See related commentary on pg 740 LETTERS TO THE EDITOR

Common Genetic Variants Influence Whorlsin Fingerprint Patterns

Journal of Investigative Dermatology (2016) 136, 859e862; doi:10.1016/j.jid.2015.10.062

TO THE EDITOREarlywork on dermatoglyphics identifiedthree major categories of fingerprintpatterns: arches, whorls, and loops,differentiated according to landmarkstructures formed by the triradii and core(Holt, 1968). These pattern formationsare determined by the ratio of volar padheight to width in utero (Mulvihill andSmith, 1969) influenced by genetic in-teractions with the intrauterine environ-ment (Penrose, 1968). Mathematicalmodels suggested for dermatoglyphicdevelopment include heterogeneousgenetic factors suggestive of a morpho-genetic field effect (Martin et al., 1982).Multivariate linkage analyses revealeda pattern of factor loadings for ridgecount that supported this argumentand found linkage to5q14.1drivenby theindex, middle, and ring fingers (Medlandet al., 2007a). A very high heritability(h2 ¼ 0.65e0.96) has been repor-ted for dermatoglyphic characteristics(Machado et al., 2010), suggesting a ge-netic basis for pattern type. Building onthese previous findings, the present studysought to identify genetic variants asso-ciated with fingerprint patterns on eachdigit using data from the QueenslandInstitute of Medical Research (QIMR)twin studies and from the Avon Longitu-dinal Study of Parents and Children(ALSPAC) birth cohort study (Boyd et al.,2013). Participants and their parents(where applicable) provided writteninformed consent, and ethical approvalwasobtained fromtheALSPACEthicsandLaw committee and the Local ResearchEthics Committees.

The QIMR cohort comprised 3,301participants from 1,764 families. Fin-gerprints were collected using rolledink prints on paper, and or usingan electronic rolled fingerprint

Abbreviations: ALSPAC, Avon Longitudinal Study ofassociation study; QIMR, Queensland Institute of Mepolymorphism

Accepted manuscript published online 18 November2016

ª 2015 The Authors. Published by Elsevier, Inc. on b

scanner (Smiths Heimann BiometricsACCO1394) (Medland et al., 2007b).Pattern intensity (the number of triradii)were then manually coded (by SEM andDZL). Within the ALSPAC cohort, 5,339individuals had genome-wide genotyp-ing and finger pattern information (thestudy website contains details of dataavailable through a fully searchabledata dictionary: http://www.bris.ac.uk/alspac/researchers/data-access/data-dictionary/). Pattern type for each digit wasscored and coded (by SEM) from photo-copies of the palmar surface of the hands(Medland et al., 2010). Any digit forwhich the fingerprint pattern was notclearly visible was coded as missing.Because the full patterns of the thumbswere not clearly visible, this digit fromexcluded from analyses. Intensity andridge count data were then recoded interms of presence or absence of whorlsand arches on each digit, with loops asthe reference category because they arethe most common pattern type. Archeswere not analyzed because of lowpattern frequency. For reference, thethumb on each hand was coded 1 andthe little finger as 5, and the right or lefthand was designated using the prefix Ror L. After quality control, 10 variableswere included in the study: presence ofwhorls across all digits (L1e5, R1e5) L1and R1were unavailable for the ALSPACcohort and L4, L5, R4, and R5 for theQIMR adult sample.

Both QIMR and ALSPAC sampleswere imputed using the Hapmap2r22.36 CEU reference. Single nucleo-tide polymorphisms (SNPs) that had aminor allele frequency >.01 and couldbe imputed with confidence (R2 > 0.3)were used in these analyses. Onlygenotyped SNPs were used for chro-mosome X.

Parents and Children; GWAS, genome-widedical Research; SNP, single nucleotide

2015; corrected proof published online 3 February

ehalf of the Society for Investigative Dermatology.

Heritability estimates were obtainedfrom the QIMR data using OpenMX(Boker et al., 2012) (see SupplementaryTable S1 online). Principal componentsanalysis was performed with Varimaxrotation to investigate latent factorswithin phenotypes after orthogonaltransformation of correlations. Resultsshowed three underlying componentsof pattern type: whorls on the middlethree fingers (digits 2, 3, and 4) on bothhands, whorls on the thumbs (digit 1),and whorls on the little fingers (digit 5)(see Supplementary Table S2 online).

