A genome-wide association study of polycystic ovary syndrome identified from electronic health records

MedRxiv : the Preprint Server for Health Sciences
Yanfei ZhangM. T. M. Lee

Abstract

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine disorder affecting women of reproductive age. Previous studies have identified genetic variants associated with PCOS identified by different diagnostic criteria. The Rotterdam Criteria is the broadest and able to identify the most PCOS cases. Objectives: To identify novel associated genetic variants, we extracted PCOS cases and controls from the electronic health records (EHR) based on the Rotterdam Criteria and performed a genome-wide association study (GWAS). Study Design: We developed a PCOS phenotyping algorithm based on the Rotterdam criteria and applied it to three EHR-linked biobanks to identify cases and controls for genetic study. In discovery phase, we performed individual GWAS using the Geisinger's MyCode and the eMERGE cohorts, which were then meta-analyzed. We attempted validation of the significantly association loci (P<1x10-6) in the BioVU cohort. All association analyses used logistic regression, assuming an additive genetic model, and adjusted for principal components to control for population stratification. An inverse-variance fixed effect model was adopted for meta-analyses. Additionally, we examined the top variants to evaluate their ...Continue Reading

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