Our understanding of the genetics of skin pigmentation has been largely skewed towards populations of European ancestry, imparting less attention to South Asian populations, who behold huge pigmentation diversity. Here, we investigate skin pigmentation variation in a cohort of 1,167 individuals in the Middle Gangetic Plain of the Indian subcontinent. Our data confirm the association of rs1426654 with skin pigmentation among South Asians, consistent with previous studies, and also show association for rs2470102 single nucleotide polymorphism. Our haplotype analyses further help us delineate the haplotype distribution across social categories and skin color. Taken together, our findings suggest that the social structure defined by the caste system in India has a profound influence on the skin pigmentation patterns of the subcontinent. In particular, social category and associated single nucleotide polymorphisms explain about 32% and 6.4%, respectively, of the total phenotypic variance. Phylogeography of the associated single nucleotide polymorphisms studied across 52 diverse populations of the Indian subcontinent shows wide presence of the derived alleles, although their frequencies vary across populations. Our results show that both polymorphisms (rs1426654 and rs2470102) play an important role in the skin pigmentation diversity of South Asians.

ObjectivePolycystic ovarian syndrome (PCOS) refers to an inheritable androgen excess disorder characterized by multiple small follicles located at the ovarian periphery. Hyperandrogenism in PCOS, and inverse correlation between androgen receptor (AR) CAG numbers and AR function, led us to hypothesize that CAG length variations may affect PCOS risk.MethodsCAG repeat region of 169 patients recruited following strictly defined Rotterdam (2003) inclusion criteria and that of 175 ethnically similar control samples, were analyzed. We also conducted a meta-analysis on the data taken from published studies, to generate a pooled estimate on 2194 cases and 2242 controls.ResultsCAG bi-allelic mean length was between 8.5 and 24.5 (mean = 17.43, SD = 2.43) repeats in the controls and between 11 and 24 (mean = 17.39, SD = 2.29) repeats in the cases, without any significant difference between the two groups. Further, comparison of bi-allelic mean and its frequency distribution in three categories (short, moderate and long alleles) did not show any significant difference between controls and various case subgroups. Frequency distribution of bi-allelic mean in two categories (extreme and moderate alleles) showed over-representation of extreme sized alleles in the cases with marginally significant value (50.3% vs. 61.5%, χ2 = 4.41; P = 0.036), which turned insignificant upon applying Bonferroni correction for multiple comparisons. X-chromosome inactivation analysis showed no significant difference in the inactivation pattern of CAG alleles or in the comparison of weighed bi-allelic mean between cases and controls. Meta-analysis also showed no significant correlation between CAG length and PCOS risk, except a minor over-representation of short CAG alleles in the cases.ConclusionCAG bi-allelic mean length did not differ between controls and cases/case sub-groups nor did the allele distribution. Over-representation of short/extreme-sized alleles in the cases may be a chance finding without any true association with PCOS risk.

Variations in the trinucleotide-CAG repeat number of the catalytic subunit of the mitochondrial DNA polymerase gamma (POLG) have been speculated to be associated with male infertility. The ten CAG repeats (10/10) were found to be the most common allele (88%), absence of which was found to be associated with male infertility. As no study on Indian population was conducted so far to support this view, we investigated the distribution of the POLG-CAG repeats in 509 oligoasthenozoospermic and 241 normozoospermic control Indian men from the same ethnic background. Our study suggested that the distribution of common allele (10/10) was almost similar in both infertile (75%) and normozoospermic (75.5%) men. Further, we had analysed the CAG repeat number in as many as 1306 Indian men belonging to different ethnic, geographical and linguistic backgrounds and found the common allele 10/10 at a frequency of 78.4%. Our study, therefore, suggests that the 10-CAG repeat is the most common allele present in Indian populations, but its absence and the occurrence of the other mutant homozygous (non 10/non 10) genotype should not be understood as being specific to infertility. It, thus, suggests that the POLG-CAG repeat variation is not associated with male infertility in Indian populations, and hence is not a useful marker for screening infertile men.

Down syndrome (DS) is the most common autosomal chromosome anomaly. DS is frequently associated with congenital heart disease (CHD). Patients with DS have 40-60% chance of having CHD. It means that CHD in DS is not only due to trisomy 21 and there are some other genetic factors underlying CHD in DS children. In this study, a total of 240 DNA samples from patients were analyzed including 100 patients with CHD only, 110 patients having CHD along with DS and 30 patients with isolated DS. A cardiovascular gene panel consisting of probes for 406 genes was used to screen DNA samples of all 240 patients for mutation identification. All variants were annotated and common variants were obtained. Briefly, 28 common variants (variants common in two or more than two individuals) were obtained in a group of samples containing DNA from DS patients having CHD as well, 63 variants were found to be unique to DS group of samples and 73 variants have been identified in patients with CHD only. In order to identify genomic variations determining the risk for CHD in DS, only those variants present in DS-CHD group and absent in isolated CHD and/or isolated DS group were considered for further analysis. Variants specific to DS-CHD group were further evaluated based on expression and function data and pathogenicity of the variant of interest. We have implicated mutations in GATA3, KCNH2, ENG, FLNA, and GUSB genes as an underlying risk factor for CHD in DS patients.

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