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- Bergen, S. E., et al.
(författare)
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Genome-wide association study in a Swedish population yields support for greater CNV and MHC involvement in schizophrenia compared with bipolar disorder
- 2012
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 17:9, s. 880-886
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Tidskriftsartikel (refereegranskat)abstract
- Schizophrenia (SCZ) and bipolar disorder (BD) are highly heritable psychiatric disorders with overlapping susceptibility loci and symptomatology. We conducted a genome-wide association study (GWAS) of these disorders in a large Swedish sample. We report a new and independent case-control analysis of 1507 SCZ cases, 836 BD cases and 2093 controls. No single-nucleotide polymorphisms (SNPs) achieved significance in these new samples; however, combining new and previously reported SCZ samples (2111 SCZ and 2535 controls) revealed a genome-wide significant association in the major histocompatibility complex (MHC) region (rs886424, P = 4.54 x 10(-8)). Imputation using multiple reference panels and meta-analysis with the Psychiatric Genomics Consortium SCZ results underscored the broad, significant association in the MHC region in the full SCZ sample. We evaluated the role of copy number variants (CNVs) in these subjects. As in prior reports, deletions were enriched in SCZ, but not BD cases compared with controls. Singleton deletions were more frequent in both case groups compared with controls (SCZ: P = 0.003, BD: P = 0.013), whereas the largest CNVs (>500 kb) were significantly enriched only in SCZ cases (P = 0.0035). Two CNVs with previously reported SCZ associations were also overrepresented in this SCZ sample: 16p11.2 duplications (P = 0.0035) and 22q11 deletions (P = 0.03). These results reinforce prior reports of significant MHC and CNV associations in SCZ, but not BD.
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- Forstner, A. J., et al.
(författare)
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Genome-wide association study of panic disorder reveals genetic overlap with neuroticism and depression
- 2021
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Ingår i: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26
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Tidskriftsartikel (refereegranskat)abstract
- Panic disorder (PD) has a lifetime prevalence of 2–4% and heritability estimates of 40%. The contributory genetic variants remain largely unknown, with few and inconsistent loci having been reported. The present report describes the largest genome-wide association study (GWAS) of PD to date comprising genome-wide genotype data of 2248 clinically well-characterized PD patients and 7992 ethnically matched controls. The samples originated from four European countries (Denmark, Estonia, Germany, and Sweden). Standard GWAS quality control procedures were conducted on each individual dataset, and imputation was performed using the 1000 Genomes Project reference panel. A meta-analysis was then performed using the Ricopili pipeline. No genome-wide significant locus was identified. Leave-one-out analyses generated highly significant polygenic risk scores (PRS) (explained variance of up to 2.6%). Linkage disequilibrium (LD) score regression analysis of the GWAS data showed that the estimated heritability for PD was 28.0–34.2%. After correction for multiple testing, a significant genetic correlation was found between PD and major depressive disorder, depressive symptoms, and neuroticism. A total of 255 single-nucleotide polymorphisms (SNPs) with p < 1 × 10−4 were followed up in an independent sample of 2408 PD patients and 228,470 controls from Denmark, Iceland and the Netherlands. In the combined analysis, SNP rs144783209 showed the strongest association with PD (pcomb = 3.10 × 10−7). Sign tests revealed a significant enrichment of SNPs with a discovery p-value of <0.0001 in the combined follow up cohort (p = 0.048). The present integrative analysis represents a major step towards the elucidation of the genetic susceptibility to PD. © 2019, The Author(s), under exclusive licence to Springer Nature Limited.
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| 6. |
- Legge, SE, et al.
(författare)
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Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia
- 2018
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Ingår i: Molecular psychiatry. - : Springer Science and Business Media LLC. - 1476-5578 .- 1359-4184. ; 23:1, s. 162-163
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Tidskriftsartikel (refereegranskat)abstract
- Correction to: Molecular Psychiatry (2017) 22: 1502-1508; advance online publication, 12 July 2017; doi: 10.1038/mp.2016.97 In the first paragraph of the Results section and Figure 1, the authors incorrectly referred to the finding of SNP rs77897117. The correct SNP is rs77897177. The corrected figure appears in previous page.
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| 9. |
- 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
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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 19 779 bipolar disorder (BP) and schizophrenia (SCZ) cases versus 19 423 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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