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- Smeland, Olav B., et al.
(författare)
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Shared genetic variants between schizophrenia and general cognitive function indicate common molecular genetic mechanisms
- 2017
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Ingår i: European Neuropsychopharmacology. - : ELSEVIER SCIENCE BV. - 0924-977X .- 1873-7862. ; 27, s. S410-S410
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)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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| 2. |
- van der Meer, Dennis, et al.
(författare)
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The role of liver fat in cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition
- 2022
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Background & AimsObesity and associated morbidities, metabolic associated liver disease (MAFLD) included, constitute some of the largest public health threats worldwide. Body composition and related risk factors are known to be heritable and identification of their genetic determinants may aid in the development of better prevention and treatment strategies. Recently, large-scale whole-body MRI data has become available, providing more specific measures of body composition than anthropometrics such as body mass index. Here, we aimed to elucidate the genetic architecture of body composition, by conducting the first genome-wide association study (GWAS) of these MRI-derived measures.MethodsWe ran both univariate and multivariate GWAS on fourteen MRI-derived measurements of adipose and muscle tissue distribution, derived from scans from 34,036 White European UK Biobank participants (mean age of 64.5 years, 51.5% female).ResultsThrough multivariate analysis, we discovered 108 loci with distributed effects across the body composition measures and 256 significant genes primarily involved in immune system functioning. Liver fat stood out, with a highly discoverable and oligogenic architecture and the strongest genetic associations. Comparison with 21 common cardiometabolic traits revealed both shared and specific genetic influences, with higher mean heritability for the MRI measures (h2=.25 vs. .16, p=1.4×10−6). We found substantial genetic correlations between the body composition measures and a range of cardiometabolic diseases, with the strongest correlation between liver fat and type 2 diabetes (rg=.48, p=1.6×10−22).ConclusionsThese findings show that MRI-derived body composition measures complement conventional body anthropometrics and other biomarkers of cardiometabolic health, highlighting the central role of liver fat, and improving our knowledge of the genetic architecture of body composition and related diseases.
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