Genome-Wide Association Analysis of Suicide Death

自杀死亡的全基因组关联分析

基本信息

批准号：
10032654
负责人：
Anna R. Docherty
金额：
$ 66.92万
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：
2020-08-17 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10032654
关键词：
Accounting Admixture Age Attention deficit hyperactivity disorder Clinical Complex Computerized Medical Record Craniocerebral Trauma DNA Data Data Aggregation Databases Development Diagnosis Diagnostic Environmental Exposure Epidemiology Etiology Feeling suicidal Funding Genetic Genetic Enhancement Genetic Heterogeneity Genetic Models Genetic Risk Genetic study Genotype Heritability Individual Link Manic Medical Medical Examiners Medical Genetics Medical Records Metabolic Modeling Molecular Genetics Mood Disorders National Institute of Mental Health Nature Pain Pathway interactions Pharmaceutical Preparations Phenotype Population Population Database Predictive Value Pregnancy Prevalence Psychiatry Psychopathology Psychotic Disorders Public Health Research Resources Risk Risk Factors Sampling Schizophrenia Sex Differences Signal Transduction Site Suicide Suicide attempt Suicide prevention Testing United States Utah Variant Work alcohol use disorder autism spectrum disorder biobank clinical heterogeneity clinical phenotype clinically actionable clinically relevant cohort comorbidity follow-up genetic analysis genetic risk factor genetic variant genome wide association study genome-wide genome-wide analysis health record ideation improved mortality risk novel opioid use population based predictive modeling psychiatric genomics sex statistics suicidal morbidity suicidal risk

项目摘要

PROJECT SUMMARY The current proposal seeks to clarify the mechanisms underlying suicide death. Suicide constitutes a severe and steadily worsening public health crisis, and suicide prevention has become a primary focus of NIMH efforts. Aggregated data across multiple large genetic studies yield heritability estimates of suicide death at approximately 45%. However, research on risk factors to date has been largely confined to epidemiological observations, with a lack of access to molecular genetic data on suicide death. This lack of access has resulted in an overwhelming focus on the genetic study of subthreshold phenotypes—ideation and attempt— which very rarely result in suicide. Currently, positive predictive values for suicide attempt are high (.9), while positive predictive values for suicide death continue to hover near zero. This research team has unprecedented access to DNA from thousands of independent, population-based suicide deaths from the Utah Office of the Medical Examiner. DNA resources are enhanced by a wealth of electronic medical record and environmental exposure data on all suicides, using the Utah Population Database, a unique resource of >10 million residents. Due to the extreme and unambiguous nature of suicide relative to psychiatric phenotypes, genotyping and genome-wide association analysis of the first 3,413 cases and 14,848 matched controls has already resulted in genome-wide significant signals and strong polygenic signal. Five novel, rare missense SNPs are also significantly associated with suicide death in these preliminary data. By genotyping additional and incoming suicide deaths, this project aims to replicate and significantly expand on genetic discoveries. In addition, approximately 20% of the population-based suicides evidence significant ancestry admixture, providing valuable diversity to enhance both discovery and generalizability. This research team will work closely in partnership with the Psychiatric Genomics Consortium and UK Biobank to examine new data on suicide death, test clinically informative risk models, and leverage large external cohorts to model complex suicide etiologies. Some of the high-impact deliverables from this project include a) comprehensive co- morbidity, mode of death, and risk factor statistics from the largest population-based suicide cohort to date, b) the first genome-wide data and summary statistics for suicide death, linked to a wealth of risk phenotypes, polygenic risks, and diagnoses (e.g., ADHD, affective disorders, alcohol use disorder, autism spectrum disorder, pain, mania, metabolic conditions, opiate use, pregnancy, psychosis), c) genetic correlation estimates of suicide death with a range of phenotypes, for the development of genetic risk models, and d) clinically informative genetic and environmental predictors of suicide, accounting for sex, ancestry, and age.

项目概要目前的提案旨在澄清自杀构成严重死亡的机制。公共卫生危机不断恶化，预防自杀已成为 NIMH 的首要关注点多项大型遗传研究的汇总数据得出了自杀死亡的遗传性估计值大约 45%。然而，迄今为止对危险因素的研究主要局限于流行病学。观察，缺乏有关自杀死亡的分子遗传学数据。导致人们对阈下表型的遗传研究产生了压倒性的关注——构思和尝试—— 目前，自杀企图的阳性预测值很高（0.9），而自杀企图很少。该研究小组对自杀死亡的阳性预测值继续徘徊在零附近。史无前例地从犹他州数千名独立的、基于人群的自杀死亡事件中获取 DNA 丰富的电子病历和 DNA 资源增强了法医办公室的能力。所有自杀事件的环境暴露数据，使用犹他州人口数据库，这是一个超过 10 的独特资源由于自杀相对于精神表型的极端性和明确性，对首批 3,413 例病例和 14,848 例匹配对照进行基因分型和全基因组关联分析已经产生了全基因组的重要信号和强多基因信号。通过额外的基因分型，在这些初步数据中，SNP 也与自杀死亡显着相关。和即将到来的自杀死亡，该项目旨在复制并显着扩展基因发现。此外，大约 20% 的人口自杀事件表明有明显的血统混合，提供有价值的多样性以增强发现和普遍性该研究团队将努力工作。与精神病学基因组学联盟和英国生物银行密切合作，检查有关的新数据自杀死亡，测试临床信息丰富的风险模型，并利用大型外部队列来建模复杂的模型该项目的一些具有高影响力的成果包括：迄今为止最大的基于人群的自杀队列的发病率、死亡方式和危险因素统计数据，b) 第一个全基因组数据和自杀死亡汇总统计数据，与大量风险表型相关，多基因风险和诊断（例如多动症、情感障碍、酒精使用障碍、自闭症谱系疾病、疼痛、躁狂、代谢状况、阿片类药物使用、怀孕、精神病），c) 遗传相关性估计具有一系列表型的自杀死亡，用于开发遗传风险模型，以及 d) 临床自杀的信息遗传和环境预测因子，考虑了性别、血统和年龄。