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Cited by 160Genetic Associations and EpidemiologySuicide and Self-Harm StudiesNeurotransmitter Receptor Influence on Behavior

GWAS meta-analysis of suicide attempt: identification of 12 genome-wide significant loci and implication of genetic risks for specific health factors

Open access
Docherty, Anna R., Mullins, Niamh, Ashley-Koch, Allison E., Qin, Xuejun, Coleman, Jonathan R.I., Shabalin, Andrey, Kang, JooEun, Murnyak, Balasz +248 more·2023·American Journal of Psychiatry
DOI 10.1176/appi.ajp.21121266PMC PMC10603363
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Abstract

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: ). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors. CONCLUSIONS: This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

AI snapshot

Written from the paper’s full text.

TL;DR

This study conducted the largest GWAS meta-analysis of suicide attempt to date, combining ISGC and MVP cohorts (43,871 cases, 915,025 controls) across multiple ancestry admixtures. It identified 12 genome-wide significant risk loci and found shared genetic risk with psychiatric and nonpsychiatric health factors.

Key findings

  • Multi-ancestry and European ancestry meta-analyses identified 12 genome-wide significant loci (p<5×10−8); the multi-ancestry analysis found 8 loci and the EUR analysis found 4 additional loci, implicating genes including DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2.
  • Multi-ancestry SNP-based heritability of suicide attempt was 5.7% on the liability scale (SE=0.003, p=5.7×10−80); EUR h2SNP was 7.0% (SE=0.4%), while AFR and EAS each had h2SNP=9.8% but no genome-wide significant loci.
  • Genetic correlations with smoking (rG=0.46, SE=0.03, p=8.06×10−63), ADHD (rG=0.55, SE=0.04, p=2.98×10−41), risk tolerance (rG=0.32, SE=0.02, p=1.34×10−59), and chronic pain (rG=0.45, SE=0.03, p=9.50×10−50) remained significant after conditioning on MDD and PTSD.
  • Out-of-sample polygenic risk score prediction improved, with maximum liability-scale R2 of 0.66% in AFR (p=0.01), 0.34% in EAS (p=8.1×10−6), and 1.11% in EUR (p=6.2×10−22).

Methods

  • Meta-analysis of 22 cohorts from the International Suicide Genetics Consortium (ISGC) and Million Veteran Program (MVP), including 43,871 suicide attempt/suicide death cases and 915,025 ancestry-matched controls.
  • Multi-ancestry and ancestry-specific GWAS meta-analyses used inverse variance-weighted fixed-effects models in METAL, followed by LD score regression, cov-LDSC, Popcorn, mtCOJO conditioning, MAGMA/FUMA enrichment, SMR with brain eQTLs, phenome-wide genetic correlation, genetic causal proportion, and PRS-CS analyses.
  • Cases were predominantly European ancestry admixtures (81%), with 11% African, 5% East Asian, and 3% Hispanic/Latino ancestry admixtures; case definition was lifetime suicide attempt, with ~13% of all cases having died by suicide.

Limitations

  • The paper states that meta-analyzing many diverse cohorts with different suicide attempt assessments could reduce statistical power by increasing heterogeneity, though GWS effect sizes were similar across cohorts and fixed/meta-regression models.
  • The paper states that the lack of GWS loci in African and East Asian ancestry-specific meta-analyses underscores a strong need for greater ancestral diversity and representation in suicide genetics research, and notes high variability in ancestral cohort sample sizes.
  • Evident from the text: several downstream analyses were restricted to European ancestry data (e.g., SMR, conditioning on MDD/PTSD, genetic correlations), Hispanic/Latino could not be meta-analyzed because it was limited to a single cohort, and it remains undetermined which individuals with suicide attempt may have later died by suicide.

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Integrity signals

Registry

Crossref · 10.1176/appi.ajp.21121266

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 17 cited sources checked · 0 supported · 0 flagged

  • Findingown data

    At other genome-wide significant loci, index SNPs were intronic in SLC6A9, DRD2, HS6ST3, and FURIN.

    “At other GWS loci, index SNPs were intronic in the SLC6A9, DRD2, HS6ST3, and FURIN genes (Table 2; see Table S1B in the online supplement for additional summary data on all GWS loci).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.
  • Findingown data

    The genetic correlation between European ancestry GWAS meta-analyses for ISGC and MVP was 0.81 (SE=0.091, p=2.85×10−19), indicating consistent common-variant genetic architecture.

    “However, examination of the genetic correlation of EUR GWAS meta-analyses for ISGC and MVP (rG=0.81, SE=0.091, p=2.85×10−19) indicated consistency of common-variant genetic architecture across these meta-analyses.”
    Quote in the paperSubstantial claim
  • Findingown data

    After conditioning suicide attempt on both major depressive disorder and posttraumatic stress disorder, suicide attempt shared genetic variation with attention deficit hyperactivity disorder, smoking, and risk tolerance.

