Genetic risk discovery using WGS from a population-based resource of 10,000 suicide deaths with DNA

摘要 自杀是第十大死亡原因，仅在美国每年就有超过47，000例可预防的死亡。的 在过去的二十年里，美国的自杀死亡率上升了33%。尽管这一戏剧性的 公共卫生危机，自杀研究远远落后于其他主要的健康状况，因为人们认为， 风险因素过于复杂和无法控制，无法进行研究。重要的是，虽然环境不可否认 有证据表明，遗传因素在自杀死亡中起着重要作用。虽然遗传学的研究 因此，自杀风险是有希望的，大多数自杀遗传学研究都集中在更常见的特征上， 自杀的想法和行为。这一战略使其他研究小组能够充分获得 电动样品。然而，自杀行为很难量化， 这些人有很大的自杀死亡风险。利用犹他州的独特资源 自杀遗传风险研究（USGRS），我们能够研究明确的，高影响的遗传风险 直接影响自杀死亡者的健康。USGRS目前拥有来自超过6，000人口的DNA-确定 自杀死亡;这一资源在前所未有的二十年中每年增加约650例 与犹他州卫生部集中的医学检查员办公室（OME）合作。我们有 完整的全基因组序列（WGS）数据的一个子集的281个犹他州自杀死亡的选择， 高遗传风险。我们有Illumina PsychArray关于这些案例和其他犹他州自杀事件的数据（总数 N= 4，382）。所有病例都与犹他州人口数据库（UTB）相关联，该数据库是一个全州范围的资源，包括 人口统计数据和全面的医疗记录。BMPB表型数据还包括独特的 有关家庭风险的信息远远超过其他数据资源， 追溯到18世纪真正了解自杀死亡的风险并实施高效的干预措施 为那些最有可能死亡的人提供适当的，有针对性的服务，我们必须特别了解风险 与自杀死亡有关。本提案侧重于识别、验证、表征和 具有高功能影响的变异体的复制，这些变异体涉及对疾病风险重要的基因和基因途径。 自杀死亡。从我们的WGS数据中，我们已经检测到了高影响力的结构变体（SV）和单个 显示全基因组显著基因通路富集和蛋白质-蛋白质 交互.这些途径也得到了与我们全基因组关联相关的基因的支持 对3，413例犹他州自杀死亡的分析表明，在罕见和常见风险的功能水平上存在重叠 变化量广泛的家族风险数据和大样本量将允许我们选择760个额外的子集 具有增强遗传风险的自杀者复制和扩展我们目前的发现， 识别高危人群，并制定有针对性的干预措施。

ABSTRACT Suicide is the 10th leading cause of death, with over 47,000 preventable deaths per year in the U.S. alone. The rate of suicide death across the U.S. has risen by 33% over the past two decades. In spite of this dramatic public health crisis, suicide research lags far behind other major health conditions due to the perception that risk factors are too complex and uncontrollable for study. Importantly, while environment has undeniable impact, evidence suggests that genetic factors play a major role in suicide death. While the study of genetic risks is therefore promising, most studies of suicide genetics have focused on the much more common traits of suicidal thoughts and behaviors. This strategy has allowed other research groups to acquire sufficiently statistically-powered samples. However, suicidal behaviors can be difficult to quantify, and represent individuals with a wide range of risk for later suicide death. Using the unique resources available to the Utah Suicide Genetic Risk Study (USGRS), we are able to study the genetic risks of the unambiguous, high-impact health outcome of suicide death directly. The USGRS currently has DNA from >6,000 population-ascertained suicide deaths; this resource grows by ~650 cases per year through an unprecedented two-decade collaboration with the Utah Department of Health’s centralized Office of the Medical Examiner (OME). We have completed whole genome sequence (WGS) data on a subset of 281 of the Utah suicide deaths selected for high genetic risk. We have Illumina PsychArray data on these cases and additional Utah suicides (total N=4,382). All cases are linked to the Utah Population Database (UPDB), a statewide resource that includes demographic data and comprehensive medical records. The UPDB phenotypic data also includes unique information on familial risk far exceeding that of other data resources through genealogical records that go back to the 1700s. To truly understand risk of suicide death and to implement highly effective interventions that provide appropriate, targeted services to those most likely to die, we must understand the risks specifically associated with suicide deaths. This proposal focuses on the identification, validation, characterization, and replication of variants with high functional impact that implicate genes and gene pathways important for risk of suicide death. From our WGS data, we have already detected high-impact structural variants (SVs) and single nucleotide variants (SNVs) showing genome-wide significant gene pathway enrichment and protein-protein interactions. These pathways are also supported by genes implicated in our genome-wide association analyses of 3,413 Utah suicide deaths, suggesting overlap at the functional level of rare and common risk variation. Extensive familial risk data and large sample size will allow us to select an additional subset of 760 suicides with enhanced genetic risk to replicate and extend our current findings, setting the stage for identification of high-risk individuals, and for development of targeted interventions.