Genomics and phenomics of body mass index reveals a complex disease network
Author
Huang, J.Huffman, J.E.
Huang, Y.
Do Valle, Í.
Assimes, T.L.
Raghavan, S.
Voight, B.F.
Liu, C.
Barabási, A.-L.
Huang, R.D.L.
Hui, Q.
Nguyen, X.-M.T.
Ho, Y.-L.
Djousse, L.
Lynch, J.A.
Vujkovic, M.
Tcheandjieu, C.
Tang, H.
Damrauer, S.M.
Reaven, P.D.
Miller, D.
Phillips, L.S.
Ng, M.C.Y.
Graff, M.
Haiman, C.A.
Loos, R.J.F.
North, K.E.
Yengo, L.
Smith, G.D.
Saleheen, D.
Gaziano, J.M.
Rader, D.J.
Tsao, P.S.
Cho, K.
Chang, K.-M.
Wilson, P.W.F.
Sun, Y.V.
O’Donnell, C.J.
VA Million Veteran Program
Affiliation
College of Medicine, University of ArizonaIssue Date
2022-12-29
Metadata
Show full item recordPublisher
Nature ResearchCitation
Huang, J., Huffman, J. E., Huang, Y., Do Valle, Í., Assimes, T. L., Raghavan, S., ... & O’Donnell, C. J. (2022). Genomics and phenomics of body mass index reveals a complex disease network. Nature Communications, 13(1), 7973.Journal
Nature CommunicationsRights
This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. This is an open access article distributed under the terms of the Creative Commons CC BY license.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.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. © 2022, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.Note
Open access journalISSN
2041-1723PubMed ID
36581621Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1038/s41467-022-35553-2
Scopus Count
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Except where otherwise noted, this item's license is described as This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply. This is an open access article distributed under the terms of the Creative Commons CC BY license.
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