Genome-wide meta-analysis of myasthenia gravis uncovers new loci and provides insights into polygenic prediction
Alice Braun, Sudhanshu Shekhar, Daniel F. Levey, Péter Straub, Julia Kraft, Georgia Panagiotaropoulou, Karl Heilbron, Swapnil Awasthi, Rafael Meleka Hanna, Sarah Hoffmann, Maike Stein, Sophie Lehnerer, Philipp Mergenthaler, Abdelrahman G. Elnahas, Apostolia Topaloudi, Maria Koromina, Teemu Palviainen, Bergrún Ásbjörnsdóttir, Hreinn Stefánsson, Ástrós Skúladóttir, Ingileif Jónsdóttir, Kāri Stefánsson, Kadri Reis, Tõnu Esko, Aarno Palotie, Frank Leypoldt, Murray B. Stein, Pierre Fontanillas, Jaakko Kaprio, Joel Gelernter, Lea K. Davis, Peristera Paschou, Martijn R. Tannemaat, Jan J.G.M. Verschuuren, Gregor Kuhlenbäumer, Peter K. Gregersen, Maartje G. Huijbers, Frauke Stascheit, Andreas Meisel, Stephan Ripke
Abstract
Abstract Myasthenia gravis (MG) is a rare autoantibody-mediated disease affecting the neuromuscular junction. We performed a genome-wide association study of 5708 MG cases and 432,028 controls of European ancestry and a replication study in 3989 cases and 226,643 controls provided by 23andMe Inc. We identified 12 independent genome-wide significant hits ( P < 5e −8 ) across 11 loci. Subgroup analyses revealed two of these were associated with early-onset (at age <50) and four with late-onset MG (at age ≥ 50). Imputation of human leukocyte antigen alleles revealed inverse effect sizes for late- and early-onset, suggesting a potential modulatory influence on the time of disease manifestation. We assessed the performance of polygenic risk scores for MG, which significantly predicted disease status in an independent target cohort, explaining 4.21% of the phenotypic variation ( P = 5.12e −9 ). With this work, we aim to enhance our understanding of the genetic architecture of MG.