Discovery of novel heart rate-associated loci using the Exome Chip.

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses.Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods.We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies.

Genetic insights into resting heart rate and its role in cardiovascular disease.

Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.

Variant Location Is a Novel Risk Factor for Individuals With Arrhythmogenic Cardiomyopathy Due to a Desmoplakin (DSP) Truncating Variant.

BACKGROUND: Truncating variants in desmoplakin (DSPtv) are an important cause of arrhythmogenic cardiomyopathy; however the genetic architecture and genotype-specific risk factors are incompletely understood. We evaluated phenotype, risk factors for ventricular arrhythmias, and underlying genetics of DSPtv cardiomyopathy. METHODS: Individuals with DSPtv and any cardiac phenotype, and their gene-positive family members were included from multiple international centers. Clinical data and family history information were collected. Event-free survival from ventricular arrhythmia was assessed. Variant location was compared between cases and controls, and literature review of reported DSPtv performed. RESULTS: There were 98 probands and 72 family members (mean age at diagnosis 43±8 years, 59% women) with a DSPtv, of which 146 were considered clinically affected. Ventricular arrhythmia (sudden cardiac arrest, sustained ventricular tachycardia, appropriate implantable cardioverter defibrillator therapy) occurred in 56 (33%) individuals. DSPtv location and proband status were independent risk factors for ventricular arrhythmia. Further, gene region was important with variants in cases (cohort n=98; Clinvar n=167) more likely to occur in the regions resulting in nonsense mediated decay of both major DSP isoforms, compared with n=124 genome aggregation database control variants (148 [83.6%] versus 29 [16.4%]; P<0.0001). CONCLUSIONS: In the largest series of individuals with DSPtv, we demonstrate that variant location is a novel risk factor for ventricular arrhythmia, can inform variant interpretation, and provide critical insights to allow for precision-based clinical management.

Relationship of Arterial Stiffness Index and Pulse Pressure With Cardiovascular Disease and Mortality.

BACKGROUND: Vascular aging results in stiffer arteries and may have a role in the development of cardiovascular disease (CVD). Arterial stiffness index (ASI), measured by finger photoplethysmography, and pulse pressure (PP) are 2 independent vascular aging indices. We investigated whether ASI or PP predict new-onset CVD and mortality in a large community-based population. METHODS AND RESULTS: We studied 169 613 UK Biobank participants (mean age 56.8 years; 45.8% males) who underwent ASI measurement and blood pressure measurement for PP calculation. Mean±SD ASI was 9.30±3.1 m/s and mean±SD PP was 50.98±13.2 mm Hg. During a median disease follow-up of 2.8 years (interquartile range 1.4-4.0), 18 190 participants developed CVD, of which 1587 myocardial infarction (MI), 4326 coronary heart disease, 1192 heart failure, and 1319 stroke. During a median mortality follow-up of 6.1 years (interquartile range 5.8-6.3), 3678 participants died, of which 1180 of CVD. Higher ASI was associated with increased risk of overall CVD (unadjusted hazard ratio 1.27; 95% confidence interval [CI], 1.25-1.28), myocardial infarction (1.38; 95% CI, 1.32-1.44), coronary heart disease (1.31; 95% CI, 1.27-1.34), and heart failure (1.31; 95% CI 1.24-1.37). ASI also predicted mortality (all-cause, CVD, other). Higher PP was associated with overall CVD (1.57; 95% CI, 1.55-1.59), myocardial infarction (1.48; 95% CI, 1.42-1.54), coronary heart disease (1.47; 95% CI, 1.43-1.50), heart failure (1.47; 95% CI, 1.40-1.55), and CVD mortality (1.47; 95% CI, 1.40-1.55). PP improved risk reclassification of CVD in a non-laboratory-based Framingham Risk Score by 5.4%, ASI by 2.3%. CONCLUSIONS: ASI and PP are independent predictors of CVD and mortality outcomes. Although both improved risk prediction for new-onset disease, PP appears to have a larger clinical value than ASI.

