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

基本信息

批准号：
10553712
负责人：
Hilary Coon
金额：
$ 38.13万
依托单位：
UNIVERSITY OF UTAH
依托单位国家：
美国
项目类别：
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/10553712
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 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 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 population innovation novel pharmacologic 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

项目摘要

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。尽管情况如此惊人，但过去 20 年来，美国的自杀死亡率仍上升了 33%。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难以控制，但不可否认的是，环境因素是不可否认的。影响，有证据表明遗传因素在自杀死亡中发挥着重要作用，而遗传研究。因此，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这种策略已经让其他研究小组充分了解了自杀想法和行为。然而，自杀行为可能很难量化和表征。利用犹他州可用的独特资源，帮助那些具有广泛自杀风险的个人。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 USGRS 目前已确定超过 6,000 名人口的 DNA。自杀死亡人数在前所未有的二十年里每年增加约 650 例我们与犹他州卫生部的中央体检办公室 (OME) 合作。完成了 281 例犹他州自杀死亡事件的全基因组序列 (WGS) 数据我们有这些病例和犹他州其他自杀病例的 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综合医疗记录还包括独特的表型数据。有关家庭风险的信息远远超过通过遗传记录获得的其他数据资源回到 1700 年代，真正了解自杀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该提案的重点是识别、验证、特征描述和自杀死亡。具有高功能影响的变异的复制意味着基因和基因途径对风险很重要从我们的 WGS 数据中，我们已经检测到高影响结构变异 (SV) 和单一死亡。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。