Diversity and scale: Genetic architecture of 2068 traits in the VA Million Veteran Program
Anurag Verma, Jennifer E. Huffman, Alex A Rodriguez, Mitchell Conery, Molei Liu, Yuk‐Lam Ho, Youngdae Kim, David Heise, Lindsay Guare, Vidul Ayakulangara Panickan, Helene Garcon, Franciel Linares, Lauren Costa, Ian Goethert, Ryan Tipton, Jacqueline Honerlaw, Laura Davies, Stacey B. Whitbourne, Jérémy Cohen, Daniel Posner, Rahul Sangar, Michael Murray, Xuan Wang, Daniel Dochtermann, Poornima Devineni, Yunling Shi, Tarak Nandi, Themistocles L. Assimes, Charles A. Brunette, Robert J. Carroll, Royce E. Clifford, Scott L. DuVall, Joel Gelernter, Adriana M. Hung, Sudha K. Iyengar, Jacob Joseph, Rachel L. Kember, Henry R. Kranzler, Colleen Morse Kripke, Daniel F. Levey, Shiuh‐Wen Luoh, Victoria C. Merritt, Cassie Overstreet, Joseph D. Deak, Struan F.A. Grant, Renato Polimanti, Panos Roussos, Gabrielle Shakt, Yan V. Sun, Noah L. Tsao, Sanan Venkatesh, Georgios Voloudakis, Amy C. Justice, Edmon Begoli, Rachel Ramoni, Georgia D. Tourassi, Saiju Pyarajan, Philip S. Tsao, Christopher J. O’Donnell, Sumitra Muralidhar, Jennifer Moser, Juan P. Casas, Alexander G. Bick, Wei Zhou, Tianxi Cai, Benjamin F. Voight, Kelly Cho, J. Michael Gaziano, Ravi Madduri, Scott M. Damrauer, Katherine P. Liao
Abstract
One of the justifiable criticisms of human genetic studies is the underrepresentation of participants from diverse populations. Lack of inclusion must be addressed at-scale to identify causal disease factors and understand the genetic causes of health disparities. We present genome-wide associations for 2068 traits from 635,969 participants in the Department of Veterans Affairs Million Veteran Program, a longitudinal study of diverse United States Veterans. Systematic analysis revealed 13,672 genomic risk loci; 1608 were only significant after including non-European populations. Fine-mapping identified causal variants at 6318 signals across 613 traits. One-third ( n = 2069) were identified in participants from non-European populations. This reveals a broadly similar genetic architecture across populations, highlights genetic insights gained from underrepresented groups, and presents an extensive atlas of genetic associations.