Examining Suicide Risk from a Biopsychosocial Framework: A Large-Scale Cross-Sectional Study

从生物心理社会框架审视自杀风险：一项大规模横断面研究

基本信息

批准号：
10537739
负责人：
Matthew Thompson
金额：
$ 2.52万
依托单位：
HENRY M. JACKSON FDN FOR THE ADV MIL/MED
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-08-15 至 2023-06-09
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10537739
关键词：
Address Adult Algorithms Anisotropy Area Behavior Behavioral Biological Brain Cross-Sectional Studies Data Data Set Detection Differentiation Antigens Educational workshop Feeling suicidal Functional Magnetic Resonance Imaging Generations Genes Genetic Goals Individual Intervention Investments Lateral Logistic Regressions Machine Learning Mental Depression Mentorship Methodology Modeling National Institute of Mental Health National Research Service Awards Participant Prefrontal Cortex Principal Investigator Psychosocial Factor Public Health Questionnaires Recording of previous events Research Research Personnel Research Priority Research Training Rest Risk Role Sampling Schizophrenia Self-Direction Series Structure Suicide Suicide attempt Suicide prevention Supervision Symptoms Technical Expertise Thinking Training Training Programs Trauma United Kingdom Violence Writing adverse childhood events anxiety symptoms behavioral disinhibition big biomedical data biobank biopsychosocial candidate marker career classification algorithm demographics depressive symptoms gray matter ideation imaging genetics improved individualized medicine multimodal neuroimaging multimodality neuroimaging polygenic risk score programs psychosocial skills statistics study population suicidal suicidal behavior suicidal morbidity suicidal risk symposium trend white matter

项目摘要

PROJECT SUMMARY/ABSTRACT Suicide remains a significant public health crisis nationally and globally. Suicide-related thoughts and behaviors are transdiagnostic phenomena associated with heterogeneous biopsychosocial risk indicators. Findings suggest that suicide risk is associated with distinct resting-state functional connectivity, structural brain differences, and polygenetic risk score (PRS) profiles. There are notable gaps in our understanding of biopsychosocial vulnerabilities for suicide. The first research gap involves a lack of in-depth understanding of candidate markers for differentiating between individuals who only think about self-directed violence versus those who ultimately attempt suicide. The second research gap involves a lack of an in-depth understanding of how biological risk indicators in combination with psychosocial risk indicators contribute to suicide risk. Understanding the biopsychosocial risk profile for individuals most at risk for eventual death by suicide remains critical for enhancing suicide risk detection strategies and developing targeted interventions. To address these gaps, the overall objective of the proposed project is to investigate the combined associations of brain structure and connectivity, genetic, and behavioral risk indicators for suicide. Biopsychosocial data from an estimated 4566 participants drawn from the UK Biobank will be analyzed to differentiate those at risk for suicidal behavior from self-directed violence thoughts alone. This proposal sets the stage for Mr. Thompson’s goal to develop a program of research investigating biopsychosocial markers of suicide risk. Aim 1 of the proposed project is to compare brain structure and connectivity, genetic, and psychosocial risk indicators between two groups: adults with lifetime suicide attempt(s) and adults with lifetime self-directed violence thoughts alone. Aim 2 is to determine the relative importance of biological and psychosocial candidate markers by comparing classification algorithms utilizing biological (i.e., brain structure and connectivity, genetic variance), above and beyond psychosocial risk indicators alone, in differentiating between these two groups. Findings will advance our understanding of the biopsychosocial risk indicators associated with suicide to highlight mechanisms, improve risk detection, and ultimately inform targeted intervention strategies. Overall, the goals of the proposed project will be accomplished within the context of a research training program aimed at developing expertise in (1) biopsychosocial underpinnings of suicidality, (2) advanced statistics and machine learning, (3) multimodal neuroimaging, (4) generation of PRS, and (5) scholarly dissemination skills. The training plan includes attendance at selected workshops, scientific writing and academic conference presentations, and individual supervision and mentorship by a team of sponsors and collaborators with complementary areas of expertise.

项目概要/摘要自杀仍然是全国和全球范围内与自杀相关的思想和行为的重大公共卫生危机。是与异质生物心理社会风险指标相关的跨诊断现象。表明自杀风险与不同的静息态功能连接、大脑结构我们对差异和多基因风险评分（PRS）概况的理解存在显着差距。第一个研究空白涉及缺乏对自杀的深入了解。用于区分只考虑自我暴力的个人与那些仅考虑自我暴力的个人的候选标记第二个研究空白涉及对如何自杀缺乏深入了解。生物风险指标与社会心理风险指标相结合有助于了解自杀风险。最终自杀死亡风险最高的个体的生物心理社会风险状况对于加强自杀风险检测策略并制定有针对性的干预措施，以弥补这些差距。该项目的总体目标是研究大脑结构和估计的自杀生物心理社会数据的连通性、遗传和行为风险指标。来自英国生物银行的 4566 名参与者将接受分析，以区分那些有自杀行为风险的人这项提议为汤普森先生制定一个目标奠定了基础。调查自杀风险的生物心理社会标记的研究计划拟议项目的目标 1 是比较两组之间的大脑结构和连通性、遗传和社会风险指标：成人终生有自杀企图的成年人和终生有自我导向暴力想法的成年人，目标 2 就是：通过比较分类确定生物和心理社会候选标记的相对重要性利用生物学（即大脑结构和连接性、遗传方差）的算法，超越仅心理社会风险指标就可以区分这两个群体。了解与自杀相关的生物心理社会风险指标，以突出机制，改善风险检测，并最终为有针对性的干预策略提供信息总体而言，拟议项目的目标。将在旨在发展以下方面专业知识的研究培训计划的背景下完成：自杀的生物心理社会基础，(2) 高级统计和机器学习，(3) 多模式培训计划包括：神经影像、(4) PRS 的生成、以及 (5) 学术传播技能。参加选定的研讨会、科学写作和学术会议演讲，以及个人由具有互补专业领域的发起人和合作者团队进行监督和指导。