengen van de last van

klein zijn evenals voor de evaluatie van behandeling, zowel voor de klinische praktijk

als voor wetenschappelijk onderzoek.

164

9


Algemene Conclusie

In dit proefschrift hebben we verschillende aspecten van de menselijke groei, waaron-

der de etiologie, verwijzing, diagnostisch onderzoek, behandeling en de kwaliteit van

het leven, besproken en onderzocht. Er is een volgende een stap gezet in het vergroten

van de kennis van groeistoornissen en behandelstrategieën en er zijn suggesties gege-

ven voor toekomstig onderzoek.

Gezien de grote variatie aan vormen van groeicurves en de vele mogelijke onderlig-

gende aandoeningen die een verstoorde groei kunnen veroorzaken, lijkt het nastreven

van een ideale combinatie van criteria voor groeimonitoring misschien niet haalbaar.

We erkennen en benadrukken het belang van groeimonitoring in de jeugdgezond-

heidszorg en kindergeneeskunde. We zouden willen aanbevelen om daarbij te focussen

op elk van de drie hoofdprincipes voor groei (lengte, afstand tot ‘target height’ en een

groeiafbuiging) met behulp van de huidige evidence-based richtlijnen, en daarbij de

Finse en de Nederlandse richtlijnen als leidraad te gebruiken, in combinatie met een

goede medische anamnese en volledig lichamelijk onderzoek.

De medische professie heeft richtlijnen die gebaseerd zijn op gedegen en betrouwbaar

onderzoek nodig, maar een arts mag nooit stoppen voor zichzelf te denken: richtlijnen

zijn gemaakt om richting te geven, maar de meest waardevolle leidraad voor een indivi-

duele medische beoordeling is het kind zelf. Toekomstig onderzoek zou zich, volgens

ons, daarom minder moeten richten op het nastreven van ideale criteria en meer op

het nut van het verrichten van aanvullend onderzoek bij kinderen die verwezen worden

met een vermoedelijke groeistoornis, maar zonder aanwijzingen voor een specifieke

diagnose.

Gezien de, in het algemeen, beperkte kennis van genetische afwijkingen bij jeugd- en

kinderartsen en de ondergeschikte rol van de klinisch geneticus in dit diagnostische

proces, willen we het belang van genetische diagnostiek en haar snelle ontwikkelingen

benadrukken. Misschien zal de arts op een dag in staat zijn om elk kind met een ver-

stoord groeipatroon een ‘whole genome sequence’ aan te bieden, evenals ‘genoom-wijd

epigenetisch’ onderzoek. Echter, men zal hierbij altijd met een kritische blik moeten

kijken naar de ethische kwesties die hiermee gepaard gaan.

Tot slot. In dit hele diagnostische proces moet de medische professie er zorg voor dra-

gen dat ernstige stoornissen en aandoeningen, die behandeling behoeven, opgespoord

worden. Maar tegelijkertijd pleiten we ervoor dat men probeert niet elk klein of lang

kind te medicaliseren of stigmatiseren. Want hoe zou onze wereld eruitzien als iedereen


9

dezelfde lengte zou hebben, dezelfde oogkleur of dezelfde gezichtsvorm? Wij zijn van

mening dat deze variatie, binnen bepaalde grenzen, ieder mens uniek en interessant

maakt. Door dit te accepteren en te waarderen en deze opvatting door te geven aan de

volgende generatie, kan de kwaliteit van leven van kinderen met niet-pathogene kleine

of lange gestalte worden verbeterd zonder de tussenkomst van groeihormoonbehande-

ling of chirurgische remming van de groei.

Appendices

169Curriculum Vitae

Curriculum Vitae

Susanne Stalman was born in Amsterdam on the 16th of February 1988. She moved to

Bussum with her parents and older sister, where she completed secondary school at

the Willem de Zwijger College in 2006. In this year, she moved back to Amsterdam

and started Medical School at the VU University Medical Center. In the first year of her

medical study she did her nursing internship at the Diakonessen Hospital in Surinam.

During her medical study she worked as a doctor’s assistant at the VU University Medi-

cal Center General Practice and cared for a boy with Duchenne muscular dystrophy.

Between her Bachelor’s and Master’s degree, she lived in Barcelona for three months,

where she took a Spanish course. In 2012, she went to South Africa for her surgery in-

ternship. She finished her final clinical elective internship in Pediatrics & Neonatology

in 2013 at the VU Medical Center and soon after started her scientific research intern-

ship at the pediatric Growth Clinic of Tergooi Hospitals, supervised by dr. Plötz and dr.

Kamp from Tergooi Hospitals and prof. Wit from Leiden University Medical Center.

During this research internship, she worked on different projects studying guidelines

for diagnostic workup in children with short or tall stature and she was given the op-

portunity to extend these studies into a PhD project. During the subsequent period she

worked on a project evaluating growth hormone treatment in children with a syndro-

mal growth disorder and participated in a project on the quality of life in short children.

Prof. Hennekam was approached to act as her promotor and supervised the ongoing

projects and the genetic studies in small newborns, which was partly conducted at the

Institute of Child Health in London during nine months under supervision of prof.

Moore and prof. Stanier. In the summer of 2016 she started working as a paediatric

resident at the Spaarne Gasthuis Hospital and hopes to start her training to become a

paediatrician in the future.

Susanne loves travelling, cooking, film, interior design, cycle racing, diving and piano.

She lives together with Thijs in Amsterdam.

171List of Co-Authors

List of Co-Authors

Sayeda Abu-Amero – Department of Genetics and Genomic Medicine, Institute of

Child Health, University College London, London, United Kingdom

Marielle Alders – Department of Clinical Genetics, Academic Medical Centre, Univer-

sity of Amsterdam, Amsterdam, The Netherlands

Cristina Alemán-Charlet – Department of Genetics and Genomic Medicine, Institute of

Child Health, University College London, London, United Kingdom

Lucas Alvizi – Department of Genetics and Developmental Biology, University of São

Paulo, São Paulo, Brazil

William Baird – Department of Genetics and Genomic Medicine, Institute of Child

Health, University College London, London, United Kingdom

Monika Bullinger – Department of Medical Psychology, University Medical Centre

Hamburg-Eppendorf, Hamburg, Germany

Charalambos Demetriou – Department of Genetics and Genomic Medicine, Institute

of Child Health, University College London, London, United Kingdom

Paula van Dommelen – Department of Child Health, TNO, Leiden, The Netherlands

Leo Dunkel – Centre for Endocrinology, William Harvey Research Institute, Barts

and the London School of Medicine and Dentistry, Queen Mary University of London,

London, United Kingdom

Ilse Hellinga – Department of Pediatrics, University Medical Centre Utrecht/Wilhelmina

Children’s Hospital, Utrecht, The Netherlands

Yvonne M Hendriks – Department of Clinical Genetics, VU Medical Centre, VU Univer-

sity, Amsterdam, The Netherlands

172 Appendices

Raoul C Hennekam – Department of Pediatrics, Academic Medical Centre/Emma

Children’s Hospital, University of Amsterdam, Amsterdam, Netherlands

Peter Henneman – Department of Clinical Genetics, Academic Medical Centre, Univer-

sity of Amsterdam, Amsterdam, The Netherlands

Miho Ishida – Department of Genetics and Genomic Medicine, Institute of Child


Chela T James – UCL Cancer Institute, University College London, London, United

Kingdom

Gerdine A Kamp – Department of Pediatrics, Tergooi Hospitals, Blaricum, The Neth-

erlands

Lia C Knegt – Department of Clinical Genetics, Academic Medical Centre, University of

Amsterdam, Amsterdam, The Netherlands

Lydia J Leon – Department of Genetics and Genomic Medicine, Institute of Child


Marcel MAM Mannens – Department of Clinical Genetics, Academic Medical Centre,

University of Amsterdam, Amsterdam, The Netherlands

Adri N Mul – Department of Clinical Genetics, Academic Medical Centre, University of

Amsterdam, Amsterdam, The Netherlands

Gudrun E Moore – Department of Genetics and Genomic Medicine, Institute of Child


Nicole A Nibbering – Department of Clinical Genetics, Academic Medical Centre,

University of Amsterdam, Amsterdam, The Netherlands

Emma Peskett – Department of Genetics and Genomic Medicine, Institute of Child


173List of Co-Authors

Frans B Plötz – Department of Pediatrics, Tergooi Hospitals, Blaricum, The Nether-

lands

Anke Pons –Brian and Mind Centre, University of Sydney, Sydney, Australia

Joris AM van der Post – Department of Gynaecology and Obstetrics, Academic Medical

Centre, Amsterdam, University of Amsterdam, The Netherlands

Julia H Quitmann – Department of Medical Psychology, University Medical Centre


Faisal I Rezwan – Deparment of Human Development and Health, Southampton Gen-

eral Hospital, University of Southampton, Southampton, United Kingdom

Carrie Ris-Stalpers - Department of Gynaecology and Obstetrics, Academic Medical

Centre, Amsterdam, University of Amsterdam, The Netherlands

Anja C Rohenkohl – Department of Medical Psychology, University Medical Centre


Joost Rotteveel – Department of Pediatics, VU Medical Centre, VU University, Amster-

dam, The Netherlands

Antti Saari– Department of Pediatrics, Kuopio University Hospital, Kuopio, Finland

Ulla Sankilampi – Department of Pediatrics, Kuopio University Hospital, Kuopio,

Finland

Nita Solanky – Department of Genetics and Genomic Medicine, Institute of Child


Philip Stanier – Department of Genetics and Genomic Medicine, Institute of Child


174 Appendices

Jan M Wit – Department of Pediatrics, Leiden University Medical Centre, Leiden, The

Netherlands

175PhD Portfolio

PhD Portfolio

1. PhD training Year ECTS

General courses

Searching for Systematic Reviews 2014 0,1

Systematic Reviews 2014 0,6

Basiscursus Regelgeving en Organisatie voor Klinisch

onderzoekers (BROK)

2014 0,9

Clinical Data Managment 2015 0,1

Specific courses

27th course in Medical Genetics, Bertinoro, Italy 2014 3

Laboratory Safety 2014 0,4

DNA Technology 2015 1,5

Genetic Epidemiology 2015 0,5

Seminars, workshops and master classes

Monthly research meetings 2014 1,0

Oral presentation training Dutch Association of Pediatrics (NVK)

Congress 2014

2014 0,1

Weekly department seminars 2015 1,3

Two-weekly research meetings 2015 1,5

Presentations

Research Symposium Tergooi Hospitals, Blaricum. “Te kleine

kinderen”

2014 0,5

Pediatric Endocrinology meeting, VU University Medical Centre,

Amsterdam. “Kinderen met een kleine lengte”

2014 0,5

Dutch Association of Pediatrics Congress 2014, Veldhoven.