Genome-wide analyses were con-ducted using merlin-offline (QIMR) orMach2dat (ALSPAC) (Abecasis et al.,2002), for each digit in each cohort andcombined using Stouffer’s Z scoremethod in METAL to calculate meta-analytic P-values (Willer and Abecasis,2010). There was no evidence ofsystematic inflation in the QIMR(l ¼ 1.004e1.027) or ALSPAC(l ¼ 1.007e1.034) results (seeSupplementary Figures S1eS3 online).Several genome-wide significant SNPswere found (P < 5 � 10e8). UnivariateGWAS for the QIMR sample yieldedgenome-wide significant P-values forrs1523452 (P ¼ 7.12 � 10e9) and foradjacent SNPs rs 2244503 (P ¼ 1.52 �10e8), rs796973 (P ¼ 5.47 � 10e8), andrs17071864 (P ¼ 5.42 � 10e8) for theWL5 phenotype (see SupplementaryTable S3 online). These were indepen-dently replicated in the ALSPAC sample(rs1523452, P ¼ 1.60 � 10e20;rs2244503, P¼ 3.76� 10e19; rs796973,P ¼ 2.15 � 10e20; rs17071864, P ¼5.68 � 10e20) and are encompassedby a single gene ADAMTS9-AS2 (seeSupplementary Figure S4 online). Thesesignals were strengthened in meta-analysis (Figure 1). SNPs within a 2-kbpintergenic region downstream of TBX3and upstream of MED13L within chr12were also genome-wide significant forWL4 and WR4, peaking at rs1863718(P ¼ 8.04 � 10e9 and 1.36 � 10e8,respectively), and a variant within theOLA1 gene region was significant for

www.jidonline.org 859

Figure 1. Manhattan plots for meta-analysis results. rs1523452 within the ADAMTS9-AS2 gene region presented the strongest signal for phenotypes WL5

(P ¼ 9.74 � 10e27) and WR5 (P ¼ 7.62 � 10e15), accounting for 1.61% and 0.93% of the variance. rs1523452 also influences WL4 (P ¼ 2.16 � 10e21), WR4

(P ¼ 1.33 � 10e17), and WR2 (P ¼ 3.08 � 10e10), attenuating at WL2 (P ¼ 9.24 � 10e6) and further reduced for WL1 (P ¼ 2.66 � 10e5) and WR1 (P ¼ 0.0001).

YYW Ho et al.Variant Influence on Whorls

Journal of Investigative Dermatology (2016), Volume 136860

Figure 2. Histograms of meta-analyses results. (a) elog10 (P-values) and (b) percent variation explained

by rs1523452 (within the ADAMTS9-AS2 gene region) across digits, obtained by Z2 /(N-2 þ Z2). (c) Trait

frequency as a function of allelic variation. Frequency of whorls on the left little finger (WL5; blue bars) and

right little finger (WR5; red bars) as a function of the genotype rs1523452 in a sample of unrelated

individuals from the QIMR1 cohort (n[AA] ¼ 708, n[AG] ¼ 335, n[GG] ¼ 49). With more G alleles, the

proportion of whorls increases. Vertical bars correspond to the 95% confidence intervals on prevalence.

YYW Ho et al.Variant Influence on Whorls

WL2 (rs10201863, P ¼ 3.46 � 10e8). Tofurther explore variants at the genelevel, gene-based tests were conductedusing GATES procedure in KGG2.5 (seeSupplementary Table S4 online) (Li et al.,2011).

ADAMTS9-AS2 and OLA1 are docu-mented oncogenes down-regulated inglioma (Yao et al., 2014). They are alsoinvolved in the inhibition of in vitro cellmigration of breast cancer cell lines(Zhang et al., 2009). The associationsobserved on chromosome 12 between113904923 and 113903069 bp arelocated in an intergenic region close

to TBX3, which is a known cause ofulnar mammary syndrome. This findingconcurs with previous literature thatlimb development in utero influencessubsequent fingerprint patterns thatemerge (Mulvihill and Smith, 1969).

ADAMTS9-AS2 is an antisense RNAlocated at 3p14.1, which may be anmRNA inhibitor for the adjacent geneADAMTS9. Although there is no directexplanation for the role of ADAMTS9-AS2 in the development of whorls onthe little fingers, RNA sequencing showshigh expression in reproductive organsas well as in the colon and lungs,

suggesting it may be influential in earlyorgan development. ADAMTS9 andOLA1 are also expressed in low tomedium levels in the skin. Interestingly,variants in ADAMTS9-AS2 appear toinfluence whorls on all digits to differinglevels (Figure 2a and b) consistent withthe hypothesis of a morphogenic field.Allele frequencies at this variant showthat the G allele was associated with ahigher incidence of whorls (Figure 2c).

Although this study did not finddirect evidence for the effects of singlegenetic variants on specific fingerprintpattern phenotypes, variants withinADAMTS9-AS2 show a gradient influ-ence on whorls across all digits.

CONFLICT OF INTERESTThe authors state no conflict of interest.

