Genome-Wide Association Study of Parity in Bangladeshi Women

Aschebrook-Kilfoy, Briseis; Argos, Maria; Pierce, Brandon L.; Tong, Lin; Jasmine, Farzana; Roy, Shantanu; Parvez, Muhammad F.; Ahmed, Alauddin; Islam, Tariqul; Kibriya, Muhammad G.; Ahsan, Habibul

Human fertility is a complex trait determined by gene-environment interactions in which genetic factors represent a significant component. To better understand inter-individual variability in fertility, we performed one of the first genome-wide association studies (GWAS) of common fertility phenotypes, lifetime number of pregnancies and number of children in a developing country population. The fertility phenotype data and DNA samples were obtained at baseline recruitment from individuals participating in a large prospective cohort study in Bangladesh. GWAS analyses of fertility phenotypes were conducted among 1,686 married women. One SNP on chromosome 4 was non-significantly associated with number of children at P <10^-7and number of pregnancies at P <10^-6. This SNP is located in a region without a gene within 1 Mb. One SNP on chromosome 6 was non-significantly associated with extreme number of children at P <10^-6. The closest gene to this SNP is HDGFL1, a hepatoma-derived growth factor. When we excluded hormonal contraceptive users, a SNP on chromosome 5 was non-significantly associated at P <10^-5 for number of children and number of pregnancies. This SNP is located near C5orf64, an open reading frame, and ZSWIM6, a zinc ion binding gene. We also estimated the heritability of these phenotypes from our genotype data using GCTA (Genome-wide Complex Trait Analysis) for number of children (hg² = 0.149, SE = 0.24, p-value = 0.265) and number of pregnancies (hg² = 0.007, SE = 0.22, p-value = 0.487). Our genome-wide association study and heritability estimates of number of pregnancies and number of children in Bangladesh did not confer strong evidence of common variants for parity variation. However, our results suggest that future studies may want to consider the role of 3 notable SNPs in their analysis.


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Environmental Health Sciences
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February 2, 2016