lack of evidence of a major gene acting on postaxial polydactyly in south america

Lack of Evidence of a Major Gene Acting onPostaxial Polydactyly in South America

Mary F. Feitosa,1* Eduardo E. Castilla,1,2 Maria da Graca Dutra,1 and Henrique Krieger3

1Departamento de Genetica, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil2Centro de Educacion Medica e Investigaciones Clınicas: CEMIC, Buenos Aires, Argentina3Departamento de Parasitologia, Universidade de Sao Paulo, Sao Paulo, Brazil

Data on polydactyly were obtained from twolarge samples: the Latin American Collabo-rative Study of Congenital Malformations(ECLAMC), and from a migrant Northeast-ern Brazilian population of rural origin(Hospedaria). ECLAMC is a case-controlclinical epidemiological program compris-ing 10,035 individuals distributed among2,030 segregating nuclear families. Hospe-daria data consisted of 6,586 examined indi-viduals belonging to 1,040 nuclear families.Using complex segregation analysis meth-odology we found no evidence of two loci (amajor gene and a modifier locus) acting onpostaxial polydactyly in the present study.Very high heritability values (in a classicalmultifactorial model) of postaxial polydac-tyly were detected, for several sets of analy-ses in ECLAMC and in Hospedaria. For thewhole ECLAMC sample there is a peculiarsuggestion of a major recessive gene effectresponsible for the trait; however, no com-parison with a model involving transmis-sion probabilities (t) was possible in thishighly heterogeneous sample. If the wholeECLAMC sample is divided in subsamples,according to Black admixture proportions,the same multifactorial picture emerges.Two different inheritance patterns wereverified for hand (HP) and foot (FP) post-axial polydactyly: For HP there is evidenceof a non-Mendelian transmission mecha-nism, while for FP the parental/sib trans-mission appears to be due only to multifac-

torial causes. Am. J. Med. Genet. 80:466–472,1998. © 1998 Wiley-Liss, Inc.

KEY WORDS: segregation analysis; geneticepidemiology; polydactyly

INTRODUCTION

The basic dysmorphogenesis leading to the formationof extra digits seems to be similar among mammals,and the existence of genetic homologies between poly-dactylies in mouse and humans has been proposed[Winter, 1988]. Furthermore, from the oligogenicmechanism in Wright’ s [1934] classic work with poly-dactylous guinea pigs, to the effect of cytotoxic agentsproducing tissue excess and subsequent extra digits ingenetically susceptible rodents [Bynum, 1991], it isgenerally accepted that non-syndromal postaxial poly-dactyly is not a pure Mendelian trait in mammals.

Postaxial polydactyly has been recognized as a he-reditary malformation in humans, and it has been de-scribed as a dominant trait [Radhakrishna et al., 1997]with low penetrance and variable expressivity [Castillaet al., 1973]. Even though this malformation did not fitinto the multifactorial model [Castilla et al., 1992], itwas also postulated that it is an oligogenic trait, withat least four loci involved [Paz et al., 1976], similar topolydactyly in guinea pigs [Wright, 1934].

The world distribution of polydactyly shows that it isabout 10 times more frequent in Blacks than in Cau-casians [Frazier, 1960; Altemus and Ferguson, 1965].In Nigeria, Scott-Emuakpor and Madueke [1976] foundprevalences of 17.92 and 27.08 per thousand for fe-males and males, respectively. These authors con-cluded that the malformation is an autosomal domi-nant trait with penetrance of 64.9%, and they could notfind phenotypic difference between homozygotes andheterozygotes.

Segregation distortion in the offspring of Afro-American fathers with postaxial polydactyly was inter-preted as the effect of a sex-linked recessive modifiergene acting during gametogenesis on an autosomaldominant polydactyly gene, and the modifier gene be-ing more frequent in Africans [Orioli, 1995].

