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A Polygenic and Phenotypic Risk Prediction for Polycystic Ovary Syndrome Evaluated by Phenome-Wide Association Studies

Sciprofile linkYoonjung Yoonie Joo, Ky’Era Actkins, Jennifer A Pacheco, Anna O Basile, Robert Carroll, David R Crosslin, Felix Day, Joshua C Denny, Digna R Velez Edwards, Hakon Hakonarson, John B Harley, Scott J Hebbring, Kevin Ho, Gail P Jarvik, Michelle Jones, Tugce Karaderi, Frank D Mentch, Cindy Meun, Bahram Namjou, Sarah Pendergrass, Marylyn D Ritchie, Ian B Stanaway, Sciprofile linkM. Urbanek, Theresa L Walunas, Maureen Smith, Rex L Chisholm, Abel N Kho, Lea Davis, Sciprofile linkM. Geoffrey Hayes, International PCOS Consortium, Chunyan He, Alex Drong, Peter Kraft, Nan Lin, Hongyan Huang, Linda Broer, Reedik Magi, Richa Saxena, Triin Laisk-Podar, Gudmar Thorleifsson, Juan Fernandez-Tajes, Anubha Mahajan, Benjamin H Mullin, Bronwyn G A Stuckey, Timothy D Spector, Scott G Wilson, Mark O Goodarzi, Barbara Obermeyer-Pietsch, André G Uitterlinden, Verneri Anttila, Benjamin M Neale, Marjo-Riitta Jarvelin, Bart Fauser, Irina Kowalska, Jenny A Visser, Marianne Anderson, 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 Perry, Andrea Dunaif, Joop Laven, Steve Franks, Cecilia M Lindgren, Corrine K Welt
The Journal of Clinical Endocrinology & Metabolism , Volume 105, pp 1918-1936; doi:10.1210/clinem/dgz326

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Keywords: polycystic ovary syndrome / genomic prediction / Polygenic risk score / Phenome-wide Association Study
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