| 1. |
- 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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| 2. |
- 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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| 3. |
- Mullins, Niamh, et al.
(author)
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GWAS of Suicide Attempt in Psychiatric Disorders and Association With Major Depression Polygenic Risk Scores
- 2019
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In: American Journal of Psychiatry. - : American Psychiatric Association Publishing. - 0002-953X .- 1535-7228. ; 176:8, s. 651-660
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Journal article (peer-reviewed)abstract
- Objective: More than 90% of people who attempt suicide have a psychiatric diagnosis; however, twin and family studies suggest that the genetic etiology of suicide attempt is partially distinct from that of the psychiatric disorders themselves. The authors present the largest genome-wide association study (GWAS) on suicide attempt, using cohorts of individuals with major depressive disorder, bipolar disorder, and schizophrenia from the Psychiatric Genomics Consortium.Methods: The samples comprised 1,622 suicide attempters and 8,786 nonattempters with major depressive disorder; 3,264 attempters and 5,500 nonattempters with bipolar disorder; and 1,683 attempters and 2,946 nonattempters with schizophrenia. A GWAS on suicide attempt was performed by comparing attempters to nonattempters with each disorder, followed by a meta-analysis across disorders. Polygenic risk scoring was used to investigate the genetic relationship between suicide attempt and the psychiatric disorders.Results: Three genome-wide significant loci for suicide attempt were found: one associated with suicide attempt in major depressive disorder, one associated with suicide attempt in bipolar disorder, and one in the meta-analysis of suicide attempt in mood disorders. These associations were not replicated in independent mood disorder cohorts from the UK Biobank and iPSYCH. No significant associations were found in the meta-analysis of all three disorders. Polygenic risk scores for major depression were significantly associated with suicide attempt in major depressive disorder (R2=0.25%), bipolar disorder (R2=0.24%), and schizophrenia (R2=0.40%).Conclusions: This study provides new information on genetic associations and demonstrates that genetic liability for major depression increases risk for suicide attempt across psychiatric disorders. Further collaborative efforts to increase sample size may help to robustly identify genetic associations and provide biological insights into the etiology of suicide attempt.
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| 4. |
- Kaufmann, Tobias, et al.
(author)
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Common brain disorders are associated with heritable patterns of apparent aging of the brain
- 2019
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In: Nature Neuroscience. - : Nature Publishing Group. - 1097-6256 .- 1546-1726. ; 22:10, s. 1617-
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Journal article (peer-reviewed)abstract
- Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.
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| 5. |
- Chen, Chi-Hua, et al.
(author)
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Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure
- 2017
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 7
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Journal article (peer-reviewed)abstract
- Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10−8). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen.
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| 6. |
- Córdova-Palomera, Aldo, et al.
(author)
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Genetic control of variability in subcortical and intracranial volumes
- 2021
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In: Molecular Psychiatry. - : Nature Publishing Group. - 1359-4184 .- 1476-5578. ; 26:8, s. 3876-3883
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Journal article (peer-reviewed)abstract
- Sensitivity to external demands is essential for adaptation to dynamic environments, but comes at the cost of increased risk of adverse outcomes when facing poor environmental conditions. Here, we apply a novel methodology to perform genome-wide association analysis of mean and variance in ten key brain features (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, intracranial volume, cortical surface area, and cortical thickness), integrating genetic and neuroanatomical data from a large lifespan sample (n = 25,575 individuals; 8-89 years, mean age 51.9 years). We identify genetic loci associated with phenotypic variability in thalamus volume and cortical thickness. The variance-controlling loci involved genes with a documented role in brain and mental health and were not associated with the mean anatomical volumes. This proof-of-principle of the hypothesis of a genetic regulation of brain volume variability contributes to establishing the genetic basis of phenotypic variance (i.e., heritability), allows identifying different degrees of brain robustness across individuals, and opens new research avenues in the search for mechanisms controlling brain and mental health.
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| 7. |
- Lo, Min-Tzu, et al.
(author)
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Genome-wide analyses for personality traits identify six genomic loci and show correlations with psychiatric disorders
- 2017
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 49:1, s. 152-156
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Journal article (peer-reviewed)abstract
- Personality is influenced by genetic and environmental factors(1) and associated with mental health. However, the underlying genetic determinants are largely unknown. We identified six genetic loci, including five novel loci(2,3), significantly associated with personality traits in a meta-analysis of genome-wide association studies (N = 123,132-260,861). Of these genome-wide significant loci, extraversion was associated with variants in WSCD2 and near PCDH15, and neuroticism with variants on chromosome 8p23.1 and in L3MBTL2. We performed a principal component analysis to extract major dimensions underlying genetic variations among five personality traits and six psychiatric disorders (N = 5,422-18,759). The first genetic dimension separated personality traits and psychiatric disorders, except that neuroticism and openness to experience were clustered with the disorders. High genetic correlations were found between extraversion and attention-deficit- hyperactivity disorder (ADHD) and between openness and schizophrenia and bipolar disorder. The second genetic dimension was closely aligned with extraversion-introversion and grouped neuroticism with internalizing psychopathology (e.g., depression or anxiety).