“Teenagers with short stature: evaluation of referral criteria and

diagnostic workup”

2014 0,5

Research Symposium Tergooi Hospitals, Blaricum. “Van

wetenschapsstudent naar promovenda” and a poster presentation.

2014 1,0

176 Appendices

Genetics and Epigenetics in Health and Disease (GEHD) seminar,

Institute of Child Health, University College London, London,

United Kingdom. “Children with growth disorders: diagnostic

workup, treatment and genetic analyses”

2015 0,5

Amsterdam Kinder Symposium (AKS), Academic Medical Centre

and VU University Medical Centre, Amsterdam. “Positive effect

of growth hormone treatment in maternal uniparental disomy

chromosome 14”

2016 0,5

Workgroup Genetics of Growth, Leiden University Medical Centre,

Leiden. “Children with growth disorders: diagnostic workup,

treatment and genetic analyses”

2016 0,5

Conferences

Dutch Association of Pediatrics (NVK) Congress 2014, Veldhoven. 2014 0,5

Amsterdam Kinder Symposium (AKS) 2015, Amsterdam. 2015 0,5

Amsterdam Kinder Symposium (AKS) 2016, Amsterdam. 2016 0,5

2. Teaching Year ECTS

Supervision of Scientific Internship student, Tergooi Hospitals,

Blarium. (14 weeks)

2014 4

Teaching DNA extractions and DNA quantification, ‘Work

Experience Week’ at the Institute of Child Health, University

College London, London.

2014 0,1

3. Grants Year

Tergooi Research Support Grant 2014

Jo Kolk Study Fund 2015

Tergooi Research Support Grant 2015

KNAW Ter Meulen Fund 2015

ZonMW Rare Diseases Network Grant 2015

177PhD Portfolio

4. Publications Year

Maternale Uniparentale Disomie 14 - In De Differentiaal Diagnose

bij het Prader Willi Syndroom.

Nederlands Tijdschrift voor Geneeskunde 2015;159(0):A8240

2015

Application of the Dutch, Finnish and British Screening Guidelines

in a Cohort of Children with Growth Failure.


2015

Positive Effect of Growth Hormone Treatment in Maternal

Uniparental Disomy Chromosome 14.

Clinical Endocrinology (Oxf ) 2015;83(5):671-6

2015

Diagnostic Work-up and Follow-up in Children with Tall Stature: A

Simplified Algorithm for Clinical Practice.


2015

Growth Failure in Adolescents: Etiology, the Role of Pubertal

Timing and Most Useful Criteria for Diagnostic Workup.


2016

Psychometric Performance of the Quality of Life in Short Stature

Youth (QoLISSY) Questionnaire in the Netherlands.


2016

Genetic Analysis in Small for Gestational Age Newborns.

[Submitted]

2016

A New Biological and Clinical Resource for Research into

Pregnancy Complications: the Baby Bio Bank.

[Accepted by Placenta]

2016

179Dankwoord (Acknowledgements)

Dankwoord (Acknowledgements)

Beste professor Hennekam, lieve Raoul, na ongeveer een jaar met mijn onderzoek bezig te

zijn, vroeg Jan Maarten, die zelf niet meer op kon treden als mijn promotor, of jij daar

iets in zag. Een gouden zet, want jij begon met vol enthousiasme aan de begeleiding en

samen gaven we vorm aan het genetische vervolgproject van mijn proefschrift. Dankzij

jouw warme banden met Londen kreeg ik ook nog de mogelijkheid mijn onderzoek

deels te vervolgen aan het Institute of Child Health. Ondanks je vele promovendi,

bergen ander werk en regelmatige buitenlandbezoeken, heb jij het vermogen toch al je

onderzoekers het gevoel te geven dat alle aandacht en tijd naar ze uitgaat. De snelheid

en kwaliteit waarmee jij stukken reviseert en terugstuurt, geregeld op de zaterdagavond

om elf uur, verdient een onderscheiding. En dan erbij vermelden “dat ik me niet te

veel aan moet trekken van al het rood hoor”, typeert jou. Naast die vriendelijkheid en

goedheid, ben je een lopend dysmorfologie encyclopedie en weet je van ingewikkelde

materie iets simpels en logisch te maken. Ik hoop dat we in de toekomst een mooi

vervolg kunnen geven aan onze projecten. Dank je wel!

Beste dr. Plötz, lieve Frans, als co-assistent in Tergooi klopte ik bij je aan voor een

onderzoek voor mijn wetenschappelijke stage. Een aantal maanden later startten

we samen met Gerdine en Jan Maarten een onderzoek op vanuit de groeipoli van

Tergooi en rondden andere lopende onderzoeken af. Er ontstond een mooie basis

voor dit proefschrift en dat is waar dit promotie-avontuur begon. Een avontuur dat

zich in het begin kenmerkte door veel onzekerheden, maar waarin jij steeds gefocust

bleef op de toekomst en de potentie die je zag in het onderzoek en in mij. Je leerde

me plezier te hebben in het doen van onderzoek, structuur in stukken aan te brengen

en dingen soms wat meer te relativeren. Dit, en jouw nooit aflatende betrokken-

heid, positiviteit en bovenal enorme enthousiasme (“super gaaf!” zo beantwoord

je veel van mijn mailtjes) waren onmisbaar voor me om te komen waar ik nu ben.

Dank je wel dat je me deze kans hebt gegeven en me bij hebt gestaan, zonder jou was dit

proefschrift er niet geweest.

Beste dr. Kamp, lieve Gerdine, moeder van de Tergooise groeipoli. De groeipoli, daar waar

de basis van mijn promotietraject ligt, en daar waar jij als een vis in het water bent en

de patiënten met je weg lopen. Je bent altijd vol trots over onze onderzoeken en op mij.

Je zorgde met je contacten voor een groot deel van de projecten in dit proefschrift, wist

180 Appendices

allerlei potjes te benutten om het begin van dit promotietraject te financieren en had als

geen ander klinisch belang bij dit onderzoek. Je maakte de vertaling naar de kliniek,

met een kritische blik keek jij naar wat je in de praktijk doet en of en hoe het beter kan.

Jouw onvoorwaardelijke steun, uitingen van trots en blijvende betrokkenheid hebben

me er vaak doorheen gesleept en waardeer ik enorm. Dank je wel!

Beste prof. dr. Wit, beste Jan Maarten, eigenlijk ook een beetje mijn promotor, want wat heb

jij een enorme bijdrage geleverd aan dit proefschrift. Als oud-promotor van Gerdine

betrok zij jou bij onze onderzoeken op de Groeipoli. Jouw vertrouwen in dit promotie-

traject en jouw kennis en expertise binnen de kinderendocrinologie en groeistoornis-

sen in het bijzonder, hebben onze onderzoeken en uiteindelijk dit proefschrift naar

een hoger niveau getild. Ik ken weinig mensen met zo veel passie voor hun vak en de

wetenschap en ik heb ontzettend veel van je geleerd. Je hebt je al die jaren belangeloos

voor me ingezet, meegewerkt aan alle projecten van dit proefschrift, geholpen bij de

vele subsidieaanvragen en me door de jaren heen voorzien van de laatste relevante

literatuur. Ik ben je enorm dankbaar voor alles.

Dear prof. Moore and prof. Stanier, dear Gudrun and Phil, you gave me and our research an

amazing opportunity. When Raoul approached Gudrun to ask if we could use the

Baby Bio Bank’s DNA samples for our studies, from growth restricted newborns Great

Ormond Street Children’s Hospital and St. Mary’s Hospital have been collecting for

years, and if I could perhaps join your research group to perform genetic studies under

your supervision, you immediately said yes. You and your research team have welcomed

me with open arms, taught me incredibly much, were critical and supportive and have

played a huge role in the final part of my PhD. Your ability to connect people and lead

a group of researchers of different levels and personalities and make it feel like a big

family, with the right balance between hard work and humour, is admirable. I cannot

thank you both enough for allowing me to be part of that family.

Geachte Commissieleden, prof. dr. M.A. Grootenhuis, prof. dr. H.S.A. Heymans, prof. dr. M.M.A.M.

Mannens, dr. A.S.P. van Trotsenburg, prof. dr. A.C.S. Hokken-Koelega, dr. W. Oostdijk en dr. M.M. van

Weissenbruch, dank voor het kritisch lezen en beoordelen van mijn proefschrift.


Beste Peter, Adri en Marielle, dank jullie wel voor jullie waardevolle hulp bij het opzetten

en vormgeven van de genetische studie van dit proefschift, hulp bij het uitvoeren van

labwerk, de statistische analyses en interpretatie daarvan.

Beste Andrea, Izabela, Femke, Sander, Jet, Karin, Jessica, Patricia en Truus, dank jullie wel voor de

begeleiding in het laboratorium in het AMC en hulp bij het verrichten van het labwerk.

Beste Carrie en prof. van der Post, veel dank voor het beschikbaar stellen van de PANDA

Biobank samples, die hebben gediend als controle cohort voor de genetische studie

van dit proefschrift.

Lieve Liselotte en Ilse, dank jullie wel voor het inwerken op alle projecten op de groeipoli.

Samen met jullie en Anke vormden wij het onderzoeks-team aan het begin van mijn

promotietraject in Tergooi. Bedankt jullie alledrie voor de gezelligheid, hulp en betrok-

kenheid bij het schrijven van de stukken. Jullie maakten de wekenlange zoektocht naar

patiëntendossiers in de kelders van Tergooi een stuk dragelijker!