Radhakrishna et al. [1997] showed linkage between

Contract grant sponsor: Conselho Nacional de Desenvolvim-ento Cientıfico e Tecnologico (CNPq) of Brazil; Contract grantsponsor: Fundacao de Amparo a Pesquisa do Estado de Sao Paulo(FAPESP) of Brazil; Contract grant sponsor: Consejo Nacional deInvestigaciones Cientificas y Tecnicas (CONICET) of Argentina.

*Correspondence to: Dr. Mary Furlan Feitosa, Departamentode Genetica, Instituto Oswaldo Cruz, FIOCRUZ, Av. Brasil, 4365,CEP: 21045-080; Rio de Janeiro, RJ, Brasil. E-mail: [email protected]

Received 30 March 1998; Accepted 19 May 1998

American Journal of Medical Genetics 80:466–472 (1998)

© 1998 Wiley-Liss, Inc.

the phenotype of postaxial polydactyly type A andmarkers on chromosome region 7p15-q11.23 in a five-generation Indian family. Within the postaxial poly-dactylies (ulnar/fibular), type A refers to a well-formed,articulated extra digit, while type B is an incomplete,unarticulated, non-functional extra digit, also knownas ‘‘post-minimus’’ [Temtamy and McKusick, 1978;Winter and Tickle, 1993; McKusick, 1996]. However,most of the times, the phenotypic distinction betweentypes A and B is not clear. The presence of both typesin different members of a given family [Scott-Emuakpor and Madueke, 1976; Ventruto et al., 1980;Kucheria et al., 1981], and in different limbs from thesame individual [Ventruto et al., 1980; Kucheria et al.,1981], were reported several times. Therefore, whenworking with populational rather than single familymaterial, it is reasonable not to subdivide postaxialpolydactyly in types A and B. Hand (HP) and foot (FP)postaxial polydactyly have been regarded as a uniquesingle trait [Castilla et al., 1973; McKusick, 1996]. Nev-ertheless, Castilla et al. [1997] found different clinicaland epidemiologic characteristics for both of them.Consequently, the mechanism of polydactyly transmis-sion, environmental and genetic (if existent), could bedisguised due to its causal heterogeneity.

The aim of the present study is to investigate thepresence of genetic factors that may operate on thetransmission of postaxial polydactyly, in two largesamples from South America. Hand, foot, and both(hand and foot) polydactylies were investigated bymeans of complex segregation analyses [Lalouel et al.,1983; Morton et al., 1991].

MATERIAL AND METHODSSamples

Data on polydactyly were obtained from twosamples: Latin American Collaborative Study of Con-genital Malformations (ECLAMC), and from a migrantNortheastern Brazilian population of rural origin(Hospedaria).

ECLAMC is a case-control clinical and epidemiologi-cal program of congenital malformations [cf. Castillaand Orioli, 1983]. Just cases with postaxial polydactylyas the only defect (fifth-digit duplication) were ac-cepted [cf. Castilla et al., 1996], and considered as pro-bands in a body of incomplete ascertainment data. Thissample involves nine South-American countries (Ar-gentina, Brazil, Bolivia, Chile, Colombia, Ecuador,Peru, Uruguay, and Venezuela), including 64 partici-pating maternity hospitals during the period of 1967–1992, comprising 2,933 affected individuals distributedamong 2,030 nuclear families. Table I shows the dis-tribution of polydactyly birth incidence by participat-ing country. Family history was taken by the pediatri-cians from the mothers of the affected infant (proband).Ethnic origin information was collected since January1970, by asking the mother whether the baby had oneor more ancestors from each of the following eight cat-egories: Latin Europeans, non-Latin Europeans, Jews,‘‘Natives’’ (Indian with Latin-American European an-cestry), Arabians, Blacks, Orientals, and other. Eachfamily was assumed to belong to the same ethnic cat-

egory as the proband. For simplicity, the individualswere pooled together in just two groups: Black and non-Black.

