A multi-population phenome-wide association study of genetically-predicted height in the Million Veteran Program
Year: 2022
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Height has been associated with many clinical traits but whether such associations are causal versus secondary to confounding remains unclear in many cases. To systematically examine this question, we performed a Mendelian Randomization-Phenome-wide association study (MR-PheWAS) using clinical and genetic data from a national healthcare system biobank. METHODS AND FINDINGS: Analyses were performed using data from the US Veterans Affairs (VA) Million Veteran Program in non-Hispanic White (EA, n = 222,300) and non-Hispanic Black (AA, n = 58,151) adults in the US. We estimated height genetic risk based on 3290 height-associated variants from a recent European-ancestry genome-wide meta-analysis. We compared associations of measured and genetically-predicted height with phenome-wide traits derived from the VA electronic health record, adjusting for age, sex, and genetic principal components. We found 345 clinical traits associated with measured height in EA and an additional 17 in AA. Of these, 127 were associated with genetically-predicted height at phenome-wide significance in EA and 2 in AA. These associations were largely independent from body mass index. We confirmed several previously described MR associations between height and cardiovascular disease traits such as hypertension, hyperlipidemia, coronary heart disease (CHD), and atrial fibrillation, and further uncovered MR associations with venous circulatory disorders and peripheral neuropathy in the presence and absence of diabetes. As a number of traits associated with genetically-predicted height frequently co-occur with CHD, we evaluated effect modification by CHD status of genetically-predicted height associations with risk factors for and complications of CHD. We found modification of effects of MR associations by CHD status for atrial fibrillation/flutter but not for hypertension, hyperlipidemia, or venous circulatory disorders. CONCLUSIONS: We conclude that height may be an unrecognized but biologically plausible risk factor for several common conditions in adults. However, more studies are needed to reliably exclude horizontal pleiotropy as a driving force behind at least some of the MR associations observed in this study.
Source: PLoS Genetics
Authors: Sridharan Raghavan, Jie Huang, Catherine Tcheandjieu, Jennifer E. Huffman, Elizabeth Litkowski, Chang Liu, Yuk-Lam A. Ho, Haley Hunter-Zinck, Hongyu Zhao, Eirini Marouli, Kari E. North, the VA Million Veteran Program, Ethan Lange, Leslie A. Lange, Benjamin F. Voight, J. Michael Gaziano, Saiju Pyarajan, Elizabeth R. Hauser, Philip S. Tsao, Peter W. F. Wilson, Kyong-Mi Chang, Kelly Cho, Christopher J. O’Donnell, Yan V. Sun, Themistocles L. Assimes
Institutions: VA Eastern Colorado Health Care System, University of Colorado Anschutz, Southern University of Science and Technology, VA Palo Alto Health Care System, Stanford Medicine, Stanford University, VA Boston Healthcare System, Emory University, Veterans Health Administration, Atlanta VA Medical Center, Yale University, VA Connecticut Healthcare System, Queen Mary University of London, William Harvey Research Institute, University of North Carolina at Chapel Hill, Philadelphia VA Medical Center, University of Pennsylvania, Brigham and Women's Hospital, Harvard University, Durham VA Health Care System, Duke Medical Center, Durham VA Medical Center
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,655
Funders: U.S. Department of Veterans Affairs, Boettcher Foundation, Office of Research and Development, National Heart and Lung Institute, National Institutes of Health, National Heart, Lung, and Blood Institute, National Human Genome Research Institute, National Institute of Diabetes and Digestive and Kidney Diseases, National Center for Advancing Translational Sciences
Awards: G1044130170, G1458435566, G1615475955, G1852267882, G1900021819, G2033544460, G2464355595, G2550089513, G287178428, G3033820005, G3856074833, G4110762795, PAGE III: Population Architecture using Genomics and Epidemiology, Algorithms to identify non-coding mutational burden and disease-relevant pathways, G5397575833, G5946272055, G6111149256, G6521380809, G6571272935, G758060882, Functional Interrogation of T2D-associated genes in human stem cell-derived models and mice, G8271222709, G8326906686, G9000061729, G9000134020, G9000180154, G9000226307, G9000253606, G9000259410, Yale Clinical and Translational Science Award, G942818495
OpenAlex ID: W4281857359