Beste Emile, Merel en Eileen, dank voor jullie hulp bij de data invoer.

Alle kinderartsen en assistenten uit Tergooi, dank jullie wel voor de leuke tijd die ik heb gehad

in Tergooi en veel dank aan de vakgroep voor jullie financiële steun, waardoor een groot

deel van dit proefschrift mogelijk is gemaakt.

Beste Irene, Desirée, Lidi en Ingrid, dank jullie wel voor jullie goede zorgen voor de patiënten

op de groeipoli en het verrichten van alle metingen.

Beste Hester, Karen en Bea, dank jullie wel voor het onderscheppen van belangrijke post,

het plannen van afspraken, het verzorgen van handtekeningen, papierwerk en andere

administratie. Dear Chris and Farha, thank you for arranging all the paperwork and other

administration before and during my stay at ICH.

Beste co-auteurs, dank jullie voor de fijne samenwerking en voor al jullie waardevolle

input. Dear co-authors, thank you for the nice collaboration and all your valuable input.

Beste Marieke, dank je wel voor je prachtige illustraties voor dit boekje.

182 Appendices

Mijn lieve AMC collega’s uit de Rode Luifel, Joep, Floor, Gé-Ann, Stephanie Bas, Nina, Merel,

Lindsay, Anna, Robbert, Jop, Lieke, Jos, Petra en Aslihan, dank jullie wel voor jullie gezellige

aanwezigheid in deze uithoek van het AMC.

Helaas werden we begin dit jaar bruut uit elkaar gehaald en werd H7-235 voor een deel

van ons een nieuw tweede huis. Gé, ik ben blij dat jij AMC’s grootste vlogster bent en

ik zo op de hoogte blijf van de gekkigheid op onze kamer. Steef, wederhelft van 235’s

komisch duo Gé-Ann & Stephanie. Naast een geweldige dokter en onderzoeker, had

je ook food-blogger kunnen worden. Bas, gelukkig kunnen we bij jou altijd terecht

voor advies, want… jij weet bíjna overal wel íets van. Respect voor hoe jij het uithield

met al die vrouwen op één kamer zonder ramen toen Joep ons tijdelijk verliet. Joep,

keiharde werker, jouw gezelligheid en schaterlach werden enorm gemist, H7-235 was

niet meer hetzelfde zonder jou toen je naar Seattle vertrok. Floor, was iedereen maar zo

georganiseerd als jij, we zijn allemaal een beetje jaloers op jouw fijne met mapjes en

post-its geordende bureau. Olga, eigenlijk leef jij meer in het lab dan in 235, maar het

was fijn je af en toe bij ons te hebben. Lindsay, ons metabole wonder, wat zouden de

Sanfilippo patiënten zonder jou moeten. Merel, wat een fijne toevoeging was jij aan onze

kamer, een beetje chirurgische pit in ons midden! En Nina, officieel niet in 235 maar

toch onlosmakelijk met ons verbonden, regen van energie en ambassadrice van Bukje,

wat zou de vrijdagmiddagborrel daar zijn zonder jou. Ik ga jullie, de avocado-lunch,

office-pranks, AH-koffietjes en de vrijdagmiddagborrels missen!

Lieve Hanneke, wat een geluk dat wij dankzij Raoul samen op de genetica cursus in Italië

belandden. Niet alleen omdat we ongeveer de enige niet-genetici waren en de helft niet

konden volgen, maar ook omdat daar de basis van onze dierbare vriendschap ontstond.

Terwijl de andere deelnemers ‘genoten’ van het universiteits-buffet, verkenden wij de

buurt en kwamen we op de mooiste plekjes en in de leukste restaurantjes terecht. Bijna

dagelijkse koffiedates in het AMC volgden, waar we van alles bespraken wat ons bezig-

hield bij het onderzoek, onze liefde voor lekker eten en interieur en hoe gezegend we

ons voelden met Raoul als promotor. Ik wil je bedanken voor al je hulp, betrokkenheid

en promotie-tips.

To all my dear ICH colleagues, Lydia, Lucas, Javier, Kevin, Nita, Sayeda, Emma, Dale, Miho,

Karina, Cristina, Farha, Xiye, Will, Pambos, Diana, Cloë, Lara, Rimante, working at ICH with

you was lovely, every single day. You have all welcomed me and made me feel part of

your team from day one. As an unexperienced doctor in the laboratory hardly knowing


how to handle a pipette, you have helped me with the greatest patience, taught me tons

and made time for me whenever I needed it. I had such a great time with you, also

outside work; pale ales and scotch eggs every Friday (and many other days… hence

my rapid weight gain) after work at the Lamb, Arsenal games, Incredible Midtown,

Spectre, lunches at the park, at Burgers ‘n Shake and Nando’s, the Heartbreak Hotel,

and the list continues... You are the best and I miss you all!

Lieve Marijn, toen ik hoorde van een Nederlandse arts-onderzoeker uit het AMC die ook

aan het Institute of Child Health haar promotieonderzoek deed, zocht ik je op. En na de

eerste koffiedate volgden er bijna dagelijks meer. We waren vaste klant bij de Espresso

Room tegenover Great Ormond Street waar we elkaar leerden kennen, praatten over

ons onderzoek, de soms eenzame en lange dagen in het lab, onze toekomstplannen en

het leven in Londen en Amsterdam. We legden daar de basis voor onze vriendschap,

eentje die nu al heel vertrouwd voelt. Ik kan niet wachten tot je ook weer naar Amster-

dam komt! Dank je wel dat je Londen komt vertegenwoordigen en me bij wilt staan

tijdens de verdediging van mijn proefschrift.

Lieve Derk, buurman, vriend en mijn AMC-maatje in goede en slechte tijden. Jij bent als

geen ander betrokken geweest bij mijn promotieonderzoek. Onze gezamenlijke ritjes

van de Linnaeuskade naar het AMC, lunchen met onze zelfgebouwde salades, jouw

onmisbare ICT hulp bij mijn worsteling met programmeren in R en Python en bij het

crashen van mijn harde schijf in Londen (lang leve de remote control!), jouw peptalks,

onze ontelbare gesprekken over onderzoek, toekomstplannen en andere levensdilem-

ma’s. Jouw passie voor jouw bedrijf Castor, en onuitputtelijke doorzettingsvermogen

om daarnaast ook nog een proefschrift te schrijven is bewonderenswaardig. Geweldig

dat we dit tijdperk samen als elkaars paranimf en met een mooi feest kunnen afsluiten.

Dank je wel dat je me bij wilt staan tijdens de verdediging van mijn proefschrift.

Lieve Wim, Bram en Eileen, hooggeleerde leden van MediStal. Dank jullie wel voor de

jaarlijkse dinertjes met veel eten, gezelligheid en vunzige anekdotes. Hopelijk kunnen

we nog een paar generaties Stalmannen warm maken voor het doktersvak!

Lieve Alyn, mijn surrogaat zusje. Wij kennen elkaar zo lang als we het ons kunnen herin-

neren. Een vriendschap zo vertrouwd en dierbaar. Je bent altijd zo trots en staat altijd

voor me klaar, dank je wel daarvoor.

184 Appendices

Lieve Jo & Renee, mijn musketiers. Een driehoeksverhouding die verrassend goed werkt.

Samen delen wij alles (inclusief onze PhD’s), kennen elkaar als geen ander, staan klaar

voor elkaar als dat nodig is en hebben vrijwel elk festival en feestje samen afgelopen.

Het leven met jullie is genieten, dank daarvoor!

Lieve Anna, dank je wel voor je geduld, begrip en goede zorgen op al die avonden dat

Derk en ik met de laptop op schoot ons proefschrift zaten te tikken. En niet te vergeten

je creatieve input, luisterend oor en het feit dat je altijd voor iedereen klaarstaat.

Lieve vriendinnen en vrienden, dank jullie wel dat jullie in mijn leven zijn en het tot een feest

maken!

Lieve ooms, tantes, neven en nichten Stalman en de Broekert en lieve schoonfamilie, dank jullie wel

voor jullie warmte, gezelligheid en betrokkenheid.

Lieve Janneke, dank je wel voor je altijd enorme interesse, medeleven en lieve zorgen.

Lieve Oma, wat ben ik blij dat je dit nog mee kan maken. Jouw levenslust en kracht,

ondanks de tegenslagen in jouw leven, bewonder ik enorm. Dank je wel voor dat goede

voorbeeld en natuurlijk voor al je gulle giften!

Lieve Sofie, liefste zus, in veel opzichten zijn we zo verschillend maar we delen toch ook

zo veel. Jij was de hulplijn die ik inschakelde bij kleine mental-breakdowns, die soms

ook bij het promoveren horen, en jouw altijd scherpe analyses en adviezen hielpen

me er snel weer bovenop. Je bent een geboren psychologe. De afgelopen jaren waren

turbulent, maar ik ben blij dat we altijd elkaar hadden om bij te spuien en steun bij te

vinden. Dank je wel lieve zus.

Lieve papa en mama, jullie hebben samen de basis gelegd voor mijn toekomst. Jullie leer-

den ons van het leven te genieten, hielpen onze kwaliteiten en potenties te ontplooien,

steunden ons in de keuzes die we maakten en waren kritisch als dat moest, stonden

dag en nacht voor ons klaar, stimuleerden ons de wereld te ontdekken en gaven ons een

veilig, zorgzaam thuis. In de afgelopen jaren is er veel gebeurd en veranderd, maar dit

blijft onveranderd: ik hou van jullie en dank jullie voor alles.

Allerliefste Thijs, jouw rust, relativerend vermogen en onvoorwaardelijke liefde voor mij

zijn onmisbaar in mijn leven, en onmisbaar geweest tijdens mijn promotietraject. Je

bent mijn maatje, mijn thuis, samen reizen we de wereld over en genieten van het leven.

Ik maakte het jou niet makkelijk door 9 maanden voor mijn onderzoek naar Londen te

vertrekken, maar je liet mij zonder twijfel gaan, steunde me onvoorwaardelijk en greep

elke kans aan me op te zoeken. En ook na afloop gaf je me de ruimte afscheid te nemen

van het Londense leven dat ik af en toe zo mis. Dank je wel voor alles. Ik hou van je!