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| 8. |
- Lo, Min-Tzu, et al.
(author)
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Modeling prior information of common genetic variants improves gene discovery for neuroticism
- 2017
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In: Human Molecular Genetics. - : OXFORD UNIV PRESS. - 0964-6906 .- 1460-2083. ; 26:22, s. 4530-4539
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Journal article (peer-reviewed)abstract
- Neuroticism reflects emotional instability, and is related to various mental and physical health issues. However, the majority of genetic variants associated with neuroticism remain unclear. Inconsistent genetic variants identified by different genome-wide association studies (GWAS) may be attributable to low statistical power. We proposed a novel framework to improve the power for gene discovery by incorporating prior information of single nucleotide polymorphisms (SNPs) and combining two relevant existing tools, relative enrichment score (RES) and conditional false discovery rate (FDR). Here, SNP's conditional FDR was estimated given its RES based on SNP prior information including linkage disequilibrium (LD)-weighted genic annotation scores, total LD scores and heterozygosity. A known significant locus in chromosome 8p was excluded before estimating FDR due to long-range LD structure. Only one significant LD-independent SNP was detected by analyses of unconditional FDR and traditional GWAS in the discovery sample (N = 59 225), and notably four additional SNPs by conditional FDR. Three of the five SNPs, all identified by conditional FDR, were replicated (P < 0.05) in an independent sample (N = 170 911). These three SNPs are located in intronic regions of CADM2, LINGO2 and EP300 which have been reported to be associated with autism, Parkinson's disease and schizophrenia, respectively. Our approach using a combination of RES and conditional FDR improved power of traditional GWAS for gene discovery providing a useful framework for the analysis of GWAS summary statistics by utilizing SNP prior information, and helping to elucidate the links between neuroticism and complex diseases from a genetic perspective.
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| 9. |
- Smeland, Olav B., et al.
(author)
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Shared genetic variants between schizophrenia and general cognitive function indicate common molecular genetic mechanisms
- 2017
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In: European Neuropsychopharmacology. - : ELSEVIER SCIENCE BV. - 0924-977X .- 1873-7862. ; 27, s. S410-S410
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Journal article (other academic/artistic)abstract
- Background: Schizophrenia (SCZ) is a severe mental disorder characterized by widespread cognitive impairments including deficits in learning, memory, processing speed, attention and executive functioning. Although cognitive deficits are a strong predictor of functional outcome in SCZ, current treatment strategies largely fail to ameliorate these impairments. Thus, in order to develop more efficient treatment strategies in SCZ, a better understanding of the pathogenesis of these cognitive deficits is needed. Given that both SCZ and cognitive ability are substantially heritable, we here aimed to determine whether SCZ share genetic influences with general cognitive function (COG), a phenotype that captures the shared variation in performance across several cognitive domains. Methods: We analyzed GWAS results in the form of summary statistics (p-values and z-scores) from SCZ (the Psychiatric Genomics Consortium; n=82 315) and COG (CHARGE Consortium; n=53 949). We applied a conditional false discovery rate (FDR) framework. By leveraging SNP-associations in a secondary trait (SCZ or COG), the conditional FDR approach increases power to detect loci in the primary trait (COG or SCZ), regardless of the directions of allelic effects of the risk loci. We then applied the conjunction FDR to identify shared loci between the phenotypes. The conjunction FDR is defined as the maximum of the conditional FDRs for both directions, and we used an overall FDR threshold of 0.05. Results: To visualize pleiotropic enrichment, we constructed conditional Q-Q plots which indicate substantial polygenetic overlap between SCZ and COG. For progressively stringent p-value thresholds for SCZ SNPs, we found approximately 150-fold enrichment for COG. For progressively stringent p-value thresholds for COG SNPs, we found approximately 100-fold enrichment for SCZ. We then used the conjunction FDR and identified fourteen independent loci shared between SCZ and COG. The majority of the shared loci show inverse associations in SCZ and COG, in line with the observed cognitive dysfunction in SCZ. Discussion: Our preliminary findings indicate shared molecular genetic mechanisms between SCZ and COG, which may provide important new insights into the pathogenesis of cognitive dysfunction in SCZ.
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