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- Zhou, Wei, et al.
(author)
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Global Biobank Meta-analysis Initiative : Powering genetic discovery across human disease
- 2022
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In: Cell Genomics. - : Elsevier. - 2666-979X. ; 2:10
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Journal article (peer-reviewed)abstract
- Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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3. |
- Schuermans, Art, et al.
(author)
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Clonal haematopoiesis of indeterminate potential predicts incident cardiac arrhythmias
- 2024
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In: European Heart Journal. - 0195-668X. ; 45:10, s. 791-805
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Journal article (peer-reviewed)abstract
- Background and Clonal haematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells with preleukemic mutaAims tions, is associated with atherosclerotic cardiovascular disease and heart failure. This study aimed to test the association of CHIP with new-onset arrhythmias.Methods UK Biobank participants without prevalent arrhythmias were included. Co-primary study outcomes were supraventricular arrhythmias, bradyarrhythmias, and ventricular arrhythmias. Secondary outcomes were cardiac arrest, atrial fibrillation, and any arrhythmia. Associations of any CHIP [variant allele fraction (VAF) ≥ 2%], large CHIP (VAF ≥10%), and gene-specific CHIP subtypes with incident arrhythmias were evaluated using multivariable-adjusted Cox regression. Associations of CHIP with myocardial interstitial fibrosis [T1 measured using cardiac magnetic resonance (CMR)] were also tested. Results This study included 410 702 participants [CHIP: n = 13 892 (3.4%); large CHIP: n = 9191 (2.2%)]. Any and large CHIP were associated with multi-variable-adjusted hazard ratios of 1.11 [95% confidence interval (CI) 1.04–1.18; P = .001] and 1.13 (95% CI 1.05–1.22; P = .001) for supraventricular arrhythmias, 1.09 (95% CI 1.01–1.19; P = .031) and 1.13 (95% CI 1.03–1.25; P = .011) for bradyarrhythmias, and 1.16 (95% CI, 1.00–1.34; P = .049) and 1.22 (95% CI 1.03–1.45; P = .021) for ventricular arrhythmias, respectively. Associations were independent of coronary artery disease and heart failure. Associations were also heterogeneous across arrhythmia subtypes and strongest for cardiac arrest. Gene-specific analyses revealed an increased risk of arrhythmias across driver genes other than DNMT3A. Large CHIP was associated with 1.31-fold odds (95% CI 1.07–1.59; P = .009) of being in the top quintile of myocardial fibrosis by CMR. Conclusions CHIP may represent a novel risk factor for incident arrhythmias, indicating a potential target for modulation towards arrhythmia prevention and treatment.
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