The polycystic ovary syndrome evolutionary paradox: A genome-wide association studies-based, in silico, evolutionary explanation

Abstract

Context: Polycystic ovary syndrome (PCOS) is a common female endocrine disorder characterized by phenotypes ranging from hyperandrogenism to metabolic disorders, more prevalent in people of African/Caucasian and Asian ancestry. Because PCOS impairs fertility without diminishing in prevalence, it was considered an evolutionary paradox. Genome-Wide Association Studies identified 17 single nucleotide polymorphisms (SNPs) associated with PCOS, with different allele frequencies, ethnicity-related, in 11 susceptibility loci. Objective: In this study we analyze the PCOS phenotype-genotype relationship in silico, using SNPs of representative genes for analysis of genetic clustering and distance, to evaluate the degree of genetic similarity. Data Source: 1000 Genomes, HapMap, and Human Genome Diversity Project databases were used as source of allele frequencies of the SNPs, using data from male and female individuals grouped according to their geographical ancestry. Setting and Design: Genetic clustering was calculated from SNPs data by Bayesian inference. The inferred ancestry of individuals was matched with PCOS phenotype data, extracted from a previous meta-analysis. The measure of genetic distance was plotted against the geographic distance between the populations. Results: The individuals were assigned to five genetic clusters, matching with different world regions (Kruskal-Wallis/Dunn's post test; P