Campos Adrian I, Garcia-Marin Luis M, Christensen Helen, Batterham Philip J, van Velzen Laura S, Schmaal Lianne, Rabinowitz Jill A, Jahanshad Neda, Martin Nicholas G, Cuellar-Partida Gabriel, Ruderfer Douglas, Mullins Niamh, Rentería Miguel E
Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD Australia.
Aust N Z J Psychiatry. 2023 Mar;57(3):423-431. doi: 10.1177/00048674221091499. Epub 2022 Apr 11.
Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt.
We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology.
Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator.
Suicide attempt risk is likely explained by a combination of behavioural phenotypes and risk for both physical and psychiatric disorders. Our results also suggest that substance use behaviours and pain-related conditions are associated with an increased suicide attempt risk, elucidating important causal mechanisms that underpin this significant public health problem.
每年约有100万人死于自杀。尽管自杀已被视为一个公共卫生问题,但针对自杀未遂风险因果决定因素的大规模研究却很匮乏。在此,我们利用近期一项自杀未遂的全基因组关联研究(GWAS)结果,对与自杀未遂有因果关系的特质进行数据驱动的筛选。
我们对自杀未遂风险与1520种特质之间的因果关系进行了假设生成性全表型组筛选,这些特质已在复杂性状基因组学虚拟实验室平台上系统汇总。我们采用了潜在因果变量(LCV)方法,该方法利用GWAS结果评估因果关系是否能解释两个特质之间的遗传相关性。如果一个特质对另一个特质有因果影响,那么增加因果特质风险的基因变异也会增加结果的风险,从而导致遗传相关性。然而,当特质共享共同途径时也可观察到遗传相关性。LCV方法可以评估两个遗传相关特质的遗传效应模式是否支持因果关联而非共同病因。
我们的方法识别出62种会增加自杀未遂风险的特质。识别出的风险因素可大致分为:(1)身体健康障碍,包括食管炎、纤维肌痛、疝气和癌症;(2)与心理健康相关的特质,如抑郁症、物质使用障碍和焦虑症;(3)生活方式特质,包括参与战斗或暴露于战区,以及特定职业类别,如卡车司机或机器操作员。
自杀未遂风险可能由行为表型以及身体和精神疾病风险共同解释。我们的结果还表明,物质使用行为和疼痛相关状况与自杀未遂风险增加有关,阐明了这一重大公共卫生问题背后的重要因果机制。