Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 new QT interval-associated loci in 298 unrelated probands with LQTS identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies new candidate genes for ventricular arrhythmias, LQTS and SCD

Feasibility and validation of trans-valvular flow derived by four-dimensional flow cardiovascular magnetic resonance imaging in patients with atrial fibrillation

Background: Four-dimensional (4D) flow cardiovascular magnetic resonance imaging (MRI) is an emerging technique used for intra-cardiac blood flow assessment. The role of 4D flow cardiovascular MRI in the assessment of trans-valvular flow in patients with atrial fibrillation (AF) has not previously been assessed. The purpose of this study was to assess the feasibility, image quality, and internal validity of 4D flow cardiovascular MRI in the quantification of trans-valvular flow in patients with AF. Methods: Patients with AF and healthy controls in sinus rhythm underwent cardiovascular MRI, including 4D flow studies. Quality assurance checks were done on the raw data and streamlines. Consistency was investigated by trans-valvular flow assessment between the mitral valve (MV) and the aortic valve (AV). Results: Eight patients with AF (88% male, mean age 62±13 years, mean heart rate (HR) 83±16 beats per minute (bpm)) were included and compared with ten healthy controls (70% male, mean age 41±20 years, mean HR 68.5±9 bpm). All scans were of either good quality with minimal blurring artefacts, or excellent quality with no artefacts. No significant bias was observed between the AV and MV stroke volumes in either healthy controls (–4.8, 95% CI –15.64 to 6.04; P=0.34) or in patients with AF (1.64, 95% CI –4.7 to 7.94; P=0.56). A significant correlation was demonstrated between MV and AV stroke volumes in both healthy controls (r=0.87, 95% CI 0.52 to 0.97; P=0.001) and in AF patients (r=0.82, 95% CI 0.26 to 0.97; P=0.01). Conclusions: In patients with AF, 4D flow cardiovascular MRI is feasible with good image quality, allowing for quantification of trans-valvular flow

The Diagnostic Potential of Fe Lines Applied to Protostellar Jets

We investigate the diagnostic capabilities of iron lines for tracing the physical conditions of shock-excited gas in jets driven by pre-main sequence stars. We have analyzed the 3000-25000 \uc5, X-shooter spectra of two jets driven by the pre-main sequence stars ESO-H\u3b1 574 and Par-Lup 3-4. Both spectra are very rich in [Fe II] lines over the whole spectral range; in addition, lines from [Fe III] are detected in the ESO-H\u3b1 574 spectrum. Non-local thermal equilibrium codes solving the equations of the statistical equilibrium along with codes for the ionization equilibrium are used to derive the gas excitation conditions of electron temperature and density and fractional ionization. An estimate of the iron gas-phase abundance is provided by comparing the iron lines emissivity with that of neutral oxygen at 6300 \uc5. The [Fe II] line analysis indicates that the jet driven by ESO-H\u3b1 574 is, on average, colder (T e 3c 9000 K), less dense (n e 3c 2 7 104 cm-3), and more ionized (x e 3c 0.7) than the Par-Lup 3-4 jet (T e 3c 13,000 K, n e 3c 6 7 104 cm-3, x e < 0.4), even if the existence of a higher density component (n e 3c 2 7 105 cm-3) is probed by the [Fe III] and [Fe II] ultra-violet lines. The physical conditions derived from the iron lines are compared with shock models suggesting that the shock at work in ESO-H\u3b1 574 is faster and likely more energetic than the Par-Lup 3-4 shock. This latter feature is confirmed by the high percentage of gas-phase iron measured in ESO-H\u3b1 574 (50%-60% of its solar abundance in comparison with less than 30% in Par-Lup 3-4), which testifies that the ESO-H\u3b1 574 shock is powerful enough to partially destroy the dust present inside the jet. This work demonstrates that a multiline Fe analysis can be effectively used to probe the excitation and ionization conditions of the gas in a jet without any assumption on ionic abundances. The main limitation on the diagnostics resides in the large uncertainties of the atomic data, which, however, can be overcome through a statistical approach involving many line

Drug–gene interactions and the search for missing heritability: a cross-sectional pharmacogenomics study of the QT interval

Variability in response to drug use is common and heritable, suggesting that genome-wide pharmacogenomics studies may help explain the “missing heritability” of complex traits. Here, we describe four independent analyses in 33,781 participants of European ancestry from ten cohorts that were designed to identify genetic variants modifying the effects of drugs on QT interval duration (QT). Each analysis cross-sectionally examined four therapeutic classes: thiazide diuretics (prevalence of use=13.0%), tri/tetracyclic antidepressants (2.6%), sulfonylurea hypoglycemic agents (2.9%), and QT prolonging drugs as classified by the University of Arizona Center for Education and Research on Therapeutics (4.4%). Drug-gene interactions were estimated using covariable adjusted linear regression and results were combined with fixed-effects meta-analysis. Although drug-SNP interactions were biologically plausible and variables were well-measured, findings from the four cross-sectional meta-analyses were null (Pinteraction>5.0×10−8). Simulations suggested that additional efforts, including longitudinal modeling to increase statistical power, are likely needed to identify potentially important pharmacogenomic effects

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

Оценка качества образования на основе компетентностного подхода

В работе представлен практический опыт оценки качества образования в новом формате компетентностного подход

Drug-Gene Interactions of Antihypertensive Medications and Risk of Incident Cardiovascular Disease: A Pharmacogenomics Study from the CHARGE Consortium

BackgroundHypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals.MethodsUsing a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases).ResultsAlthough drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

B-type natriuretic peptide and C-reactive protein in the prediction of atrial fibrillation risk: the CHARGE-AF Consortium of community-based cohort studies

B-type natriuretic peptide (BNP) and C-reactive protein (CRP) predict atrial fibrillation (AF) risk. However, their risk stratification abilities in the broad community remain uncertain. We sought to improve risk stratification for AF using biomarker information