Background: Clinical trials testing pharmacogenomic-guided warfarin dosing for patients with atrial fibrillation have demonstrated conflicting results. Non-vitamin K antagonist oral anticoagulants are expensive and contraindicated for several conditions. A strategy optimizing anticoagulant selection remains an unmet clinical need.
Methods and results: Characteristics from 14 206 patients with atrial fibrillation were integrated into a validated warfarin clinical trial simulation framework using iterative Bayesian network modeling and a pharmacokinetic-pharmacodynamic model. Individual dose-response for patients was simulated for 5 warfarin protocols-a fixed-dose protocol, a clinically guided protocol, and 3 increasingly complex pharmacogenomic-guided protocols. For each protocol, a complexity score was calculated using the variables predicting warfarin dose and the number of predefined international normalized ratio (INR) thresholds for each adjusted dose. Study outcomes included optimal time in therapeutic range ≥65% and clinical events. A combination of age and genotype identified different optimal protocols for various subpopulations. A fixed-dose protocol provided well-controlled INR only in normal responders ≥65, whereas for normal responders <65 years old, a clinically guided protocol was necessary to achieve well-controlled INR. Sensitive responders ≥65 and <65 and highly sensitive responders ≥65 years old required pharmacogenomic-guided protocols to achieve well-controlled INR. However, highly sensitive responders <65 years old did not achieve well-controlled INR and had higher associated clinical events rates than other subpopulations.
Conclusions: Under the assumptions of this simulation, patients with atrial fibrillation can be triaged to an optimal warfarin therapy protocol by age and genotype. Clinicians should consider alternative anticoagulation therapy for patients with suboptimal outcomes under any warfarin protocol.
Background: Aortic valvular stenosis (AS) is the most common cause of cardiac valvular replacement surgery. During the last century, the pathogenesis of AS has undergone transitions in developed countries, from rheumatic heart disease to a degenerative calcific pathogenesis. Although a familial component has been described for a subset of cases with a bicuspid valve, data are limited on the overall familial aggregation of this disease.
Methods and results: Contemporary information on 6 117 263 Swedish siblings, of which 13 442 had a clinical diagnosis of AS, was collected from the nationwide Swedish Multi-Generation Register and the National Patient Register. A total of 4.8% of AS cases had a sibling history of AS. Having at least 1 sibling with AS was associated with a hazard ratio of 3.41 (95% confidence interval, 2.23-5.21) to be diagnosed with AS in an adjusted model. Individuals with >1 sibling with AS had an exceptionally high risk (hazard ratio, 32.84) but were uncommon (34 siblings from 11 sibships). In contrast, spouses of subjects with AS were only slightly more likely to be diagnosed with AS compared with subjects without spousal AS (hazard ratio 1.16 for husbands and 1.18 for wives).
Conclusions: A sibling history of clinically diagnosed AS was associated with increased risk of AS. Spouses of patients with AS only had a modest risk increase, suggesting that shared adult environmental factors contribute less to the development of AS than genetic factors.
Background: Genetic variant interpretation contributes to testing yield differences reported for sudden unexplained death. Adapting a high-resolution variant interpretation framework, which considers disease prevalence, reduced penetrance, genetic heterogeneity, and allelic contribution to determine the maximum tolerated allele count in gnomAD, we report an evaluation of cardiac channelopathy and cardiomyopathy genes in a large, demographically diverse sudden unexplained death cohort that underwent thorough investigation in the United States' largest medical examiner's office.
Methods and results: The cohort has 296 decedents: 147 Blacks, 64 Hispanics, 49 Whites, 22 Asians, and 14 mixed ethnicities; 142 infants (1 to 11 months), 39 children (1 to 17 years), 74 young adults (18 to 34 years), and 41 adults (35 to 55 years). Eighty-nine cardiac disease genes were evaluated. Using a high-resolution variant interpretation workflow, we classified 17 variants as pathogenic or likely pathogenic (2 of which were incidental findings and excluded in testing yield analysis), 46 novel variants of uncertain significance, and 130 variants of uncertain significance. Nine pathogenic or likely pathogenic variants in ClinVar were reclassified to likely benign and excluded in testing yield analysis. The yields of positive cases by ethnicity and age were 21.4% in mixed ethnicities, 10.2% Whites, 4.5% Asians, 3.1% Hispanics, and 2% Blacks; 7.7% children, 7.3% in adults, 5.4% young adults, and 2.8% infants. The percentages of uncertain cases with variants of uncertain significance by ethnicity were 45.5% in Asians, 45.3% Hispanics, 44.20% Blacks, 36.7% Whites, and 14.3% in mixed ethnicities.
Conclusions: High-resolution variant interpretation provides diagnostic accuracy and healthcare efficiency. Under-represented populations warrant greater inclusion in future studies.