Hospedaria data were collected during the period1962–1963 [Morton et al., 1965; Krieger et al., 1965].The medical examination was performed by only onephysician (Dr. Eliane Azevedo) on the total sample.The utilized sample consisted of 6,586 individuals be-longing to 1,040 nuclear families. The prevalenceamong examined individuals was 0.66%, of which 16%of the affected individuals had other associated malfor-mations [Mi et al., 1965].

Segregation Analysis

The computer programs POINTER [Lalouel et al.,1983] and COMDS [Morton et al., 1991] were used on aSUN Sparc Station 10 computer running on the UNIXoperating system.

POINTER

This analysis was performed using the unified model[Lalouel et al., 1983], which incorporates the transmis-sion frequencies of Elston and Stewart [1971] into themixed model [Morton and MacLean, 1974]. The mixedmodel assumes an underlying liability scale to which amajor locus, a multifactorial component, and randomenvironment contribute independently. The major ef-fect results under a genetic hypothesis from segrega-tion at a single locus with two alleles (A and a), wheregenotypes are distributed in Hardy-Weinberg propor-tions. The frequency of the abnormal allele A is denotedby q. The distance between the two homozygous geno-type class means is represented by t, referred to asdisplacement. The position of the heterozygous geno-type mean relative to the means of the two homozygousgenotypes is represented by d, the degree of domi-nance. Variation around each major genotype mean isassumed to be normally distributed, with common vari-ance, C + E. C is the variance due to multifactorialtransmissible effects and E is the residual environmen-tal variance component that is not transmitted withinfamilies. The total phenotypic variance is denoted V.The ratio C/V is H, the heritability, which reflectspolygenic transmission. Additional parameters, tAA,tAa, taa, can be estimated to test deviations from Men-delian transmission of the major effect from parent tooffspring, and denote the probabilities of transmitting

TABLE I. Distribution of Postaxial Polydactyly BirthPrevalence by Country

Country Probands Total birthBirth prevalence

(0⁄000)

Venezuela 703 325,969 2.157Brazil 508 603,929 0.841Bolivia 33 48,777 0.677Argentina 512 1,060,024 0.483Colombia 24 56,245 0.427Ecuador 45 108,180 0.416Chile 125 322,031 0.388Uruguay 66 189,365 0.349Peru 14 90,357 0.155Total 2,030 2,804,877 0.723

Postaxial Polydactyly 467

allele A for genotypes AA, Aa, and aa, respectively.Different hypotheses were tested by estimating or fix-ing parameters of the complete model. Comparisons ofnested models were made by taking x2 distribution.Alternatively, the Akaike Information Criterion (AIC)[Akaike, 1974] was used to compare the likelihood ofnonnested models. AIC is defined as −2lnL plus twicethe number of estimated parameters, and the lowestAIC value is considered the best model.

COMDS

For monogenic inheritance and a simple phenotype(affected or normal), the POINTER and COMDS mod-els give identical parameter estimates as well as −2lnL.However, the COMDS program also implements a two-locus model [MacLean et al., 1984; Morton et al., 1991].Transmissible effects not attributable to the majorgene are assigned to a second (modifier) locus, withparameters qm, tm, and dm, which are analogous, re-spectively, to q, t, and d, described above.

Segregation analysis was applied to the followingbodies of data:

1. Total ECLAMC data were considered since 1970,presenting 9,690 individuals distributed in 1,957 fami-lies, only one class of liability (li) 4 0.13% [Castilla etal., 1996] and ascertainment probability (p) 4 0.3, inview of its size and data consistency with incompleteselection (using p below this value, the models ren-dered negative likelihood ratios).

2. Black sub-sample of ECLAMC data having 3,963individuals belonging to 742 families, li 4 2.2% (ac-cording to the average value of Nigeria’s prevalence, cf.Scott-Emuakpor and Madueke, 1976] and p 4 0.3.

3. Hand polydactyly (HP) sub-sample of ECLAMCdata with 7,534 individuals and 1,511 families, li 40.11% [Castilla et al., 1997] and p 4 0.3.

