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- 2019
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Journal article (peer-reviewed)
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| 2. |
- Docherty, Anna R, et al.
(author)
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GWAS Meta-Analysis of Suicide Attempt: Identification of 12 Genome-Wide Significant Loci and Implication of Genetic Risks for Specific Health Factors.
- 2023
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In: The American journal of psychiatry. - : American Psychiatric Association Publishing. - 1535-7228 .- 0002-953X. ; 180:10, s. 723-738
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Journal article (peer-reviewed)abstract
- 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.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.Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). 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.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.
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| 3. |
- Mullins, Niamh, et al.
(author)
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Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors
- 2022
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In: Biological Psychiatry. - : Elsevier. - 0006-3223 .- 1873-2402. ; 91:3, s. 313-327
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Journal article (peer-reviewed)abstract
- BACKGROUND: Suicide 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.METHODS: We 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.RESULTS: Two 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.CONCLUSIONS: Our 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.
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- Vargas, Kris G, et al.
(author)
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Variations on classification of main types of myocardial infarction : a systematic review and outcome meta-analysis
- 2019
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In: Clinical Research in Cardiology. - : Springer. - 1861-0684 .- 1861-0692. ; 108:7, s. 749-762
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Journal article (peer-reviewed)abstract
- OBJECTIVE: Classifying myocardial infarction into type 1 (T1MI) or type 2 (T2MI) remains a challenge in clinical practice. We aimed to identify factors contributing to variation in the classifications of MI into type 1 or type 2. In addition, pooled analyses of long-term mortality and reinfarction outcomes were performed.METHODS: We searched Medline, Embase and Web of Science through January 2018 for observational studies or clinical trials classifying patients as either T1MI or T2MI. Studies with baseline characteristics allowing a comparison between both groups were included. Inverse variance random-effects models were used to pool risk ratios (RR).RESULTS: Overall, 93,194 patients from 20 included observational studies were classified as T1MI and 9291 as T2MI; corresponding to 87.9% and 8.8% of all patients diagnosed with MI. Inclusion of ST-elevation MI patients was inconsistent among studies. Coronary angiography was performed in 77.7% and 31.5% of all patients with T1MI and T2MI, respectively. From a subgroup of 11 studies, percutaneous coronary intervention was performed in 79.2% of all patients classified as T1MI (range 44.2-93.0%) and 40.2% of all T2MI patients (range 0-87.5%). A meta-analysis of 6 studies (44,366 in total) on 2-year mortality showed worse outcome among T2MI patients (RR: 1.52, CI 1.07-2.17, P = 0.02; I2 = 92%). Risk of reinfarction at 1.6 years was higher among T2MI patients (RR: 1.68, CI 1.22-2.31, P = 0.001; I2 = 9%).CONCLUSIONS: Classification of T1MI and T2MI varies widely among studies. A standardized approach with clear definitions is needed to avoid misclassification and ensure appropriate patient management.
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