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  5. Large-Scale Genome-Wide Meta Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria

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Preprint
en
2018

Large-Scale Genome-Wide Meta Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria

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0 Files

en
2018
DOI: 10.1101/290502

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Paul M Ridker
Paul M Ridker

Harvard University

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Felix R. Day
Tugce Karaderi
Michelle R. Jones
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Abstract

Abstract Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction and polycystic ovarian morphology. Affected women frequently have metabolic disturbances including insulin resistance and dysregulation of glucose homeostasis. PCOS is diagnosed with two different sets of diagnostic criteria, resulting in a phenotypic spectrum of PCOS cases. The genetic similarities between cases diagnosed with different criteria have been largely unknown. Previous studies in Chinese and European subjects have identified 16 loci associated with risk of PCOS. We report a meta-analysis from 10,074 PCOS cases and 103,164 controls of European ancestry and characterisation of PCOS related traits. We identified 3 novel loci (near PLGRKT, ZBTB16 and MAPRE1 ), and provide replication of 11 previously reported loci. Identified variants were associated with hyperandrogenism, gonadotropin regulation and testosterone levels in affected women. Genetic correlations with obesity, fasting insulin, type 2 diabetes, lipid levels and coronary artery disease indicate shared genetic architecture between metabolic traits and PCOS. Mendelian randomization analyses suggested variants associated with body mass index, fasting insulin, menopause timing, depression and male-pattern balding play a causal role in PCOS. Only one locus differed in its association by diagnostic criteria, otherwise the genetic architecture was similar between PCOS diagnosed by self-report and PCOS diagnosed by NIH or Rotterdam criteria across common variants at 13 loci.

How to cite this publication

Felix R. Day, Tugce Karaderi, Michelle R. Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Mägi, Richa Saxena, Triin Laisk-Podar, Margrit Urbanek, M. Geoffrey Hayes, Guðmar Þorleifsson, Juan Fernández‐Tajes, Anubha Mahajan, Benjamin H. Mullin, Bronwyn Stuckey, Timothy D. Spector, Scott G. Wilson, Mark O. Goodarzi, Lea K. Davis, Barbara Obermeyer-Pietsch, André G. Uitterlinden, Verneri Anttila, Benjamin M. Neale, Paul M Ridker, Bart Fauser, Irina Kowalska, Jenny A. Visser, Marianne Anderson, Ken K. Ong, Elisabet Stener‐Victorin, David A. Ehrmann, Richard S. Legro, Andres Salumets, Mark I. McCarthy, Laure Morin‐Papunen, Unnur Þorsteinsdóttir, Kāri Stefánsson, Unnur Styrkársdóttir, John R. B. Perry, Andrea Dunaif, Joop S.E. Laven, Steve Franks, Cecilia M. Lindgren, Corrine K. Welt (2018). Large-Scale Genome-Wide Meta Analysis of Polycystic Ovary Syndrome Suggests Shared Genetic Architecture for Different Diagnosis Criteria. , DOI: https://doi.org/10.1101/290502.

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Publication Details

Type

Preprint

Year

2018

Authors

49

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1101/290502

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