A Gene-by-Environment Genome-Wide Interaction Study (GEWIS) of Suicidal Thoughts and Behaviors in Veterans

平均每天有18名退伍军人自杀身亡。事实上，从2009年到2018年，超过64，000名退伍军人死亡 死于自杀的人数与越战中的美军死亡人数大致相同， 伊拉克和阿富汗的总和。虽然自杀想法和行为的遗传率估计在30- 55%，自杀的遗传基础在很大程度上仍然未知。我们的研究团队领导并参与了 迄今为止，许多关于自杀想法和行为的大型全基因组关联研究（GWAS）， 包括在退伍军人和军人样本中进行的每一项最大规模的研究。我们最近的工作涉及到 在参加百万退伍军人计划的40多万名退伍军人中进行自杀企图的GWAS 计划（MVP）。本研究确定了多个泛种族和祖先特异性的全基因组显著位点 与退伍军人自杀未遂的风险有关。此外，途径分析发现， 具有高临床意义的许多生物学途径的过度表达，包括催产素信号传导， 多巴胺能突触、皮质醇合成与分泌、多巴胺能突触与昼夜节律。在 与此同时，我们一直在研究自杀想法和行为的各种环境风险因素 在退伍军人，如性创伤，创伤后应激障碍，抑郁症，物质使用障碍，边缘性人格 疾病，慢性疼痛，创伤性脑损伤和睡眠障碍（以及其他）。我们也在积极 努力确定新的环境风险因素，包括地理空间因素[例如，社会经济地位 (SES)其中许多在以前的大规模自杀遗传研究中没有被检查过 风险我们认为，要完全了解复杂的表型，需要了解相关的 遗传风险因素、相关环境风险因素以及这些风险因素相互作用的方式。 因此，在我们的研究计划的下一阶段，我们建议进行最大的基因-由- 环境全基因组相互作用研究（GEWIS）的自杀想法和行为的日期。这项工作将 使我们能够找到新的方法来改善高风险退伍军人的识别，同时也大大提高了 我们对自杀的生物学基础的理解我们的长期目标是发展有效的筛查， 干预策略，以减少退伍军人自杀和自杀行为的发生。整体 这项具体应用的目的是发现新的、可复制的GxE相互作用， 自杀想法和行为的风险。这项研究的基本原理是识别遗传变异， 环境因素，以及与自杀想法和行为可靠相关的GxE相互作用 可能会导致更好地识别高风险的退伍军人和发现额外的临床意义 生物途径。这些发现反过来又可能导致新的和更好的治疗和预防 接近。在目标1中，我们将确定与环境风险最密切相关的环境风险因素。 MVP队列中自杀企图、自杀意念和自杀死亡的发生率。在目标2中，我们 进行迄今为止最大规模的自杀想法和行为的GEWIS，以识别新的、可复制的GxE 预测自杀企图，自杀意念和退伍军人自杀死亡的相互作用。在目标3中， 为了评估我们研究结果的临床效用，我们将与我们的业务合作伙伴合作，以确定 我们的顶级遗传风险因素，环境风险因素和GxE相互作用的增加提高了预测 恢复参与和协调健康退伍军人增强治疗（REACH VET） MVP队列中的自杀风险算法。从拟议的工作中获得的结果可以从根本上 改变对自杀生物学的理解，导致新的和改进的治疗方法，并改善VA的努力， 识别和干预有自杀风险的退伍军人。因此，本申请具有巨大的优势。 潜在的先进VA的使命和改善退伍军人的健康，安全和福祉。

On average, 18 Veterans die by suicide each day. In fact, from 2009 to 2018, more than 64,000 Veterans died by suicide, which is roughly the same number of U.S. military fatalities that resulted from the wars in Vietnam, Iraq, and Afghanistan combined. While heritability estimates for suicidal thoughts and behaviors range from 30- 55%, the genetic basis of suicide remains largely unknown. Our research team has led and participated in many of the largest genome-wide association studies (GWAS) of suicidal thoughts and behaviors to date, including each of the largest conducted in Veteran and military samples. Our most recent work has involved conducting a GWAS of suicide attempts among more than 400,000 Veterans enrolled in the Million Veteran Program (MVP). This study identified multiple pan-ethnic and ancestry-specific genome-wide significant loci associated with risk for attempting suicide among Veterans. Moreover, pathway analyses found evidence of overrepresentation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. In parallel, we have been studying a broad array of environmental risk factors for suicidal thoughts and behaviors in Veterans, such as sexual trauma, PTSD, depression, substance use disorders, borderline personality disorder, chronic pain, traumatic brain injury, and sleep disturbance (among others). We are also actively working to identify novel environmental risk factors, including geospatial factors [e.g., socioeconomic status (SES), rurality], many of which have not been previously examined in large-scale genetic studies of suicide risk. We believe that complete understanding of a complex phenotype requires understanding of relevant genetic risk factors, relevant environmental risk factors, as well as the ways in which these risk factors interact. Accordingly, during the next phase of our program of research, we propose to conduct the largest gene-by- environment genome-wide interaction study (GEWIS) of suicidal thoughts and behaviors to date. This work will enable us to identify new ways to improve the identification of high-risk Veterans, while also greatly increasing our understanding of the biological basis of suicide. Our long-term goal is to develop effective screening and intervention strategies to reduce the occurrence of suicide and suicidal behavior among Veterans. The overall objective of this specific application is to discover novel, replicable GxE interactions that increase Veterans’ risk for suicidal thoughts and behaviors. The rationale for this research is that identification of genetic variants, environmental factors, and GxE interactions that are reliably associated with suicidal thoughts and behaviors could lead to improved identification of high-risk Veterans and the discovery of additional clinically-meaningful biological pathways. Such findings could, in turn, lead to new and improved treatment and prevention approaches. In Aim 1, we will determine the environmental risk factors most strongly associated with the occurrence of suicide attempts, suicidal ideation, and suicide deaths within the MVP cohort. In Aim 2, we will conduct the largest GEWIS of suicidal thoughts and behaviors to date to identify novel, replicable GxE interactions predictive of suicide attempts, suicidal ideation, and suicide deaths among Veterans. In Aim 3, in order to evaluate the clinical utility of our findings, we will work with our operational partners to determine if the addition of our top genetic risk factors, environmental risk factors, and GxE interactions improves the predictive utility of the Recovery Engagement and Coordination for Health-Veterans Enhanced Treatment (REACH VET) suicide risk algorithm within the MVP cohort. Findings obtained from the proposed work could fundamentally shift understanding of the biology of suicide, lead to new and improved treatments, and improve VA’s efforts to identify and intervene with Veterans at risk for suicide. As such, the present application has tremendous potential to advanced VA’s mission and improve Veterans’ health, safety, and well-being.