4. Foot polydactyly (FP) sub-sample of ECLAMCdata with 1,499 individuals belonging to 309 families, li4 0.02% [Castilla et al., 1997] and p 4 0.4.

5. Hospedaria data having 6,586 individuals distrib-uted within 1,040 families, li 4 0.66%, p 4 1 (completeascertainment).

RESULTSThe tables of segregation analyses are arranged in

three parts. The first part shows results obtained onlyby POINTER (Mendelian mixed, no major gene, spo-radic and involving ts models). The second part showsresults involving just single-loci models, that are com-mon for both, POINTER and COMDS. The third partdisplays the two-locus models, a major gene with eithera pseudopolygenic component or a modifier locus, ana-lyzed by COMDS.

Table II shows the results of segregation analysis forthe total ECLAMC sample. Compared to the Mende-lian mixed (1), a model ignoring familial resemblance(3) was rejected (3 vs. 1: x2

4 4 3041.37, P <0.001). Themodel with no major effect (2) did not converge whenthe usual iterative procedure was utilized. Therefore, agradient of fixed values of H was used and the modelthat provided the smallest value of −2lnL was taken asthe minimum chi-square estimator. As can be seen,using this approach the models with no major effect (2)or without a multifactorial component were rejected (2vs. 1: x2

3 4 83.02, P <0.001; 4 vs. 1: x21 4 85.02, P

<0.001, respectively). Compared to the general two-locus model (8), the general single-locus model (4) wasrejected (4 vs. 8: x2

3 4 14.20, P 4 0.003). Despite thefact that two-locus model (8) is consistent with thedata, the AIC criterion identifies the Mendelian mixed(1) as the best model. Nevertheless, the models includ-ing the estimation of the transmission probabilities (ts)did not reach convergence. Consequently, there is noevidence to suggest unique genetic determinants forpostaxial polydactyly in the total ECLAMC sample.Similar results (not shown) were obtained when segre-gation analysis was applied using different sex depen-dent liabilities.

TABLE II. Segregation Analyses of Postaxial Polydactyly*

POINTER

Model d t q H tAA tAa taa −2lnL AIC

1. Mendelian mixed 0.001 3.583 0.196 0.459 [1] [1/2] [0] 510.71 518.712. No major gene [0] [0] [0] 0.990b — — — 593.73 595.733. Sporadic [0] [0] [0] [0] — — — 3552.08 3552.08

POINTER/COMDS

Model d t q −2lnL AIC

4. No multifactorial 0.200 3.798 0.027 595.73 601.735. Recessive Mendelian [0] 3.345 0.031 611.18 615.186. Codominant Mendelian [0.5] 5.026 0.026 615.11 619.117. Dominant Mendelian [1] 3.056 0.001 639.61 643.61

COMDS

Model d t q dm tm qm −2lnL AIC

8. 2 loci 0.0a 2.633 0.041 0.000 8.910 0.015 581.53 593.539. (d 4 0, dm 4 0.5) [0] 3.345 0.031 [0.5] 0.641 0.0a 611.18 619.1810. (d 4 0.5, dm 4 0.5) [0.5] 5.023 0.026 [0.5] 0.050 0.0a 615.11 623.1111. (d 4 1, dm 4 0.5) [1] 3.265 0.0a [0.5] 5.364 0.023 608.01 616.01

*ECLAMC Data; p 4 0.3; Class of Liability 4 0.13%; number of individuals 4 9,690; number of families 4 1957.aReached its bound.bH was fixed.