    “There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder.”
    Quote in the paperSubstantial claim
  • Findingown data

    Genetic causal proportion analyses implicated shared genetic risk for specific health factors.

    “Genetic causal proportion analyses implicated shared genetic risk for specific health factors.”
    Quote in the paperSubstantial claim
  • Findingown data

    The multi-ancestry GWAS meta-analysis identified eight genome-wide significant loci.

    “The multi-ancestry GWAS meta-analysis identified eight GWS loci (p<5×10−8) (Figure 1).”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.
  • May combine two claims. 33
  • Classified as probably not a substantial claim. 21

  • May combine two claims.

    Findingown data

    The cov-LDSC intercept was 1.04 (SE=0.01, p=1.59×10−5) and the attenuation ratio was 0.13 (SE=0.03), indicating most inflation of GWAS test statistics is likely due to polygenicity.

    “The cov-LDSC intercept was 1.04 (SE=0.01, p=1.59×10−5), and the attenuation ratio was 0.13 (SE=0.03), indicating that the majority of inflation of GWAS test statistics is likely due to polygenicity (see Figure S1 in the online supplement).”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.

  • May combine two claims.

    Findingown data

    Significant enrichment was observed for brain tissue gene expression and drug sets.

    “Significant brain tissue gene expression and drug set enrichment were observed.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.

  • May combine two claims.

    Findingown data

    On chromosome 3, a genome-wide significant SNP localized to the 5′ untranslated region of NLGN1, although the index SNP lacked neighboring SNPs in LD.

    “On chromosome 3, a GWS SNP localized to the 5′ untranslated region of the NLGN1 gene, although the index SNP lacked neighboring SNPs in LD.”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.

  • May combine two claims.

    Findingown data

    For African ancestry cohorts, the maximum variance explained (R2) was 0.66% (p=0.01), with a maximum increase of 146%.

    “particularly for the AFR cohorts, where the maximum variance explained (R2) was 0.66% (p=0.01), with a maximum increase of 146%”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Only one drug, the insecticide cyfluthrin, was significantly enriched when grouping genes targeted by individual drugs, and this was observed only in the European ancestry GWAS results.

    “Only one drug, the insecticide cyfluthrin, was significantly enriched when grouping genes targeted by individual drugs (from DGIdb v.2 and the Psychoactive Drug Screening Ki Database), and this was observed only in the EUR GWAS results”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The drug-gene interaction databases used for drug target enrichment are complete and accurate.

  • May combine two claims.

    Findingown data

    Brain is the predominant tissue enriched for genes associated with suicide attempt in this study, and there is also significant enrichment in pituitary gland.

    “Brain is the predominant tissue enriched for associated genes, and there is also significant enrichment in pituitary gland”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Two loci implicated specific genes, FES and TIAF1, that were significantly associated with suicide attempt in SMR analyses and passed the HEIDI test.

    “Two loci implicated specific genes, FES and TIAF1, that were significantly associated with SA in SMR analyses and passed the HEIDI test.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: SMR and HEIDI results indicate causal mediation by FES and TIAF1 rather than being due to horizontal pleiotropy or linkage.

  • May combine two claims.

    Findingown data

    For East Asian ancestry cohorts, R2 was 0.34% (p=8.1×10−6), with a 36% increase.

    “EAS cohorts, where R2 was 0.34% (p=8.1×10−6), with a 36% increase”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Genetic correlations of suicide attempt across ancestral groupings were attenuated, with estimated rG values ranging from 0.064 (SE=0.574) for East Asian with Latino/admixed to 0.997 (SE=0.537) for European with Latino/admixed.

    “The genetic correlations of SA across each of the ancestral groupings were attenuated, with estimated rG values between 0.064 (SE=0.574) (EAS with LAT) and 0.997 (SE=0.537) (EUR with LAT)”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: LDSC and Popcorn genetic correlation estimates reflect true shared genetic architecture and are not confounded by population stratification or sample overlap.

  • May combine two claims.

    Findingown data

    GWASs of the primary data sets typically produced significant and high genetic correlation estimates.

    “However, GWASs of the primary data sets typically produced significant—and high—genetic correlation estimates.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The nearest genes to the additional European ancestry loci were PDE4B, OTX2-AS1, and CACNG2, and one locus was in the major histocompatibility complex.

    “The nearest genes were PDE4B, OTX2-AS1, CACNG2, and one locus was in the major histocompatibility complex.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Gene-set analyses from the multi-ancestry and European ancestry GWAS identified 519 significant gene sets (31 and 488, respectively), spanning multiple domains including epigenetics, gene regulation and transcription, cellular response to stress, DNA repair, and immunologic signatures.

    “Gene-set analyses from the multi-ancestry and EUR GWAS identified 519 significant gene sets (31 and 488, respectively), spanning multiple domains, including epigenetics, gene regulation and transcription, cellular response to stress, DNA repair, and immunologic signatures”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For European ancestry, the maximum variance explained was 1.11% (p=6.2×10−22), a 24% increase from previous ISGC analyses.

