We present the first quantitative trait GWAS of suicide attempts. We obtained novel findings that overlapped with the emerging biological model of suicidality. Our results from gene-based approaches support previously reported links to apoptosis, and additionally, GWS SNPs were identified in proximity to genes involved in the regulation of circadian rhythms, energy production, and catecholamine catabolism. Two design features—the use of a quantitative phenotype, and the exclusion of subjects with suicidal ideation but no history of suicide attempts—may have increased the statistical power to identify genetic associations in both available populations, AAs and EAs.

In constructing our scale from available data in the SSADDA, we did not assign differential severity weighting based on the number of suicide attempts for an individual because, while a previous suicide attempt is one of the largest risk factors for death by suicide, the number of past suicide attempts beyond the initial attempt does not necessarily reflect increased risk; the opposite may be true because individuals who attempt suicide attempt frequently without completing have self-evidently not selected highly lethal methods, so may have less desire to die and lower intent to harm themselves. While previous suicide attempts and self harm increase the risk of future suicide attempt or death, most suicide attempters do not go on to die by suicide24,25,26, Most deaths by suicide occur on the first known attempt27,28.

Classical work29 on the complexity of suicidal behavior and intent have examined quantitative scales for suicide, for example, the Suicidal Intent Scale (SIS), a 15 item questionnaire containing objective details on the nature of the suicide attempt (questions 1–8) and subjective self report of the attempter. Items from the SIS cluster into 6 factors that might better represent specific dimensions of suicidal behavior than scoring all items in one general scale30. The work of Beck informed modern scales such as the Columbia-Suicide Severity Rating Scale (C-SSRS) which seek to distinguish domains of suicidal ideation and behavior, which could have great value in the design of future prospective studies for domains of suicidal behavior31. While the SSADDA instrument predates the C-SSRS, our approach was informed by evidence that subtypes are present within suicidal behavior32,33

Our scale derived from the SSADDA resembles Beck’s Factor I, “attitudes toward attempt”. Accordingly, we scored severity based on the lethality of the attempt according to whether subjects required medical treatment or hospitalization following the attempt, or lethality of the method using available data from the SSADDA instrument.

Overall, SNP-based heritability within EAs was ascertained by GCTA on unrelated subjects in the EA cohort (Heritability = 0.24, p = 0.011). We identified several GWS SNPs for EAs at the LDHB locus; and LDHB was also identified as GWS in the gene-based association analysis. The SNPs identified in and around this gene were replicated in an independent cohort of LATs (rs1677091, p = 6.5 × 10−3, EA-LAT meta p = 4.7 × 10−9) but not EAs (p = 0.74, EA-EA meta p = 0.02). This ubiquitously-expressed gene encodes the B subunit of the lactate dehydrogenase enzyme and is vital in the anaerobic conversion of NADH to NAD + and lactate to pyruvate and conversion between NAD + and NADH. Increases in expression of LDHB protein have been found in peripheral blood mononuclear cells of first onset antipsychotic naive schizophrenics34.

Gene-based association analysis of data from EAs also identified PHLDB2. Previous studies have found increased expression of this gene in peripheral blood from subjects with increasing suicidal thoughts and behaviors when followed longitudinally35,36, The increase occurred when the subject’s suicidal thoughts and behaviors increased. PHLDB2 may warrant further study as a possible peripheral blood biomarker candidate for suicidal risk.

The third gene identified for EAs with gene-based association analysis was PGBD5; it maps 5 MB from “Nucleoporin 133” (NUP133); the latter locus was epigenome-wide significant in a study using a quantitative suicidality score37. Although the authors of that study focused more on NUP133, PGBD5 was discussed for its proximity to top findings and overlap with findings in panic-induced epigenetic H3K27me3 modifications in mice38. Recent panic attacks and the diagnosis of panic disorder within 12-months are significantly related to suicidal ideation and attempts, even when co-morbidities are controlled for39. We speculate that the role of this gene in acute panic may be relevant to suicide attempts.

Overall, SNP-based heritability within AAs was ascertained by GCTA on unrelated subjects in the AA cohort (Heritability = 0.13, p = 0.026). Several GWS loci for the severity of suicide attempts were identified in AAs. The lead SNP (rs683813) maps close to ARNTL2-AS1. ARNTL2, also known as BMAL2, is a paralog of BMAL1 and plays an important role in circadian rhythms and regulation. SNPs in ARNTL2 have shown suggestive evidence for association with rapid cycling of mood along with a diurnal phenotype of worsening mood in the evening40. A candidate gene study identified a polymorphism in ARNTL2 that was nominally related to morning preference in 966 British participants41. Suicide biomarker studies in the peripheral blood of U.S. participants have highlighted genes whose expression tracks longitudinal changes in suicidal ideation and may be enriched for core regulators of the circadian clock33,35. This observation suggests further that time-of-day and season-of-the-year may be noteworthy factors that affect suicide biology. Additional studies will be needed to understand this mechanism potentially associated with suicidal behaviors.

