Studying individual risk factors for self-harm in the UK Biobank: A polygenic scoring and Mendelian randomisation study

• Published in: PLoS medicine Vol. 17; no. 6; p. e1003137
• Main Authors: Lim, Kai Xiang, Rijsdijk, Frühling, Hagenaars, Saskia P., Socrates, Adam, Choi, Shing Wan, Coleman, Jonathan R. I., Glanville, Kylie P., Lewis, Cathryn M., Pingault, Jean-Baptiste
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.06.2020; Public Library of Science (PLoS)
• Subjects: Aged; Aged, 80 and over; Attention Deficit Disorder with Hyperactivity - complications; Attention Deficit Disorder with Hyperactivity - genetics; Attention deficit hyperactivity disorder; Biobanks; Biology and Life Sciences; Bipolar disorder; Bipolar Disorder - complications; Bipolar Disorder - genetics; Cannabis; Cognitive ability; Databases as Topic; Depressive Disorder, Major - complications; Depressive Disorder, Major - genetics; Drug dependence; Drug use; Epidemiology; Female; Genetic aspects; Genetic Predisposition to Disease - genetics; Genome-Wide Association Study; Genomes; Genomics; Health surveys; Humans; Impulsive behavior; Logistic Models; Male; Marijuana; Medical research; Medicine and Health Sciences; Mendelian Randomization Analysis; Mental depression; Mental disorders; Mental health; Middle Aged; Multifactorial Inheritance - genetics; Neurosciences; Personality traits; Poisoning; Polygenic inheritance; Psychiatry; Questionnaires; Regression analysis; Risk Factors; Schizophrenia; Self destructive behavior; Self-Injurious Behavior - epidemiology; Self-Injurious Behavior - etiology; Self-Injurious Behavior - genetics; Self-injury; Software; Substance abuse; Substance use; Substance-Related Disorders - complications; Substance-Related Disorders - genetics; Suicides & suicide attempts; Supervision; Surveys and Questionnaires; United Kingdom - epidemiology; United Kingdom; United Kingdom > UK; New York; United States > US
• ISSN: 1549-1676; 1549-1277; 1549-1676
• DOI: 10.1371/journal.pmed.1003137

Identifying causal risk factors for self-harm is essential to inform preventive interventions. Epidemiological studies have identified risk factors associated with self-harm, but these associations can be subject to confounding. By implementing genetically informed methods to better account for confounding, this study aimed to better identify plausible causal risk factors for self-harm. Using summary statistics from 24 genome-wide association studies (GWASs) comprising 16,067 to 322,154 individuals, polygenic scores (PSs) were generated to index 24 possible individual risk factors for self-harm (i.e., mental health vulnerabilities, substance use, cognitive traits, personality traits, and physical traits) among a subset of UK Biobank participants (N = 125,925, 56.2% female) who completed an online mental health questionnaire in the period from 13 July 2016 to 27 July 2017. In total, 5,520 (4.4%) of these participants reported having self-harmed in their lifetime. In binomial regression models, PSs indexing 6 risk factors (major depressive disorder [MDD], attention deficit/hyperactivity disorder [ADHD], bipolar disorder, schizophrenia, alcohol dependence disorder, and lifetime cannabis use) predicted self-harm, with effect sizes ranging from odds ratio (OR) = 1.05 (95% CI 1.02 to 1.07, q = 0.008) for lifetime cannabis use to OR = 1.20 (95% CI 1.16 to 1.23, q = 1.33 × 10-35) for MDD. No systematic differences emerged between suicidal and non-suicidal self-harm. To further probe causal relationships, two-sample Mendelian randomisation (MR) analyses were conducted, with MDD, ADHD, and schizophrenia emerging as the most plausible causal risk factors for self-harm. The genetic liabilities for MDD and schizophrenia were associated with self-harm independently of diagnosis and medication. Main limitations include the lack of representativeness of the UK Biobank sample, that self-harm was self-reported, and the limited power of some of the included GWASs, potentially leading to possible type II error. In addition to confirming the role of MDD, we demonstrate that ADHD and schizophrenia likely play a role in the aetiology of self-harm using multivariate genetic designs for causal inference. Among the many individual risk factors we simultaneously considered, our findings suggest that systematic detection and treatment of core psychiatric symptoms, including psychotic and impulsivity symptoms, may be beneficial among people at risk for self-harm.