Genome-Wide Association Analysis of Suicide Death

项目总结 目前的提案试图澄清自杀死亡的潜在机制。自杀构成了严重的 和日益恶化的公共卫生危机，自杀预防已成为NIMH的首要重点 努力。多项大型基因研究的汇总数据得出了自杀死亡的遗传力估计 大约45%。然而，到目前为止，对危险因素的研究主要局限于流行病学。 无法获得自杀死亡的分子遗传数据。这种缺乏访问权限的情况 导致了对亚阈值表型的遗传研究的压倒性关注--构思和尝试-- 很少会导致自杀。目前，自杀未遂的阳性预测值很高(0.9)，而 自杀死亡的积极预测值继续徘徊在零附近。这个研究团队已经 从犹他州数千名独立的、基于人群的自杀死亡中史无前例地获得DNA 法医办公室。DNA资源因丰富的电子病历和 所有自杀的环境暴露数据，使用犹他州人口数据库，这是&gt；10的一个独特资源 百万居民。由于自杀相对于精神症状的极端和明确的性质， 前3,413例患者和14,848名匹配对照的基因分型和全基因组关联分析 已经产生了全基因组显著信号和强烈的多基因信号。五个新奇的、罕见的误解 在这些初步数据中，SNP也与自杀死亡显著相关。通过对其他基因分型 和即将到来的自杀死亡，这个项目的目标是复制和显著扩大基因发现。在……里面 此外，大约20%的以人口为基础的自杀者有明显的血统混杂， 提供有价值的多样性，以提高发现和推广能力。这个研究小组将致力于 与精神病学基因组联合会和英国生物库密切合作，审查关于 自杀死亡，测试具有临床信息性的风险模型，并利用大量外部队列来模拟复杂性 自杀原因。该项目的一些高影响交付成果包括)全面的联合- 迄今最大的基于人群的自杀队列的发病率、死亡模式和风险因素统计，b) 第一个全基因组范围的自杀死亡数据和汇总统计数据，与大量的风险表型有关， 多基因风险和诊断(例如，ADHD、情感障碍、酒精使用障碍、自闭症谱系 疾病、疼痛、躁狂、新陈代谢状况、鸦片使用、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 自杀的信息性遗传和环境预测因子，包括性别、血统和年龄。

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.