Using 'Big Data' and Precision Medicine to Assess and Manage Suicide Risk in U.S. Veterans

减少自杀和自杀行为(即自我导向的暴力)是新闻部的当务之急 退伍军人事务部。最近的统计数据显示，美国平均每天有20名退伍军人自杀身亡。 家庭、收养和双胞胎研究表明，遗传因素占自杀遗传率的30%-50%。 行为。许多候选基因和基因组广泛的关联研究(GWAS)已经被进行到 识别与自杀行为相关的变异；然而，所有先前的遗传学研究在这方面的主要限制 研究领域是统计能力低，因为样本量小，自杀的频率很低 行为就会发生。另一个重要的限制是先前大多数自杀基因研究的失败。 包括退伍军人在内的行为，尽管退伍军人自杀和 自杀行为。 拟议的研究将通过利用现有的遗传和表型数据来解决这些限制 通过百万退伍军人计划(MVP)和其他关键管理数据库执行最大和 到目前为止最有自杀行为的人。识别新基因的潜在影响 可靠地预测自杀行为的标记物将是巨大的。它可以从根本上改变电流 了解自杀的生物学，导致新的和改进的自杀预防方法 退伍军人和平民，并显著改善退伍军人管理局正在进行的识别和干预高危人群的努力 在退伍军人从事自杀行为之前，要冒险。 我们的长期目标是制定有效的筛查和干预策略，以减少 自杀和自杀行为。这项应用的总体目标是发现新的遗传变异， 增加退伍军人自杀行为的风险。拟议研究的基本原理是确定 与自杀行为可靠相关的基因变异可能会导致发现新的， 临床上有意义的生物途径，反过来可能导致新的和改进的自杀预防 退伍军人的方法。我们将通过以下具体目标，实现总体目标： 在目标1中，我们将改进我们将用来定义MVP中自杀行为的表型。在AIM 2，我们将使用GWAS来识别与自杀企图和自杀意念相关的新的基因变异 在MVP的退伍军人中。在目标3中，我们将复制从MVP队列中获得的重要发现 中大西洋MIRECC和陆军STARRS队列。在目标4中，我们将探索基因发现是否 从MVP获得的信息可以用于提高退伍军人识别有自杀行为风险的退伍军人的能力。

Reducing suicide and suicidal behavior (i.e., self-directed violence) is a top priority for the Department of Veterans Affairs. Recent statistics indicate that, on average, 20 Veterans die by suicide in the U.S. each day. Family, adoption, and twin studies indicate that genetic factors account for 30-50% of the heritability in suicidal behavior. Numerous candidate gene and genome wide association studies (GWAS) have been conducted to identify variants associated with suicidal behavior; however, a major limitation of all prior genetic studies in this area of research is low statistical power due to small sample sizes and the infrequency with which suicidal behavior occurs. Another significant limitation concerns the failure of most prior genetic studies of suicidal behavior to include Veterans, despite the fact that Veterans are at significantly increased risk for suicide and suicidal behavior. The proposed research will address these limitations by leveraging the genetic and phenotypic data available through the Million Veteran Program (MVP) and other key administrative databases to perform the largest and most well-powered GWAS of suicidal behavior to date. The potential impact of identifying novel genetic markers that reliably predict suicidal behavior would be enormous. It could fundamentally shift current understanding of the biology of suicide, lead to new and improved approaches to suicide prevention for Veterans and civilians alike, and significantly improve VA's ongoing efforts to identify and intervene with high risk Veterans before they engage in suicidal behavior. Our long-term goal is to develop effective screening and intervention strategies to reduce the occurrence of suicide and suicidal behavior. The overall objective of this application is to discover novel genetic variants that increase Veterans' risk for suicidal behavior. The rationale for the proposed research is that identification of genetic variants that are reliably associated with suicidal behavior could lead to the discovery of novel, clinically-meaningful biological pathways that could, in turn, lead to new and improved suicide prevention approaches for Veterans. We will accomplish our overall objective by pursuing the following specific aims: In Aim 1, we will refine the phenotypes that we will use to define cases of suicidal behavior within MVP. In Aim 2, we will use GWAS to identify novel genetic variants associated with suicide attempts and suicidal ideation among Veterans in MVP. In Aim 3, we will replicate significant findings obtained from the MVP cohort in the Mid-Atlantic MIRECC and Army STARRS Cohorts. In Aim 4, we will explore whether the genetic findings obtained from MVP can be used to improve VA's ability to identify Veterans at risk for suicidal behavior.