Supplemental Materials (Chapter 5)

189Supplemental Materials (Chapter 5)

Supplemental Materials (Chapter 5)

Supplemental Table 1. Genes Known to be Aberrantly Methylated in Low Birthweight Newborns

Gene Chromosome Imprinted Association with low birth weight Reference

AGR2 7p21.3 Decrease in DNA methylation in FGR-arteries [1]

ALDH3B2 11q13 Decreased methylation associated with SGA or FGR [2]

ANKRD11 16q24.3 Possibly imprinted gene, associated with 16q24.3 microdele-tion, KBG syndrome and hypermethylation of CpG island near ANKRD11 in Silver-Russel syndrome

[3-5]

ANXA2R 5p12 Hypomethylated in fetal growth restriction [6]

APBA2 15q11-q12 Hypermethylated in small for gestational age placentas [2]

APOL1 22q13.1 Hypomethylated in fetal growth restriction [6]

ARID5B 10q21.2 Differential methylation associated with decreased birth weight [7]

ATL2 2p22.3 Hypermethylated in fetal growth restriction [6]

BRCA1 17q21 Hypermethylation described in fetal growth restriction [6]

C6orf211 6q25.1 Hypermethylation described in fetal growth restriction [6]

CCDC86 11q12.2 Differentially expressed in growth restricted and non-growth restricted placentas

[8]

CDKAL1 6p22.3 Differentially expressed in growth restricted and non-growth restricted placentas

[8]

CDKN1C 11p15.5 Yes Highly expressed in placenta, associated with fetal growth restriction; Upregulation associated with FGR placentas, loss of function associated with Beckwith-Wiedemann syndrome, gain of function with Silver-Russel syndrome

[9-12]

CHML 1q43 Increased methylation associated with SGA or FGR [2]

CSTA 3q21 Decreased methylation associated with SGA or FGR [2]

DBP 19q13.3 Increased methylation associated with SGA or FGR [6]

DHCR24 1p32.3 Differential expressed in growth restricted and non- growth restricted placentas

[8]

DLK1 14q32 Yes Highly expressed in placenta; associated with pre- and postnatal growth restriction and UPD14

[10, 13]

DNAAF1 16q24.1 Increased methylation associated with SGA or FGR

[6]

DNAJB4 1p31.1 Decreased methylation associated with SGA or FGR [2]

DSTN 20p12.1 Increased methylation associated with SGA or FGR [6]

FGF14 13q34 Decreased methylation associated with SGA or FGR [2]

FOXP1 3p14.1 Hypermethylated in fetal growth restriction [6]

GGPS1 1q43 Decreased methylation associated with SGA or FGR [2]

GIMAP2 7q36.1 Decreased methylation associated with SGA or FGR [2]

GNAS 20q13.3 Yes Decreased expression observed in FGR placentas [14]

GNASAS 20q13.32 Yes Loss of methylation in FGR patients [15]

190 Supplements

Supplemental Table 1. Genes Known to be Aberrantly Methylated in Low Birthweight Newborns (continued)


GPR4 19q13.3 Decreased methylation associated with SGA or FGR [2]

GRB10 7p12.2 Yes Highly expressed in placenta, implicated in Silver-Russell syndrome, loss of methylation in FGR patients

[10, 15]

GYS2 12p12.2 Decreased methylation associated with SGA or FGR [2]

H19 11p15.5 Yes Highly expressed in the placenta. ICR1 hypomethylation in FGR samples, hypomethylation and copy number variant in Silver- Russell syndrome

[3, 9, 10, 15]

HIST1H3I 6p22.1 Increased methylation associated with SGA or FGR [6]

HIST1H4J 6p22.1 Increased methylation associated with SGA or FGR [6]

HIST1H4L 6p22.1 Increased methylation associated with SGA or FGR [6]

HNRNPH3 10q22 Increased methylation associated with SGA or FGR [6]

HOXB4 17q21.32 Increased methylation associated with SGA or FGR [6]

HSD11B2 16q22 Site-specific methylation of placental HSD11B2 gene promoter, hypermethylated in FGR

[16]

HSD11B1 1q32-q41 Hypomethylated HSD11B1 in LGA infants [17]

HSDL1 16q23.3 Increased methylation associated with SGA or FGR [6]

HSPBAP1 3q21.1 Increased methylation associated with SGA or FGR [15]

IGF2 11p15.5 Yes Highly expressed in placenta; hypomethylation of H19/IGF2 control region is associated with FGR

[9, 10, 18, 19]

IGF2AS 11p15.5 Yes Expressed in antisense to IGF2 (geneimprint.com)

IGF2R 6q26 Yes Highly expressed in placenta; hypomethylated in FGR [10, 15]

IGFBP3 7p12.3 Significant differences in promoter methylation rate of IGFBP3 between FGR and AGA newborns

[20]

IL27RA 19p13.11 Increased methylation associated with SGA or FGR [6]

ILK2 11p15.4 Differential expression between growth restricted and non-restricted placentas

[8]

INS 11p15.5 Yes Imprinted gene on 11p15.5 region. (geneimprint.com)

INS-IGF2 11p15.5 Yes Imprinted gene on 11p15.5 region; involved in growth and metabolism.

(geneimprint.com)[21]

JARID2 6p24-p23 Increased methylation associated with SGA or FGR [6]

KCNQ1 11p15.5 Yes Upregulated in FGR samples; genetic variants associated with Beckwith-Wiedemann

[9, 22]

KCNQ1OT1 11p15 Yes Loss of methylation in FGR patients [15]

KLF9 9q13 Differential methylation associated with decreased birth weight [7]

KLHL5 4p14 Decreased methylation associated with SGA or FGR [2]

LEP 7q31.3 DNA methylation levels in SGA group were not sign. different from AGA group

[21]

LRRC41 1p34.1 Increased methylation associated with SGA or FGR [6]

MACROD2 20p12.2 Decreased methylation associated with SGA or FGR [6]




MEG3 14q32 Yes Highly expressed in placenta, reduced expression in FGR placentas.

[10, 14]

MEP1A 6p12-p11 Increased methylation associated with SGA or FGR [2]

MEST 7q32 Yes Highly expressed in placenta, implicated in Silver-Russell syndrome

[10]

MFAP1 15q15.3 Decreased methylation associated with SGA or FGR [2]

MRPL36 5p15.3 Decreased methylation associated with SGA or FGR

[6]

NBR2 17q21 Increased methylation associated with SGA or FGR [6]

NCOA4 10q11.2 Decreased methylation associated with SGA or FGR [2]

NDUFS6 5p15.33 decreased methylation associated with SGA or FGR [6]

NFKBIZ 3p12-q12 Decreased methylation associated with SGA or FGR [2]

NNAT 20q11.2-q12 Yes Hypermethylation in placenta associated with FGR [8]

NOS3 7q36 Decrease in DNA methylation in FGR-arteries and increase in FGR-veins

[1]

NPR3 5p13.3 Hypermethylation described in fetal growth restricted umbilical cord blood.

[6]

NR3C1 5q31.3 Methylation status of glucocorticoid receptor gene (NR3C1) in placenta correlates with birthweight.

[23]

NSD1 5q35 Loss of function associated with overgrowth (Sotos syndrome) [24]

OAT 10q26 Decreased methylation associated with SGA or FGR [2]

OMG 17q11.2 Increased methylation associated with SGA or FGR [2]

PBLD 10q21.3 Increased methylation associated with SGA or FGR [6]

PDC 1q25.2 Increased methylation associated with SGA or FGR [2]

PEG10 7q21.3 Yes Imprinted gene highly expressed in the placenta. Differential ex-pression between growth restricted and non-restricted placentas

[8, 10, 15]

PEG3 19q13.4 Yes Imprinted gene highly expressed in the placenta. Loss of meth-ylation in FGR patients.

[10, 15]

PHF21B 22q13.31 Increased methylation associated with SGA or FGR [6]

PHLDA2 11p15.4 Yes Highly expressed in placenta. Differential expression between growth restricted and non-restricted placentas

[8-10, 25, 26]

PIAS3 1q21 Increased methylation associated with SGA or FGR [6]

PIK3CG 7q22.3 Increased methylation associated with SGA or FGR [6]

PLAGL1 6q24-q25 Yes Highly expressed in placenta. Differential expression between growth restricted and non-restricted placentas.

[8, 10, 27]

PNPLA3 22q13.31 Increased methylation associated with SGA or FGR [6]

QDPR 4p15.31 Increased methylation associated with SGA or FGR [6]

RAD50 5q31.3 Increased methylation associated with SGA or FGR [6]

RIOK3 18q11.2 Increased methylation associated with SGA or FGR [6]

RIT1 1q22 Increased methylation associated with SGA or FGR [6]

RMND1 6q25.1 Increased methylation associated with SGA or FGR [6]

192 Supplements



RPA1 17p13.3 Increased methylation associated with SGA or FGR [6]

RPE65 1p31 Increased methylation associated with SGA or FGR [2]

RPL14 3p22-p21.2 Increased methylation associated with SGA or FGR [6]

RPL17 18q21 Increased methylation associated with SGA or FGR [6]

RTL1 14q32.2 Yes Imprinted gene associated with UPD14 phenotypes [28]

RTN4 2p16.3 Increased methylation associated with SGA or FGR [6]

RUFY1 5q35.3 Increased methylation associated with SGA or FGR [6]

SEC1P 19q13.33 Increased methylation associated with SGA or FGR [6]

SEPT7 7p14.2 Increased methylation associated with SGA or FGR [6]

SERPINA5 14q32.1 Increased methylation associated with SGA or FGR [2]

SHC1 1q21 DNA methylation of the p66Shc promoter is decreased in placental tissue from women delivering intrauterine growth restricted neonates

[29]

SHMT2 12q12-q14 Increased methylation associated with SGA or FGR [6]

SLC25A18 11p15.5 Yes Increased methylation associated with SGA or FGR [2]

SMYD4 17p13.3 Increased methylation associated with SGA or FGR [6]