    “EUR maximum variance explained was 1.11% (p=6.2×10−22), a 24% increase from previous ISGC analyses”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Pathways enriched in the multi-ancestry GWAS were absent of histone-coding genes and contained protein-coding genes mapped from genome-wide significant loci such as FURIN, FES, and DRD2.

    “Pathways enriched in the multi-ancestry GWAS were absent of histone-coding genes and contained protein-coding genes mapped from GWS loci such as FURIN, FES, and DRD2.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Inflation of test statistics due to polygenicity or cryptic relatedness was assessed using the LDSC attenuation ratio.

    “Inflation of test statistics due to polygenicity or cryptic relatedness was assessed using the LDSC attenuation ratio ([LDSC intercept—1]/[mean of association chi-square statistics—1]).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductcitation

    MVP GWAS analyses were performed within ancestral admixtures using PLINK2, covarying for genetic ancestry principal components, age, and sex.

    “Subsequent MVP GWAS analyses were performed within ancestral admixtures using PLINK2 (16), covarying for genetic ancestry principal components, age, and sex.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [16] Chang CC, Chow CC, Tellier LC,: Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience 2015; 4: 7 25722852 PMC4342193 source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductown data

    Fixed and meta-regression models gave comparable results in the multi-ancestry and EUR GWAS meta-analyses (all GWS effect size correlations >0.99), indicating ancestry and cohort ascertainment were unlikely to confound observed genetic effects.

    “Results from both fixed and meta-regression models were comparable in the multi-ancestry and EUR GWAS meta-analyses (all GWS effect size correlations >0.99), indicating that ancestry and cohort ascertainment were unlikely to confound observed genetic effects (Table S1B).”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductcitation

    ISGC GWASs were conducted within study and genetic ancestral admixtures, covarying for at least 10 principal components of genetic ancestry, genomic relatedness matrices, or factors capturing site of recruitment or genotyping batch.

    “For the ISGC meta-analysis, GWASs were conducted within study and genetic ancestral admixtures, covarying for at least 10 principal components of genetic ancestry, genomic relatedness matrices, or factors capturing site of recruitment or genotyping batch, as required (7).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [7] Mullins N, Kang J, Campos AI,: Dissecting the shared genetic architecture of suicide attempt, psychiatric disorders, and known risk factors. Biol Psychiatry 2022; 91: 313– 327 34861974 PMC8851871 source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    SNPs with mean weighted minor allele frequency <1%, mean weighted imputation INFO <0.6, or present in <80% of total effective sample size were removed to ensure adequate statistical power.

    “SNPs with a mean weighted minor allele frequency of <1%, a mean weighted imputation INFO score <0.6, or SNPs present in <80% of the total effective sample size were removed to ensure adequate statistical power at every variant included.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Imputation used the largest available ancestrally matched reference panels, either the 1000 Genomes Project or the Haplotype Reference Consortium.

    “Imputation was performed using the largest available ancestrally matched reference panels, either from the 1000 Genomes Project or the Haplotype Reference Consortium.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The chromosome 7 intergenic locus from ISGC stayed significant after conditioning on psychiatric disorders and was independently replicated in the MVP cohort.

    “The intergenic locus on chromosome 7 remained significant after conditioning on psychiatric disorders and was independently replicated (p=3.27×10−3) (8) in the Million Veteran Program (MVP) cohort (9).”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [8] Kimbrel NA, Ashley-Koch AE, Qin XJ,: A genome-wide association study of suicide attempts in the Million Veterans Program identifies evidence of pan-ancestry and ancestry-specific risk loci. Mol Psychiatry 2022; 27: 2264– 2272 35347246 PMC9910180 source

      Not checked in the free run.

    • cites [9] Gaziano JM, Concato J, Brophy M,: Million Veteran Program: a mega-biobank to study genetic influences on health and disease. J Clin Epidemiol 2016; 70: 214– 223 26441289 source

      Not checked in the free run.

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    ICD codes were coupled with emergency department information and physician notes to maximize evidence that suicidal intent was present.

    “ICD codes were coupled with information from emergency department settings and information on reason for contact and attempt methods that were mined from physician notes, in order to maximize evidence that suicidal intent was present.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    The multi-ancestry analysis identified several loci contributing to suicide attempt risk and established significant shared genetic covariation with clinical phenotypes.

    “This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    In ISGC, all interviews and self-report items asked explicitly about suicide attempt rather than self-harm.

    “All interviews and self-report items asked explicitly about SA rather than self-harm (which would also include nonsuicidal self-injury).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Genome-wide significant loci for SA were examined for heterogeneity across cohorts via I2 inconsistency metric and forest plots.

    “GWS loci for SA were examined for heterogeneity across cohorts via the I2 inconsistency metric and forest plots.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Standard parameters were used to retain individuals and SNPs after quality control for missingness, relatedness, and Hardy-Weinberg equilibrium.

