Genomics and phenomics of body mass index reveals a complex disease network
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Genomics and phenomics of body mass index reveals a complex disease network. / Huang, Jie; Huffman, Jennifer E.; Huang, Yunfeng; Do Valle, Ítalo; Assimes, Themistocles L.; Raghavan, Sridharan; Voight, Benjamin F.; Liu, Chang; Barabási, Albert László; Huang, Rose D.L.; Hui, Qin; Nguyen, Xuan Mai T.; Ho, Yuk Lam; Djousse, Luc; Lynch, Julie A.; Vujkovic, Marijana; Tcheandjieu, Catherine; Tang, Hua; Damrauer, Scott M.; Reaven, Peter D.; Miller, Donald; Phillips, Lawrence S.; Ng, Maggie C.Y.; Graff, Mariaelisa; Haiman, Christopher A.; Loos, Ruth J.F.; North, Kari E.; Yengo, Loic; Smith, George Davey; Saleheen, Danish; Gaziano, J. Michael; Rader, Daniel J.; Tsao, Philip S.; Cho, Kelly; Chang, Kyong Mi; Wilson, Peter W.F.; Sun, Yan V.; O’Donnell, Christopher J.; VA Million Veteran Program.
In: Nature Communications, Vol. 13, No. 1, 7973, 2022.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Genomics and phenomics of body mass index reveals a complex disease network
AU - Huang, Jie
AU - Huffman, Jennifer E.
AU - Huang, Yunfeng
AU - Do Valle, Ítalo
AU - Assimes, Themistocles L.
AU - Raghavan, Sridharan
AU - Voight, Benjamin F.
AU - Liu, Chang
AU - Barabási, Albert László
AU - Huang, Rose D.L.
AU - Hui, Qin
AU - Nguyen, Xuan Mai T.
AU - Ho, Yuk Lam
AU - Djousse, Luc
AU - Lynch, Julie A.
AU - Vujkovic, Marijana
AU - Tcheandjieu, Catherine
AU - Tang, Hua
AU - Damrauer, Scott M.
AU - Reaven, Peter D.
AU - Miller, Donald
AU - Phillips, Lawrence S.
AU - Ng, Maggie C.Y.
AU - Graff, Mariaelisa
AU - Haiman, Christopher A.
AU - Loos, Ruth J.F.
AU - North, Kari E.
AU - Yengo, Loic
AU - Smith, George Davey
AU - Saleheen, Danish
AU - Gaziano, J. Michael
AU - Rader, Daniel J.
AU - Tsao, Philip S.
AU - Cho, Kelly
AU - Chang, Kyong Mi
AU - Wilson, Peter W.F.
AU - Sun, Yan V.
AU - O’Donnell, Christopher J.
AU - VA Million Veteran Program
N1 - Publisher Copyright: © 2022, This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
U2 - 10.1038/s41467-022-35553-2
DO - 10.1038/s41467-022-35553-2
M3 - Journal article
C2 - 36581621
AN - SCOPUS:85145152971
VL - 13
JO - Nature Communications
JF - Nature Communications
SN - 2041-1723
IS - 1
M1 - 7973
ER -
ID: 335676711