Background: Left ventricular noncompaction (LVNC) can occur in isolation or can co-occur with a cardiomyopathy phenotype or cardiovascular malformation. The yield of cardiomyopathy gene panel testing in infants, children, and adolescents with a diagnosis of LVNC is unknown. By characterizing a pediatric population with LVNC, we sought to determine the yield of cardiomyopathy gene panel testing, distinguish the yield of testing for LVNC with or without co-occurring cardiac findings, and define additional factors influencing genetic testing yield.
Methods and results: One hundred twenty-eight individuals diagnosed with LVNC at ≤21 years of age were identified, including 59% with idiopathic pathogenesis, 32% with familial disease, and 9% with a syndromic or metabolic diagnosis. Overall, 75 individuals had either cardiomyopathy gene panel (n=65) or known variant testing (n=10). The yield of cardiomyopathy gene panel testing was 9%. The severity of LVNC by imaging criteria was not associated with positive genetic testing, co-occurring cardiac features, pathogenesis, family history, or myocardial dysfunction. Individuals with isolated LVNC were significantly less likely to have a positive genetic testing result compared with those with LVNC and co-occurring cardiomyopathy (0% versus 12%, respectively; P<0.01).
Conclusions: Genetic testing should be considered in individuals with cardiomyopathy co-occurring with LVNC. These data do not suggest an indication for cardiomyopathy gene panel testing in individuals with isolated LVNC in the absence of a family history of cardiomyopathy.
Background: Gene-environmental interaction analysis can identify novel genetic factors for blood pressure (BP). We performed genome-wide analyses to identify genomic loci that interact with potassium to influence BP using single-marker (1 and 2 df joint tests) and gene-based tests among Chinese participants of the GenSalt study (Genetic Epidemiology Network of Salt Sensitivity).
Methods and results: Among 1876 GenSalt participants, the average of 3 urine samples was used to estimate potassium excretion. Nine BP measurements were taken using a random-zero sphygmomanometer. A total of 2.2 million single nucleotide polymorphisms were imputed using Affymetrix 6.0 genotype data and the Chinese Han of Beijing and Japanese of Tokyo HapMap reference panel. Promising findings (P<1.00×10-4) from GenSalt were evaluated for replication among 775 Chinese participants of the MESA (Multi-ethnic Study of Atherosclerosis). Single nucleotide polymorphism and gene-based results were meta-analyzed across the GenSalt and MESA studies to determine genome-wide significance. The 1 df tests identified interactions for ARL15 rs16882447 on systolic BP (P=2.83×10-9) and RANBP3L rs958929 on pulse pressure (P=1.58×10-8). The 2 df tests confirmed the ARL15 rs16882447 signal for systolic BP (P=1.15×10-9). Genome-wide gene-based analysis identified CC2D2A (P=2.59×10-7) at 4p15.32 and BNC2 (P=4.49×10-10) at 9p22.2 for systolic BP, GGNBP1 (P=1.18×10-8), and LINC00336 (P=1.36×10-8) at 6p21 for diastolic BP, DAB1 (P=1.05×10-13) at 1p32.2, and MIR4466 (P=5.34×10-8) at 6q25.3 for pulse pressure. The BNC2 (P=3.57×10-8) gene was also significant for mean arterial pressure.
Conclusions: We identified 2 novel BP loci and 6 genes through the examination of single nucleotide polymorphism- and gene-based interactions with potassium.
Background: Previous reports have implicated multiple genetic loci associated with AF, but the contributions of genome-wide variation to AF susceptibility have not been quantified.
Methods and results: We assessed the contribution of genome-wide single-nucleotide polymorphism variation to AF risk (single-nucleotide polymorphism heritability, h2g ) using data from 120 286 unrelated individuals of European ancestry (2987 with AF) in the population-based UK Biobank. We ascertained AF based on self-report, medical record billing codes, procedure codes, and death records. We estimated h2g using a variance components method with variants having a minor allele frequency ≥1%. We evaluated h2g in age, sex, and genomic strata of interest. The h2g for AF was 22.1% (95% confidence interval, 15.6%-28.5%) and was similar for early- versus older-onset AF (≤65 versus >65 years of age), as well as for men and women. The proportion of AF variance explained by genetic variation was mainly accounted for by common (minor allele frequency, ≥5%) variants (20.4%; 95% confidence interval, 15.1%-25.6%). Only 6.4% (95% confidence interval, 5.1%-7.7%) of AF variance was attributed to variation within known AF susceptibility, cardiac arrhythmia, and cardiomyopathy gene regions.
Conclusions: Genetic variation contributes substantially to AF risk. The risk for AF conferred by genomic variation is similar to that observed for several other cardiovascular diseases. Established AF loci only explain a moderate proportion of disease risk, suggesting that further genetic discovery, with an emphasis on common variation, is warranted to understand the causal genetic basis of AF.
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