    “Standard parameters were used to retain individuals and SNPs after quality control for missingness, relatedness, and Hardy-Weinberg equilibrium.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The MVP suicide attempt GWAS found two genome-wide significant multi-ancestry loci, on chromosomes 20 and 1.

    “The MVP cohort GWAS of suicide attempt (total N=409,153; 14,089 cases) resulted in two genome-wide significant multi-ancestry loci, on chromosomes 20 (index SNP: rs56817213; p=3.64×10−9) and 1 (index SNP: rs72730526; p=3.69×10−8) (8).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [8] Kimbrel NA, Ashley-Koch AE, Qin XJ,: A genome-wide association study of suicide attempts in the Million Veterans Program identifies evidence of pan-ancestry and ancestry-specific risk loci. Mol Psychiatry 2022; 27: 2264– 2272 35347246 PMC9910180 source

      Not checked in the free run.

  • May combine two claims.

    Study design and conductreasoning

    In the mtCOJO analysis, statistical power to detect genetic associations at individual SNPs was reduced relative to the unconditioned analysis by additional model parameters, but genetic correlations using conditioned summary statistics provide valuable insights into risk factors for SA over and above MDD and PTSD.

    “In this analysis, statistical power to detect genetic associations at individual SNPs was reduced relative to the unconditioned analysis by the additional model parameters, but the genetic correlations using the conditioned summary statistics provide valuable insights into the relevant risk factors for SA over and above those related to MDD and PTSD.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    For any evidence of inflation, the intercept was used to adjust the standard error of summary statistics.

    “For any evidence of inflation, the intercept was used to adjust the standard error of the summary statistics.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisereasoning

    Earlier GWASs suggested that larger studies would find additional genomic risk loci and improve genetic risk metrics.

    “Together, these GWASs suggested that larger studies will identify additional genomic risk loci and refine genetic risk metrics.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductcitation

    Tests were Bonferroni corrected, adjusting for up to 18 phenotypes hypothesized to be associated with SA based on previous epidemiological or genetic association evidence.

    “Tests were Bonferroni corrected, adjusting for up to 18 phenotypes hypothesized to be associated with SA based on previous epidemiological association or previous evidence of genetic association in LD Hub (34).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [34] Zheng J, Erzurumluoglu AM, Elsworth BL,: LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics 2017; 33: 272– 279 27663502 PMC5542030 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    For eight cohorts with high control:case ratios (>15:1), LDSC attenuation ratio statistics were examined for evidence of population stratification or uncontrolled type I error.

    “Eight of the cohorts had high control: case ratios (using an arbitrary cutoff of >15:1). In these cases, the linkage disequilibrium (LD) score regression (LDSC) (14) attenuation ratio statistics were examined for evidence of population stratification or uncontrolled type I error in the”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] Bulik-Sullivan BK, Loh PR, Finucane HK,: LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet 2015; 47: 291– 295 25642630 PMC4495769

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    h2 estimates remained stable across >2% and >5% MAF thresholds.

    “h2 estimates remained stable across >2% and >5% MAF thresholds.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Earlier GWASs showed that the common variant genetic architecture of suicide attempt is complex and that sample size is critical for discovering novel replicable risk loci.

    “These studies established the complexity of the common variant genetic architecture of suicide attempt and demonstrated the critical role of sample size for discovering novel, replicable risk loci for suicide phenotypes through GWASs (10).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [10] Sullivan PF, Agrawal A, Bulik CM,: Psychiatric genomics: an update and an agenda. Am J Psychiatry 2018; 175: 15– 27 28969442 PMC5756100 source

      Not checked in the free run.

  • May combine two claims.

    Premisecitation

    The ISGC GWAS found two genome-wide significant suicide attempt loci in mainly European ancestry admixtures, located on chromosomes 6 and 7.

    “The International Suicide Genetics Consortium (ISGC) (total N=549,743; 29,782 cases) identified two loci reaching genome-wide significance for suicide attempt in individuals of primarily European ancestry admixtures, on chromosomes 6 (index SNP: rs71557378; p=1.97×10−8) and 7 (index SNP: rs62474683; p=1.91×10−10) (7).”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [7] Mullins N, Kang J, Campos AI,: Dissecting the shared genetic architecture of suicide attempt, psychiatric disorders, and known risk factors. Biol Psychiatry 2022; 91: 313– 327 34861974 PMC8851871 source

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    The findings provide insight into genetic factors for suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.

    “These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    FES has previously been implicated in cross-ancestry schizophrenia.

    “FES has previously been implicated in cross-ancestry schizophrenia (53).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [53] Ikeda M, Takahashi A, Kamatani Y,: Genome-wide association study detected novel susceptibility genes for schizophrenia and shared trans-populations/diseases genetic effect. Schizophr Bull 2019; 45: 824– 834 30285260 PMC6581133

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    A meta-analysis of many diverse cohorts with different assessments of suicide attempt could reduce statistical power by increasing heterogeneity.

