57 research outputs found
Independent susceptibility markers for atrial fibrillation on chromosome 4q25
Background-: Genetic variants on chromosome 4q25 are associated with atrial fibrillation (AF). We sought to determine whether there is more than 1 susceptibility signal at this locus. Methods and results-: Thirty-four haplotype-tagging single-nucleotide polymorphisms (SNPs) at the 4q25 locus were genotyped in 790 case and 1177 control subjects from Massachusetts General Hospital and tested for association with AF. We replicated SNPs associated with AF after adjustment for the most significantly associated SNP in 5066 case and 30 661 referent subjects from the German Competence Network for Atrial Fibrillation, Atherosclerosis Risk In Communities Study, Cleveland Clinic Lone AF Study, Cardiovascular Health Study, and Rotterdam Study. All subjects were of European ancestry. A multimarker risk score composed of SNPs that tagged distinct AF susceptibility signals was constructed and tested for association with AF, and all results were subjected to meta-analysis. The previously reported SNP, rs2200733, was most significantly associated with AF (minor allele odds ratio 1.80, 95% confidence interval 1.50 to 2.15, P=1.2×10) in the discovery sample. Adjustment for rs2200733 genotype revealed 2 additional susceptibility signals marked by rs17570669 and rs3853445. A graded risk of AF was observed with an increasing number of AF risk alleles at SNPs that tagged these 3 susceptibility signals. Conclusions-: We identified 2 novel AF susceptibility signals on chromosome 4q25. Consideration of multiple susceptibility signals at chromosome 4q25 identifies individuals with an increased risk of AF and may localize regulatory elements at the locus with biological relevance in the pathogenesis of AF
Arrhythmic risk prediction in arrhythmogenic right ventricular cardiomyopathy : external validation of the arrhythmogenic right ventricular cardiomyopathy risk calculator
Aims: Arrhythmogenic right ventricular cardiomyopathy (ARVC) causes ventricular arrhythmias (VAs) and sudden cardiac death (SCD). In 2019, a risk prediction model that estimates the 5-year risk of incident VAs in ARVC was developed (ARVCrisk.com). This study aimed to externally validate this prediction model in a large international multicentre cohort and to compare its performance with the risk factor approach recommended for implantable cardioverter-defibrillator (ICD) use by published guidelines and expert consensus. Methods and results: In a retrospective cohort of 429 individuals from 29 centres in North America and Europe, 103 (24%) experienced sustained VA during a median follow-up of 5.02 (2.05-7.90) years following diagnosis of ARVC. External validation yielded good discrimination [C-index of 0.70 (95% confidence interval-CI 0.65-0.75)] and calibration slope of 1.01 (95% CI 0.99-1.03). Compared with the three published consensus-based decision algorithms for ICD use in ARVC (Heart Rhythm Society consensus on arrhythmogenic cardiomyopathy, International Task Force consensus statement on the treatment of ARVC, and American Heart Association guidelines for VA and SCD), the risk calculator performed better with a superior net clinical benefit below risk threshold of 35%. Conclusion: Using a large independent cohort of patients, this study shows that the ARVC risk model provides good prognostic information and outperforms other published decision algorithms for ICD use. These findings support the use of the model to facilitate shared decision making regarding ICD implantation in the primary prevention of SCD in ARVC
Genetic burden of TNNI3K in diagnostic testing of patients with dilated cardiomyopathy and supraventricular arrhythmias
BACKGROUND:Genetic variants in TNNI3K (troponin-I interacting kinase) have previously been associated with dilated cardiomyopathy (DCM), cardiac conduction disease, and supraventricular tachycardias. However, the link between TNNI3K variants and these cardiac phenotypes shows a lack of consensus concerning phenotype and protein function. METHODS:We describe a systematic retrospective study of a cohort of patients undergoing genetic testing for cardiac arrhythmias and cardiomyopathy including TNNI3K. We further performed burden testing of TNNI3K in the UK Biobank. For 2 novel TNNI3K variants, we tested cosegregation. TNNI3K kinase function was estimated by TNNI3K autophosphorylation assays. RESULTS:We demonstrate enrichment of rare coding TNNI3K variants in DCM patients in the Amsterdam cohort. In the UK Biobank, we observed an association between TNNI3K missense (but not loss-of-function) variants and DCM and atrial fibrillation. Furthermore, we demonstrate genetic segregation for 2 rare variants, TNNI3K-p.Ile512Thr and TNNI3K-p.His592Tyr, with phenotypes consisting of DCM, cardiac conduction disease, and supraventricular tachycardia, together with increased autophosphorylation. In contrast, TNNI3K-p.Arg556_Asn590del, a likely benign variant, demonstrated depleted autophosphorylation. CONCLUSIONS:Our findings demonstrate an increased burden of rare coding TNNI3K variants in cardiac patients with DCM. Furthermore, we present 2 novel likely pathogenic TNNI3K variants with increased autophosphorylation, suggesting that enhanced autophosphorylation is likely to drive pathogenicity.Genetics of disease, diagnosis and treatmen
Gene-gene Interaction Analyses for Atrial Fibrillation
Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in a
Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium
It is unclear whether genetic markers interact with risk factors to influence atrial fibrillation (AF) risk. We performed genome-wide interaction analyses between genetic variants and age, sex, hypertension, and body mass index in the AFGen Consortium. Study-specific results were combined using meta-analysis (88,383 individuals of European descent, including 7,292 with AF). Variants with nominal interaction associations in the discovery analysis were tested for association in four independent studies (131,441 individuals, including 5,722 with AF). In the discovery analysis, the AF risk associated with the minor rs6817105 allele (at the PITX2 locus) was greater among subjects ≤ 65 years of age than among those > 65 years (interaction p-value = 4.0 × 10-5). The interaction p-value exceeded genome-wide significance in combined discovery and replication analyses (interaction p-value = 1.7 × 10-8). We observed one genome-wide significant interaction with body mass index and several suggestive interactions with age, sex, and body mass index in the discovery analysis. However, none was replicated in the independent sample. Our findings suggest that the pathogenesis of AF may differ according to age in individuals of European descent, but we did not observe evidence of statistically significant genetic interactions with sex, body mass index, or hypertension on AF risk
