Genomics and phenomics of body mass index reveals a complex disease network

Jie Huang, Jennifer E. Huffman, Yunfeng Huang, Ítalo Valle, Themistocles L. Assimes, Sridharan Raghavan, Benjamin F. Voight, Chang Liu, Albert-László Barabási, Rose D. L. Huang, Qin Hui, Xuan-Mai T. Nguyen, Yuk-Lam Ho, Luc Djousse, Julie A. Lynch, Marijana Vujkovic, Catherine Tcheandjieu, Hua Tang, Scott M. Damrauer, Peter D. Reaven, Donald Miller, Lawrence S. Phillips, Maggie C. Y. Ng, Mariaelisa Graff, Christopher A. Haiman, Ruth J. F. Loos, Kari E. North, Loic Yengo, George Davey Smith, Danish Saleheen, J. Michael Gaziano, Daniel J. Rader, Philip S. Tsao, Kelly Cho, Kyong-Mi Chang, Peter W. F. Wilson, Yan V. Sun () and Christopher J. O’Donnell ()
Additional contact information
Jie Huang: Southern University of Science and Technology
Jennifer E. Huffman: VA Boston Healthcare System
Yunfeng Huang: Emory University Rollins School of Public Health
Ítalo Valle: Northeastern University
Themistocles L. Assimes: VA Palo Alto Health Care System
Sridharan Raghavan: VA Eastern Colorado Healthcare System
Benjamin F. Voight: Corporal Michael J. Crescenz VA Medical Center
Chang Liu: Emory University Rollins School of Public Health
Albert-László Barabási: Northeastern University
Rose D. L. Huang: VA Boston Healthcare System
Qin Hui: Emory University Rollins School of Public Health
Xuan-Mai T. Nguyen: Carle Illinois College of Medicine
Yuk-Lam Ho: VA Boston Healthcare System
Luc Djousse: VA Boston Healthcare System
Julie A. Lynch: VA Salt Lake City Healthcare
Marijana Vujkovic: Corporal Michael J. Crescenz VA Medical Center
Catherine Tcheandjieu: VA Palo Alto Health Care System
Hua Tang: VA Palo Alto Health Care System
Scott M. Damrauer: Corporal Michael J. Crescenz VA Medical Center
Peter D. Reaven: Phoenix VA Health Care System
Donald Miller: Bedford VA Medical Center
Lawrence S. Phillips: Atlanta VA Health Care System
Maggie C. Y. Ng: Vanderbilt University Medical Center
Mariaelisa Graff: University of North Carolina Chapel Hill
Christopher A. Haiman: University of Southern California
Ruth J. F. Loos: Icahn School of Medicine at Mount Sinai
Kari E. North: University of North Carolina Chapel Hill
Loic Yengo: The University of Queensland
George Davey Smith: University of Bristol
Danish Saleheen: Center for Non-Communicable Diseases
J. Michael Gaziano: VA Boston Healthcare System
Daniel J. Rader: University of Pennsylvania
Philip S. Tsao: VA Palo Alto Health Care System
Kelly Cho: VA Boston Healthcare System
Kyong-Mi Chang: Corporal Michael J. Crescenz VA Medical Center
Peter W. F. Wilson: Emory University Rollins School of Public Health
Yan V. Sun: Emory University Rollins School of Public Health
Christopher J. O’Donnell: VA Boston Healthcare System

Nature Communications, 2022, vol. 13, issue 1, 1-10

Abstract: 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.

Date: 2022
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DOI: 10.1038/s41467-022-35553-2

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