    “First, a meta-analysis of such a large number of diverse cohorts, with different assessments of SA, could reduce statistical power by increasing heterogeneity.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Discovery of three of the novel genome-wide significant loci, and improved out-of-sample PRS prediction across ancestry, was only possible with the aggregation of all ancestral admixture cohorts.

    “Discovery of three of the novel GWS loci, and improved out-of-sample PRS prediction across ancestry, was only possible with the aggregation of all ancestral admixture cohorts.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Drug target enrichment analyses do not identify causal relationships but may implicate genes relevant to pharmacotherapy.

    “These analyses do not identify causal relationships but may implicate genes relevant to pharmacotherapy.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    A nonsignificant HEIDI test suggests a direct causal role of SA-associated SNPs on gene expression rather than a pleiotropic effect.

    “A nonsignificant HEIDI test suggests a direct causal role of the SA-associated SNPs on gene expression, rather than a pleiotropic effect.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [51] Ge T, Chen CY, Ni Y,: Polygenic prediction via Bayesian regression and continuous shrinkage priors. Nat Commun 2019; 10: 1776 30992449 PMC6467998 source

      Not checked in the free run.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Individual cohort GWASs had variable statistical power to estimate genetic correlations with other cohorts.

    “Individual cohort GWASs were variably powered to estimate genetic correlation estimates with the other cohorts.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    The increase in sample size and statistical power led to the identification of several new genome-wide significant loci and improved out-of-sample PRS prediction across ancestries relative to previous ISGC-only analyses.

    “As expected, the increase in sample size, and the resulting increase in statistical power, led to the identification of several new GWS loci and improved out-of-sample PRS prediction, across ancestries, relative to the previous ISGC-only analyses.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Health factors play a role in suicide attempt risk that are both shared with and distinct from psychiatric disorders.

    “This suggests a potential role for health factors in SA risk that are both shared with and distinct from psychiatric disorders, as proposed in Mann and Rizk’s stress-diathesis model (55)”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [55] Mann JJ, Rizk MM: A brain-centric model of suicidal behavior. Am J Psychiatry 2020; 177: 902– 916 32998550 PMC7676389

      Not checked in the free run.

  • May combine two claims.

    Interpretationown data

    SMR results suggested that suicide attempt risk may be mediated by increased expression of FES and decreased expression of TIAF1 in cortex.

    “SMR results suggested that SA risk may be mediated by an increased expression of FES (previously implicated in cross-ancestry schizophrenia [53]) and decreased expression of TIAF1 in cortex”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [53] Ikeda M, Takahashi A, Kamatani Y,: Genome-wide association study detected novel susceptibility genes for schizophrenia and shared trans-populations/diseases genetic effect. Schizophr Bull 2019; 45: 824– 834 30285260 PMC6581133

      Not checked in the free run.

    • Rests on an assumption: SMR and HEIDI results indicate causal mediation by FES and TIAF1 rather than being due to horizontal pleiotropy or linkage.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Competitive gene-set tests were conducted to correct for gene size, variant density, and LD within and between genes.

    “Competitive gene-set tests were conducted to correct for gene size, variant density, and LD within and between genes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    This study is the largest GWAS meta-analysis of suicide attempt to date, incorporating multiple ancestral admixture populations and expanding the set of genome-wide significant loci from four to 12.

    “This study reflects the largest GWAS meta-analysis of SA to date, incorporating multiple ancestral admixture populations and expanding the set of GWS loci from four to 12.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Inclusion of age and sex covariates in three of the ISGC cohorts and MVP made the analyses more conservative.

    “Our analyses remain still more conservative with the inclusion of age and sex covariates in three of the ISGC cohorts and MVP.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    The SA GWAS meta-analysis was repeated excluding each cohort in turn to create independent discovery data sets.

    “The SA GWAS meta-analysis was repeated, excluding each cohort in turn, to create independent discovery data sets.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    Genome-wide significant loci produced similar effect sizes across cohorts and across fixed and meta-regression models, with correlations of European ancestry and multi-ancestry GWS effect sizes across models exceeding 0.99.

    “GWS loci produced similar effect sizes across cohorts and across fixed and meta-regression models (correlations of EUR and multi-ancestry GWS effect sizes across models exceeded 0.99).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    High variability in sample sizes of individual ISGC and MVP ancestral cohorts, with case Ns ranging from 115 to 9,196, meant some GWASs yielded h2 and rG estimates while others did not.

    “With high variability of sample sizes of individual ISGC and MVP ancestral cohorts (case Ns ranging from 115 to 9,196), some GWASs yielded h2 and rG estimates, while others did not.”
    Quote in the paperNot a substantial claim
51 of 51

  • The authors state this as an assumption.

    The multi-ancestry meta-analysis assumes that genetic risk effects are shared across ancestry admixtures.

