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OBJECTIVE: Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures. METHODS: This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses. RESULTS: Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values

BackgroundSuicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders.MethodsWe conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors.ResultsTwo loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged.ConclusionsOur results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.

Evidence suggests there may be increased risk for suicidal behavior among individuals with autism spectrum disorder (ASD). An emerging body of research explores social factors that may contribute to increased risk, however little is known about the potential role of biological factors. The current project addresses this knowledge gap through a preliminary study of genes associated with both ASD and suicidal behavior. Gene set enrichment tests of eight genes strongly associated with both ASD and suicidal behavior revealed overrepresentation of nine biological processes, including cognition and synapse function, and 14 cellular components, including the neuron, the synapse, and the synaptic and postsynaptic membrane. These results can be used to inform future investigations of the biological underpinnings of suicidal behavior and ASD.

Approximately 5% of individuals with schizophrenia die from suicide. However, suicide in psychosis is still poorly characterized, partly due to a lack of adequate population-based clinical or genetic data on suicide death. The Utah Suicide Genetics Research Study (USGRS) provides a large population-based cohort of suicide deaths with medical record and genome-wide data (N = 4380). Examination of this cohort identified medical and genetic risks associated with type of suicide death and investigated the relative contributions of psychotic and affective symptoms to method of suicide. Key differences in method of suicide (common vs. atypical methods) were tested in relation to lifetime psychosis and genome-wide genetic risk for schizophrenia, major depressive disorder, and neuroticism. Consistent with previous studies, psychosis-spectrum disorders were observed to be common in suicide (15% of the cohort). Individuals with psychosis more frequently died from atypical methods, with rates of atypical suicide increasing across the schizophrenia spectrum. Genetic risk for schizophrenia was also associated with atypical suicide, regardless of clinical diagnosis, though this association weakened when filtering individuals with schizophrenia from the analysis. Follow-up examination indicated that high rates of atypical suicide observed in schizophrenia are not likely accounted for by restricted access to firearms. Overall, better accounting for the increased risk of atypical suicide methods in psychosis could lead to improved prevention strategies in a large portion of the suicide risk population. [ABSTRACT FROM AUTHOR]

Background: Borderline personality disorder (BPD) is a debilitating condition characterized by pervasive instability across multiple major domains of functioning. The majority of persons with BPD engage in self-injury and up to 10% die by suicide - rendering persons with this condition at exceptionally elevated risk of comorbidity and premature mortality. Better characterization of clinical risk factors among persons with BPD who die by suicide is urgently needed., Methods: We examined patterns of medical and psychiatric diagnoses (1580 to 1700 Phecodes) among persons with BPD who died by suicide ( n = 379) via a large suicide death data resource and biobank. In phenotype-based phenome-wide association tests, we compared these individuals to three other groups: (1) persons who died by suicide without a history of BPD ( n = 9468), (2) persons still living with a history of BPD diagnosis ( n = 280), and (3) persons who died by suicide with a different personality disorder (other PD n = 589)., Results: Multivariable logistic regression models revealed that persons with BPD who died by suicide were more likely to present with co-occurring psychiatric diagnoses, and have a documented history of self-harm in the medical system prior to death, relative to suicides without BPD. Posttraumatic stress disorder was more elevated among those with BPD who died by suicide relative to the other PD group., Conclusions: We found significant differences among persons with BPD who died by suicide and all other comparison groups. Such differences may be clinically informative for identifying high-risk subtypes and providing targeted intervention approaches.

Background: Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation., Methods: A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394)., Results: Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported., Conclusions: Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations., Competing Interests: Disclosures Ole Andreassen: Consultant to Cortechs.ai and Precision-Health.ai, and received speaker’s honorarium from Lundbeck, Sunovion, Janssen and Otsuka. Murray Stein: MBS has in the past 3 years received consulting income from Aptinyx, atai Life Sciences, BigHealth, Biogen, Bionomics, Boehringer Ingelheim, Delix Therapeutics, EmpowerPharm, Engrail Therapeutics, Janssen, Jazz Pharmaceuticals, Karuna Therapeutics, Lykos Therapeutics, NeuroTrauma Sciences, Otsuka US, PureTech Health, Sage Therapeutics, Seaport Therapeutics, and Roche/Genentech. Dr. Stein has stock options in Oxeia Biopharmaceuticals and EpiVario. He has been paid for his editorial work on Depression and Anxiety (Editor-in-Chief), Biological Psychiatry (Deputy Editor), and UpToDate (Co-Editor-in-Chief for Psychiatry). He is on the scientific advisory board of the Brain and Behavior Research Foundation and the Anxiety and Depression Association of America. Philip Harvey: Dr. Harvey consults for a variety of pharmaceutical and device manufacturers on phase 2 and 3 studies of cognition and negative symptoms in SMI. These activities have been reviewed and determined not to be related to the content of this paper. John Mann: Dr. Mann receives royalties for commercial use of the C-SSR S from the Research Foundation of Mental Hygiene and from Columbia University for the Columbia Pathways App. All other listed authors declare no conflicts of interest.