SNORD58A 18q21 Increased methylation associated with SGA or FGR [6]

SPEF1 20p13 Decreased methylation associated with SGA or FGR [2]

TAF5 10q24-q25.2 Increased methylation associated with SGA or FGR [6]

TAL1 1p32 Increased methylation associated with SGA or FGR [6]

TBX15 1p11.1 Promotor hypomethylation leads to TBX15 decrease in FGR placentas

[30]

TMOD2 15q21.2 Increased methylation associated with SGA or FGR [6]

TRPS1 8q24.12 Increased methylation associated with SGA or FGR [6]

UQCRH 1p34.1 Increased methylation associated with SGA or FGR [6]

WNT2 7q31.2 WNT2 promoter methylation in placenta is associated with low birthweight

[31]

ZIC1 3q24 Predicted Decreased methylation associated with SGA or FGR [6]

ZMIZ1 10q22.3 Increased methylation associated with SGA or FGR [6]

ZNF141 4p16.3 Decreased methylation associated with SGA or FGR [6]

ZNF331 19q13.42 Differential expression between growth restricted and non-restricted placentas

[8]


Supplemental Figure 1. Clustering of Male and Female Samples

-100 0 100 200 300 Principal Component 1 (16.5%)

Prin

cipal

Com

pone

nt 2

(7.1%

)

-6

0

-40

-

20

0

20

4

0

60

194 Supplements

Supplemental Table 2. Genes Known to be Involved in (Regulation of ) DNA-Methylation

Gene Chromosome Role in regulation of DNA-methylation Reference

AICDA 12p13 May play a role in epigenetic regulation of gene expression by participating in DNA demethylation

uniprot.org

ALKBH1 14q24.3 Role in DNA demethylation uniprot.org

ALKBH2 12q24.11 Dioxygenase that repairs alkylated DNA containing 1-methyladenine and 3-methylcytosine by oxidative demethylation

uniprot.org

ALKBH3 11p11.2 Dioxygenase that repairs alkylated DNA containing 1-methyladenine (1meA) and 3-methylcytosine (3meC) by oxidative demethylation

uniprot.org

APEX1 14q11.2 May play a role in epigenetic regulation of gene expression by participating in DNA demethylation

uniprot.org

APOBEC1 12p13.1 May play a role in epigenetic regulation of gene expression by participating in DNA demethylation

uniprot.org

APOBEC2 6p21 May a role in epigenetic regulation of gene expression through the process of active DNA demethylation

uniprot.org

APOBEC3A 22q13.1-q13.2 Role in epigenetic regulation of gene expression through the process of active DNA demethylation

uniprot.org

APOBEC3C 22q13.1 Role in epigenetic regulation of gene expression through the process of active DNA demethylation

uniprot.org

APOBEC3F 22q13.1 Role in epigenetic regulation of gene expression through the process of active DNA demethylation

uniprot.org

ASZ1 7q31.2 Role in DNA methylation involved in gamete generation uniprot.org

ATF7IP 12p13.1 Required to stimulate histone methyltransferase activity and facilitates conversion of dimethylated to trimethylated H3 ‘Lys-9’. Represses transcription and couples DNA methylation and histone H3 ‘Lys-9’ trimethylation

uniprot.org

ATRX Xq21.1 Role in DNA methylation uniprot.org

BAZ2A 12q13.3 Mediates silencing of rDNA by recruiting histone-modifying enzymes and DNA methyltransferases.

uniprot.org

BEND3 6q21 Role in DNA methylation uniprot.org

BRCA1 17q21 Regulator of DNA-methylation uniprot.org

CTCF 16q22.1 Involved in epigenetic regulation uniprot.org

CTCFL 20q13.31 Involved in gene imprinting in male germline, by participating in the establishment of differential methylation at the IGF2/H19 imprinted control region

uniprot.org

DMAP1 1p34 DNA methyltransferase 1-associated protein 1. Involved in transcription repression and activation.

uniprot.org

DNMT1 19p13.2 Methylates CpG residues, essential for epigenetic inheritance. Responsible for maintaining methylation patterns established in development.

uniprot.org

DNMT3A 2p23 Required for genome-wide de novo methylation and essential for the establishment of DNA methylation patterns during development

uniprot.org

DNMT3B 20q11.2 Required for genome-wide de novo methylation and essential for establishing DNA methylation patterns during development

uniprot.org


Supplemental Table 2. Genes Known to be Involved in (Regulation of ) DNA-Methylation (continued)


DNMT3L 21q22.3 Catalytically inactive regulatory factor of DNA methyltransferases; essential for functioning of DNMT3A and DNMT3B

uniprot.org

DPPA3 12p13.31 Primordial germ cell (PGCs)-specific protein involved in epigenetic chromatin reprogramming in the zygote following fertilization

uniprot.org

EHMT1 9q34.3 Histone methyltransferase that specifically mono- and dimethylates ‘Lys-9’ of histone H3 (H3K9me1 and H3K9me2, respectively) in euchromatin

uniprot.org

EHMT2 6p21.31 Histone methyltransferase that specifically mono- and dimethylates ‘Lys-9’ of histone H3 (H3K9me1 and H3K9me2, respectively) in euchromatin

uniprot.org

EZH2 7q35-q36 Histone-lysine N-methyltransferase EZH2 (EC 2.1.1.43) (ENX-1) (Enhancer of zeste homolog 2) (Lysine N-methyltransferase 6)

uniprot.org

FKBP6 7q11.23 Role in DNA methylation involved in gamete generation uniprot.org

FOS 14q24.3 Fos may transform cells through alterations in DNA methylation uniprot.org

FTO 16q12.2 Dioxygenase repairing alkylated DNA and RNA by oxidative demethylation

uniprot.org

GATA3 10p15 Regulation of histone H3-K27 and H3-K4 methylation ensembl.org

GATAD2A 19p13.11 Role in DNA methylation uniprot.org

GATAD2B 1q21.3 Role in DNA methylation uniprot.org

GNAS 20q13.3 Role in DNA methylation uniprot.org

GRHL2 8q22.3 Inhibits DNA methylation, possibly by interfering with DNMT1 enzyme activity

uniprot.org

H1FOO 3q22.1 May play a role in the control of gene expression during oogenesis and early embryogenesis, presumably through perturbation of chromatin structure

uniprot.org

H3F3A; H3F3B

1q42.12;17q25.1

Role in DNA methylation on cytosine. Deposited at sites of nucleosomal displacement throughout transcribed genes, suggesting that it represents an epigenetic imprint of transcriptionally active chromatin

uniprot.org

HELLS 10q24.2 Required for de novo or maintenance of DNA methylation; may control silencing of CDKN1C gene through DNA methylation

uniprot.org

HEMK1 3p21.3 N5-glutamine methyltransferase responsible for methylation of the GGQ triplet of the mitochondrial translation release factor MTRF1L

uniprot.org

HIST1H3A; HIST1H3B; HIST1H3C; HIST1H3D; HIST1H3E; HIST1H3F; HIST1H3G; HIST1H3H; HIST1H3I; HIST1H3J

6p22.1-2 Role in DNA methylation on cytosine uniprot.org

196 Supplements



HIST1H4A; HIST1H4B; HIST1H4C; HIST1H4D; HIST1H4E; HIST1H4F; HIST1H4H; HIST1H4I; HIST1H4J; HIST1H4K; HIST1H4L

6p22.1-2 Role in DNA methylation on cytosine uniprot.org

HIST2H4A; HIST2H4B

1q21 Role in DNA methylation on cytosine uniprot.org

HIST4H4 12p12.3 Role in DNA methylation on cytosine uniprot.org

HIST2H3A; HIST2H3C; HIST2H3D

1q21.2 Role in DNA methylation on cytosine uniprot.org

KDM1B 6p22.3 Required for de novo DNA methylation of a subset of imprinted genes during oogenesis

uniprot.org

KHDC3L 6q13 Possible regulator of genomic imprinting in the human oocyte [32]

KMT2A 11q23 Histone methyltransferase that plays an essential role in early development and hematopoiesis

uniprot.org

KMT2E 7q22.1 Histone methyltransferase that specifically mono- and dimethylates ‘Lys-4’ of histone H3 (H3K4me1 and H3K4me2)

uniprot.org

MAEL 1q24.1 Role in DNA methylation involved in gamete generation uniprot.org

MBD1 18q21 Transcriptional repressor that binds CpG islands in promoters where the DNA is methylated at position 5 of cytosine within CpG dinucleotides

uniprot.org

MBD3 19p13.3 Transcriptional repressor, plays a role in gene silencing. Binds to DNA with a preference for sites containing methylated CpG dinucleotides. Recruits histone deacetylases and DNA methyltransferases

uniprot.org

MECP2 Xq28 Chromosomal protein that binds to methylated DNA uniprot.org

MGMT 10q26 O6-Methylguanine-DNA methyltransferase, DNA methyltransferase, known to have significant fetal effects

uniprot.org, [33]

MIS18A 21q22.11 Regulator of DNA methylation uniprot.org

MPHOSPH8 13q12.11 Key epigenetic regulator by bridging DNA methylation and chromatin modification

uniprot.org

MTA2 11q12-q13.1 May be involved in the regulation of gene expression as repressor and activator. The repression might be related to covalent modification of histone proteins

uniprot.org

MTRR 5p15.31 Necessary for utilization of methyl groups from the folate cycle, thereby affecting transgenerational epigenetic inheritance

uniprot.org

NLRP2 19q13.42 Mutation NLRP2 associated with familial imprinting disorder [34]

NLRP5 19q13.43 Mutations associated with multilocus imprinting disorders [35]




NLRP7 19q13.42 Mutations associated with multilocus inprinting disorders and intrauterine growth retardation

[35]

PICK1 22q13.1 Role in DNA methylation involved in embryo development and gamete generation

uniprot.org

PIWIL2 8p21.3 Acts via the piRNA metabolic process, acts upstream of known mediators of DNA methylation.

uniprot.org

PIWIL4 11q21 Acts via the piRNA metabolic process, acts upstream of known mediators of DNA methylation.