    “A multi-ancestry meta-analysis of SA GWAS summary statistics was conducted using an inverse variance-weighted fixed-effects model (standard error) in METAL (17), assuming shared risk effects across ancestry admixtures.”

  • The paper relies on this without support.

    Combining cohorts with different assessments of suicide attempt yields valid meta-analysis estimates despite potential heterogeneity.

    “a meta-analysis of such a large number of diverse cohorts, with different assessments of SA, could reduce statistical power by increasing heterogeneity”

  • The paper relies on this without support.

    LDSC and Popcorn genetic correlation estimates reflect true shared genetic architecture and are not confounded by population stratification or sample overlap.

    “The genetic correlations of SA across each of the ancestral groupings were attenuated, with estimated rG values between 0.064 (SE=0.574) (EAS with LAT) and 0.997 (SE=0.537) (EUR with LAT)”

  • The paper relies on this without support.

    SMR and HEIDI results indicate causal mediation by FES and TIAF1 rather than being due to horizontal pleiotropy or linkage.

    “Two loci implicated specific genes, FES and TIAF1, that were significantly associated with SA in SMR analyses and passed the HEIDI test.”

  • The paper relies on this without support.

    The drug-gene interaction databases used for drug target enrichment are complete and accurate.

    “Only one drug, the insecticide cyfluthrin, was significantly enriched when grouping genes targeted by individual drugs (from DGIdb v.2 and the Psychoactive Drug Screening Ki Database), and this was observed only in the EUR GWAS results”

  • The paper relies on this without support.

    Genetic causal proportion analyses identify causal nonpsychiatric risks rather than only correlated associations.

    “Genetic causal proportion analyses implicated several nonpsychiatric genetic risks in EUR SA, including particulate air matter pollution exposure (PM2.5), smoking exposures, and pulmonary health factors.”

  • The paper relies on this without support.

    Suicide attempt and suicide death phenotypes lie on a severity continuum such that genetic correlations can index severity.

    “our preliminary comparison of genetic correlations across SA versus suicide death GWAS cohorts appears to implicate risk tolerance in the severity of the suicide phenotype”
7 of 7

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Docherty et al. analyzed over 44,000 cases and 900,000 controls, identifying 12 risk loci near DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2.

    “For instance, Docherty et al. analyzed over 44,000 cases and 900,000 controls, identifying 12 risk loci near DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2 (38).”

    From Exploring the neurobiological markers of suicidal behaviors in pediatric population: a narrative review (2026) · cites this paper as [38]

    The Abstract Methods report 43,871 cases—not over 44,000—and 915,025 controls. The Abstract Results and Results section report 12 genome-wide significant loci implicating the listed genes, so the control count and locus findings are supported, but the case count is overstated. (LLM, conf=0.91)

    Experimental — accuracy not yet measured

  • Large-scale GWAS from the Psychiatric Genomics Consortium and UK Biobank have identified several risk loci associated with suicide attempt.

    “Large-scale GWAS from the Psychiatric Genomics Consortium (PGC) and UK Biobank have identified several risk loci associated with suicidal attempt.”

    From Exploring the neurobiological markers of suicidal behaviors in pediatric population: a narrative review (2026) · cites this paper as [38]

    The Abstract (Conclusions; page not provided) reports suicide-attempt risk loci from large GWAS, and the paper reports 12 loci in its own meta-analysis. But it identifies the contributing studies as the International Suicide Genetics Consortium and Million Veteran Program, not GWAS from the PGC and UK Biobank. The Results (Enrichment of SA GWS Loci; page not provided) mention UK Biobank in a subsequent phenome-wide analysis, not as the source of the suicide-attempt loci. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • The largest genome-wide meta-analysis of suicide attempt identified twelve genome-wide significant loci across about 44,000 cases.

    “At the molecular level, the largest genome-wide meta-analysis of suicide attempt identified twelve genome-wide significant loci across about 44,000 cases (38)”

    From Exploring the neurobiological markers of suicidal behaviors in pediatric population: a narrative review (2026) · cites this paper as [38]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • PTSD is cited to a depression study

    Minor

    The text cites reference 32 for PTSD, but reference 32 is titled as a depression genome-wide meta-analysis. The citations for MDD and PTSD appear to be reversed.

  • MDD is cited to a PTSD study

    Minor

    The text cites reference 27 for major depressive disorder, but reference 27 is titled as a PTSD genome-wide association study.

