| 11. |
- Jonsson, Lina, 1982, et al.
(författare)
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Characterisation of age and polarity at onset in bipolar disorder
- 2021
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Ingår i: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 219:6, s. 659-669
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Tidskriftsartikel (refereegranskat)abstract
- Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (beta = -0.34 years, s.e. = 0.08), major depression (beta = -0.34 years, s.e. = 0.08), schizophrenia (beta = -0.39 years, s.e. = 0.08), and educational attainment (beta = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
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| 12. |
- Maier, R., et al.
(författare)
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Joint Analysis of Psychiatric Disorders Increases Accuracy of Risk Prediction for Schizophrenia, Bipolar Disorder, and Major Depressive Disorder
- 2015
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 96:2, s. 283-294
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Tidskriftsartikel (refereegranskat)abstract
- Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk prediction is low. Here we use a multivariate linear mixed model and apply multi-trait genomic best linear unbiased prediction for genetic risk prediction. This method exploits correlations between disorders and simultaneously evaluates individual risk for each disorder. We show that the multivariate approach significantly increases the prediction accuracy for schizophrenia, bipolar disorder, and major depressive disorder in the discovery as well as in independent validation datasets. By grouping SNPs based on genome annotation and fitting multiple random effects, we show that the prediction accuracy could be further improved. The gain in prediction accuracy of the multivariate approach is equivalent to an increase in sample size of 34% for schizophrenia, 68% for bipolar disorder, and 76% for major depressive disorders using single trait models. Because our approach can be readily applied to any number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low polygenic risk.
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| 13. |
- Mullins, N., et al.
(författare)
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
- 2021
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.
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| 14. |
- Munn-Chernoff, M. A., et al.
(författare)
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Shared genetic risk between eating disorder- and substance-use-related phenotypes: Evidence from genome-wide association studies
- 2021
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Ingår i: Addiction Biology. - : Wiley. - 1355-6215 .- 1369-1600. ; 26:1
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Tidskriftsartikel (refereegranskat)abstract
- Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r(g)], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from similar to 2400 to similar to 537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r(g) = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r(g) = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r(g) = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r(gs) = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.
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| 15. |
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| 16. |
- Ruderfer, D M, et al.
(författare)
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Polygenic dissection of diagnosis and clinical dimensions of bipolar disorder and schizophrenia.
- 2014
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Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 19:9, s. 1017-1024
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Tidskriftsartikel (refereegranskat)abstract
- Bipolar disorder and schizophrenia are two often severe disorders with high heritabilities. Recent studies have demonstrated a large overlap of genetic risk loci between these disorders but diagnostic and molecular distinctions still remain. Here, we perform a combined genome-wide association study (GWAS) of 19779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19423 controls, in addition to a direct comparison GWAS of 7129 SCZ cases versus 9252 BP cases. In our case-control analysis, we identify five previously identified regions reaching genome-wide significance (CACNA1C, IFI44L, MHC, TRANK1 and MAD1L1) and a novel locus near PIK3C2A. We create a polygenic risk score that is significantly different between BP and SCZ and show a significant correlation between a BP polygenic risk score and the clinical dimension of mania in SCZ patients. Our results indicate that first, combining diseases with similar genetic risk profiles improves power to detect shared risk loci and second, that future direct comparisons of BP and SCZ are likely to identify loci with significant differential effects. Identifying these loci should aid in the fundamental understanding of how these diseases differ biologically. These findings also indicate that combining clinical symptom dimensions and polygenic signatures could provide additional information that may someday be used clinically.Molecular Psychiatry advance online publication, 26 November 2013;
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| 17. |
- Smoller, JW, et al.
(författare)
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Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis.
- 2013
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Ingår i: Lancet. - 1474-547X. ; 381:9875, s. 1371-9
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Tidskriftsartikel (refereegranskat)abstract
- Findings from family and twin studies suggest that genetic contributions to psychiatric disorders do not in all cases map to present diagnostic categories. We aimed to identify specific variants underlying genetic effects shared between the five disorders in the Psychiatric Genomics Consortium: autism spectrum disorder, attention deficit-hyperactivity disorder, bipolar disorder, major depressive disorder, and schizophrenia.
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| 18. |
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| 19. |
- Witt, S. H., et al.
(författare)
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Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia
- 2017
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Ingår i: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P = 4.42 x 10(-7)) and PKP4 (P = 8.67 x 10(-7)); and gene-set analysis yielded a significant finding for exocytosis (GO: 0006887, PFDR = 0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (r(g) = 0.28 [P = 2.99 x 10(-3)]), SCZ (r(g) = 0.34 [P = 4.37 x 10(-5)]) and MDD (r(g) = 0.57 [P = 1.04 x 10(-3)]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.
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