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Body mass index stratified meta-analysis of genome-wide association studies of polycystic ovary syndrome in women of European ancestry

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posted on 2024-05-02, 09:23 authored by Kharis Burns, Benjamin H Mullin, Loes ME Moolhuijsen, Triin Laisk, Jaakko S Tyrmi, Jinrui Cui, Ky’Era V Actkins, Yvonne V Louwers, Andres Metspalu, Lili Milani, Tõnu Esko, Mari Nelis, Georgi Hudjashov, Lea K Davis, Frank DudbridgeFrank Dudbridge, Ricardo Azziz, Mark O Goodarzi, Hannele Laivuori, Reedik Mägi, Jenny A Visser, Joop SE Laven, Scott G Wilson, Tugce Karaderi, Michelle R Jones, Cindy Meun, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Richa Saxena, Margrit Urbanek, M Geoffrey Hayes, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Timothy D Spector, Barbara Obermayer-Pietsch, André G Uitterlinden, Verneri Anttila, Benjamin M Neale, Marjo-Riitta Jarvelin, Mark Daly, Bart Fauser, Irina Kowalska, Marianne Andersen, Ken Ong, Elisabet Stener-Victorin, David Ehrmann, Richard S Legro, Andres Salumets, Mark I McCarthy, Laure Morin-Papunen, Unnur Thorsteinsdottir, Kari Stefansson, Unnur Styrkarsdottir, John RB Perry, Andrea Dunaif, Steve Franks, Cecilia M Lindgren, Corrine K Welt, Felix R Day, Bronwyn GA Stuckey

Background Polycystic ovary syndrome (PCOS) is a complex multifactorial disorder with a substantial genetic component. However, the clinical manifestations of PCOS are heterogeneous with notable differences between lean and obese women, implying a different pathophysiology manifesting in differential body mass index (BMI). We performed a meta-analysis of genome-wide association study (GWAS) data from six well-characterised cohorts, using a case–control study design stratified by BMI, aiming to identify genetic variants associated with lean and overweight/obese PCOS subtypes. Results The study comprised 254,588 women (5,937 cases and 248,651 controls) from individual studies performed in Australia, Estonia, Finland, the Netherlands and United States of America, and separated according to three BMI stratifications (lean, overweight and obese). Genome-wide association analyses were performed for each stratification within each cohort, with the data for each BMI group meta-analysed using METAL software. Almost half of the total study population (47%, n = 119,584) were of lean BMI (≤ 25 kg/m2). Two genome-wide significant loci were identified for lean PCOS, led by rs12000707 within DENND1A (P = 1.55 × 10–12) and rs2228260 within XBP1 (P = 3.68 × 10–8). One additional locus, LINC02905, was highlighted as significantly associated with lean PCOS through gene-based analyses (P = 1.76 × 10–6). There were no significant loci observed for the overweight or obese sub-strata when analysed separately, however, when these strata were combined, an association signal led by rs569675099 within DENND1A reached genome-wide significance (P = 3.22 × 10–9) and a gene-based association was identified with ERBB4 (P = 1.59 × 10–6). Nineteen of 28 signals identified in previous GWAS, were replicated with consistent allelic effect in the lean stratum. There were less replicated signals in the overweight and obese groups, and only 4 SNPs were replicated in each of the three BMI strata. Conclusions Genetic variation at the XBP1, LINC02905 and ERBB4 loci were associated with PCOS within unique BMI strata, while DENND1A demonstrated associations across multiple strata, providing evidence of both distinct and shared genetic features between lean and overweight/obese PCOS-affected women. This study demonstrated that PCOS-affected women with contrasting body weight are not only phenotypically distinct but also show variation in genetic architecture; lean PCOS women typically display elevated gonadotrophin ratios, lower insulin resistance, higher androgen levels, including adrenal androgens, and more favourable lipid profiles. Overall, these findings add to the growing body of evidence supporting a genetic basis for PCOS as well as differences in genetic patterns relevant to PCOS BMI-subtype.

Funding

Cedars Sinai – Mark Goodarzi was supported by the Eris M.Field Chair in Diabetes Research and NIDDK P30-DK063481. Ricardo Azziz was supported by NICHD grants R01-HD29364 and K24-HD01346. BioVU—N/A WA-PCOS—This study was supported by a grant from the Sir Charles Gairdner Osborne Park Health Care Group Research Advisory Committee, (Grant number: RAC2019-20/029) and, in part, by funding from the National Health and Medical Research Council of Australia (APP2003629 to B.H.M) and a Department of Health (Western Australia) Merit Award (No. 1186046 to B.H.M). The Estonian Biobank work was supported by the Estonian Research council grant PRG1911 and by European Union through the European Regional Development Fund Project No. 2014–2020.4.01.15–0012 GENTRANSMED. The FinnGen project is funded by two grants from Business Finland (HUS 4685/31/2016 and UH 4386/31/2016) and the following industry partners: AbbVie Inc., AstraZeneca UK Ltd, Biogen MA Inc., Bristol Myers Squibb (and Celgene Corporation & Celgene International II Sarl), Genentech Inc., Merck Sharp & Dohme Corp., Pfizer Inc., GlaxoSmithKline Intellectual Property Development Ltd., Sanofi US Services Inc., Maze Therapeutics Inc., Janssen Biotech Inc, Novartis AG, and Boehringer Ingelheim International GmbH. The Lifelines Cohort Study "The Lifelines initiative has been made possible by subsidy from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the University Medical Center Groningen (UMCG), Groningen University and the Provinces in the North of the Netherlands (Drenthe, Friesland, Groningen)."

History

Author affiliation

College of Life Sciences/Population Health Sciences

Version

  • VoR (Version of Record)

Published in

BMC Genomics

Volume

25

Issue

1

Pagination

208

Publisher

Springer Science and Business Media LLC

issn

1471-2164

eissn

1471-2164

Copyright date

2024

Available date

2024-05-02

Spatial coverage

England

Language

en

Deposited by

Professor Frank Dudbridge

Deposit date

2024-04-27

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  • No

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