468 Feitosa et al.

Table III shows the results of segregation analysisfor the Black subsample of ECLAMC data. Comparedto the Mendelian mixed (1), a model ignoring familialresemblance (3) was rejected (3 vs. 1: x2

4 4 554.24, P<0.001). However, the ‘‘no major effect’’ model (2) wasnot rejected (2 vs. 1: x2

3 4 1.32, P 4 0.724), nor the notmultifactorial (5) one (5 vs. 1: x2

1 4 0.02, P 4 0.888).The free taus model (4) did not differ significantly fromthe Mendelian mixed model (1) (1 vs. 4: x2

3 4 4.61, P 40.203), and the non-transmission of the gene (equal ts)model did not converge. There was no evidence for asecond locus, the single locus model (5) was not rejectedwhen compared to the two-loci (9) (5 vs. 9: x2

3 4 0.0, P>0.99). Therefore, either a multifactorial mechanism

(2) or a major gene (5) alone could explain the variabil-ity of postaxial polydactyly. Nevertheless, the firstmodel (H 4 0.871 ± 0.030) is more acceptable since it ismore parsimonious and, also, it has the lower AIC.

Taking into account that hand postaxial polydactyly(HP) is more frequent than the foot abnormality (FP),and that the transmission pattern could be differentbetween them, we analyzed hands and feet, separately,using ECLAMC sample. For HP (Table IV), the modelsignoring familial resemblance (3) and with no majoreffect (2) (H 4 0.990, which provided the smallestvalue of −2lnL) were rejected (3 vs. 1: x2

4 4 2695.62, P<0.001; 2 vs. 1: x2

3 4 33.08, P <0.001, respectively).Also, the model without a multifactorial component (6)

TABLE III. Segregation Analyses of Postaxial Polydactyly*

POINTER


1. Mendelian mixed 0.145 5.789 0.069 0.020 [1] [1/2] [0] 615.92 623.922. No major gene [0] [0] [0] 0.871 — — — 617.24 619.243. Sporadic [0] [0] [0] [0] — — — 1170.16 1170.164. d, t, q, H, tAA, tAA, tAA 0.176 5.776 0.042 0.131 1.0a 0.372 0.0a 611.31 625.31

POINTER/COMDS


5. No multifactorial 0.145 6.000 0.072 615.94 621.946. Recessive Mendelian [0] 2.569 0.108 622.76 626.767. Condominant Mendelian [0.5] 3.311 0.093 632.69 636.698. Dominant Mendelian [1] 2.085 0.009 638.80 642.80

COMDS


9. 2 loci 0.144 6.019 0.072 0.495 2.115 0.0a 615.94 627.9410. (d 4 0, dm 4 0.5) [0] 2.569 0.108 [0.5] 2.135 0.0a 622.76 630.7611. (d 4 0.5, dm 4 0.5) [0.5] 3.311 0.093 [0.5] 1.800 0.0a 632.69 640.6912. (d 4 1, dm 4 0.5) [1] 2.085 0.009 [0.5] 1.013 0.0a 638.80 646.80

*Black subsample of ECLAMC data; p 4 0.3; class of liability 4 2.2%; number of individuals 4 3,963, number of families 4 742.aReached its bound

TABLE IV. Segregation Analyses of Hand Postaxial Polydactyly*

POINTER


1. Mendelian mixed 0.0a 3.456 0.029 0.553 [1] [1/2] [0] 625.43 633.432. No major gene [0] [0] [0] 0.990b — — — 658.51 660.513. Sporadic [0] [0] [0] [0] — — — 3321.05 3321.054. d, t, q, H, tAA, tAA, tAA* 0.0a 3.183 0.302 0.100 1.0a 0.0a 0.0a 544.54 558.545. d, t, q, H, tAA 4 tAA 4 tAA 0.0a 4.230 0.206 0.959 0.0a 0.0a 0.0a 602.77 612.77

POINTER/COMDS


6. No multifactorial 0.230 3.968 0.026 630.73 636.737. Recessive Mendelian [0] 3.343 0.032 651.02 655.028. Condominant Mendelian [0.5] 5.180 0.025 639.70 643.709. Dominant Mendelian [1] 3.144 0.0a 808.20 812.20

