Genomics and phenomics of body mass index reveals a complex disease network
Jie Huang, Jennifer E. Huffman, Yunfeng Huang, Ítalo Faria do Valle, Themistocles L. Assimes, Sridharan Raghavan, Benjamin F. Voight, Chang Liu, Albert-Ĺaszló Barabási, Rose D. L. Huang, Qin Hui, Xuan‐Mai T. Nguyen, Yuk‐Lam Ho, Luc Djoussé, Julie A. Lynch, Marijana Vujković, Catherine Tcheandjieu, Hua Tang, Scott M. Damrauer, Peter D. Reaven, Donald R. Miller, Lawrence S. Phillips, Maggie C. Y. Ng, Mariaelisa Graff, Christopher A. Haiman, Ruth J. F. Loos, Kari E. North, Loïc Yengo, George Davey Smith, Danish Saleheen, J. Michael Gaziano, Daniel J. Rader, Philip S. Tsao, Kelly Cho, Kyong‐Mi Chang, Peter W.F. Wilson, VA Million Veteran Program, Yan V. Sun, Christopher J. O’Donnell
Abstract
Elevated body mass index (BMI) is heritable and associated with many health conditions that impact morbidity and mortality. The study of the genetic association of BMI across a broad range of common disease conditions offers the opportunity to extend current knowledge regarding the breadth and depth of adiposity-related diseases. We identify 906 (364 novel) and 41 (6 novel) genome-wide significant loci for BMI among participants of European (N~1.1 million) and African (N~100,000) ancestry, respectively. Using a BMI genetic risk score including 2446 variants, 316 diagnoses are associated in the Million Veteran Program, with 96.5% showing increased risk. A co-morbidity network analysis reveals seven disease communities containing multiple interconnected diseases associated with BMI as well as extensive connections across communities. Mendelian randomization analysis confirms numerous phenotypes across a breadth of organ systems, including conditions of the circulatory (heart failure, ischemic heart disease, atrial fibrillation), genitourinary (chronic renal failure), respiratory (respiratory failure, asthma), musculoskeletal and dermatologic systems that are deeply interconnected within and across the disease communities. This work shows that the complex genetic architecture of BMI associates with a broad range of major health conditions, supporting the need for comprehensive approaches to prevent and treat obesity.