Identification of 15 novel risk loci for coronary artery disease and genetic risk of recurrent events, atrial fibrillation and heart failure.

Coronary artery disease (CAD) is the major cause of morbidity and mortality in the world. Identification of novel genetic determinants may provide new opportunities for developing innovative strategies to predict, prevent and treat CAD. Therefore, we meta-analyzed independent genetic variants passing P <× 10-5 in CARDIoGRAMplusC4D with novel data made available by UK Biobank. Of the 161 genetic variants studied, 71 reached genome wide significance (p < 5 × 10-8) including 15 novel loci. These novel loci include multiple genes that are involved in angiogenesis (TGFB1, ITGB5, CDH13 and RHOA) and 2 independent variants in the TGFB1 locus. We also identified SGEF as a candidate gene in one of the novel CAD loci. SGEF was previously suggested as a therapeutic target based on mouse studies. The genetic risk score of CAD predicted recurrent CAD events and cardiovascular mortality. We also identified significant genetic correlations between CAD and other cardiovascular conditions, including heart failure and atrial fibrillation. In conclusion, we substantially increased the number of loci convincingly associated with CAD and provide additional biological and clinical insights.

Statin Effects on Metabolic Profiles: Data From the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial).

BACKGROUND: Statins lower cholesterol by inhibiting HMG-CoA reductase, the rate-limiting enzyme of the metabolic pathway that produces cholesterol and other isoprenoids. Little is known about their effects on metabolite and lipoprotein subclass profiles. We, therefore, investigated the molecular changes associated with pravastatin treatment compared with placebo administration using a nuclear magnetic resonance-based metabolomics platform. METHODS AND RESULTS: We performed metabolic profiling of 231 lipoprotein and metabolite measures in the PREVEND IT (Prevention of Renal and Vascular End-stage Disease Intervention Trial) study, a placebo-controlled randomized clinical trial designed to test the effects of pravastatin (40 mg once daily) on cardiovascular risk. Metabolic profiles were assessed at baseline and after 3 months of treatment. Pravastatin lowered low-density lipoprotein cholesterol (change in SD units [95% confidence interval]: -1.01 [-1.14, -0.88]), remnant cholesterol (change in SD units [95% confidence interval]: -1.03 [-1.17, -0.89]), and apolipoprotein B (change in SD units [95% confidence interval]: -0.98 [-1.11, -0.86]) with similar effect magnitudes. In addition, pravastatin globally lowered levels of lipoprotein subclasses, with the exception of high-density lipoprotein subclasses, which displayed a more heterogeneous response pattern. The lipid-lowering effect of pravastatin was accompanied by selective changes in lipid composition, particularly in the cholesterol content of very-low-density lipoproteinparticles. In addition, pravastatin reduced levels of several fatty acids but had limited effects on fatty acid ratios. CONCLUSIONS: These randomized clinical trial data demonstrate the widespread effects of pravastatin treatment on lipoprotein subclass profiles and fatty acids. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT03073018.

Effect of Metformin on Metabolites and Relation With Myocardial Infarct Size and Left Ventricular Ejection Fraction After Myocardial Infarction.

