The genetic architecture of sporadic and multiple consecutive miscarriage
Triin Laisk, Ana Gonçalves Soares, Teresa Ferreira, Jodie N. Painter, Jenny C. Censin, Samantha Laber, Jonas Bačelis, Chia‐Yen Chen, Maarja Lepamets, Kuang Lin, Siyang Liu, Iona Y. Millwood, Avinash Ramu, Jennifer H. Southcombe, Marianne Andersen, Ling Yang, Christian M. Becker, Anders D. Børglum, Scott D. Gordon, Jonas Bybjerg‐Grauholm, Øyvind Helgeland, David M. Hougaard, Xin Jin, Stefan Johansson, Julius Juodakis, Christiana Kartsonaki, Viktorija Kukushkina, Penelope A. Lind, Andres Metspalu, Grant W. Montgomery, Andrew P. Morris, Ole Mors, Preben Bo Mortensen, Pål R. Njølstad, Merete Nordentoft, Dale R. Nyholt, Margaret Lippincott, Stephanie B. Seminara, Andres Salumets, Harold Snieder, Krina T. Zondervan, Thomas Werge, Zhengming Chen, Donald F. Conrad, Bo Jacobsson, Liming Li, Nicholas G. Martin, Benjamin M. Neale, Rasmus Nielsen, Robin Walters, Ingrid Granne, Sarah E. Medland, Reedik Mägi, Debbie A. Lawlor, Cecilia M. Lindgren
Abstract
Abstract Miscarriage is a common, complex trait affecting ~15% of clinically confirmed pregnancies. Here we present the results of large-scale genetic association analyses with 69,054 cases from five different ancestries for sporadic miscarriage, 750 cases of European ancestry for multiple (≥3) consecutive miscarriage, and up to 359,469 female controls. We identify one genome-wide significant association (rs146350366, minor allele frequency (MAF) 1.2%, P = 3.2 × 10 −8 , odds ratio (OR) = 1.4) for sporadic miscarriage in our European ancestry meta-analysis and three genome-wide significant associations for multiple consecutive miscarriage (rs7859844, MAF = 6.4%, P = 1.3 × 10 −8 , OR = 1.7; rs143445068, MAF = 0.8%, P = 5.2 × 10 −9 , OR = 3.4; rs183453668, MAF = 0.5%, P = 2.8 × 10 −8 , OR = 3.8). We further investigate the genetic architecture of miscarriage with biobank-scale Mendelian randomization, heritability, and genetic correlation analyses. Our results show that miscarriage etiopathogenesis is partly driven by genetic variation potentially related to placental biology, and illustrate the utility of large-scale biobank data for understanding this pregnancy complication.