COMDS


10. 2 loci 0.105 2.683 0.042 0.0a 8.698 0.016 620.21 632.2111. (d 4 0, dm 4 0.5) [0] 3.343 0.032 [0.5] 1.235 0.0a 651.02 659.0212. (d 4 0.5, dm 4 0.5) [0.5] 0.0a 0.017 [0.5] 5.180 0.025 639.70 647.70

*ECLAMC data; p 4 0.3; class of liability 4 0.11%; number of individuals 4 7,534, number of families 4 1,511.aReached its bound.bH was fixed.


was rejected (6 vs. 1: x21 4 5.30, P 4 0.021). A two-

locus model combining a single major gene with a modi-fier component (10) provided a significantly better fit tothe data than did a single-locus model alone (6) (6 vs.10: x2

3 4 10.52, P 4 0.015). However, the best modelincludes a multifactorial component with a furthertransmissible parameter that differs significantly fromthe Mendelian one (4 vs. 1: x2

3 4 80.89, P <0.001),while the equal transmission model (5) was rejected (5vs. 4: x2

2 4 58.23, P < 0.001).For FP (Table V), a model ignoring family resem-

blance (3) was rejected (3 vs. 1:x24 4 65.82, P <0.001).

However, the no major gene (2) and no multifactorial(6) models were not rejected (2 vs. 1: x2

3 4 1.33, P 4

0.722; 6 vs. 1: x21 4 0.02, P 4 0.888). The single-locus

model (6) was not significantly different from the two-locus model (10) (6 vs. 10: x2

3 4 0.04, P 4 0.998). Thefree taus (4) and the equal taus (5) models were notrejected (4 vs. 1: x2

3 4 0.20, P 4 0.978; 5 vs. 4: x22 4

0.62, P 4 0.733, respectively). The model having onlythe multifactorial component (2) (H 4 0.867 ± 0.057) ismore acceptable, since it is the most parsimonious andalso presents the lowest AIC value. Consequently, theresults suggest that there is no major genetic compo-nent acting on FP.

In the Hospedaria data (Table VI) neither the nomajor gene (2) nor the multifactorial (4) models wererejected (2 vs. 1: x2

3 4 0.34, P 4 0.952; 3 vs. 1: x21 4

TABLE V. Segregation Analyses of Foot Postaxial Polydactyly*

POINTER


1. Mendelian mixed 0.0a 2.462 0.038 0.008 [1] [1/2] [0] 10.21 18.212. No major gene [0] [0] [0] 0.867 — — — 11.54 13.543. Sporadic [0] [0] [0] [0] — — — 76.03 76.034. d, t, q, H, tAA, tAA, tAA 0.0a 5.881 0.087 0.223 1.0a 0.688 0.0a 10.01 24.015. d, t, q, H, tAA 4 tAA 4 tAA 0.0a 2.801 0.278 0.258 0.0a 0.0a 0.0a 10.63 20.63

POINTER/COMDS


6. No multifactorial 0.0a 2.555 0.038 10.23 16.237. Recessive Mendelian [0] 2.555 0.038 10.23 14.238. Codominant Mendelian [0.5] 4.760 0.054 10.33 14.339. Dominant Mendelian [1] 5.337 0.003 11.13 15.13

COMDS


10. 2 loci 0.246 0.664 0.0a 0.0a 2.554 0.038 10.19 22.1911. (d 4 0, dm 4 0.5) [0] 1.725 0.103 [0.5] 2.857 0.377 10.19 18.1912. (d 4 0.5, dm 4 0.5) [0.5] 0.425 0.003 [0.5] 5.980 0.058 10.21 18.2113. (d 4 1, dm 4 0.5) [1] 2.054 0.062 [0.5] 3.206 0.121 10.42 18.42

*ECLAMC data; p 4 0.4; class of liability 4 0.02%; number of individuals 4 1,499, number of families 4 309.aReached its bound.