ACKNOWLEDGMENTSQIMR: This work was funded by the AustralianResearch Council (ARC), the Australian NationalHealth and Medical Research Council (NHMRC),Visigen, Identitas Inc., the Australian Federal PoliceForensics, and the Victorian Police Forensic Ser-vices Centre. We are grateful to the families whoparticipated in our studies, from theQIMRBrisbaneAdolescent Twin Study, the adult twins in theQIMRSSAGA study, and the ALSPAC group in Bristol. Weextend special thanks to the ALSPAC researchers forgenerating and sharing their genome-wide associ-ation results. ALSPAC: We are extremely grateful toall the families that took part in this study, themidwives for their help in recruiting the families,and the whole ALSPAC team, which includes in-terviewers, computer and laboratory technicians,clerical workers, research scientists, volunteers,managers, receptionists, and nurses. GWAS datawere generated by Sample Logistics and Genotyp-ing Facilities at the Wellcome Trust Sanger Instituteand LabCorp (Laboratory Corporation of America)using support from 23andMe. The UK MedicalResearch Council and the Wellcome Trust (grantreference 102215/2/13/2) and the University ofBristol provide core support for ALSPAC. Thispublication is the work of the authors, and DMEwill serve as guarantor for the contents of this paper.This work was supported by the Medical ResearchCouncil MC_UU_12013/4 to DME andMC_UU_12013/3 to NJT. DME is funded by anAustralian Research Council Future Fellowship(FT130101709). In memory of Bodgan Mdzewski,who contributed significantly to counting QIMRfingerprint intensity scores. Study carried out inBrisbane, Queensland, Australia, and Bristol, UK.

Yvonne Y.W. Ho1,2,*

David M. Evans3,4,*,Grant W. Montgomery1,Anjali K. Henders1, John P. Kemp3,4,Nicholas J. Timpson3

Beate St. Pourcain5,6,Andrew C. Heath7,Pamela A.F. Madden7,Danuta Z. Loesch8, Dennis McNevin9,Runa Daniel10, George Davey-Smith3,

www.jidonline.org 861

K Buzas et al.C. Pneumoniae Increases Survival in Melanoma

862

Nicholas G. Martin1 andSarah E. Medland1

1QIMR Berghofer Medical Research Institute,Brisbane, Australia; 2School of Psychology,University of Queensland, Brisbane, Australia;3MRC Integrative Epidemiology Unit, School ofSocial and Community Medicine, University ofBristol, Bristol, UK; 4University of QueenslandDiamantina Institute, Translational ResearchInstitute, Brisbane, Australia; 5School of Social& Community Medicine, University of Bristol,Oakfield House, Oakfield Grove, Bristol, UK;6Max Planck Institute for Psycholinguistics,Nijmegen, The Netherlands; 7Department ofPsychiatry, Washington University, St. Louis,Missouri, USA; 8Department of Psychology, LaTrobe University, Melbourne, Australia;9National Centre for Forensic Studies, Facultyof Education, Science, Technology andMathematics, University of Canberra,Canberra, Australia; and 10Office of the ChiefForensic Scientist, Forensic ServicesDepartment, Victoria Police, Australia*Corresponding author e-mail: Yvonne.Ho@qimrberghofer.edu.au or d.evans1@uq.edu.au

SUPPLEMENTARY MATERIAL

Supplementary material is linked to the onlineversion of the paper at www.jidonline.org, and athttp://dx.doi.org/10.1016/j.jid.2015.10.062.

Abbreviations: BOLD, bleomycin, oncovin, lomustinChlamydophila pneumoniae; LM, lung metastasis

Accepted manuscript published online 29 DecemFebruary 2016

ª 2015 The Authors. Published by Elsevier, Inc. on b

Journal of Investigative Dermatology (2016), Volum

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Bacterial Sepsis Increases Survival inMetastatic Melanoma: ChlamydophilaPneumoniae Induces MacrophagePolarization and Tumor Regression

Journal of Investigative Dermatology (2016) 136, 862e865; doi:10.1016/j.jid.2015.12.032

TO THE EDITORThe initiative of this study was the un-expected complete tumor regressionin a patient with stage IV cutaneousmetastatic melanoma, who sufferedmultifactorial sepsis syndrome duringBOLD (bleomycin, oncovin, lomustine,and dacarbazine) chemotherapy (seeSupplementary Figure S1 online).After targeted antibiotic treatment andcombined complication-free chemo-therapy, the patient’s physical con-dition improved, and the metastases

unexpectedly disappeared. The patienthas been asymptomatic and metastasis-free since the end of BOLD therapy. Asignificant decrease in the volume ofthe previously palpable axillary andabdominal metastases had alreadybeen observed when BOLD therapywas interrupted because of sepsis. Atimeline of events is given in Table 1.

Molecular genetics research in thelast decade assisted in the developmentof BRAF inhibitors and immuno-oncological agents, which resulted in

significant improvement in the lifeexpectancy of melanoma patients.Dacarbazine-based chemotherapies,once the gold standard (Hobohm,2001; Wiemann and Starnes, 1994),are still approved and widely applied inmelanoma therapy, but their efficacy isrelatively low (Garbe et al., 2011).Therefore, the fact that clinicalimprovement was observed quite earlyduring the chemotherapy suggestedother factors behind the outcome, andthe concurrent sepsis seemed to offer apotential explanation.

It has long been recognized thatcancer patients might recover afterbacterial infections (Hobohm, 2001).The hypothesis was that fever and tu-mor necrosis factor-a induced by the