Investigation of the Genetic Architecture of Polycystic Ovary Syndrome

Dapas, Matthew

doi:https://doi.org/10.21985/n2-9fy7-kk39

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Investigation of the Genetic Architecture of Polycystic Ovary Syndrome

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Polycystic ovary syndrome (PCOS) is among the most common endocrine disorders of premenopausal women, affecting 5-15% of this population depending on the diagnostic criteria applied. It is characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. PCOS is highly heritable, but only a small proportion of this heritability can be accounted for by the common genetic susceptibility variants identified to date. In the studies reported herein, we implemented a series of novel bioinformatic approaches to investigate whether two potential explanations for this missing heritability, rare variants and genetic heterogeneity, contribute to pathogenesis of PCOS. Utilizing whole genome sequencing data from 76 two-generation families that include daughters with PCOS, we first performed non-parametric linkage analysis followed by a genome-wide, rare variant quantitative trait association meta-analysis. We identified 32, primarily noncoding, rare variants in the DENND1A gene that were significantly associated with PCOS quantitative traits that were collectively found in 50% of families. Next, we performed unsupervised hierarchical cluster analyses on quantitative anthropometric, reproductive, and metabolic traits in a genotyped discovery cohort of 893 PCOS cases and an ungenotyped validation cohort of 466 PCOS cases. We identified two PCOS phenotypic subtypes: a “reproductive” group (21-23%) characterized by higher luteinizing hormone (LH) and sex hormone binding globulin (SHBG) levels with relatively low body mass index (BMI) and insulin levels; and a “metabolic” group (37-39%), characterized by higher BMI, glucose, and insulin levels with lower SHBG and LH levels. We then performed a genome-wide association study on the genotyped cohort, limiting the cases to either the reproductive or metabolic subtypes. We identified alleles in four novel loci that were associated with the reproductive subtype at genome-wide significance and one locus that was significantly associated with the metabolic subtype. We then classified the reproductive and metabolic subtypes in the family-based WGS cohort and found the reproductive and metabolic subtypes tend to cluster in families and that carriers of rare DENND1A variants are significantly more likely to have reproductive subtype of PCOS. Collectively, our results suggest that rare noncoding variants contribute to the distinctive hormonal profile of PCOS; hyperandrogenemia is a causal pathway in PCOS independent of insulin resistance, with DENND1A as a core regulator of this pathway; and there are reproductive and metabolic subtypes of PCOS with distinct genetic architectures. From a methodological standpoint, we demonstrated that using a quantitative trait meta-analysis can be a powerful approach in rare variant association testing, particularly for complex diseases with pleiotropic etiologies, and that precise phenotypic delineation can be more powerful and informative than increases in sample size for genetic association studies.

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