Heterogeneous myocyte enhancer factor-2 (Mef2) activation in myocytes predicts focal scarring in hypertrophic cardiomyopathy

Unknown molecular responses to sarcomere protein gene mutations account for pathologic remodeling in hypertrophic cardiomyopathy (HCM), producing myocyte growth and increased cardiac fibrosis. To determine if hypertrophic signals activated myocyte enhancer factor-2 (Mef2), we studied mice carrying the HCM mutation, myosin heavy-chain Arg403Gln, (MHC403/+) and an Mef2-dependent β-galactosidase reporter transgene. In young, prehypertrophic MHC403/+ mice the reporter was not activated. In hypertrophic hearts, activation of the Mef2-dependent reporter was remarkably heterogeneous and was observed consistently in myocytes that bordered fibrotic foci with necrotic cells, MHC403/+ myocytes with Mef2-dependent reporter activation reexpressed the fetal myosin isoform (βMHC), a molecular marker of hypertrophy, although MHC403/+ myocytes with or without βMHC expression were comparably enlarged over WT myocytes. To consider Mef2 roles in severe HCM, we studied homozygous MHC403/403 mice, which have accelerated remodeling, widespread myocyte necrosis, and neonatal lethality. Levels of phosphorylated class II histone deacetylases that activate Mef2 were substantially increased in MHC403/403 hearts, but Mef2-dependent reporter activation was patchy. Sequential analyses showed myocytes increased Mef2-dependent reporter activity before death. Our data dissociate myocyte hypertrophy, a consistent response in HCM, from heterogeneous Mef2 activation and reexpression of a fetal gene program. The temporal and spatial relationship of Mef2-dependent gene activation with myocyte necrosis and fibrosis in MHC403/+ and MHC403/403 hearts defines Mef2 activation as a molecular signature of stressed HCM myocytes that are poised to die

Association of Exhaled Carbon Monoxide With Stroke Incidence and Subclinical Vascular Brain Injury

Background and purposeExhaled carbon monoxide (CO) is associated with cardiometabolic traits, subclinical atherosclerosis, and cardiovascular disease, but its specific relations with stroke are unexplored. We related exhaled CO to magnetic resonance imaging measures of subclinical cerebrovascular disease cross-sectionally and to incident stroke/transient ischemic attack prospectively in the Framingham Offspring study.MethodsWe measured exhaled CO in 3313 participants (age 59±10 years; 53% women), and brain magnetic resonance imaging was available in 1982 individuals (age 58±10 years; 54% women). Participants were analyzed according to tertiles of exhaled CO concentration.ResultsIn age- and sex-adjusted models, the highest tertile of exhaled CO was associated with lower total cerebral brain volumes, higher white-matter hyperintensity volumes, and greater prevalence of silent cerebral infarcts (P<0.05 for all). The results for total cerebral brain volume and white-matter hyperintensity volume were consistent after removing smokers from the sample, and the association with white-matter hyperintensity volume persisted after multivariable adjustment (P=0.04). In prospective analyses (mean follow-up 12.9 years), higher exhaled CO was associated with 67% (second tertile) and 97% (top tertile) increased incidence of stroke/transient ischemic attack relative to the first tertile that served as referent (P<0.01 for both). These results were consistent in nonsmokers and were partially attenuated upon adjustment for vascular risk factors.ConclusionsIn this large, community-based sample of individuals without clinical stroke/transient ischemic attack at baseline, higher exhaled CO was associated with a greater burden of subclinical cerebrovascular disease cross-sectionally and with increased risk of stroke/transient ischemic attack prospectively. Further investigation is necessary to explore the biological mechanisms linking elevated CO with stroke

Serum apelin and galectin-3 in preeclampsia in Iraq

Objective This study investigates the correlation between serum apelin and galectin-3 levels with insulin resistance (IR) in women with preeclampsia (PE). Methods Serum apelin, galectin-3, and insulin levels were measured in 60 PE women and 30 normotensive pregnant. Results The PE group had significantly lower apelin and higher galectin-3 levels than the control group. PE group exhibited dyslipidemia and had higher β-cell functions than the controls. Galectin-3 level correlates with insulin, glucose, and IR. High galectin-3 also is correlated positively with dyslipidemia. Conclusion In PE, there is a possible contribution of galectin-3 to the harmful effects of IR and dyslipidemia

Associations of a Panel of Adipokines with Fat Deposits and Metabolic Phenotypes in a General Population