uniprot.org

PLD6 17p11.2 piRNA-mediated transposon silencing is critical for maintaining genome stability, in particular in germline cells when transposons are mobilized as a consequence of wide-spread genomic demethylation

uniprot.org

PRDM14 8q13.3 May play an essential role in germ cell development by epigenetic reprogramming

uniprot.org

PRMT5 14q11.2

Arginine methyltransferase, mediates methylation required for the assembly and biogenesis of snRNP core particles

uniprot.org

PRMT7 16q22.1 Plays a role in gene imprinting by being recruited by CTCFL at the H19 imprinted control region and methylating histone H4 to form H4R3me2s, possibly leading to recruit DNA methyltransferases at these sites

uniprot.org

SMCHD1 18p11.32 Required for maintenance of X inactivation in females and hypermethylation of CpG islands associated with inactive X. Involved in a pathway that mediates the methylation of a subset of CpG islands slowly and requires the de novo methyltransferase DNMT3B

uniprot.org

TDG 12q24.1 DNA glycosylase that plays a key role in active DNA demethylation uniprot.org

TDRD1 10q25.3 Role in DNA methylation involved in gamete generation uniprot.org

TDRD12 19q13.11 Acts via the piRNA metabolic process, which mediates the repression of transposable elements during meiosis by forming complexes composed of piRNAs and Piwi proteins and governs the methylation and subsequent repression of transposons.

uniprot.org

TDRD5 1q25.2 Probably acts via the piRNA metabolic process, which mediates the repression of transposable elements during meiosis by forming complexes composed of piRNAs and Piwi proteins and govern the methylation and subsequent repression of transposons

uniprot.org

TDRD9 14q32.33 Acts via the piRNA metabolic process, which mediates the repression of transposable elements during meiosis by forming complexes composed of piRNAs and Piwi proteins and govern the methylation and subsequent repression of transposons

uniprot.org

TDRKH 1q21 The piRNA metabolic process mediates the repression of transposable elements during meiosis by forming complexes composed of piRNAs and Piwi proteins and govern the methylation and subsequent repression of transposons

uniprot.org

TET1 10q21 Dioxygenase that catalyzes the conversion of the modified genomic base 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC) and plays a key role in active DNA demethylation

uniprot.org

198 Supplements



TET2 4q24 Dioxygenase that catalyzes the conversion of the modified genomic base 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC) and plays a key role in active DNA demethylation

uniprot.org

TET3 2p13.1 Dioxygenase that catalyzes the conversion of the modified genomic base 5-methylcytosine (5mC) into 5-hydroxymethylcytosine (5hmC) and plays a key role in epigenetic chromatin reprogramming in the zygote following fertilization

uniprot.org

TRIM28 19q13.4 Role in DNA methylation involved in embryo development and negative regulation of DNA demethylation.

uniprot.org

UHRF1 19p13.3 Key epigenetic regulator by bridging DNA methylation and chromatin modification

uniprot.org

UHRF2 9p24.1 Through cooperative DNA and histone binding, may contribute to a tighter epigenetic control of gene expression in differentiated cells

uniprot.org

USP7 16p13.3 Involved in maintenance of DNA methylation via its interaction with UHRF1 and DNMT1: acts by mediating deubiquitination of UHRF1 and DNMT1, preventing their degradation and promoting DNA methylation by DNMT1

uniprot.org

ZFP57 6p22.1 Transcription regulator required to maintain maternal and paternal gene imprinting, including DNA methylation. Acts by controlling DNA methylation during the earliest multicellular stages of development at multiple imprinting control regions

uniprot.org, [36]


Supplemental Table 3. Genes in which Sequence Variants are Associated with a Low Birthweight

Gene Chromosome Disorder Inheritance Reference

ACAN 15q26.1 Spondyloepimetaphy-al dysplasia aggrecan type; Spondyloepiphyseal dysplasia type Kimberley

AR; AD [37, 38]

ADA 20q13.12 Dwarfism - immunodeficiency type 1 AR [39]

ADAMTS10 19p13.2 Weill–Marchesani syndrome AR [40]

ADCY5 3q21.1 Associated with fetal growth and birthweight [41]

ALG12 22q13.33 Congenital disorder of glycosylation type 1g AR [39]

ALMS1 2p13 Almström syndrome AR [42]

ANKRD11 16q24.3 KBG syndrome AD [39]

ARID1A 1p35.3 Coffin–Siris syndrome AD [43]

ARID1B 6q25.1 Coffin–Siris syndrome AD [43]

ALB4 1 Defective nonhomologous endjoining DNA damage repair

AR [44]

ATP6VOA2 12q24.31 Cutis laxa type IIA AR [39]

PAPSS2 10q24 Spondyloepimetaphyseal dysplasia type Pakistan AR [39]

ATR 3q23 Seckel syndrome AR [45]

ATRIP 3p21.31 Seckel syndrome AR [45]

ATRX Xq21.1 X-linked intellectual disability - hypotonic facies syndrome

XLR [46]

AUTS2 7q11.22 Chromosome 7q11.22 microdeletion Microdeletion [39]

B3GALTL 13 Peters’ plus syndrome AR [39]

BCS1L 2q33 Gracile bone syndrome AR [39]

BLM 15q26.1 Bloom syndrome AR [39]

BMP2 20p12 Brachydactyly A2

AD [47]

BMPR1B 4q22-q24 Brachydactyly A1 AD [48]

BRAF 7q34 Noonan syndrome; LEOPARD syndrome AD [49]

BSND 1p32.1 Bartter syndrome AR [39]

BTK Xq21.33-q22 Isolated GHD type III XLR [50, 51]

MPLKIP 7p14.1 Trichothiodystrophy AR [39]

CALY 10q26.3 Chromosome 10q26 microdeletion Microdeletion [3]

CBL 11q23.3 Noonan-like syndrome AD [39]

CCDC8 19q13.32 Three-M syndrome AR [39, 52]

200 Supplements

Supplemental Table 3. Genes in which Sequence Variants are Associated with a Low Birthweight (continued)


CCNL1 3q25.31 Associated with fetal growth and birthweight [41]

CDC6 17q21.3 Meier-Gorlin syndrome AR [53]

CDKN1C 11p15.5 Silver–Russell syndrome; IMAGe syndrome AD (IMAGe) [54-56]

CDT1 16q24.3 Meier-Gorlin syndrome AR [53]

CENPE 4q24-q25 Microcephalic primordial dwarfism AR [39]

CENPJ 13q12.12 Seckel syndrome AR [57]

CEP152 15q21.1 Seckel syndrome AR [58]

CEP63 3q22.2 Seckel syndrome AR [59]

CERS3 15q26.3 Chromosome 15q26.3 microdeletion Microdeletion [39]

CHD7 8q12.2 CHARGE syndrome AD [39, 60, 61]

CLCNKA 1p36 Bartter syndrome AR [39]

CLCNKB 1p36 Bartter syndrome AR [39]

CNTN4 3p26.3 Chromosome 3p26 microdeletion Microdeletion [39]

COG1 17q25.1 Cerebro-costo-mandibular-like syndrome AR [39]

COL10A1 6q21-q22 Metaphyseal chondro-dysplasia Schmid type AD [62]

COL1A1 17q21.33 Osteogenesis imperfecta AD [39]

COL2A1 12q13.11 Spondylo-Epiphyseal Dysplasia Congenita; Hypochondrogenesis; Achondrogenesis type 2.

AD [63, 39]

COL4A5 Xq22 Alport syndrome XLR [39]

COL9A1 6q13 Multiple epiphyseal dysplasia AD [64]

COL9A2 1p33-p32 Multiple epiphyseal dysplasia AD [64]

COL9A3 20q13.3 Multiple epiphyseal dysplasia 3 AD [64]

COMP 19p13.1 Multiple epiphyseal dysplasia AD [64]

CREBBP 16p13.3 Rubinstein–Taybi syndrome 1 AD [65]

CRIPT 2p21 Short stature with microcephaly and distinctive facies

AR [66]

CTC1 17p13.1 Revesz syndrome (Coats plus syndrome) AR [39]

CNTNAP2 7q35 Pitt-Hopkins-like syndrome AR [39]

CUL4B Xq23 Intellectual disability, X-linked, syndromic 15 (Cabezas type)

XLR [39]

CUL7 6p21.1 Three-M syndrome AR [39]

CYP19A1 15q21.1 Estrogen deficiency (tall stature) AR [24]

DKC1 Xq28 Hoyeraal-Hreidarsson syndrome AR [39]

DNA2 10q21.3-q22.1 Seckel syndrome AR [59]

DNAJC19 3q26.33 Barth-like syndrome, Canadian Hutterite type AR [39]

DUOX2 15q15.3 Thyroid dyshormonogenesis AR [24]

EMG1 12p13.3 Bowen-Conradi syndrome AR [39]

EP300 22q13.2 Rubinstein-Taybi syndrome AD [65]




ERCC3 2q21 Xeroderma pigmentosum, group B/Cockayne syndrome

AR [65]

ERCC4 16p13.12 Xeroderma pigmentosum, type F/Cockayne syndrome

AR [65]

ERCC5 13q33 Xeroderma pigmentosum, group G/Cockayne syndrome

AR [65]

ERCC6 10q11.23 Cockayne syndrome type B AR [65]

ERCC8 5q12.1 Cockayne syndrome type A AR [65]

ESR1 6q25.1 Estrogen resistance (tall stature) AR [24]

FAM111A 11q12.1 Kenny–Caffey syndrome AD [68]

COX20 1q44 Chromosome 1q44 microdeletion Microdeletion [39]

FANCA 16q24.3 Fanconi anemia AR [69]

FBN1 15q21.1 Acromicric dysplasia; Geleophysic dysplasia-2; Weill–Marchesani syndrome

AD; AD; AR [40, 70, 71]

FEZF2 3p14.2 Chromosome 3p14.3 microdeletion Microdeletion [39]

FGD1 Xp11.21 Aarskog–Scott syndrome (faciogenital dysplasia) XLR [72]

FGF8 10q24 Pallister–Hall syndrome AR [73, 74]

FGFR1 8p11.23-p11.22 Pallister–Hall syndrome; Pfeiffer syndrome (acrocephalosyndactyly type V)

