Genome-Wide Association Study of Suicide Death and Polygenic Prediction of Clinical Antecedents

Abstract

Objective: Suicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort. Methods:The analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression.Results: GWAS identified two genome-wide significant loci (6 SNPs, p<5x10 -8 ). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h 2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder. Conclusions:In this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status..

Genetic contributions to suicidal thoughts and behaviors

“…This study was limited to individuals of European ancestry because rates of other ancestries were too small, but efforts to incorporate all ancestries with larger samples are underway. This GWAS identified two genome-wide significant loci (Table 1), estimated significant SNP-based heritability of suicide at 25%, and used suicide PRS to predict case−control status, using training and test sets with two independent control cohorts (Docherty et al, 2020). Suicide cases were observed to…”

“…It is critically important to model ancestry and ancestry admixture in genetic research on STBs to better understand ancestry-specific risk factors, to examine genetic risks that may be relevant to specific populations and locations, and to reduce health disparities. This has been historically difficult with the general lack of genetic data on suicide, but efforts are underway to increase access to diverse ancestry data resources as rapidly as possible (Docherty et al, 2020). Overall, the examination of ancestry will be essential to a comprehensive genetic discovery of STBs and will be a significant improvement to the field.…”

‘Omics’ of suicidal behaviour: A path to personalised psychiatry

“…Only a handful of GWAS have analysed suicide as the primary phenotype[ 25 - 29 ] (Table 1 ). One of the most unique study designs included more than 4500 DNA samples from consecutive individuals who died by suicide in the state of Utah.…”

“…This was the first study on completed suicide with sufficient power for a GWAS. Two genome-wide significant loci were identified on chromosomes 13 and 15 that were associated with suicide, and the significant heritability based on the SNPs was estimated to be as high as 25%[ 29 ], compared to the heritability of a previous population-based study on suicidality, of 7.6%[ 31 ]. The only GWAS on an East Asian population for suicide showed the SNP-based heritability to be 35% to 48%, which again confirmed the polygenic nature of the suicide risk[ 28 ].…”

Effects of polygenic risk for suicide attempt and risky behavior on brain structure in young people with familial risk of bipolar disorder

“…Several genetic studies have also highlighted the polygenic nature of genetic determinants of SA. Specifically, polygenic risk scores (PRS) derived from discovery GWAS leave-one-out summary statistics demonstrated validity of genomic signals (Mullins et al, 2019), and PRS derived from other GWAS for SA or suicide death (Docherty et al, 2020) have shown a moderate ability to predict SA within independent cohorts (Erlangsen et al, 2020; Mullins et al, 2014; Ruderfer et al, 2020). While these findings provide tentative evidence for the existence of genetic biomarkers for SA, derived PRS account for less than 1% of variability in the logistic model odds ratios of SA using pseudo-R , thus further work is required to establish a robust biological index that may be utilized within a clinical setting to reliably predict suicide behaviors.…”