TABLE VI. Segregation Analyses of Postaxial Polydactyly*

POINTER


1. Mendelian mixed 1.0a 2.734 0.004 0.920b [1] [1/2] [0] 264.69 272.692. No major gene [0] [0] [0] 0.920b — — — 265.03 267.033. Sporadic [0] [0] [0] [0] — — — 340.56 340.56

POINTER/COMDS


4. No multifactorial 0.922 2.909 0.005 267.91 273.915. Recessive Mendelian [0] 4.760 0.118 279.32 283.326. Codominant Mendelian [0.5] 5.360 0.005 267.93 271.937. Dominant Mendelian [1] 2.681 0.005 267.91 271.91

COMDS


8. 2 loci 0.0a 0.0a 0.202 1.0a 2.681 0.005 267.91 279.919. (d 4 0, dm 4 0.5) [0] 0.0a 0.012 [0.5] 5.360 0.005 267.93 275.9310. (d 4 0.5, dm 4 0.5) [0.5] 0.0a 0.037 [0.5] 5.360 0.005 267.93 275.9311. (d 4 1, dm 4 0.5) [1] 0.0a 0.005 [0.5] 5.350 0.005 267.91 275.91

*Hospedaria data; p 4 1.0; class of liability 4 0.66%; number of individuals 4 6,586, number of families 4 1,040.aReached its bound.bH was fixed.

470 Feitosa et al.

3.22, P 4 0.073, respectively). There was no evidencefor a second locus (4 vs. 8: x2

3 4 0.0, P >0.99). Unfor-tunately the models that estimate the transmissionprobabilities did not reach convergence. Therefore, itwas not possible to verify whether the multifactorialcomponent or the major gene (or both, of course) arenecessary to explain the significant familial aggrega-tion. However, AIC criterion suggests that the multi-factorial component model is the best model.

DISCUSSION

The distribution of the birth prevalence of postaxialpolydactyly by Latin American countries (Table I)showed that Venezuela (2.16/1,000), and Brazil (0.84/1,000) presented the highest values. This is likely dueto the fact that the proportion of Black admixture ishigher in these subsamples than those of the otherECLAMC participant countries [Lopez-Camelo andOrioli, 1996], while it is well known that the prevalenceof postaxial polydactyly is significantly higher amongAfricans [Frazier, 1960].

High heritability of postaxial polydactyly is detected,either for all set of analyses in ECLAMC as well as inHospedaria, which have distinct ways of ascertainment(incomplete and complete selections, respectively). Themixed model of segregation analysis was in many in-stances not powerful enough to handle this type of fa-milial aggregation, even using different classes of li-abilities. Most models involving taus did not reachedconvergence, and those that converge led, usually, totau values completely different from those expected bygenetic theory. The presence of an autosomal dominantgene exhibiting or not variable expressivity of pen-etrance has been suggested earlier [Walker, 1961; Cas-tilla et al., 1973; Scott-Emuakpor and Madueke, 1976;Orioli, 1995], and it is generally accepted in humangenetics [McKusick, 1996]. However, this proposition isnot supported here, and the estimated penetrances inthose studies were relatively small (below 0.70) indi-cating that no clear simple genetic mechanism could beattached to the trait, since the signal/noise ratio israther low.

No evidence of a major gene and a modifier locusacting on postaxial polydactyly was observed for post-axial polydactyly in the present study. However, Orioli[1995] suggested that the segregation distortion ob-served among the offspring of affected Black fatherscould be interpreted as the effect of a sex-linked reces-sive modifier gene acting during gametogenesis on anautosomal dominant polydactyly gene.

The multifactorial hypothesis is more acceptable,due both to parsimony and by the AIC criterion, for theBlack and FP sub-samples of ECLAMC, and the Hospe-daria data. In HP, a non-Mendelian transmissionmodel is suggested. Unfortunately, in the totalECLAMC sample, the model that includes alternativetransmission probabilities (using equal and free ts) didnot reach convergence, making conclusions impossible.Nevertheless, one should keep in mind that the totalECLAMC sample is heterogeneous due to origin in sev-eral places and countries, involving different racialcompositions, therefore implying the requirement of

more restricted analyses, based on more homogeneoussamples, as was conducted here.

