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Information about genes and the biology of suicidal behavior (SB) is noisy due to heterogenous outcomes (suicide attempts or deaths), as well as many different genes and overlapping biological processes implicated. One approach to test the unbiased biological coherence of disease genes, is to use genes from hypothesis-free genetic scans and to investigate if they aggregate close to each other in cellular gene and protein interaction networks ("interactomes"). Therefore, we used network methods to study the biological coherence among genes (n = 229) from genome-wide association studies (GWAS) and whole exome sequencing (WES) of suicide outcome. Results showed that the suicide GWAS+WES genes has significant aggregation in three major interactome database assemblies, a hallmark of biological similarity and increased likelihood of being involved in the same outcome (suicide). This pinpointed e.g. genes on chromosome 19, which are also associated with lipid metabolism, schizophrenia and bipolar disorder. We identified a subset of GWAS+WES "core" genes (n = 54) which are the most proximal to each other in the context of three interactome assemblies, and present a candidate network module of suicide which is specific for nervous system tissues. The n = 54 most proximal "core" genes showed overrepresentation of synaptic and nervous system development genes, as well as network paths to other SB genes having increased evidence diversity. Overall, results suggested the existence of a coherent biology in suicide outcome and provide unbiased biological support concerning links to other SB genes, as well as e.g. bipolar disorder, excitatory/inhibitory function and ketamine treatment in SB., (Copyright © 2021. Published by Elsevier Inc.)

Suicidal behavior (SB) has a complex etiology involving different polygenic and environmental components. Here we used an excess of significant markers (ESM) test to study gene-level associations in previous genome-wide association studies (GWAS) SNP data from a family-based sample, having medically severe suicide attempt (SA) as main outcome in the offspring. In SA without major psychiatric disorders (N = 498), a screening of 5,316 genes across the genome suggested association 17 genes (at fdr < 0.05). Genes RETREG1 (a.k.a. FAM134B), GSN, GNAS, and CACNA1D were particularly robust to different methodological variations. Comparison with the more widely used Multi-marker Analysis of GenoMic Annotation (MAGMA) methods, mainly supported RETREG1, GSN, RNASEH2B, UBE2H, and CACNA1D by using the "mean" model, and ranked 13 of the same genes as ESM among its top-17. Complementing the ESM screen by using MAGMA to analyze 17,899 genes, we observed excess of genes with p < .05 by using the "top" model, and the "mean" model suggested additional genes with genome-wide fdr < 0.25. Overrepresentation analysis of 10 selected gene sets using all genes with p < .05, showed significant results for synaptic genes, genes differentially expressed in brain development and for ~12% of the SA polygenic association genes identified previously in this sample. Exploratory analysis linked some of the ESM top-17 genes to psychotropic drugs and we examined the allelic heterogeneity in the previous SA candidate GRIN2B. This study complemented previous GWAS on SB outcomes, implicating both previous candidate (e.g., GRIN2B and GNAS) and novel genes in SA outcomes, as well as synaptic functions and brain development., (© 2018 Wiley Periodicals, Inc.)

Suicidal behavior (SB) has a complex etiology involving genes and environment. One of the genetic components in SB could be copy number variations (CNVs), as CNVs are implicated in neurodevelopmental disorders. However, a recently published genome-wide and case-control study did not observe any significant role of CNVs in SB. Here we complemented these initial observations by instead using a family-based trio-sample that is robust to control biases, having severe suicide attempt (SA) in offspring as main outcome (n = 660 trios). We first tested for CNV associations on the genome-wide Illumina 1M SNP-array by using FBAT-CNV methodology, which allows for evaluating CNVs without reliance on CNV calling algorithms, analogous to a common SNP-based GWAS. We observed association of certain T-cell receptor markers, but this likely reflected inter-individual variation in somatic rearrangements rather than association with SA outcome. Next, we used the PennCNV software to call 385 putative rare (<1%) and large (>100 kb) CNVs, observed in n = 225 SA offspring. Nine SA offspring had rare CNV calls in a set of previously schizophrenia-associated loci, indicating the importance of such CNVs in certain SA subjects. Several additional, very large (>1MB) sized CNV calls in 15 other SA offspring also spanned pathogenic regions or other neural genes of interest. Overall, 45 SA had CNVs enriched for 65 medically relevant genes previously shown to be affected by CNVs, which were characterized by a neurodevelopmental biology. A neurodevelopmental implication was partly congruent with our previous SNP-based GWAS, but follow-up analysis here indicated that carriers of rare CNVs had a decreased burden of common SNP risk-alleles compared to non-carriers. In conclusion, while CNVs did not show genome-wide association by the FBAT-CNV methodology, our preliminary observations indicate rare pathogenic CNVs affecting neurodevelopmental functions in a subset of SA, who were distinct from SA having increased SNP risk-allele burden. These observations may open up new avenues in the genetic etiology of SB., Competing Interests: The authors have declared that no competing interests exist.

Suicidal behaviors represent a fatal dimension of mental ill-health, involving both environmental and heritable (genetic) influences. The putative genetic components of suicidal behaviors have until recent years been mainly investigated by hypothesis-driven research (of "candidate genes"). But technological progress in genotyping has opened the possibilities towards (hypothesis-generating) genomic screens and novel opportunities to explore polygenetic perspectives, now spanning a wide array of possible analyses falling under the term Genome-Wide Association Study (GWAS). Here we introduce and discuss broadly some apparent limitations but also certain developing opportunities of GWAS. We summarize the results from all the eight GWAS conducted up to date focused on suicidality outcomes; treatment emergent suicidal ideation (3 studies), suicide attempts (4 studies) and completed suicides (1 study). Clearly, there are few (if any) genome-wide significant and reproducible findings yet to be demonstrated. We then discuss and pinpoint certain future considerations in relation to sample sizes, the units of genetic associations used, study designs and outcome definitions, psychiatric diagnoses or biological measures, as well as the use of genomic sequencing. We conclude that GWAS should have a lot more potential to show in the case of suicidal outcomes, than what has yet been realized., (Copyright © 2014 Elsevier B.V. and ECNP. All rights reserved.)

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.