BACKGROUND: Left ventricular ejection fraction (LVEF) and infarct size (ISZ) are key predictors of long-term survival after myocardial infarction (MI). However, little is known about the biochemical pathways driving LV dysfunction after MI. To identify novel biomarkers predicting post-MI LVEF and ISZ, we performed metabolic profiling in the GIPS-III randomized clinical trial (Glycometabolic Intervention as Adjunct to Primary Percutaneous Intervention in ST Elevation Myocardial Infarction). We also investigated the metabolic footprint of metformin, a drug associated with improved post-MI LV function in experimental studies. METHODS AND RESULTS: Participants were patients with ST-segment-elevated MI who were randomly assigned to receive metformin or placebo for 4 months. Blood samples were obtained on admission, 24 hours post-MI, and 4 months post-MI. A total of 233 metabolite measures were quantified using nuclear magnetic resonance spectrometry. LVEF and ISZ were assessed 4 months post-MI. Twenty-four hours post-MI measurements of high-density lipoprotein (HDL) triglycerides (HDL-TG) predicted LVEF (ß=1.90 [95% confidence interval (CI), 0.82 to 2.98]; P=6.4×10-4) and ISZ (ß=-0.41 [95% CI, -0.60 to -0.21]; P=3.2×10-5). In addition, 24 hours post-MI measurements of medium HDL-TG (ß=-0.40 [95% CI, -0.60 to -0.20]; P=6.4×2×10-5), small HDL-TG (ß=-0.34 [95% CI, -0.53 to -0.14]; P=7.3×10-4), and the triglyceride content of very large HDL (ß=-0.38 [95% CI, -0.58 to -0.18]; P=2.7×10-4) were associated with ISZ. After the 4-month treatment, the phospholipid content of very large HDL was lower in metformin than in placebo-treated patients (28.89% versus 38.79%; P=7.5×10-5); alanine levels were higher in the metformin group (0.46 versus 0.44 mmol/L; P=2.4×10-4). CONCLUSIONS: HDL triglyceride concentrations predict post-MI LVEF and ISZ. Metformin increases alanine levels and reduces the phospholipid content in very large HDL particles. CLINICAL TRIAL REGISTRATION: URL: https://clinicaltrials.gov/ct2/show/NCT01217307. Unique Identifier: NCT01217307.

The contemporary value of peak creatine kinase-MB after ST-segment elevation myocardial infarction above other clinical and angiographic characteristics in predicting infarct size, left ventricular ejection fraction, and mortality.

BACKGROUND: Complex multimarker approaches to predict outcome after ST-elevation myocardial infarction (STEMI) have only considered a single baseline sample, while neglecting easily obtainable peak creatine kinase and creatine kinase-MB (CK-MB) values during hospitalization. METHODS: We studied 476 patients undergoing primary percutaneous coronary intervention for STEMI and cardiac magnetic resonance imaging (CMRI) at 4-6 months after STEMI. We determined the association with cardiac biomarkers (peak CK-MB, peak troponin T, N-terminal pro-brain natriuretic peptide), clinical and angiographic characteristics with infarct size, and LVEF, followed by association with mortality in 1120 STEMI patients. RESULTS: Peak CK-MB was the strongest predictor for infarct size (P<0.001, R 2 =0.60) and LVEF (P<0.001, R 2 =0.40). The additional value of clinical and angiographic characteristics was limited. The optimal peak CK-MB cutpoints, for differentiation among small (<10% of the left ventricle), moderate (≥10%-<30%), and large infarct size (≥30%), were 210 U/L and 380 U/L, respectively. These cutpoints were associated with 90-day mortality; the hazard ratio for moderate infarct was 2.99 (95% confidence interval [CI]: 1.51-5.93, P=0.002) and for large infarct 6.53 (95% CI: 3.63-11.76, P<0.001). CONCLUSIONS: Classical peak CK-MB measured during hospitalization for STEMI was superior to other clinical and angiographic characteristics in predicting CMRI-defined infarct size and LVEF, and should be included and validated in future multimarker studies. Peak CK-MB cutpoints differentiated among infarct size categories and were associated with increased 90-day mortality risk.

Identification of genomic loci associated with resting heart rate and shared genetic predictors with all-cause mortality.