2 of 2

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. Luo Y, 2021, Hum Mol Genet, 30, 1521

Cited by

Sorted by citations

Related

Authors
Docherty, A. R., Mullins, N., Ashley-Koch, A. E., Qin, X., Coleman, J. R. I., Shabalin, A., Kang, J., Murnyak, B., Wendt, F., Adams, M., Campos, A. I., DiBlasi, E., Fullerton, J. M., Kranzler, H. R., Bakian, A. V., Monson, E. T., Rentería, M. E., Walss-Bass, C., Andreassen, O. A., Behera, C., Bulik, C. M., Edenberg, H. J., Kessler, R. C., Mann, J. J., Nurnberger, J. I., Pistis, G., Streit, F., Ursano, R. J., Polimanti, R., Dennis, M., Garrett, M., Hair, L., Harvey, P., Hauser, E. R., Hauser, M. A., Huffman, J., Jacobson, D., Madduri, R., McMahon, B., Oslin, D. W., Trafton, J., Awasthi, S., Berrettini, W. H., Bohus, M., Chang, X., Chen, H.-C., Chen, W. J., Christensen, E. D., Crow, S., Duriez, P., Edwards, A. C., Fernández-Aranda, F., Galfalvy, H., Gandal, M., Gorwood, P., Guo, Y., Hafferty, J. D., Hakonarson, H., Halmi, K. A., Hishimoto, A., Jain, S., Jamain, S., Jiménez-Murcia, S., Johnson, C., Kaplan, A. S., Kaye, W. H., Keel, P. K., Kennedy, J. L., Kim, M., Klump, K. L., Levey, D. F., Li, D., Liao, S.-C., Lieb, K., Lilenfeld, L., Marshall, C. R., Mitchell, J. E., Okazaki, S., Otsuka, I., Pinto, D., Powers, A., Ramoz, N., Ripke, S., Roepke, S., Rozanov, V., Scherer, S. W., Schmahl, C., Sokolowski, M., Starnawska, A., Strober, M., Su, M.-H., Thornton, L. M., Treasure, J., Ware, E. B., Watson, H. J., Witt, S. H., Woodside, D. B., Yilmaz, Z., Zillich, L., Adolfsson, R., Agartz, I., Alda, M., Alfredsson, L., Appadurai, V., Artigas, M. S., Van der Auwera, S., Azevedo, M. H., Bass, N., Bau, C. H. D., Baune, B. T., Bellivier, F., Berger, K., Biernacka, J. M., Bigdeli, T. B., Binder, E. B., Boehnke, M., Boks, M. P., Braff, D. L., Bryant, R., Budde, M., Byrne, E. M., Cahn, W., Castelao, E., Cervilla, J. A., Chaumette, B., Corvin, A., Craddock, N., Djurovic, S., Foo, J. C., Forstner, A. J., Frye, M., Gatt, J. M., Giegling, I., Grabe, H. J., Green, M. J., Grevet, E. H., Grigoroiu-Serbanescu, M., Gutierrez, B., Guzman-Parra, J., Hamshere, M. L., Hartmann, A. M., Hauser, J., Heilmann-Heimbach, S., Hoffmann, P., Ising, M., Jones, I., Jones, L. A., Jonsson, L., Kahn, R. S., Kelsoe, J. R., Kendler, K. S., Kloiber, S., Koenen, K. C., Kogevinas, M., Krebs, M.-O., Landén, M., Leboyer, M., Lee, P. H., Levinson, D. F., Liao, C., Lissowska, J., Mayoral, F., McElroy, S. L., McGrath, P., McGuffin, P., McQuillin, A., Mehta, D., Melle, I., Mitchell, P. B., Molina, E., Morken, G., Nievergelt, C., Nöthen, M. M., O’Donovan, M. C., Ophoff, R. A., Owen, M. J., Pato, C., Pato, M. T., Penninx, B. W. J. H., Potash, J. B., Power, R. A., Preisig, M., Quested, D., Ramos-Quiroga, J. A., Reif, A., Ribasés, M., Richarte, V., Rietschel, M., Rivera, M., Roberts, A., Roberts, G., Rouleau, G. A., Rovaris, D. L., Sanders, A. R., Schofield, P. R., Schulze, T. G., Scott, L. J., Serretti, A., Shi, J., Sirignano, L., Sklar, P., Smeland, O. B., Smoller, J. W., Sonuga-Barke, E. J. S., Trzaskowski, M., Tsuang, M. T., Turecki, G., Vilar-Ribó, L., Vincent, J. B., Völzke, H., Walters, J. T. R., Weickert, C. S., Weickert, T. W., Weissman, M. M., Williams, L. M., Wray, N. R., Zai, C. C., Agerbo, E., Børglum, A. D., Breen, G., Demontis, D., Erlangsen, A., Gelernter, J., Glatt, S. J., Hougaard, D. M., Hwu, H.-G., Kuo, P.-H., Lewis, C. M., Li, Q. S., Liu, C.-M., Martin, N. G., McIntosh, A. M., Medland, S. E., Mors, O., Nordentoft, M., Olsen, C. M., Porteous, D., Smith, D. J., Stahl, E. A., Stein, M. B., Wasserman, D., Werge, T., Whiteman, D. C., Willour, V., (MVP), V. M. V. P., Workgroup, M. S. E., Suicide Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Eating Disorder Working Group of the Psychiatric Genomics Consortium, German Borderline Genomics Consortium, Coon, H., Beckham, J. C., Kimbrel, N. A., & Ruderfer, D. M.
Affiliations
  • Virginia Commonwealth University (US)
  • Huntsman Mental Health Institute, Salt Lake City (Docherty, Shabalin, Murnyak, DiBlasi, Coon); Department of Psychiatry (Docherty, Shabalin, Murnyak, DiBlasi, Bakian, Monson, Coon), Department of Pathology (Christensen), and Biomedical Informatics (Coon), University of Utah School of Medicine, Salt Lake City; Department of Psychiatry, Virginia Commonwealth University, Richmond (Docherty, Edwards, Bigdeli, Kendler); Department of Genetics and Genomic Sciences (Mullins, Pinto, Sklar, Stahl), Department of...
