Tight Glycemic Control Reduces Heart Inflammation and Remodeling During Acute Myocardial Infarction in Hyperglycemic Patients

Figures

• 

  Fig. 1. Risk of MI and mortality from MI in individuals with and without diabetes in the UK Biobank Cohort. Incidence of MI (a) and mortality from MI (b) in individuals with and without diabetes. Statistical significance was assessed using a chi-squared test. c Synergistic interaction between common cardiovascular disease biomarkers and diabetes on the incidence of MI and mortality in the UK Biobank. The predictor term (green dots) represents the risk conferred by the factor on MI incidence (n individuals = 262,706) or mortality (n individuals = 6234). The residual risk is defined as diabetes risk unexplained by the biomarker, and the term (black dots) represents the risk conferred by diabetes on MI incidence or mortality. The interaction term (blue dots) represents if the risk conferred by the risk factor is decreased or increased by the presence of diabetes. LDL low-density lipoprotein, HDL high-density lipoprotein, HbA1c Haemoglobin A1C, BMI body mass index. Effects of known diabetes biomarker (HbA1c) on time to MI incidence (n = 251,124) (d) and mortality (n = 5,979) (e). These outcomes are compared between individuals with biomarker levels in the high quantile (top 30%), middle…

• 

  Fig. 2. Comparative analysis of glycaemic stress on ischaemia sensitivity in an in vivo model of diabetes. a Schematic of protocol for an in vivo diabetic model of high-fat diet (HFD)-induced diabetes exposed to variable (vG) or constant (cG) glycaemic stress, followed by acute MI surgery and tissue harvest for histological analysis. b Echocardiographic assessment of heart function based on measures of isovolumic relaxation time (IVRT), cardiac output, heart rate and ejection fraction. c Post-MI mortality analysis. For in vivo studies, n = 11–12 per group. d Post-MI echocardiographic analysis of ejection fraction. e Representative Masson’s trichrome staining of transverse heart sections from cG and vG mice at 7 days post-MI. Scale bar = 50 mm. f Quantification of fibrotic regions in heart sections collected at 330 μm below the ligation suture. n = 10 (cG), n = 9 (vG); 20 sequential sections per heart. Box plots show the median (centre line), the interquartile range (25th–75th percentiles; box) and the full data range (minimum to maximum; whiskers). MI myocardial infarction. Data are presented as mean ± SEM. Statistical analysis by two-tailed student’s t-test (b, d, f), or two-sided…

• 

  Fig. 3. Comparative analysis of glycaemic stress for modelling ischaemic sensitivity in diabetes in vitro. a Protocol for hiPSC-CM diabetic and ischaemic stress model using a backbone medium (control) with diabetes-inducing neurohormonal mediators versus cells exposed to backbone + variable (vG) or constant glucose (cG). b Lipid uptake analysis based on Oil Red O staining. Arrows highlight areas of lipid accumulation indicative of lipid toxicity. Scale Bar = 50 µm. RNA-sequencing of differentially expressed (DE) genes between cG and vG (c) with a table of gene-associated GWAS traits (d). e Contractility investigated by impedance-based analysis (CardioExcyte 96) showing raw contractility traces (e-i) and bar plots (e-ii). f Cell death measured by release of lactate dehydrogenase (LDH) in hiPSC-CMs exposed to in vitro ischaemia-reperfusion (IR) injury. g LDH-based quantification of cell death in vG-conditioned cardiomyocytes subjected to in vitro IR injury at the 22 h timepoint in the presence of 10 nM Hi1a, a selective ASIC1a inhibitor. Schematic of the hiPSC-CM glycaemic and ischaemic stress model showing cells exposed to backbone with vG or cG glycaemic stressors only (h), with…

• 

  Fig. 4. Evaluation of the effect of clinical human blood samples on cardiac function. a Schematic of protocol for hiPSC-CM contractility assays evaluating blood plasma from patients with high versus low GV (Coefficient of Variation >36% considered as high). Impedance-based contractility analysis comparing plasma samples with high versus low GV (b) or the percentage of time for which blood glucose levels were very high (i.e. glucose levels >13.9 mmol/L for more than 25% of the time) (c). Representative surface-enhanced Raman spectroscopy images (d) illustrating examples of high and low GV, along with quantification of cardiac injury biomarkers (e) using plasmonic barcodes to detect BNP, ANP, CK-MB and cTnI. Scale Bar = 10 µm. For human plasma samples assay, n = 3 independent biological cardiomyocyte replicates, each with 2 technical replicates. Data are presented as mean ± SEM, with statistical analysis by Two-Way ANOVA (b, c) or two-tailed student’s t-test (e). Two-way ANOVA (group × time) for b, c showed no significant interaction (b: p = 0.5975; c: p = 0.9999). Both panels showed a significant time effect (p < 1 × 10−15). A significant group effect was observed in b (p = 6 × 10−7) but…