1,721,085 research outputs found
MOESM2 of Exome sequencing reveals a high prevalence of BRCA1 and BRCA2 founder variants in a diverse population-based biobank
No full textAdditional file 2. Banner Author Lists and Contribution Statements. The Charles Bronfman Institute of Personalized Medicine (CBIPM) Genomics Team Banner Author List and Contribution Statements. Regeneron Genetics Center Banner Author List and Contribution Statements
Association of Thyroid Function with Blood Pressure and Cardiovascular Disease: A Mendelian Randomization.
Full text linkThyroid function has a widespread effect on the cardiometabolic system. However, the causal association between either subclinical hyper- or hypothyroidism and the thyroid hormones with blood pressure (BP) and cardiovascular diseases (CVD) is not clear. We aim to investigate this in a two-sample Mendelian randomization (MR) study. Single nucleotide polymorphisms (SNPs) associated with thyroid-stimulating hormone (TSH), free tetraiodothyronine (FT4), hyper- and hypothyroidism, and anti-thyroid peroxidase antibodies (TPOAb), from genome-wide association studies (GWAS), were selected as MR instrumental variables. SNPs-outcome (BP, CVD) associations were evaluated in a large-scale cohort, the Malmö Diet and Cancer Study (n = 29,298). Causal estimates were computed by inverse-variance weighted (IVW), weighted median, and MR-Egger approaches. Genetically increased levels of TSH were associated with decreased systolic BP and with a lower risk of atrial fibrillation. Hyperthyroidism and TPOAb were associated with a lower risk of atrial fibrillation. Our data support a causal association between genetically decreased levels of TSH and both atrial fibrillation and systolic BP. The lack of significance after Bonferroni correction and the sensitivity analyses suggesting pleiotropy, should prompt us to be cautious in their interpretation. Nevertheless, these findings offer mechanistic insight into the etiology of CVD. Further work into the genes involved in thyroid functions and their relation to cardiovascular outcomes may highlight pathways for targeted intervention
The genetic architecture of Plakophilin 2 cardiomyopathy
Full text linkPurpose: The genetic architecture of Plakophilin 2 (PKP2) cardiomyopathy can inform our understanding of its variant pathogenicity and protein function. Methods: We assess the gene-wide and regional association of truncating and missense variants in PKP2 with arrhythmogenic cardiomyopathy (ACM), and arrhythmogenic right ventricular cardiomyopathy (ARVC) specifically. A discovery data set compares genetic testing requisitions to gnomAD. Validation is performed in a rigorously phenotyped definite ARVC cohort and non-ACM individuals in the Geisinger MyCode cohort. Results: The etiologic fraction (EF) of ACM-related diagnoses from truncating variants in PKP2 is significant (0.85 [0.80,0.88], p < 2 × 10 −16), increases for ARVC specifically (EF = 0.96 [0.94,0.97], p < 2 × 10 −16), and is highest in definite ARVC versus non-ACM individuals (EF = 1.00 [1.00,1.00], p < 2 × 10 −16). Regions of missense variation enriched for ACM probands include known functional domains and the C-terminus, which was not previously known to contain a functional domain. No regional enrichment was identified for truncating variants. Conclusion: This multicohort evaluation of the genetic architecture of PKP2 demonstrates the specificity of PKP2 truncating variants for ARVC within the ACM disease spectrum. We identify the PKP2 C-terminus as a potential functional domain and find that truncating variants likely cause disease irrespective of transcript position
The genomics of heart failure: design and rationale of the HERMES consortium
Full text linkAims: The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure. Methods and results: The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome-wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow-up following heart failure diagnosis ranged from 2 to 116 months. Forty-nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low-frequency variants (allele frequency 0.01–0.05) at P < 5 × 10 −8 under an additive genetic model. Conclusions: HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction
Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure
Full text linkHeart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies
Correction to: The genetic architecture of Plakophilin 2 cardiomyopathy
Full text linkThe original article can be found online at https://doi.org/10.1038/s41436-021-01233-7. Correction to: Genetics in Medicine 2021; https://doi.org/10.1038/s41436-021-01233-7 published online 12 June 2021 Due to a processing error Cynthia James, Brittney Murray, and Crystal Tichnell were assigned to the wrong affiliation. Cynthia James, Brittney Murray, and Crystal Tichnell have as their affiliation 5 Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA. In addition Hana Zouk, Megan Hawley, and Birgit Funke were assigned only to affiliation 3; they also have affiliation 4 Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. The original article has been corrected
Thrombotic risk determined by CREB3L1 variants in a population-based cohort study linkage disequilibrium with prothrombin mutation
No full textSERPINH1 variants and thrombotic risk among middle-aged and older adults a population-based cohort study
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Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank.
No full textWhole-genome sequencing (WGS), whole-exome sequencing (WES) and array genotyping with imputation (IMP) are common strategies for assessing genetic variation and its association with medically relevant phenotypes. To date, there has been no systematic empirical assessment of the yield of these approaches when applied to hundreds of thousands of samples to enable the discovery of complex trait genetic signals. Using data for 100 complex traits from 149,195 individuals in the UK Biobank, we systematically compare the relative yield of these strategies in genetic association studies. We find that WGS and WES combined with arrays and imputation (WES + IMP) have the largest association yield. Although WGS results in an approximately fivefold increase in the total number of assayed variants over WES + IMP, the number of detected signals differed by only 1% for both single-variant and gene-based association analyses. Given that WES + IMP typically results in savings of lab and computational time and resources expended per sample, we evaluate the potential benefits of applying WES + IMP to larger samples. When we extend our WES + IMP analyses to 468,169 UK Biobank individuals, we observe an approximately fourfold increase in association signals with the threefold increase in sample size. We conclude that prioritizing WES + IMP and large sample sizes rather than contemporary short-read WGS alternatives will maximize the number of discoveries in genetic association studies
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