Different sources of diagnostic error could still affectthe present data, namely:

1. Under-ascertainment of affected individuals (pro-band and relatives) due to spontaneous in utero ped-icle torsion, followed by aseptic necrosis and intra-amniotic reabsorption, leaving either a subtle skinscar or only an extra d triradius in palm dermato-glyphs [Nishimura, 1974].

2. Under-ascertainment of affected relatives, mainlyon the paternal family side, due to neonatal removalof a pedunculated skin tag on the ulnar/fibular sideof the limb, unidentified as an extra digit.

3. Oversight of syndromal polydactyly cases mainly inthe perinatal ECLAMC series.

Considering that the presence of polydactyly in thesesamples could be underestimated when compared withthe frequencies shown by Scott-Emuakpor and Mad-ueke [1976], many other analyses based on severalclasses of liabilities (not described here) were per-formed (up to 10 times the liability values), withoutchanging, substantially, the general picture.

The ECLAMC data could present a limitation on fa-milial occurrence, since they are obtained only throughthe probands’ mothers. The presence of associated dis-orders (16%) in the Hospedaria data could obscure thetransmission of this malformation. Nevertheless, thesesamples are valuable for the study of polydactyly in-heritance due to their several unique aspects: i) thesamples are very large; ii) utilization and comparisonof two distinct ascertainment categories (complete andincomplete selection); iii) the same criterion to collectthe malformation from several maternity hospitals inthe ECLAMC, and all individuals diagnosed by onlyone physician in Hospedaria.

This study suggests that the transmission patternsof postaxial polydactyly are different between hands(HP) and feet (FP). In HP there is evidence that thereis an extra non-Mendelian transmission, while for FP,the parental-sibs inheritance happens only by classicalmultifactorial causes. The present results seem to sup-port previous observations [Castilla et al., 1997] on thedifference between the two types of postaxial polydac-tyly. Castilla et al. [1997] have shown that postaxialpolydactyly of the feet differs from that of the hands inseveral aspects, namely, it has no increased parentalconsanguinity, no sex influenced familial segregationdistortion, a lower familial recurrence rate, and nopreference for race.

Aside from the peculiar result of the whole ECLAMCsample that suggests the existence of a possible reces-sive gene responsible for the trait (against the over-whelming evidence from the pertinent literature), theresults of the present study suggest that the influenceof the environment in conjunction with a complex ge-netic component, displaying high heritability, playsuch an important role as to potentially obscure thedetection of major genetic mechanisms (if present) act-ing on polydactyly, even when only hands were consid-ered. Nevertheless, the existence of a single major


Mendelian mechanism responsible for postaxial poly-dactyly was not supported in these present SouthAmerican samples. One may admit that there shouldexist several genetic mechanisms acting on this highlyheterogeneous trait.

Other genetic epidemiological methods involvinglinkage analysis will be helpful for resolving the pres-ence of some more conspicuous genes associated withthis postaxial polydactyly. In humans, Radhakrishnaet al. [1997] have shown linkage between the polydac-tyly postaxial type-A phenotype and markers on chro-mosome 7p15-q11.23, in an Indian sample. Studies us-ing this markers, among others, and considering handsand feet separately as well as dividing the differenttypes of polydactyly should be applied on informativepopulations.

ACKNOWLEDGMENTS

This study was supported by the Conselho Nacionalde Desenvolvimento Cientıfico e Tecnologico (CNPq) ofBrazil, Fundacao de Amparo a Pesquisa do Estado deSao Paulo (FAPESP) of Brazil and Consejo Nacional deInvestigaciones Cientificas y Tecnicas (CONICET) ofArgentina.

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