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

使用全基因组测序 (WGS) 从 10,000 例自杀死亡病例的人口资源中发现遗传风险

• 批准号: 10337286
• 负责人: Hilary Coon
• 金额: $ 40.03万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10337286
• 关键词: Age; Autopsy; Back; Behavior; Cause of Death; Cessation of life; Collaborations; Complex; DNA; Data; Development; Diagnosis; Diagnostic; Environment; Environmental Exposure; Feeling suicidal; Genealogy; Genes; Genetic; Genetic Enhancement; Genetic Risk; Genetic study; Geography; Hand; Health; Heritability; Individual; Intervention; Knowledge; Link; Medical; Medical Examiners; Medical Records; Meta-Analysis; Methods; Molecular; Outcome; Pathway interactions; Pharmaceutical Preparations; Pharmacology; Phenotype; Play; Population; Population Database; Public Health; Recording of previous events; Records; Recurrence; Research; Resources; Risk; Risk Factors; Role; Sample Size; Sampling; Services; Single Nucleotide Polymorphism; Suicide; Utah; Validation; Variant; data resource; demographics; effective intervention; genetic variant; genome sequencing; genome wide association study; genome-wide; high risk; innovation; novel; phenotypic data; polygenic risk score; population based; preventable death; protein protein interaction; risk perception; risk variant; sample collection; suicidal behavior; suicidal morbidity; suicidal risk; suicide rate; trait; variant detection; whole genome

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.

抽象的 自杀是第十大死因，仅在美国每年就有超过 47,000 例可预防的死亡。这 过去20年，美国自杀死亡率上升了33%。尽管发生了这样的戏剧性事件 在公共卫生危机中，自杀研究远远落后于其他主要健康状况，因为人们认为 危险因素过于复杂且无法控制，无法进行研究。重要的是，虽然环境无可否认 影响，有证据表明遗传因素在自杀死亡中发挥着重要作用。在研究遗传的同时 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 自杀念头和行为。这一策略使其他研究小组能够充分获取 统计样本。然而，自杀行为可能难以量化和表征 具有多种日后自杀死亡风险的个人。利用犹他州可用的独特资源 自杀遗传风险研究（USGRS），我们能够研究明确的、高影响力的遗传风险 自杀死亡直接影响健康。 USGRS 目前已确定超过 6,000 名人口的 DNA 自杀死亡；在前所未有的二十年里，该资源每年增加约 650 个案例 与犹他州卫生部的中央体检医师办公室 (OME) 合作。我们有 完成了 281 例犹他州自杀死亡事件的全基因组序列 (WGS) 数据 高遗传风险。我们有关于这些案例和犹他州其他自杀案例的 Illumina PsychArray 数据（总计 N=4,382）。所有病例均链接至犹他州人口数据库 (UPDB)，这是一个全州范围的资源，其中包括 人口统计数据和全面的医疗记录。 UPDB 表型数据还包括独特的 有关家庭风险的信息远远超过通过家谱记录获得的其他数据资源 回到1700年代。真正了解自杀死亡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，我们必须具体了解风险 与自杀死亡有关。该提案侧重于识别、验证、表征和 具有高功能影响的变异的复制，涉及对风险重要的基因和基因途径 自杀死亡。从我们的 WGS 数据中，我们已经检测到高影响的结构变异 (SV) 和单一 核苷酸变异（SNV）显示全基因组显着的基因途径富集和蛋白质-蛋白质 互动。这些途径也得到了与我们全基因组关联有关的基因的支持 对犹他州 3,413 例自杀死亡的分析表明罕见风险和常见风险在功能层面上存在重叠 变化。广泛的家族风险数据和大样本量将使我们能够选择 760 个额外的子集 具有较高遗传风险的自杀来复制和扩展我们目前的发现，为 识别高风险个体，并制定有针对性的干预措施。