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- Mullins, N., et al.
(author)
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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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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Journal article (peer-reviewed)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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- Dareng, EO, et al.
(author)
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Polygenic risk modeling for prediction of epithelial ovarian cancer risk
- 2022
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In: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
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Journal article (peer-reviewed)abstract
- Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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- Fromentin, S., et al.
(author)
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Microbiome and metabolome features of the cardiometabolic disease spectrum
- 2022
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In: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 28:2, s. 303-314
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Journal article (peer-reviewed)abstract
- By studying individuals along a spectrum of cardiometabolic disease and adjusting for effects of lifestyle and medication, this investigation identifies alterations of the metabolome and microbiome from dysmetabolic conditions, such as obesity and type 2 diabetes, to ischemic heart disease. Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages-acute coronary syndrome, chronic IHD and IHD with heart failure-and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.
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- Retamozo, S., et al.
(author)
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Influence of the age at diagnosis in the disease expression of primary Sjogren's syndrome : Analysis of 12,753 patients from the Sjogren Big Data Consortium
- 2021
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In: Clinical and Experimental Rheumatology. - : CLINICAL & EXPER RHEUMATOLOGY. - 0392-856X .- 1593-098X. ; 39:6, s. S166-S174
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Journal article (peer-reviewed)abstract
- Objective. To analyse how the main components of the disease phenotype (sicca symptoms, diagnostic tests, immunological markers and systemic disease) can be driven by the age at diagnosis of primary Sjogren's syndrome (pSS).Methods. By January 2021, the participant centres had included 12,753 patients from 25 countries that fulfilled the 2002/2016 classification criteria for pSS. The age at diagnosis was defined as the time when the attending physician confirmed fulfilment of the criteria. Patients were clustered according to age at diagnosis. 50 clusters with more than 100 observations (from 27 to 76 years) were used to study the influence of the age at diagnosis in the disease expression.Results. There was a consistent increase in the frequency of oral dryness according to the age at diagnosis, with a frequency of <90% in patients diagnosed at the youngest ages and >95% in those diagnosed at the oldest ages. The smooth curves that best fitted a linear model were the frequency of dry mouth (adjusted R-2 0.87) and the frequency of abnormal oral tests (adjusted R-2 0.72). Therefore, for each 1-year increase in the age at diagnosis, the frequency of dry mouth increased by 0.13%, and the frequency of abnormal oral diagnostic tests by 0.11%. There was a consistent year-by-year decrease in the frequency of all autoantibodies and immunological markers except for cryoglobulins. According to the linear models, for each 1-year increase in the age at diagnosis, the frequency of a positive result decreased by 0.57% (for anti-Ro antibodies), 0.47% (for RF) and 0.42% (for anti-La antibodies). The ESSDAI domains which showed a more consistent decrease were glandular and lymph node involvement (for each 1-year increase in the age at diagnosis, the frequency of activity decreased by 0.18%), and constitutional, cutaneous, and haematological involvements (the frequency decreased by 0.09% for each 1-year increase). In contrast, other domains showed an ascending pattern, especially pulmonary involvement (for each 1-year increase in the age at diagnosis, the frequency of activity increased by 0.22%), and peripheral nerve involvement (the frequency increased by 0.09% for each 1-year increase).Conclusion. The influence of the age at diagnosis on the key phenotypic features of pSS is strong, and should be considered critical not only for designing a personalised diagnostic approach, but also to be carefully considered when analysing the results of diagnostic tests and immunological parameters, and when internal organ involvement is suspected at diagnosis.
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