Genome-wide and phenome-wide analysis of ideal cardiovascular health in the VA Million Veteran Program

• Type of Material: Article
• Authors: Rose D. L. Huang, VA Boston Healthcare System; Xuan-Mai T. Nguyen, VA Boston Healthcare System; Gina M. Peloso, VA Boston Healthcare System; Mark Trinder, The University of British Columbia; Daniel C. Posner, VA Boston Healthcare System; Krishna G. Aragam, Broad Institute; Yuk-Lam Ho, VA Boston Healthcare System; Julie A. Lynch, VA Medical Center; Scott M. Damrauer, VA Medical Center; Kyong-Mi Chang, VA Medical Center; Philip S. Tsao, VA Palo Alto Health Care System; Pradeep Natarajan, Broad Institute; Themistocles Assimes, VA Palo Alto Health Care System; J. Michael Gaziano, VA Boston Healthcare System; Luc Djousse, VA Boston Healthcare System; Kelly Cho, VA Boston Healthcare System; Peter Wilson, Emory University; Jennifer E. Huffman, VA Boston Healthcare System; Christopher J. O'Donnell, VA Boston Healthcare System
• Language: English
• Date: 2022-05-01
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
• License: Creative Commons Universal : Public Domain Dedication
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pone.0267900
• Title of Journal or Parent Work: PLoS ONE
• Volume: 17
• Issue: 5 May
• Start Page: e0267900
• End Page: e0267900
• Grant/Funding Information: The funder is the U.S. Department Veteran’s Affairs via the VA Office of Research and Development (I01-BX003340, I01-BX004821, I01-BX003362, IK2-CX001780).
• Keywords: Male; Female; Cardiovascular Diseases; Veterans; Genome-Wide Association Study; Health Status; Phenomics; Humans; Risk Factors
• Research Categories: Biology, Biostatistics; Biology, Bioinformatics; Health Sciences, Health Care Management; Biology, Genetics

Abstract

Background Genetic studies may help identify causal pathways; therefore, we sought to identify genetic determinants of ideal CVH and their association with CVD outcomes in the multi-population Veteran Administration Million Veteran Program. Methods An ideal health score (IHS) was calculated from 3 clinical factors (blood pressure, total cholesterol, and blood glucose levels) and 3 behavioral factors (smoking status, physical activity, and BMI), ascertained at baseline. Multi-population genome-wide association study (GWAS) was performed on IHS and binary ideal health using linear and logistic regression, respectively. Using the genome-wide significant SNPs from the IHS GWAS, we created a weighted IHS polygenic risk score (PRSIHS) which was used (i) to conduct a phenome-wide association study (PheWAS) of associations between PRSIHS and ICD-9 phenotypes and (ii) to further test for associations with mortality and selected CVD outcomes using logistic and Cox regression and, as an instrumental variable, in Mendelian Randomization. Results The discovery and replication cohorts consisted of 142,404 (119,129 European American (EUR); 16,495 African American (AFR)), and 45,766 (37,646 EUR; 5,366 AFR) participants, respectively. The mean age was 65.8 years (SD = 11.2) and 92.7% were male. Overall, 4.2% exhibited ideal CVH based on the clinical and behavioral factors. In the multi-population meta-analysis, variants at 17 loci were associated with IHS and each had known GWAS associations with multiple components of the IHS. PheWAS analysis in 456,026 participants showed that increased PRSIHS was associated with a lower odds ratio for many CVD outcomes and risk factors. Both IHS and PRSIHS measures of ideal CVH were associated with significantly less CVD outcomes and CVD mortality. Conclusion A set of high interest genetic variants contribute to the presence of ideal CVH in a multi-ethnic cohort of US Veterans. Genetically influenced ideal CVH is associated with lower odds of CVD outcomes and mortality.