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.