ArticleNature human behaviour2024
Identifying behaviour-related and physiological risk factors for suicide attempts in the UK Biobank.
Article in Nature human behaviour, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- When Losses Matter More: A Dynamic Reference-Dependent Evaluation of Suicide Risk.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Social disconnection integrates genetic and proteomic risks in suicidal ideation and depression.Translational psychiatry · 2026Article
- Linking the exposome to the brain-behaviour phenotype.Nature reviews. Neuroscience · 2026Review
- Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.Child and adolescent psychiatry and mental health · 2026Article
- Longitudinal changes in amygdala-supplementary motor area connectivity and their association with recurrent self-harm in adolescents with mood disorders.BMC psychiatry · 2026Article
- Physical frailty, genetic risk, mediating biomarkers, and risk of suicide attempt: A prospective cohort study.PLoS medicine · 2026Article
- Imaging-based organ-specific aging clock predicts human diseases and mortality.NPJ digital medicine · 2026Article
- A phenome-wide association and Mendelian randomization study for suicide attempt within UK Biobank.Molecular psychiatry · 2026Article
- The prospect of suicide biomarkers: from neurobiology to precision prevention.Frontiers in psychology · 2026Review
- Mapping the genetic landscape of suicide risk: Insights from genomic SEM.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2026Article
- Neuroanatomical dimensions in major depression linked to cognition, adverse life events, self-harm, metabolomics and genetics.Communications medicine · 2025Article
- Metabolic syndrome increases the risk of suicide attempt: evidence from a population-based cohort and genomic analysis.Translational psychiatry · 2025Article
- Machine learning model for differentiating xanthogranulomatous cholecystitis and gallbladder cancer in multicenter largescale study.NPJ digital medicine · 2025Article
- Uncovering Genetic Risk Beyond Diagnoses in Suicidal Thoughts and Behaviors: Insights frommedRxiv : the preprint server for health sciences · 2025Article
- Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning-Based Advanced Perspectives.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Distinguishing clinical and genetic risk factors for suicidal ideation and behavior in a diverse hospital population.Translational psychiatry · 2025Article
- Moving Toward Meaningful Evaluations of Monitoring in e-Mental Health Based on the Case of a Web-Based Grief Service for Older Mourners: Mixed Methods Study.JMIR formative research · 2024Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
Suicide is a global public health challenge, yet considerable uncertainty remains regarding the associations of both behaviour-related and physiological factors with suicide attempts (SA). Here we first estimated polygenic risk scores (PRS) for SA in 334,706 UK Biobank participants and conducted phenome-wide association analyses considering 2,291 factors. We identified 246 (63.07%) behaviour-related and 200 (10.41%, encompassing neuroimaging, blood and metabolic biomarkers, and proteins) physiological factors significantly associated with SA-PRS, with robust associations observed in lifestyle factors and mental health. Further case-control analyses involving 3,558 SA cases and 149,976 controls mirrored behaviour-related associations observed with SA-PRS. Moreover, Mendelian randomization analyses supported a potential causal effect of liability to 58 factors on SA, such as age at first intercourse, neuroticism, smoking, overall health rating and depression. Notably, machine-learning classification models based on behaviour-related factors exhibited high discriminative accuracy in distinguishing those with and without SA (area under the receiver operating characteristic curve 0.909 ± 0.006). This study provides comprehensive insights into diverse risk factors for SA, shedding light on potential avenues for targeted prevention and intervention strategies.
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Registered trials
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