Genome-Wide Association Analysis of Suicide Death

自杀死亡的全基因组关联分析

• 批准号: 10239061
• 负责人: Anna R. Docherty
• 金额: $ 63.56万
• 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: 2020-08-17 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10239061
• 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; Psychoses; 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; risk prediction; sex; statistics; suicidal morbidity; suicidal risk

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.

项目摘要 目前的建议旨在澄清自杀死亡的机制。自杀构成严重的 公共卫生危机不断恶化，自杀预防已成为NIMH的主要重点 努力多项大型遗传研究的汇总数据得出自杀死亡的遗传度估计值， 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， 由于无法获得自杀死亡的分子遗传学数据，这种缺乏接触的情况 导致了对阈下表型的遗传学研究的压倒性关注-构思和尝试- 很少导致自杀。目前，自杀企图的阳性预测值很高（0.9），而 自杀死亡的阳性预测值继续徘徊在零附近。这个研究小组有 从犹他州的数千名独立的、基于人口的自杀死亡病例中前所未有地获得了DNA 法医办公室。丰富的电子医疗记录和 所有自杀的环境暴露数据，使用犹他州人口数据库，一个独特的资源， 百万居民。由于自杀相对于精神病表型的极端和明确的性质， 对前3,413例病例和14,848例匹配对照进行了基因分型和全基因组关联分析， 已经导致了全基因组显著信号和强多基因信号。五个小说，罕见的误解 在这些初步数据中，SNP也与自杀死亡显著相关。通过基因分型， 和即将到来的自杀死亡，该项目旨在复制和显着扩大基因发现。在 此外，大约20%的基于人口的自杀证据明显的祖先混合， 提供有价值的多样性以增强发现性和概括性。这个研究小组将 与精神病基因组学联盟和英国生物银行密切合作，研究关于 自杀死亡，测试临床信息风险模型，并利用大型外部队列来模拟复杂的 自杀病因学该项目的一些高影响力的可交付成果包括：a）全面的合作， 迄今为止最大的基于人群的自杀队列的发病率、死亡方式和风险因素统计，B） 第一个自杀死亡的全基因组数据和汇总统计数据，与大量的风险表型相关， 多基因风险和诊断（例如，注意力缺陷多动障碍、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、妊娠、精神病），c）遗传相关性估计 自杀死亡与一系列表型，为发展遗传风险模型，和d）临床 自杀的信息遗传和环境预测因子，包括性别、血统和年龄。