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

Author

Listed:
  • Jie Huang

    (Southern University of Science and Technology)

  • Jennifer E. Huffman

    (VA Boston Healthcare System)

  • Yunfeng Huang

    (Emory University Rollins School of Public Health
    Atlanta VA Health Care System)

  • Ítalo Valle

    (Northeastern University
    MAVERIC, VA Boston Healthcare System)

  • Themistocles L. Assimes

    (VA Palo Alto Health Care System
    Stanford University School of Medicine)

  • Sridharan Raghavan

    (VA Eastern Colorado Healthcare System
    University of Colorado School of Medicine)

  • Benjamin F. Voight

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania
    University of Pennsylvania
    University of Pennsylvania Perelman School of Medicine)

  • Chang Liu

    (Emory University Rollins School of Public Health)

  • Albert-László Barabási

    (Northeastern University
    Harvard Medical School
    Central European University)

  • Rose D. L. Huang

    (VA Boston Healthcare System)

  • Qin Hui

    (Emory University Rollins School of Public Health
    Atlanta VA Health Care System)

  • Xuan-Mai T. Nguyen

    (Carle Illinois College of Medicine
    VA Boston Healthcare System)

  • Yuk-Lam Ho

    (VA Boston Healthcare System)

  • Luc Djousse

    (VA Boston Healthcare System
    Harvard Medical School)

  • Julie A. Lynch

    (VA Salt Lake City Healthcare
    University of Massachusetts)

  • Marijana Vujkovic

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania)

  • Catherine Tcheandjieu

    (VA Palo Alto Health Care System
    Stanford University School of Medicine)

  • Hua Tang

    (VA Palo Alto Health Care System
    Stanford University School of Medicine)

  • Scott M. Damrauer

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania
    University of Pennsylvania Perelman School of Medicine)

  • Peter D. Reaven

    (Phoenix VA Health Care System
    University of Arizona)

  • Donald Miller

    (Bedford VA Medical Center)

  • Lawrence S. Phillips

    (Atlanta VA Health Care System
    Emory University School of Medicine)

  • 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
    Icahn School of Medicine at Mount Sinai
    University of Copenhagen)

  • Kari E. North

    (University of North Carolina Chapel Hill)

  • Loic Yengo

    (The University of Queensland)

  • George Davey Smith

    (University of Bristol
    University of Bristol)

  • Danish Saleheen

    (Center for Non-Communicable Diseases
    Columbia University Irving Medical Center
    Columbia University Irving Medical Center)

  • J. Michael Gaziano

    (VA Boston Healthcare System
    Harvard Medical School)

  • Daniel J. Rader

    (University of Pennsylvania
    University of Pennsylvania Perelman School of Medicine)

  • Philip S. Tsao

    (VA Palo Alto Health Care System
    Stanford University School of Medicine)

  • Kelly Cho

    (VA Boston Healthcare System
    Harvard Medical School)

  • Kyong-Mi Chang

    (Corporal Michael J. Crescenz VA Medical Center
    University of Pennsylvania)

  • Peter W. F. Wilson

    (Emory University Rollins School of Public Health
    Atlanta VA Health Care System
    Emory University School of Medicine)

  • Yan V. Sun

    (Emory University Rollins School of Public Health
    Atlanta VA Health Care System)

  • Christopher J. O’Donnell

    (VA Boston Healthcare System
    Harvard Medical School
    VA Boston Healthcare System)

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.

Suggested Citation

  • 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 & Xu, 2022. "Genomics and phenomics of body mass index reveals a complex disease network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-35553-2
    DOI: 10.1038/s41467-022-35553-2
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    References listed on IDEAS

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    2. Louise A C Millard & Neil M Davies & Kate Tilling & Tom R Gaunt & George Davey Smith, 2019. "Searching for the causal effects of body mass index in over 300 000 participants in UK Biobank, using Mendelian randomization," PLOS Genetics, Public Library of Science, vol. 15(2), pages 1-20, February.
    3. Kyoko Watanabe & Erdogan Taskesen & Arjen Bochoven & Danielle Posthuma, 2017. "Functional mapping and annotation of genetic associations with FUMA," Nature Communications, Nature, vol. 8(1), pages 1-11, December.
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