Variants in SCN10A, which encodes a voltage-gated sodium channel, are associated with alterations of cardiac conduction parameters and the cardiac rhythm disorder Brugada syndrome; however, it is unclear how SCN10A variants promote dysfunctional cardiac conduction. Here we showed by high-resolution 4C-seq analysis of the Scn10a-Scn5a locus in murine heart tissue that a cardiac enhancer located in Scn10a, encompassing SCN10A functional variant rs6801957, interacts with the promoter of Scn5a, a sodium channel–encoding gene that is critical for cardiac conduction. We observed that SCN5A transcript levels were several orders of magnitude higher than SCN10A transcript levels in both adult human and mouse heart tissue. Analysis of BAC transgenic mouse strains harboring an engineered deletion of the enhancer within Scn10a revealed that the enhancer was essential for Scn5a expression in cardiac tissue. Furthermore, the common SCN10A variant rs6801957 modulated Scn5a expression in the heart. In humans, the SCN10A variant rs6801957, which correlated with slowed conduction, was associated with reduced SCN5A expression. These observations establish a genomic mechanism for how a common genetic variation at SCN10A influences cardiac physiology and predisposes to arrhythmia.

Diabetes is associated with an elevated risk of coronary heart disease (CHD). Previous studies have suggested that the genetic factors predisposing to excess cardiovascular risk may be different in diabetic and nondiabetic individuals. To identify genetic determinants of CHD that are specific to patients with diabetes. We studied 5 independent sets of CHD cases and CHD-negative controls from the Nurses' Health Study (enrolled in 1976 and followed up through 2008), Health Professionals Follow-up Study (enrolled in 1986 and followed up through 2008), Joslin Heart Study (enrolled in 2001-2008), Gargano Heart Study (enrolled in 2001-2008), and Catanzaro Study (enrolled in 2004-2010). Included were a total of 1517 CHD cases and 2671 CHD-negative controls, all with type 2 diabetes. Results in diabetic patients were compared with those in 737 nondiabetic CHD cases and 1637 nondiabetic CHD-negative controls from the Nurses' Health Study and Health Professionals Follow-up Study cohorts. Exposures included 2,543,016 common genetic variants occurring throughout the genome. Coronary heart disease--defined as fatal or nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous transluminal coronary angioplasty, or angiographic evidence of significant stenosis of the coronary arteries. A variant on chromosome 1q25 (rs10911021) was consistently associated with CHD risk among diabetic participants, with risk allele frequencies of 0.733 in cases vs 0.679 in controls (odds ratio, 1.36 [95% CI, 1.22-1.51]; P = 2 × 10(-8)). No association between this variant and CHD was detected among nondiabetic participants, with risk allele frequencies of 0.697 in cases vs 0.696 in controls (odds ratio, 0.99 [95% CI, 0.87-1.13]; P = .89), consistent with a significant gene × diabetes interaction on CHD risk (P = 2 × 10(-4)). Compared with protective allele homozygotes, rs10911021 risk allele homozygotes were characterized by a 32% decrease in the expression of the neighboring glutamate-ammonia ligase (GLUL) gene in human endothelial cells (P = .0048). A decreased ratio between plasma levels of γ-glutamyl cycle intermediates pyroglutamic and glutamic acid was also shown in risk allele homozygotes (P = .029). A single-nucleotide polymorphism (rs10911021) was identified that was significantly associated with CHD among persons with diabetes but not in those without diabetes and was functionally related to glutamic acid metabolism, suggesting a mechanistic link.

Background— Atrial fibrillation (AF) is the most common adverse event following coronary artery bypass graft surgery. A recent study identified chromosome 4q25 variants associated with AF in ambulatory populations. However, their role in postoperative AF is unknown. We hypothesized that genetic variants in the 4q25 chromosomal region are independently associated with postoperative AF after coronary artery bypass graft surgery. Methods and Results— Two prospectively collected cohorts of patients undergoing coronary artery bypass graft surgery, with or without concurrent valve surgery, at 3 US centers. From a discovery cohort of 959 patients, clinical and genomic multivariate predictors of postoperative AF were identified by genotyping 45 single-nucleotide polymorphisms (SNPs) encompassing the 4q25 locus. Three SNPs were then assessed in a separately collected validation cohort of 494 patients. After adjustment for clinical predictors of postoperative AF and multiple comparisons, rs2200733, rs13143308, and ...

Ulmonary bypass (CPB) would predict AKI after CABG surgery. METHODS: In a retrospective observational study, we examined the value of plasma NGAL measured after CPB for predicting the risk of developing AKI (defined as a ≥50% increase in serum creatinine from preoperative levels) in 879 patients after CABG surgery using multivariable logistic regression. Area under the curve of receiver operating characteristic curves was analyzed to assess sensitivities, specificities, and cutoff points for postoperative plasma NGAL levels to predict AKI. RESULTS: Seventy-five patients (8.6%) developed postoperative AKI. Plasma NGAL levels measured after CPB were higher in patients who subsequently developed AKI than in those who did not (AKI: 268.8 ng/mL [207.5–459.5 ng/mL], median [interquartile range], vs no AKI: 238.4 ng/mL [172.0–319.1 ng/mL]; P < 0.001) and remained higher through postoperative day 4. An optimal serum plasma NGAL cutoff of 353.5 ng/mL at the post-CPB time point had a sensitivity of 38.7%, specificity of 81.5%, and a positive predictive value of 16.3% for predicting AKI. In our multivariate regression model, post-CPB plasma NGAL levels >353.5 ng/mL were independently associated with postoperative AKI (odds ratio, 2.3; 95% confidence interval, 1.5–6.5; P = 0.002). CONCLUSION: An early increase of post-CPB plasma NGAL is associated with AKI in adult patients undergoing CABG surgery, although the sensitivity is low. Therefore, assessing early plasma NGAL alone has limited utility for predicting AKI in this patient population....

Mitral valve prolapse (MVP) is a common valvular heart disease with a prevalence of >2% in the general adult population. Despite this high incidence, there is a limited understanding of the molecular mechanism of this disease, and no medical therapy is available for this disease. We aimed to elucidate the genetic basis of MVP in order to better understand this complex disorder. We performed a meta-analysis of six genome-wide association studies that included 4884 cases and 434 649 controls. We identified 14 loci associated with MVP in our primary analysis and 2 additional loci associated with a subset of the samples that additionally underwent mitral valve surgery. Integration of epigenetic, transcriptional, and proteomic data identified candidate MVP genes including LMCD1, SPTBN1, LTBP2, TGFB2, NMB, and ALPK3. We created a polygenic risk score (PRS) for MVP and showed an improved MVP risk prediction beyond age, sex, and clinical risk factors. We identified 14 genetic loci that are associated with MVP. Multiple analyses identified candidate genes including two transforming growth factor-β signalling molecules and spectrin β. We present the first PRS for MVP that could eventually aid risk stratification of patients for MVP screening in a clinical setting. These findings advance our understanding of this common valvular heart disease and may reveal novel therapeutic targets for intervention. This study meta-analysed 4884 mitral valve prolapse (MVP) cases versus 434 649 controls, and discovered 16 genetic loci associated to MVP. Downstream analyses implicated candidate genes involved in TGF-beta signalling, cardiomyopathy and the cytoskeleton. The results from the meta-analysis were used to calculate a polygenic risk score (PRS) to aid prediction of MVP. Adding the PRS to a model with age, sex and clinical risk factors improved MVP risk prediction. Abbreviations, MVP, mitral valve prolapse, p, p-value, PRS, polygenic risk score, RF, risk factors.