Resting heart rate is a heritable trait correlated with life span. Little is known about the genetic contribution to resting heart rate and its relationship with mortality. We performed a genome-wide association discovery and replication analysis starting with 19.9 million genetic variants and studying up to 265,046 individuals to identify 64 loci associated with resting heart rate (P < 5 × 10-8); 46 of these were novel. We then used the genetic variants identified to study the association between resting heart rate and all-cause mortality. We observed that a genetically predicted resting heart rate increase of 5 beats per minute was associated with a 20% increase in mortality risk (hazard ratio 1.20, 95% confidence interval 1.11-1.28, P = 8.20 × 10-7) translating to a reduction in life expectancy of 2.9 years for males and 2.6 years for females. Our findings provide evidence for shared genetic predictors of resting heart rate and all-cause mortality.

Effect of Metformin Treatment on Lipoprotein Subfractions in Non-Diabetic Patients with Acute Myocardial Infarction: A Glycometabolic Intervention as Adjunct to Primary Coronary Intervention in ST Elevation Myocardial Infarction (GIPS-III) Trial.

OBJECTIVE: Metformin affects low density lipoprotein (LDL) and high density (HDL) subfractions in the context of impaired glucose tolerance, but its effects in the setting of acute myocardial infarction (MI) are unknown. We determined whether metformin administration affects lipoprotein subfractions 4 months after ST-segment elevation MI (STEMI). Second, we assessed associations of lipoprotein subfractions with left ventricular ejection fraction (LVEF) and infarct size 4 months after STEMI. METHODS: 371 participants without known diabetes participating in the GIPS-III trial, a placebo controlled, double-blind randomized trial studying the effect of metformin (500 mg bid) during 4 months after primary percutaneous coronary intervention for STEMI were included of whom 317 completed follow-up (clinicaltrial.gov Identifier: NCT01217307). Lipoprotein subfractions were measured using nuclear magnetic resonance spectroscopy at presentation, 24 hours and 4 months after STEMI. (Apo)lipoprotein measures were obtained during acute STEMI and 4 months post-STEMI. LVEF and infarct size were measured by cardiac magnetic resonance imaging. RESULTS: Metformin treatment slightly decreased LDL cholesterol levels (adjusted P = 0.01), whereas apoB remained unchanged. Large LDL particles and LDL size were also decreased after metformin treatment (adjusted P<0.001). After adjustment for covariates, increased small HDL particles at 24 hours after STEMI predicted higher LVEF (P = 0.005). In addition, increased medium-sized VLDL particles at the same time point predicted a smaller infarct size (P<0.001). CONCLUSION: LDL cholesterol and large LDL particles were decreased during 4 months treatment with metformin started early after MI. Higher small HDL and medium VLDL particle concentrations are associated with favorable LVEF and infarct size.

Genome-wide association reveals that common genetic variation in the kallikrein-kinin system is associated with serum L-arginine levels.

L-arginine is the essential precursor of nitric oxide, and is involved in multiple key physiological processes, including vascular and immune function. The genetic regulation of blood L-arginine levels is largely unknown. We performed a genome-wide association study (GWAS) to identify genetic factors determining serum L-arginine levels, amongst 901 Europeans and 1,394 Indian Asians. We show that common genetic variations at the KLKB1 and F12 loci are strongly associated with serum L-arginine levels. The G allele of single nucleotide polymorphism (SNP) rs71640036 (T/G) in KLKB1 is associated with lower serum L-arginine concentrations (10 µmol/l per allele copy, p=1×10-24), while allele T of rs2545801 (T/C) near the F12 gene is associated with lower serum L-arginine levels (7 µmol/l per allele copy, p=7×10-12). Together these two loci explain 7 % of the total variance in serum L-arginine concentrations. The associations at both loci were replicated in independent cohorts with plasma L-arginine measurements (p<0.004). The two sentinel SNPs are in nearly complete LD with the nonsynonymous SNP rs3733402 at KLKB1 and the 5'-UTR SNP rs1801020 at F12, respectively. SNPs at both loci are associated with blood pressure. Our findings provide new insight into the genetic regulation of L-arginine and its potential relationship with cardiovascular risk.