AD [76]

FGFR2 10q26 Pfeiffer syndrome (acrocephalosyndactyly type V) AD [75]

FGFR3 4p16.3 Thanatophoric dysplasia type I; Achondroplasia; Hypochondroplasia

AD [39, 77-79]

FMR1 Xq27.3 Chromosome Xq27.3q28 microduplication Microduplication [39]

FOXE1 9q22 Thyroid dysgenesis AD, AR [24]

GDF5 20q11.2 Brachydactyly A1, A2, C AD [47, 48, 80]

GH1 17q24.2 Isolated GHD, type 1A; IB; II; Kowarski syndrome AR; AR; AD; AD [50, 81]

GHR 5p13-p12 Laron syndrome AR (AD) [82-84]

GHRHR 7p14 Isolated GHD, type IB AR [50, 81]

GHSR 3q26.31 Isolated partial GHD AR, AD [85, 86]

GINS2 16q24.1 Chromosome 16q24 microduplication Microduplication [39]

GLB1 3p21.33 Generalised gangliosidosis type 1 AR [39]

GLI2 2q14 Holoprosencephaly AD [87, 88]

GLI3 7p13 Pallister-Hall syndrome AD [39, 88]

GNAS 20q13.3 Albright hereditary osteodystrophy Imprinted [89]

GNPTAB 12q23.2 Mucolipidosis II alpha/beta (I-cell disease) AR [39]

H19 11p15.5 Associated with high birth weight Imprinted [90, 91]

HDAC8 Xq13 Cornelia de Lange syndrome XLR [39]

202 Supplements



HESX1 3p14.3 Septo-optic dysplasia ( Combined pituitary hormone deficiency 5)

AR, AD [74, 87, 88]

HMGA2 12q15 Pallister-Hall syndrome AD [50, 92]

HNRNPU 1q44 Chromosome 1q44 microdeletion Microdeletion [39]

HOXD 2q31.1 Chromosome 2q31 microdeletion Microdeletion [39]

HRAS 11p15.5 Costello syndrome AD [49]

IDUA 4p16.3 Hurler syndrome AR [93]

IFT172 2p23.3 Almstrom syndrome AR [94]

IGF1 12q23.2 IGF1 deficiency AR [95]

IGF1R 15q26.3 Resistance to insulin-like growth factor 1 AD, AR [39, 96]

IGF2 11p15.5 Severe growth restriction with distinctive facies Paternal [97]

IGF2R 6q26 Associated with high birth weight [90, 98]

IGFALS 16p13.3 ALS deficiency AR [99]

IGSF1 Xq25 IGSF1 deficiency syndrome XLR [100]

IHH 2q33-q35 Acrocapitofemoral dysplasia AR [101]

IKBKB 8p11.2 Immunodeficiency 15 AR, AD [102]

IL2RG Xq13.1 X-linked severe combined immunodeficiency XLR [103, 104]

INPPL1 11q13 Opsismodysplasia AR [39]

INSR 19p13.3-p13.2 Donohue syndrome AR [39]

ITSN1 21q22.1-q22.2 Chromosome 21q22.11 microdeletion Microdeletion [39]

IYD 6q25.1 Thyroid dyshormonogenesis AR [24]

KANSL1 17q21.31 Chromosome 17q21.31 microdeletion Microdeletion [39]

KCNJ11 11p15.1 Transient neonatal diabetes mellitus type 3 AD [39]

KDM6A Xp11.2 Kabuki syndrome AD [105]

GSE1 16q24.1 Chromosome 16q24 microduplication Microduplication [39]

KMT2A 11q23 Wiedemann-Steiner syndrome AD [39]

KMT2D 12q13.12 Kabuki syndrome 1 AD [105]

KRAS 12p12.1 Noonan syndrome AD [49, 106, 107]

LEKR1 3q25.31 Associated with high birth weight [41]

LEMD3 12q14 Chromosome 12q14 microdeletion Microdeletion [39]

LHX3 9q34.3 Combined pituitary hormone deficiency 3 AR [87, 88, 108]

LHX4 1q25.2 Combined pituitary hormone deficiency 4 AD, AR [87, 88, 108]

LIG4 13q33-q34 Defective nonhomologous endjoining DNA damage repair

AR [109]

LIS1 17p13.3 Miller-Dieker lissencephaly syndrome Microdeletion [39]




LMNA 1q22 Hutchinson–Gilford progeria syndrome AD [110]

MATN3 2p24-p23 Multiple epiphyseal dysplasia AD [111]

MC2R 18p11.2 Familial glucocorticoid deficiency (tall stature) AR [24]

MCM4 8q11.2 Natural killer cell and glucocorticoid deficiency with DNA repair defect

AR [112, 113]

MCM9 6q22.31 Ovarian dysgenesis 4 AR [114]

MCPH1 8p23.1 Primary microcephaly 1 AR [39]

MECP2 Xq28 Rett syndrome XLD [115]

MEF2C 5q14.3 Chromosome 5q14.3 microdeletion Microdeletion [39]

NBS1 8q21 Nijmegen breakage syndrome AR [116]

NF1 17q11.2 Neurofibromatosis-Noonan syndrome; Neurofibromatosis type I

AD; AD [49, 117]

NHEJ1 2q35 Defective non-homologous endjoining (NHEJ) DNA damage repair

AR [44, 118]

NIN 14q22.1 Seckel syndrome AR [119]

NIPBL 5p13.2 Cornelia de Lange syndrome AD [120]

NKX2-1 14q13 Thyroid dysgenesis AD [24]

NKX2-5 5q34 Thyroid dysgenesis AD [24]

NPR2 9p21-p12 Acromesomelic dysplasia, Maroteaux type, (Dis)proportionate short stature

AR; AD [121, 122]

NRAS 1p13.2 Noonan syndrome AD [123]

NRXN1 2p16.3 Pitt-Hopkins-like syndrome AR [39]

NSUN2 5p15.31 Dubowitz-like syndrome AR [39]

OBSL1 2q35 Three-M syndrome AR [52]

ORC1 1p32 Meier–Gorlin syndrome 1 AR [39, 53]

ORC4 2q22-q23 Meier–Gorlin syndrome AR [53]

ORC6 16q12 Meier–Gorlin syndrome AR [53]

OTX2 14q22.3 Combined pituitary hormone deficiency 6 AD [74, 87, 88]

PAPPA2 1q25.2 ALS deficiency AR [124]

PAPSS2 10q24 Brachyolmia type 4 with mild epiphyseal and metaphyseal changes (spondyloepimetaphyseal dysplasia, Pakistani type)

AR [125, 126]

PAX6 11p13 Chromosome 11p13 microduplication Microduplication [39]

PAX8 2q13 Thyroid dysgenesis AD, AR [24]

PCNA 20pter-p12 Hypomorphic PCNA mutation AR [127]

204 Supplements



PCNT 21q22.3 Seckel Syndrome 4 AR [88, 128, 129]

PIK3R1 5q13.1 SHORT syndrome AD [130]

PITX2 4q25 Axenfeld–Rieger syndrome AD [87]

PKD2 4q22.1 Chromosome 4q21 microdeletion Microdeletion [39]

PLK4 4q28 Microcephaly and chorioretinopathy 2 AR [131]

PLOD3 7q22 Ehlers-Danlos syndrome AR [39]

POC1A 3p21.2 Primordial dwarfism, type Shaheen AR [39]

POLG 15q25 Alpers progressive infantile poliodystrophy AR [39]

POU1F1 3p11 Combined pituitary hormone deficiency 1 AR, AD [87, 88, 108]

PQBP1 Xp11.23 Sutherland-Haan syndrome XLR [39]

PRKAR1A 17q24.2 Acrodysostosis AD [132]

PRKDC 8q11 Defective nonhomologous endjoining DNA damage repair

AR [44, 133]

PROKR2 20p12.3 Pallister–Hall syndrome AD [76]

PROP1 5q35.3 Combined pituitary hormone deficiency 1 AR [87, 88, 108]

PTF1A 10p12.2 Neonatal diabetes mellitus (cerebellar hypoplasia) AR [39]

PTHLH 12p12.1-p11.2 Brachydactyly, type E2 AD [134]

PTHR1 3p22-p21.1 Jansen type of meta-physeal chondrodys-plasia AD [135]

PTPN11 12q24 Noonan syndrome 1; LEOPARD syndrome AD [136, 137]

PYCR1 17q25.3 Cutis laxa AR [39]

RAD21 8q24 Cornelia de Lange syndrome AD [120]

RAF1 3p25 Noonan syndrome AD [136]

RASGEF1B 4q21.21 Chromosome 4q21 microdeletion Microdeletion [39]

RBBP8 18q11.2 Seckel syndrome AR [59]

RECQL4 8q24.3 Rothmund–Thomson syndrome AR [138]

RIT1 1q22 Noonan syndrome AD [139]

RMRP 9p13.3 Anauxetic dysplasia AR [39]

RNPC3 1p21 Almstrom syndrome AR [140]

ROR2 9q22 Robinow syndrome AR [141]

RPS6KA3 Xp22.2-p22.1 Coffin–Lowry syndrome XLR [142]

SLC39A13 11p11.2 Ehlers-Danlos syndrome, spondylocheiro dysplastic form

AR [39]




SEMA3E 7q21.11 CHARGE syndrome AD [60]

SHOX Xp22.33;Yp11.3 Langer mesomelic dysplasia; Leri–Weill dyschondrosteosis

AR; AD [143, 144]

SLC17A5 6q13 Sialic acid storage disease, severe infantile type AR [39]

SLC26A2 5q32 de la Chapelle syndrome (neonatal osseous dysplasia)

AR [39]

SLC26A4 7q31 Thyroid dyshormonogenesis AR [24]

SLC5A5 19p13.11 Thyroid dyshormonogenesis AR [24]

DHCR7 11q13.4 Smith-Lemli-Opitz syndrome AR [39]

SMAD4 18q21.1 Myhre syndrome AD [39]

SMARCA2 9p22.3 Nicolaides-Baraitser syndrome AD [145]