Overlap of genetic loci for central serous chorioretinopathy with age-related macular degeneration
IMPORTANCE Central serous chorioretinopathy (CSC) is a serous maculopathy of unknown etiology. Two of 3 previously reported CSC genetic risk loci are also associated with AMD. Improved understanding of CSC genetics may broaden our understanding of this genetic overlap and unveil mechanisms in both diseases.OBJECTIVE To identify novel genetic risk factors for CSC and compare genetic risk factors for CSC and AMD.DESIGN, SETTING, AND PARTICIPANTS Using International Classification of Diseases, Ninth (ICD-9) and Tenth (ICD-10) Revision code-based inclusion and exclusion criteria, patients with CSC and controls were identified in both the FinnGen study and the Estonian Biobank (EstBB). Also included in ameta-analysis were previously reported patients with chronic CSC and controls. Data were analyzed from March 1 to September 31, 2022.MAIN OUTCOMES AND MEASURES Genome-wide association studies (GWASs) were performed in the biobank-based cohorts followed by ameta-analysis of all cohorts. The expression of genes prioritized by the polygenic priority score and nearest-gene methods were assessed in cultured choroidal endothelial cells and public ocular single-cell RNA sequencing data sets. The predictive utility of polygenic scores (PGSs) for CSC and AMD were evaluated in the FinnGen study.RESULTS A total of 1176 patients with CSC and 526 787 controls (312 162 female [59.3%]) were included in this analysis: 552 patients with CSC and 343 461 controls were identified in the FinnGen study, 103 patients with CSC and 178 573 controls were identified in the EstBB, and 521 patients with chronic CSC and 3577 controls were included in ameta-analysis. Two previously reported CSC risk loci were replicated (near CFH and GATA5) and 3 novel loci were identified (near CD34/46, NOTCH4, and PREX1). The CFH and NOTCH4 loci were associated with AMD but in the opposite direction. Prioritized genes showed increased expression in cultured choroidal endothelial cells compared with other genes in the loci (median [IQR] of log 2 [counts per million], 7.3 [0.6] vs 4.7 [3.7]; P =.004) and were differentially expressed in choroidal vascular endothelial cells in single-cell RNA sequencing data (mean [SD] fold change, 2.05 [0.38] compared with other cell types; P < 7.1 x 10(-20)). A PGS for AMD was predictive of reduced CSC risk (odds ratio, 0.76; 95% CI, 0.70-0.83 per +1 SD in AMD-PGS; P = 7.4 x 10(-10)). This association may have been mediated by loci containing complement genes.CONCLUSIONS AND RELEVANCE In this 3-cohort genetic association study, 5 genetic risk loci for CSC were identified, highlighting a likely role for genes involved in choroidal vascular function and complement regulation. Results suggest that polygenic AMD risk was associated with reduced risk of CSC and that this genetic overlap was largely due to loci containing complement genes.Ophthalmic researc
Common genetic variation near the connexin-43 gene is associated with resting heart rate in African Americans: A genome-wide association study of 13,372 participants
Genome-wide association studies have identified several genetic loci associated with variation in resting heart rate in European and Asian populations. No study has evaluated genetic variants associated with heart rate in African Americans
The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations
Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations
Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure
Heart 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
Rare Coding Variants Associated With Electrocardiographic Intervals Identify Monogenic Arrhythmia Susceptibility Genes: A Multi-Ancestry Analysis
Background: Alterations in electrocardiographic (ECG) intervals are well-known markers for arrhythmia and sudden cardiac death (SCD) risk. While the genetics of arrhythmia syndromes have been studied, relations between electrocardiographic intervals and rare genetic variation at a population level are poorly understood. Methods: Using a discovery sample of 29 000 individuals with whole-genome sequencing from Trans-Omics in Precision Medicine and replication in nearly 100 000 with whole-exome sequencing from the UK Biobank and MyCode, we examined associations between low-frequency and rare coding variants with 5 routinely measured electrocardiographic traits (RR, P-wave, PR, and QRS intervals and corrected QT interval). Results: We found that rare variants associated with population-based electrocardiographic intervals identify established monogenic SCD genes (KCNQ1, KCNH2, and SCN5A), a controversial monogenic SCD gene (KCNE1), and novel genes (PAM and MFGE8) involved in cardiac conduction. Loss-of-function and pathogenic SCN5A variants, carried by 0.1% of individuals, were associated with a nearly 6-fold increased odds of the first-degree atrioventricular block (P=8.4×10-5). Similar variants in KCNQ1 and KCNH2 (0.2% of individuals) were associated with a 23-fold increased odds of marked corrected QT interval prolongation (P=4×10-25), a marker of SCD risk. Incomplete penetrance of such deleterious variation was common as over 70% of carriers had normal electrocardiographic intervals. Conclusions: Our findings indicate that large-scale high-depth sequence data and electrocardiographic analysis identifies monogenic arrhythmia susceptibility genes and rare variants with large effects. Known pathogenic variation in conventional arrhythmia and SCD genes exhibited incomplete penetrance and accounted for only a small fraction of marked electrocardiographic interval prolongation
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