Dapagliflozin, inflammation and left ventricular remodelling in patients with type 2 diabetes and left ventricular hypertrophy.

BACKGROUND AND AIMS: Sodium-glucose co-transporter 2 (SGLT2) inhibitors have beneficial effects in heart failure (HF), including reverse remodelling, but the mechanisms by which these benefits are conferred are unclear. Inflammation is implicated in the pathophysiology of heart failure (HF) and there are some pre-clinical data suggesting that SGLT2 inhibitors may reduce inflammation. There is however a lack of clinical data. The aim of our study was to investigate whether improvements in cardiac remodelling caused by dapagliflozin in individuals with type 2 diabetes (T2D) and left ventricular hypertrophy (LVH) were associated with its effects on inflammation. METHODS: We measured C-reactive protein (CRP), tumor necrosis factor alpha (TNF-α), interleukin-1ß (IL-1ß), interleukin 6 (IL-6), and interleukin 10 (IL-10) and neutrophil-to-lymphocyte ratio (NLR) in plasma samples of 60 patients with T2D and left ventricular hypertrophy (LVH) but without symptomatic HF from the DAPA-LVH trial in which participants were randomised dapagliflozin 10 mg daily or placebo for 12 months and underwent cardiac magnetic resonance imaging (CMR) at baseline and end of treatment. The primary analysis was to investigate the effect of dapagliflozin on inflammation and to assess the relationships between changes in inflammatory markers and LV mass and global longitudinal strain (GLS) and whether the effect of dapagliflozin on LV mass and GLS was modulated by baseline levels of inflammation. RESULTS: Following 12 months of treatment dapagliflozin significantly reduced CRP compared to placebo (mean difference of -1.96; 95% CI -3.68 to -0.24, p = 0.026). There were no significant statistical changes in other inflammatory markers. There were modest correlations between improvements in GLS and reduced inflammation (NLR (r = 0.311), IL-1ß (r = 0.246), TNF-α (r = 0.230)) at 12 months. CONCLUSIONS: Dapagliflozin caused a significant reduction in CRP compared to placebo. There were correlations between reductions in inflammatory markers including IL-1ß and improvements in global longitudinal strain (but not reduced LV mass). Reductions in systemic inflammation might play a contributory role in the cardiovascular benefits of dapagliflozin. TRIAL REGISTRATION: Clinicaltrials.gov NCT02956811 (06/11/2016).

Limiting extracellular matrix expansion in diet-induced obese mice reduces cardiac insulin resistance and prevents myocardial remodelling.

OBJECTIVE: Obesity increases deposition of extracellular matrix (ECM) components of cardiac tissue. Since obesity aggregates with insulin resistance and heart disease, it is imperative to determine whether the increased ECM deposition contributes to this disease cluster. The hypotheses tested in this study were that in cardiac tissue of obese mice i) increased deposition of ECM components (collagens and hyaluronan) contributes to cardiac insulin resistance and that a reduction in these components improves cardiac insulin action and ii) reducing excess collagens and hyaluronan mitigates obesity-associated cardiac dysfunction. METHODS: Genetic and pharmacological approaches that manipulated collagen and hyaluronan contents were employed in obese C57BL/6 mice fed a high fat (HF) diet. Cardiac insulin sensitivity was measured by hyperinsulinemic-euglycemic clamp and cardiac function was measured by pressure-volume loop analysis in vivo. RESULTS: We demonstrated a tight association between increased ECM deposition with cardiac insulin resistance. Increased collagen deposition by genetic deletion of matrix metalloproteinase 9 (MMP9) exacerbated cardiac insulin resistance and pirfenidone, a clinically available anti-fibrotic medication which inhibits collagen expression, improved cardiac insulin resistance in obese mice. Furthermore, decreased hyaluronan deposition by treatment with PEGylated human recombinant hyaluronidase PH20 (PEGPH20) improved cardiac insulin resistance in obese mice. These relationships corresponded to functional changes in the heart. Both PEGPH20 and pirfenidone treatment in obese mice ameliorated HF diet-induced abnormal myocardial remodelling. CONCLUSION: Our results provide important new insights into the role of ECM deposition in the pathogenesis of cardiac insulin resistance and associated dysfunction in obesity of distinct mouse models. These findings support the novel therapeutic potential of targeting early cardiac ECM abnormalities in the prevention and treatment of obesity-related cardiovascular complications.

