Diversity and scale: Genetic architecture of 2,068 traits in the VA Million Veteran Program

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 as 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.

人类遗传学研究存在一项广受认可的合理诟病：研究参与者的群体多样性严重不足。必须通过规模化手段解决样本纳入不足的问题，方能精准识别疾病致病因子，并阐明健康差异的遗传根源。本研究针对美国退伍军人事务部（Department of Veterans Affairs）百万退伍军人项目（Million Veteran Program）中635966名参与者的2068项性状开展全基因组关联分析（genome-wide association），该项目是一项针对美国多元化退伍军人的纵向研究。经系统分析，共鉴定出13672个基因组风险位点；其中1608个位点仅在纳入非欧洲人群后才呈现统计学显著性。通过精细定位分析，我们在613项性状的6318个关联信号中鉴定出致病变异。其中三分之一（样本量n=2069）的参与者来自非欧洲人群。本研究揭示了不同人群间大体相似的遗传结构，凸显了从代表性不足群体中获取的遗传研究价值，并提供了一份规模宏大的遗传关联图谱。