Using 'Big Data' and Precision Medicine to Assess and Manage Suicide Risk in U.S. Veterans

使用“大数据”和精准医学评估和管理美国退伍军人的自杀风险

基本信息

  • 批准号:
    9842275
  • 负责人:
  • 金额:
    --
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2019
  • 资助国家:
    美国
  • 起止时间:
    2019-01-01 至 2020-12-31
  • 项目状态:
    已结题

项目摘要

Reducing suicide and suicidal behavior (i.e., self-directed violence) is a top priority for the Department of Veterans Affairs. Recent statistics indicate that, on average, 20 Veterans die by suicide in the U.S. each day. Family, adoption, and twin studies indicate that genetic factors account for 30-50% of the heritability in suicidal behavior. Numerous candidate gene and genome wide association studies (GWAS) have been conducted to identify variants associated with suicidal behavior; however, a major limitation of all prior genetic studies in this area of research is low statistical power due to small sample sizes and the infrequency with which suicidal behavior occurs. Another significant limitation concerns the failure of most prior genetic studies of suicidal behavior to include Veterans, despite the fact that Veterans are at significantly increased risk for suicide and suicidal behavior. The proposed research will address these limitations by leveraging the genetic and phenotypic data available through the Million Veteran Program (MVP) and other key administrative databases to perform the largest and most well-powered GWAS of suicidal behavior to date. The potential impact of identifying novel genetic markers that reliably predict suicidal behavior would be enormous. It could fundamentally shift current understanding of the biology of suicide, lead to new and improved approaches to suicide prevention for Veterans and civilians alike, and significantly improve VA's ongoing efforts to identify and intervene with high risk Veterans before they engage in suicidal behavior. Our long-term goal is to develop effective screening and intervention strategies to reduce the occurrence of suicide and suicidal behavior. The overall objective of this application is to discover novel genetic variants that increase Veterans' risk for suicidal behavior. The rationale for the proposed research is that identification of genetic variants that are reliably associated with suicidal behavior could lead to the discovery of novel, clinically-meaningful biological pathways that could, in turn, lead to new and improved suicide prevention approaches for Veterans. We will accomplish our overall objective by pursuing the following specific aims: In Aim 1, we will refine the phenotypes that we will use to define cases of suicidal behavior within MVP. In Aim 2, we will use GWAS to identify novel genetic variants associated with suicide attempts and suicidal ideation among Veterans in MVP. In Aim 3, we will replicate significant findings obtained from the MVP cohort in the Mid-Atlantic MIRECC and Army STARRS Cohorts. In Aim 4, we will explore whether the genetic findings obtained from MVP can be used to improve VA's ability to identify Veterans at risk for suicidal behavior.
减少自杀和自杀行为(即自我导向的暴力)是卫生部的首要任务

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Deep sequential neural network models improve stratification of suicide attempt risk among US veterans.
深度序列神经网络模型改善了美国退伍军人自杀未遂风险的分层。
  • DOI:
    10.1093/jamia/ocad167
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Martinez,Carianne;Levin,Drew;Jones,Jessica;Finley,PatrickD;McMahon,Benjamin;Dhaubhadel,Sayera;Cohn,Judith;MillionVeteranProgram;MVPSuicideExemplarWorkgroup;Oslin,DavidW;Kimbrel,NathanA;Beckham,JeanC
  • 通讯作者:
    Beckham,JeanC
{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

JEAN C. BECKHAM其他文献

JEAN C. BECKHAM的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('JEAN C. BECKHAM', 18)}}的其他基金