Accelerated elastin degradation by age-disease interaction: a common feature in age-related diseases.

Aging is a major driving force for many diseases but the relationship between chronological age, the aging process and age-related diseases is not fully understood. Fragmentation and loss of ultra-long-lived elastin are key features in aging and several age-related diseases leading to increased mortality. By comparing the relationship between age and elastin turnover with healthy volunteers, we show that accelerated elastin turnover by age-disease interaction is a common feature of age-related diseases.

Artificial intelligence-assisted automated heart failure detection and classification from electronic health records.

AIMS: Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. We hypothesized that by applying keyword searches to routinely stored EHR, in conjunction with AI-powered automated reading of DICOM echocardiography images and analysing biomarkers from routinely stored plasma samples, we were able to identify heart failure (HF) patients. METHODS AND RESULTS: We used EHR data between 1993 and 2021 from Tayside and Fife (~20% of the Scottish population). We implemented a keyword search strategy complemented by filtering based on International Classification of Diseases (ICD) codes and prescription data to EHR data set. We then applied DL for the automated interpretation of echocardiographic DICOM images. These methods were then integrated with the analysis of routinely stored plasma samples to identify and categorize patients into HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF), and controls without HF. The final diagnosis was verified through a manual review of medical records, measured natriuretic peptides in stored blood samples, and by comparing clinical outcomes among groups. In our study, we selected the patient cohort through an algorithmic workflow. This process started with 60 850 EHR data and resulted in a final cohort of 578 patients, divided into 186 controls, 236 with HFpEF, and 156 with HFrEF, after excluding individuals with mismatched data or significant valvular heart disease. The analysis of baseline characteristics revealed that compared with controls, patients with HFrEF and HFpEF were generally older, had higher BMI, and showed a greater prevalence of co-morbidities such as diabetes, COPD, and CKD. Echocardiographic analysis, enhanced by DL, provided high coverage, and detailed insights into cardiac function, showing significant differences in parameters such as left ventricular diameter, ejection fraction, and myocardial strain among the groups. Clinical outcomes highlighted a higher risk of hospitalization and mortality for HF patients compared with controls, with particularly elevated risk ratios for both HFrEF and HFpEF groups. The concordance between the algorithmic selection of patients and manual validation demonstrated high accuracy, supporting the effectiveness of our approach in identifying and classifying HF subtypes, which could significantly impact future HF diagnosis and management strategies. CONCLUSIONS: Our study highlights the feasibility of combining keyword searches in EHR, DL automated echocardiographic interpretation, and biobank resources to identify HF subtypes.

IL-17 is associated with disease severity and targetable inflammatory processes in heart failure.

AIMS: Heart failure (HF) is recognized as an inflammatory disease in which cytokines play an important role. In animal HF models, interleukin-17A (IL-17) has been linked to deterioration of cardiac function and fibrosis, whereas knock-out of IL-17 showed beneficial cardiac effects. However, there is limited evidence of IL-17 involvement in patients with HF. This study aims to investigate the clinical characteristics, outcomes, and pathophysiological processes associated with circulating IL-17 concentrations in patients with HF. METHODS AND RESULTS: IL-17 was measured by ELISA in 2082 patients diagnosed with HF along with 363 circulating proteins using proximity extension assay technology for differential expression and pathway analysis. Data were validated in an independent cohort of 1737 patients with HF. Patients with elevated IL-17 concentrations had more severe HF, as reflected by more frequent current or previous hospitalizations for HF, higher New York Heart Association functional class (NYHA) and higher levels of N-terminal pro-B-type natriuretic peptide (NT-proBNP). High IL-17 concentrations were independently associated with an increased risk of hospitalization for HF and mortality. In both cohorts, the most strongly up-regulated proteins in patients with high IL-17 were fibroblast growth factor 21 (FGF-21), interleukin-6 (IL-6), C-X-C motif chemokine ligand 13 (CXCL13), tumour necrosis factor receptor superfamily member 6B (TNFRSF6B) and interleukin-1 receptor antagonist (IL-1RA). Pathway over-representation analysis showed increased activity of pathways related to lymphocyte-mediated immunity, leukocyte activation and regulation of the immune response. CONCLUSIONS: In patients with HF, elevated IL-17 concentrations indicate more severe HF and increased activity of inflammatory processes known to be involved in the pathophysiology of HF. IL-17 might hold potential for identifying and targeting inflammation in HF.

