Identifying behaviour-related and physiological risk factors for suicide attempts in the UK Biobank

Bei Zhang, Jia You, Edmund T. Rolls, Xiang Wang, Jujiao Kang, Yuzhu Li, Ruohan Zhang, Wei Zhang, Huifu Wang, Shitong Xiang, Chun Shen, Yuchao Jiang, Chao Xie, Jintai Yu, Wei Cheng () and Jianfeng Feng ()
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Bei Zhang: Fudan University
Jia You: Fudan University
Edmund T. Rolls: Fudan University
Xiang Wang: Central South University
Jujiao Kang: Fudan University
Yuzhu Li: Fudan University
Ruohan Zhang: University of Warwick
Wei Zhang: Fudan University
Huifu Wang: Qingdao University
Shitong Xiang: Fudan University
Chun Shen: Fudan University
Yuchao Jiang: Fudan University
Chao Xie: Fudan University
Jintai Yu: Fudan University
Wei Cheng: Fudan University
Jianfeng Feng: Fudan University

Nature Human Behaviour, 2024, vol. 8, issue 9, 1784-1797

Abstract: 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.

Date: 2024
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DOI: 10.1038/s41562-024-01903-x

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