SMARCA4 19p13.2 Coffin–Siris syndrome AD [145]

SMARCAL1 2q35 Immunoosseous dysplasia, Schimke type AR [146]

SMARCB1 22q11.23; 22q11 Coffin–Siris syndrome AD [145]

SMC1A Xp11.22-p11.21 Cornelia de Lange syndrome XLR [120]

SMC3 10q25 Cornelia de Lange syndrome AD [120]

SOS1 2p21 Noonan syndrome AD [107]

SOX2 3q26.33 Optic nerve hypoplasia and abnormalities of the central nervous system

AD [74, 87]

SOX3 Xq27.1 X-linked panhypopituitarism; Isolated GHD, type III XLR; XLR [50, 74, 81, 87, 88]

SOX9 17q24.3 Campomelic dysplasia AD [147]

SPINK5 5q32 Netherton syndrome AR [148]

SPR 2p14-p12 Dopa-responsive dystonia due to sepiapterin reductase deficiency

AR [149]

SRCAP 16p11.2 Floating–Harbor syndrome AD [150, 151]

STAT3 17q21.31 Multisystem, infantile-onset autoimmune disease AD [152, 153]

STAT5B 17q11.2 GH insensitivity with immunodeficiency AR [154]

SYNPR 3p14.2 Chromosome 3p14.3 microdeletion Microdeletion [39]

TBCE 1q42.3 Kenny–Caffey syndrome AR [155]

TBX15 1p11.1 Cousin syndrome AR [39]

HNF1B 17q12 Chromosome 17q12 microdeletion Microdeletion [39]

TG 8q24 Thyroid dyshormonogenesis AR [24]

THRA 17q11.2 Thyroid hormone resistance AD [24]

THRB 3p24.2 Thyroid hormone resistance AD, AR [24]

206 Supplements



TINF2 14q12 Revesz syndrome (Coats plus syndrome) AR [39]

TMPO 12q22 Thyroid dyshormonogenesis AR [24]

TRIM37 17q23.2 Mulibrey nanism AR [156]

TRPV4 12q24.1 Spondyloepimetaphyseal dysplasia - type Maroteaux AD [39]

TSHR 14q31 Thyroid dysgenesis AR [24]

TUBGCP6 22q13.31-q13.33 Microcephaly and chorioretinopathy 1 AR [131]

RNU4ATAC 2q14.2 MOPD I AR [157]

WHSCR1-2 4p16.3 Wolf-Hirschhorn syndrome Microdeletion [39]

WNT4 1p36.23-p35.1 SERKAL syndrome AR [39]

WNT5A 3p21-p14 Robinow syndrome AD [141]

ERCC3 2q21 Trichothiodystrophy [39]

ERCC2 19q13.3 Trichothiodystrophy [39]

XRCC4 5q14.2 Defective nonhomologous endjoining DNA damage repair

AR [158]

ZEB2 2q22.3 Mowat-Wilson syndrome AD [39]


Supplemental Table 4. Differential Methylation in Genes Known to Be Aberrantly Methylated in Low Birth-

weight Newborns

Gene Chromosome (MapInfo) Control β-value(mean)

Case β-value(mean)

No. of probes


Hypermethylation

ANKRD11 16 (89461734-89462359) 0.25 0.51 4 Hypermethylated CpG island near ANKRD11 in Silver-Russel syndrome

APBA2 15 (29403333-29410508) 0.49 0.73 6 Hypermethylation associated with SGA or FGR

APOL1 22 (36648832-36649144) 0.19 0.47 4 Hypermethylation associated with SGA or FGR

BRCA1; NBR2

17 (41278135-41278655) 0.19 0.50 14 Hypermethylation associated with SGA or FGR

DLK1 14 (101196998-101201316) 0.39 0.64 6 Imprinted, highly expressed in the placenta, and associated with UPD14

INS; INS-IGF2

11 (2181866-2183824) 0.37 0.63 4 INS is an imprinted gene in the 11p15.5 region (geneimprint.com). INS-IGF2 involved in growth and metabolism

MEG3;MIR770

14 (101317620-101319526) 0.33 0.61 3

4

Imprinted, highly expressed in the placenta which is reduced in FGR

RTL1;MIR127;MIR136;MIR432;MIR433

14 (101348035-101350872) 0.50 0.76 4 RTL1 relevant to UPD14 phenotypes

WNT2 7 (116963193-116963500) 0.15 0.41 3 WNT2 promoter methylation in placenta is associated with low birthweight

Hypomethylation

DBP 19 (49133845-49134105) 0.47 0.23 2 Hypermethylation associated with SGA or FGR

FGF14 13 (102568345-102569815) 0.53 0.28 5 Hypomethylation associated with SGA or FGR

FOXP1 3 (71112437-71295684) 0.63 0.36 11 Hypermethylated in fetal growth restriction

GNAS;GNASAS

20 (57425515-57471672) 0.74 0.49 28 Hypomethylation of GNASAS associated with SGA. Decreased expression of GNAS observed in IUGR placentas

HOXB4 17 (46656664-46656690) 0.61 0.38 2 Hypermethylation associated with SGA or FGR

208 Supplements

Supplemental Table 4. Differential Methylation in Genes Known to Be Aberrantly Methylated in Low Birth-

weight Newborns (continued)

Gene Chromosome (MapInfo) Control β-value(mean)

Case β-value(mean)

No. of probes


IGF2AS; IGF2;INS-IGF2

11 (2162510-2163299) 0.53 0.28 5 IGF2 is imprinted and highly expressed in placenta, hypomethylation of H19/IGF2 control region is associated with FGR. INS-IGF2 involved in growth and metabolism. IGF2AS is imprinted and expressed in antisense to IGF2

KCNQ1;KCNQ1OT1

11 (2722440-2722713) 0.80

0.47 5 Upregulated KCNQ1 and loss of KCNQ1OT1 associated with IUGR; genetic variants of KCNQ1 associated with Beckwith-Wiedemann syndrome

MEST 7 (130124971-130126368) 0.55 0.31 4 Imprinted, highly expressed in the placenta, and associated with Silver -Russell syndrome

NNAT; BLCAP

20 (36148154-36151338) 0.77 0.50 28 Hypermethylation of NNAT in placenta associated with FGR

NPR3 5 (32711429-32714525) 0.39 0.17 5 Hypermethylation associated with FGR

NSD1 5 (176558909-176559563) 0.76 0.47 4 Loss of function associated with overgrowth (Sotos syndrome)

PLAGL1;HYMAI

6 (144329887-144386528) 0.72 0.46 10 Imprinted, highly expressed in placenta, associated with SGA

PEG10;SGCE

7 (94284258-94285501) 0.41 0.17 13 Imprinted gene highly expressed in the placenta. Differential expression between growth restricted and non-restricted placentas

SHC1 1 (154942566-154943932) 0.66 0.37 5 Hypomethylation in placenta associated with FGR

SLC25A18 22 (18063857-18064224) 0.80 0.52 5 Hypermethylation associated with SGA or FGR

TAL1 1 (47693873-47696701) 0.67 0.39 6 Hypermethylation associated with SGA or FGR

TBX15 1 (119521928-119532850) 0.65 0.30 27 Promotor hypomethylation leads to TBX15 decrease in FGR placentas

aFor references see Supplemental Table 1.


Supplemental Table 5. Differential Methylation and Sequence Variant in Genes Involved in (Regulation of )

DNA-Methylation in Patient SGA3

Gene Chr. (MapInfo) Control β-value(mean)

Case β-value(mean)

No. of probes

Main gene function(s) and influence(s) on DNA-methylationa

Methylation disturbances

Hypermethylated genes

APOBEC3A 22 (39353495-39354115) 0.37 0.63 3 Involved in epigenetic regulation of gene expression through DNA demethylation

BRCA1;NBR2

17 (41278135-41278655) 0.19 0.50 14 Regulator of DNA methylation

MAEL 1 (166958221-166958322) 0.32 0.66 5 Involved in DNA methylation in gamete generation

ZFP57 6 (29641443) 0.60 0.80 1 Zinc finger protein, may function as transcription repressor during early development. Associated with a heritable global imprinting disorder

Hypomethylated genes

ALKBH3 11 (43902134-43903042) 0.39 0.11 5 Dioxygenase that repairs alkylated DNA by demethylation

DNMT1 19 (10304766-10305911) 0.46 0.22 3 Methylates CpG residues, associated with DNA replication and maintaining methylation patterns

DNMT3A 2 (25499619-25500416) 0.72 0.39 4 Involved in genome-wide de novo methylation and in DNA methylation during development

FOS 14 (75746793-75747961) 0.81 0.41 4 May transform cells through alterations in DNA methylation

GNAS; GNASAS 20 (57425515-57471672) 0.74 0.49 28 Involved in DNA methylation

HIST1H4I; HIST1H2BK 6 (27106988-27107718) 0.53 0.25 8 Role in DNA methylation on cytosine

HIST1H3A 6 (26019832) 0.87 0.54 1 Role in DNA methylation on cytosine

MGMT 10 (131323986-131367623) 0.78 0.47 10 DNA methyltransferase, known to have significant fetal effects

TDRD1 10 (115939018-115939284) 0.83 0.52 3 Involved in DNA methylation at gamete generation

TET1 10 (70321668-70322874) 0.67 0.34 5 Key in active DNA demethylation

UHRF1 19 (4911058-4912006) 0.71 0.34 3 Key epigenetic regulator by bridging DNA methylation and chromatin modification

WES variant

Gene Position Alt. MAF SNP ID SIFT PolyPhen2 Main gene function(s) and influence(s) on DNA-methylationa

MPHOSPH8 13: 20224202 G>T 0.02 rs75390100 Deleterious Probably damaging

Binds methylated Lys-9 of histone H3 (H3K9me), promotes recruitment of proteins that mediate epigenetic repression (uniprot.org)

aFor references see Supplemental Table 2. Alt.=alteration; MAF=minor allele frequency (1000 Genome, ExAC); SNP=single nucleotide polymorphism; SIFT=Sorting Intolerant From Tolerant; PolyPhen2=Polymorphism Phenotyping 2

210 Supplements

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