Objective This study provides a comprehensive overview of the associations of five adipokines (adiponectin, chemerin, galectin‐3, leptin, and resistin) with fat deposits, behavioral risk factors, and metabolic phenotypes. Methods Using multivariable linear and logistic regression models, cross‐sectional data from 4,116 participants of the population‐based Study of Health in Pomerania were analyzed. Results Participants with obesity showed higher chemerin, galectin‐3, and leptin but showed lower adiponectin concentrations. Independently of other fat compounds, liver fat content, visceral adipose tissue, and subcutaneous adipose tissue (SAT) were inversely associated with adiponectin. Independent positive associations of liver fat content and SAT with chemerin as well as of SAT with galectin‐3 and leptin were observed. Physically inactive participants had higher chemerin and leptin concentrations. Smokers had higher chemerin and galectin‐3 as well as lower leptin. Alcohol consumption was associated with adiponectin (positive) and resistin (inverse). All adipokines were associated with at least one lipid marker. Associations with glucose metabolism were seen for adiponectin, chemerin, galectin‐3, and leptin. Conclusions High adiponectin concentrations were related to favorable metabolic conditions, whereas high chemerin, galectin‐3, and leptin were associated with an unfavorable metabolic profile. High leptin seems to be primarily indicative of obesity, whereas high adiponectin and chemerin are associated with a broader range of metabolic phenotypes

Circulating metabolite profile in young adulthood identifies long-term diabetes susceptibility: the Coronary Artery Risk Development in Young Adults (CARDIA) study

Aims/hypothesis: The aim of this work was to define metabolic correlates and pathways of diabetes pathogenesis in young adults during a subclinical latent phase of diabetes development. Methods: We studied 2083 young adults of Black and White ethnicity in the prospective observational cohort Coronary Artery Risk Development in Young Adults (CARDIA) study (mean ± SD age 32.1 ± 3.6 years; 43.9% women; 42.7% Black; mean ± SD BMI 25.6 ± 4.9 kg/m2) and 1797 Framingham Heart Study (FHS) participants (mean ± SD age 54.7 ± 9.7 years; 52.1% women; mean ± SD BMI 27.4 ± 4.8 kg/m2), examining the association of comprehensive metabolite profiles with endophenotypes of diabetes susceptibility (adipose and muscle tissue phenotypes and systemic inflammation). Statistical learning techniques and Cox regression were used to identify metabolite signatures of incident diabetes over a median of nearly two decades of follow-up across both cohorts. Results: We identified known and novel metabolites associated with endophenotypes that delineate the complex pathophysiological architecture of diabetes, spanning mechanisms of muscle insulin resistance, inflammatory lipid signalling and beta cell metabolism (e.g. bioactive lipids, amino acids and microbe- and diet-derived metabolites). Integrating endophenotypes of diabetes susceptibility with the metabolome generated two multi-parametric metabolite scores, one of which (a proinflammatory adiposity score) was associated with incident diabetes across the life course in participants from both the CARDIA study (young adults; HR in a fully adjusted model 2.10 [95% CI 1.72, 2.55], p<0.0001) and FHS (middle-aged and older adults; HR 1.33 [95% CI 1.14, 1.56], p=0.0004). A metabolite score based on the outcome of diabetes was strongly related to diabetes in CARDIA study participants (fully adjusted HR 3.41 [95% CI 2.85, 4.07], p<0.0001) but not in the older FHS population (HR 1.15 [95% CI 0.99, 1.33], p=0.07). Conclusions/interpretation: Selected metabolic abnormalities in young adulthood identify individuals with heightened diabetes risk independent of race, sex and traditional diabetes risk factors. These signatures replicate across the life course

Dietary metabolic signatures and cardiometabolic risk

Aims: Observational studies of diet in cardiometabolic-cardiovascular disease (CM-CVD) focus on self-reported consumption of food or dietary pattern, with limited information on individual metabolic responses to dietary intake linked to CM-CVD. Here, machine learning approaches were used to identify individual metabolic patterns related to diet and relation to long-term CM-CVD in early adulthood. Methods and results: In 2259 White and Black adults (age 32.1 ± 3.6 years, 45% women, 44% Black) in the Coronary Artery Risk Development in Young Adults (CARDIA) study, multivariate models were employed to identify metabolite signatures of food group and composite dietary intake across 17 food groups, 2 nutrient groups, and healthy eating index-2015 (HEI2015) diet quality score. A broad array of metabolites associated with diet were uncovered, reflecting food-related components/catabolites (e.g. fish and long-chain unsaturated triacylglycerols), interactions with host features (microbiome), or pathways broadly implicated in CM-CVD (e.g. ceramide/sphingomyelin lipid metabolism). To integrate diet with metabolism, penalized machine learning models were used to define a metabolite signature linked to a putative CM-CVD-adverse diet (e.g. high in red/processed meat, refined grains), which was subsequently associated with long-term diabetes and CVD risk numerically more strongly than HEI2015 in CARDIA [e.g. diabetes: standardized hazard ratio (HR): 1.62, 95% confidence interval (CI): 1.32-1.97, P < 0.0001; CVD: HR: 1.55, 95% CI: 1.12-2.14, P = 0.008], with associations replicated for diabetes (P < 0.0001) in the Framingham Heart Study. Conclusion: Metabolic signatures of diet are associated with long-term CM-CVD independent of lifestyle and traditional risk factors. Metabolomics improves precision to identify adverse consequences and pathways of diet-related CM-CVD