A Gene-by-Environment Genome-Wide Interaction Study (GEWIS) of Suicidal Thoughts and Behaviors in Veterans
退伍军人自杀想法和行为的基因与环境全基因组相互作用研究 (GEWIS)
  • 批准号:
    10487767
  • 财政年份:
    2022
  • 资助金额:
    --
  • 项目类别:
Impact of Reduced Cannabis Use on Functional Outcomes
减少大麻使用对功能结果的影响
  • 批准号:
    10437223
  • 财政年份:
    2021
  • 资助金额:
    --
  • 项目类别:
Functional Outcomes of Cannabis Use (FOCUS) in Veterans with Posttraumatic Stress Disorder
患有创伤后应激障碍的退伍军人使用大麻(FOCUS)的功能结果
  • 批准号:
    10275490
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
An evaluation of insomnia treatment to reduce cardiovascular risk in patients with posttraumatic stress disorder
失眠治疗降低创伤后应激障碍患者心血管风险的评估
  • 批准号:
    10199022
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Functional Outcomes of Cannabis Use (FOCUS) in Veterans withPosttraumatic Stress Disorder
患有创伤后应激障碍的退伍军人使用大麻(FOCUS)的功能结果
  • 批准号:
    10756927
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
An evaluation of insomnia treatment to reduce cardiovascular risk in patients with posttraumatic stress disorder
失眠治疗降低创伤后应激障碍患者心血管风险的评估
  • 批准号:
    10647818
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
An evaluation of insomnia treatment to reduce cardiovascular risk in patients with posttraumatic stress disorder
失眠治疗降低创伤后应激障碍患者心血管风险的评估
  • 批准号:
    10471176
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Functional Outcomes of Cannabis Use (FOCUS) in Veterans withPosttraumatic Stress Disorder
患有创伤后应激障碍的退伍军人使用大麻(FOCUS)的功能结果
  • 批准号:
    10508499
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Using 'Big Data' and Precision Medicine to Assess and Manage Suicide Risk in U.S. Veterans
使用“大数据”和精准医学评估和管理美国退伍军人的自杀风险
  • 批准号:
    9483413
  • 财政年份:
    2019
  • 资助金额:
    --
  • 项目类别:
Impact of Reduced Cannabis Use on Functional Outcomes
减少大麻使用对功能结果的影响
  • 批准号:
    10302325
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:

相似海外基金

Investigating the Adoption, Actual Usage, and Outcomes of Enterprise Collaboration Systems in Remote Work Settings.
调查远程工作环境中企业协作系统的采用、实际使用和结果。
  • 批准号:
    24K16436
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
WELL-CALF: optimising accuracy for commercial adoption
WELL-CALF:优化商业采用的准确性
  • 批准号:
    10093543
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Collaborative R&D
Unraveling the Dynamics of International Accounting: Exploring the Impact of IFRS Adoption on Firms' Financial Reporting and Business Strategies
揭示国际会计的动态:探索采用 IFRS 对公司财务报告和业务战略的影响
  • 批准号:
    24K16488
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
ERAMET - Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
ERAMET - 快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
  • 批准号:
    10107647
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    EU-Funded
Assessing the Coordination of Electric Vehicle Adoption on Urban Energy Transition: A Geospatial Machine Learning Framework
评估电动汽车采用对城市能源转型的协调:地理空间机器学习框架
  • 批准号:
    24K20973
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
Ecosystem for rapid adoption of modelling and simulation METhods to address regulatory needs in the development of orphan and paediatric medicines
快速采用建模和模拟方法的生态系统,以满足孤儿药和儿科药物开发中的监管需求
  • 批准号:
    10106221
  • 财政年份:
    2024
  • 资助金额:
    --
  • 项目类别:
    EU-Funded
De-Adoption Beta-Blockers in patients with stable ischemic heart disease without REduced LV ejection fraction, ongoing Ischemia, or Arrhythmias: a randomized Trial with blinded Endpoints (ABbreviate)
在没有左心室射血分数降低、持续性缺血或心律失常的稳定型缺血性心脏病患者中停用β受体阻滞剂:一项盲法终点随机试验(ABbreviate)
  • 批准号:
    481560
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Operating Grants
Our focus for this project is accelerating the development and adoption of resource efficient solutions like fashion rental through technological advancement, addressing longer in use and reuse
我们该项目的重点是通过技术进步加快时装租赁等资源高效解决方案的开发和采用,解决更长的使用和重复使用问题
  • 批准号:
    10075502
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Grant for R&D
Engage2innovate – Enhancing security solution design, adoption and impact through effective engagement and social innovation (E2i)
Engage2innovate — 通过有效参与和社会创新增强安全解决方案的设计、采用和影响 (E2i)
  • 批准号:
    10089082
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    EU-Funded
Collaborative Research: SCIPE: CyberInfrastructure Professionals InnoVating and brOadening the adoption of advanced Technologies (CI PIVOT)
合作研究:SCIPE:网络基础设施专业人员创新和扩大先进技术的采用 (CI PIVOT)
  • 批准号:
    2321091
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了