Genomics and phenomics of body mass index reveals a complex disease network.
СтатьяПоддержка NIH: внешняя программаПоддержка правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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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, VA Million Veteran Program, Sun Yan V, O'Donnell Christopher J
Аннотация
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.