Differential biomarker expression in heart failure patients with and without mitral regurgitation: Insights from BIOSTAT-CHF.

BACKGROUND: Mitral regurgitation (MR) frequently coexists with heart failure (HF). OBJECTIVES: To better understand potential pathophysiological differences between patients with HF with or without moderate-severe MR, we compared differentially expressed circulating biomarkers between these two groups. METHODS: The Olink Proteomics® Multiplex Cardiovascular (CVD) -II, CVD-III, Immune Response and Oncology-II panels of 363 unique proteins from different pathophysiological domains were used to investigate the biomarker profiles of HF patients from index and validation cohorts of the BIOSTAT-CHF study stratified according to the presence of moderate-to-severe MR or no-mild MR. RESULTS: The index cohort included 888 patients (46%) with moderate-to-severe MR and 1029 (54%) with no-mild MR at baseline. The validation cohort included 522 patients (33%) with moderate-to-severe MR and 1076 (66%) with no-mild MR at baseline. Compared to patients with no-mild MR, those with moderate-to-severe MR had lower body mass index, higher comorbidity burden, signs and symptoms of more severe HF, lower systolic blood pressure, and larger left atrial and ventricular dimensions, in both cohorts. NT-proBNP, CA125, fibroblast growth factor 23 (FGF23) and growth hormone 1 (GH1) were up-regulated, whereas leptin (LEP) was down-regulated in patients with moderate-severe MR versus no-mild MR, in both index and validation cohorts. CONCLUSION: Circulating biomarkers differently expressed in HF patients with moderate-severe MR versus no-mild MR were related to congestion, lipid and mineral metabolism and oxidative stress. These findings may be of value for the development of novel treatment targets in HF patients with MR.

Heart failure with improved versus persistently reduced left ventricular ejection fraction: A comparison of the BIOSTAT-CHF (European) study with the ASIAN-HF registry.

AIMS: We investigated the prevalence, clinical characteristics, and prognosis of patients with heart failure (HF) with improved ejection fraction (HFimpEF). METHODS AND RESULTS: We used data from BIOSTAT-CHF including patients with a left ventricular ejection fraction (LVEF) ≤40% at baseline who had LVEF re-assessed at 9 months. HFimpEF was defined as a LVEF >40% and a LVEF ≥10% increase from baseline at 9 months. We validated findings in the ASIAN-HF registry. The primary outcome was a composite of time to HF rehospitalization or all-cause mortality. In BIOSTAT-CHF, about 20% of patients developed HFimpEF, that was associated with a lower primary event rate of all-cause mortality (hazard ratio [HR] 0.52, 95% confidence interval [CI] 0.28-0.97, p = 0.040) and the composite endpoint (HR 0.46, 95% CI 0.30-0.70, p < 0.001) compared with patients who remained in persistent HF with reduced ejection fraction (HFrEF). The findings were similar in the ASIAN-HF (HR 0.40, 95% CI 0.18-0.89, p = 0.024, and HR 0.29, 95% CI 0.17-0.48, p < 0.001). Five independently common predictors for HFimpEF in both BIOSTAT-CHF and ASIAN-HF were female sex, absence of ischaemic heart disease, higher LVEF, smaller left ventricular end-diastolic and end-systolic diameter at baseline. A predictive model combining only five predictors (absence of ischaemic heart disease and left bundle branch block, smaller left ventricular end-systolic and left atrial diameter, and higher platelet count) for HFimpEF in the BIOSTAT-CHF achieved an area under the curve of 0.772 and 0.688 in the ASIAN-HF (due to missing left atrial diameter and platelet count). CONCLUSIONS: Approximately 20-30% of patients with HFrEF improved to HFimpEF within 1 year with better clinical outcomes. In addition, the predictive model with clinical predictors could more accurately predict HFimpEF in patients with HFrEF.