ORCID
Venue
American Journal of Psychiatry
Publisher
American Psychiatric Association Publishing
Published
2023-10-01
Volume
180
Issue
10
Pages
723-738
ISSN
  • 0002-953X (ISSN-L)
  • 1535-7228
DOI
10.1176/appi.ajp.21121266
PMC
PMC10603363
OpenAlex
W4387229289
Semantic Scholar
e2af2e2393a481739871006e584dd931898c7fe3
Cited by
160
References
51
Citations by year
2026: 54 · 2025: 66 · 2024: 35 · 2023: 4 · 2021: 1
FWCI
6.17
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • American Journal of Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
  • Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
  • ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
  • PubMed Central (acceptedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion, other-oa)
  • eScholarship (California Digital Library) (submittedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • Worcester Research and Publications (University of Worcester) (submittedVersion)
  • Digital Commons-TMC (Texas Medical Center) (submittedVersion)
  • HAL (submittedVersion)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • NHRI Institutional Repository (submittedVersion)
  • IRIS (submittedVersion)
  • ANU Open Research (Australian National University) (submittedVersion)
  • DZNE Pub (submittedVersion)
  • GoeScholar The Publication Server of the Georg-August-Universität Göttingen (Georg-August-Universität Göttingen) (submittedVersion, cc-by)
  • Pure Amsterdam UMC (submittedVersion, other-oa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • MPG.PuRe (Max Planck Society) (submittedVersion)
  • SERVAL (Université de Lausanne) (submittedVersion)
Funders
  • U.S. Department of Veterans Affairs (T32GM007347, lK6BX003777, I01 CX001729)
  • Brain and Behavior Research Foundation (28132, 29551, 28686)
  • American Foundation for Suicide Prevention
  • Bristol-Myers Squibb
  • Pfizer
  • AstraZeneca
  • Sanofi
  • Biogen
  • Office of Research and Development (#lK6BX003777)
  • Vanderbilt University (R01MH121455)
  • Leon Levy Foundation
  • Mayo Foundation for Medical Education and Research
  • University of Utah
  • Sunovion
  • National Alliance for Research on Schizophrenia and Depression (28132, 28686)
  • Regeneron Pharmaceuticals
  • Huntsman Cancer Institute (P30CA42014)
  • Jazz Pharmaceuticals
  • Les Laboratories Pierre Fabre
  • LivaNova
  • ACADIA Pharmaceuticals
  • Sage Therapeutics
  • American Society of Clinical Psychopharmacology
  • Fresenius Medical Care North America
  • Assurex Health
  • European Commission (REFORM/SC2020/029)
  • Lundbeckfonden
  • Eisai
  • King Abdulaziz University
  • Novo Nordisk
  • Shionogi
  • Hospital for Sick Children
  • Servier
  • H. Lundbeck A/S
  • Neuraxpharm
  • Idorsia Pharmaceuticals
  • National Institutes of Health (1s10od018522-01, 1s10od026880-01, UM1TR004409, UL1TR001863)
  • Genentech
  • School of Medicine
  • Clinical Science Research and Development (lK6BX003777)
  • Medical Research Council (MR/L010305/1)
  • Japan Society for the Promotion of Science (20KK0194, 21K07520, 21H02852)
  • National Institute of Mental Health (R01MH123619, K01MH109765, R01MH099134, R01MH121521, R01MH122412, R01MH123922, R01MH121455, R01MH116269, R01MH123489, R01MH137578)
  • National Cancer Institute (P30-CA 42014, S10OD018522, P30CA042014)
  • National Institute of General Medical Sciences (T32GM007347)
  • National Institute of Environmental Health Sciences (R01ES032028)
  • Janssen Research and Development
  • National Center for Advancing Translational Sciences
  • Cilag
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Social Sciences › Psychology › Clinical Psychology › Suicide and Self-Harm Studies
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
Keywords
suicide attempts, genetic risk, attention deficit hyperactivity disorder, smoking, risk tolerance, major depressive disorder, post-traumatic stress disorder, brain gene expression, genetic correlation, Mendelian randomization, veterans
MeSH terms
Major Depressive Disorder, Depressive Disorder, Major, Humans, Risk Factors, Suicide, Attempted, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Genetic Loci, Suicidal Ideation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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