The lead GWS SNP (rs72740082) on chromosome 15 maps to the CTXND1, LINC01314 and FAH locus. The same SNP was also GWS when run in the Yale-Penn trans-population meta-analysis of EAs and AAs. This SNP was not directly available in the STARRS sample replication, but an adjacent SNP in high LD with it that was nearly-GWS in the Yale-Penn meta-analysis (rs72740088, D’ = 0.95, R2 = 0.68, p = 7.49 × 10−8) was nominally significant in the STARRS AA sample (p = 5.22 × 10−3). When the STARRS AA and Yale-Penn samples were meta-analyzed together the p value improved (p = 1.51 × 10−9). An overall meta of all Yale-Penn and STARRS summary statistics yields an overall p = 7.84 × 10−7. In many of these situations, lack of availability of the actual Yale-Penn lead SNPs in other samples likely diminished the statistical significance of the final meta-analyzed results. Overexpression of LINC01314 was recently shown to act as a tumor suppressor in hepatoblastoma, possibly through the Hippo-YAP signaling pathway42. This pathway has been previously implicated in psychiatric conditions such as schizophrenia and anxiety through one of its key effectors, the “Nitric Oxide Synthase 1 Adaptor Protein” (NOS1AP). Interestingly, rs72740082 is in LD with another SNP (rs75782446, D’ = 0.79, R2 = 0.44) found within an intron of the FAH gene. This gene acts as the last enzyme in the catabolic pathway which breaks down the amino acid tyrosine, used for synthesis of dopamine and the other catecholamine neurotransmitters.

African ancestry is underrepresented in the literature. This is the largest GWAS of suicide to date in African Americans and we identified several GWS signals in AAs. Although these were with moderately-low MAF SNPs (0.03 range), there was no evidence of genomic inflation due to potential confounders. To evaluate whether the effects were biased by the distribution of our quantitative phenotype, we ran 1,000 permutations with randomly assigned phenotypes all sharing the same distribution of the primary experiment. The results (Supplementary Figure S1) failed to show that bias was introduced by the phenotype distribution.

The lead SNP for AAs on chromosome 18 maps to an intergenic region ~680 kb from the microRNA 4318 (MIR4318). This SNP association is a novel finding. It does not appear in the GWAS catalog nor is it a known eQTL based on lookups in the online databases BRAINEAC or GTEx. This likely reflects, in part, the sparsity of GWS findings among AAs, who are understudied, and suggests that it may identify an AA-specific functional locus.

The gene-based association identified a single gene as GWS for AAs, the “NMDA Receptor-Regulated Protein 2” (NARG2). This gene is also known as the “Interactor of Little Elongation Complex ELL Subunit 2” (ICE2). NARG2 (ICE2) is an NMDA receptor regulated protein component of the little elongation complex (LEC), which plays a role in small nuclear RNA (snRNA) transcription43,44.

PRS identified significant genetic overlap between MDD and suicide attempt severity; the PGC-MDD PRS explains up to 0.7% of the variance of suicide attempt severity in the Yale-Penn cohort. MDD is a well-known risk factor for suicidal behaviors45,46,47, with significantly increased attempts and death by suicide when compared to the general population.

We focused on suicide attempts by excluding individuals with suicidal ideation, which is likely to be significantly more heterogeneous; this reduced unaccounted for and potentially confounding complexity in the phenotype. Removing suicidal ideation also reduced the concern that individuals with a related and sometimes overlapping phenotype, that may not be on the same spectrum in every individual, would be misclassified. Depending on their future action, subjects in the “ideation” category could eventually attempt suicide (which they would be expected to do at a higher rate than subjects without ideation).

MAGMA gene-set analysis identified the caspace pathway Dwivedi et al.48 previously identified an increased ratio of p75NTR to Trk receptors, which has been shown to be pro-apoptotic, in the brains of suicide completers. Pathway analysis of biomarkers for suicidal behavior has also identified apoptosis as an enriched biological pathway for suicide49. This could be related to stress or other interacting co-morbidities and may warrant further study as an intervention or risk-detection mechanism.

Our study had several limitations. Our cohort is reasonably large compared to other published GWAS of suicidal behaviors, but larger-yet studies are needed to confirm these results and to identify low effect size genetic risk factors. Additionally, the EA findings replicated only in the LAT sample, and not the EA sample in the STARRS cohort. This curious result could reflect the inclusion of Latino individuals in the Yale-Penn EA cohort or reflect the fact that that the participants in the Army-STARRS sample were much younger and had traversed less of their lifetime risk period for suicide. Accordingly, the Army-STARRS suicide behavior had earlier age of onset; for many traits this corresponds with greater severity. It would be highly interesting to follow these individuals longitudinally to evaluate the evolutions of this phenotype.

We also considered the possibility that, because the Yale-Penn sample is made up of subjects recruited for SUD studies (affecteds and controls), our results may be more specific to suicide attempt severity in SUD. We looked up our top findings for suicide in previous published GWAS for alcohol, cocaine, and cannabis dependence performed in the same cohort but found no evidence for even nominal association with SUDs.

In summary, we identified several associations in genes or associated pathways that have previously been implicated in suicide. Epigenetic modifications near PGBD5 and NUP133 have been associated with quantitative scores for suicidality37. Suicidal ideation state changes have been associated with the increased expression of PHLDB2 in independent studies in men36 and women35. We also identified several loci that are novel for suicide but have previously been associated with psychiatric disorders that overlap with risk for suicidal behavior50. Increased LDHB expression has been associated with the first onset of psychosis in antipsychotic-naïve schizophrenia patients34. ARNTL2 and other core regulators of circadian rhythms have frequently been associated with bipolar disorder. Individuals with these disorders are at elevated risk of suicidal behavior. In addition to the novel findings, the results highlight convergent evidence in the literature of molecular genetic components as risk factors for suicidal behavior and predicted pleiotropy between psychiatric disorders and suicide attempts.

Suicidal behavior is heterogeneous and is driven by many complex interacting environmental and genetic influences. It is unlikely that any single gene could exert a large enough effect to drive such complexity (or capture the environmental influence), but although single variants may contribute only small effects individually, considered together, they may collectively provide new insight into the genetic risk factors underlying suicidal behaviors. Our success at identifying significant associations even in a comparatively modest-sized sample, bodes well for the future of this endeavor.