RESUMEN
Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome with various phenotypes, and obesity is one of the most common and clinically relevant phenotypes of HFpEF. Obesity contributes to HFpEF through multiple mechanisms, including sodium retention, neurohormonal dysregulation, altered energy substrate metabolism, expansion of visceral adipose tissue, and low-grade systemic inflammation. Glucagon-like peptide-1 (GLP-1) is a hormone in the incretin family. It is produced by specialized cells called neuroendocrine L cells located in the distal ileum and colon. GLP-1 reduces blood glucose levels by promoting glucose-dependent insulin secretion from pancreatic ß cells, suppressing glucagon release from pancreatic α cells, and blocking hepatic gluconeogenesis. Recent evidence suggests that GLP-1 receptor agonists (GLP-1 RAs) can significantly improve physical activity limitations and exercise capacity in obese patients with HFpEF. The possible cardioprotective mechanisms of GLP-1 RAs include reducing epicardial fat tissue thickness, preventing activation of the renin-angiotensin-aldosterone system, improving myocardial energy metabolism, reducing systemic inflammation and cardiac oxidative stress, and delaying the progression of atherosclerosis. This review examines the impact of obesity on the underlying mechanisms of HFpEF, summarizes the trial data on cardiovascular outcomes of GLP-1 RAs in patients with type 2 diabetes mellitus, and highlights the potential cardioprotective mechanisms of GLP-1 RAs to give a pathophysiological and clinical rationale for using GLP-1 RAs in obese HFpEF patients.
RESUMEN
Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of cardiovascular mortality and is increasingly prevalent in our population. Glucagon-like peptide-1 receptor agonists (GLP-1RAs) can safely and effectively lower glucose levels while concurrently managing the full spectrum of ASCVD risk factors and improving patients' long-term prognosis. Several cardiovascular outcome trials (CVOTs) have been carried out to further investigate the cardiovascular benefits of GLP-1RAs. Analyzing data from CVOTs can provide insights into the pathophysiologic mechanisms by which GLP-1RAs are linked to ASCVD and define the use of GLP-1RAs in clinical practice. Here, we discussed various mechanisms hypothesized in previous animal and preclinical human studies, including blockade of the production of adhesion molecules and inflammatory factors, induction of endothelial cells' synthesis of nitric oxide, protection of mitochondrial function and restriction of oxidative stress, suppression of NOD-like receptor thermal protein domain associated protein three inflammasome, reduction of foam cell formation and macrophage inflammation, and amelioration of vascular smooth muscle cell dysfunction, to help explain the cardiovascular benefits of GLP-1RAs in CVOTs. This paper provides an overview of the clinical research, molecular processes, and possible therapeutic applications of GLP-1RAs in ASCVD, while also addressing current limitations in the literature and suggesting future research directions.
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Purpose: This study aimed to analyze the hub genes of heart failure with reduced ejection fraction (HFrEF) treated with Empagliflozin using RNA sequencing (RNA-seq) and bioinformatics methods, including machine learning. Methods: From February 2021 to February 2023, nine patients with HFrEF were enrolled from our hospital's cardiovascular department. In addition to routine drug treatment, these patients received 10 mg of Empagliflozin once daily for two months. Efficacy was assessed and RNA-seq was performed on peripheral blood before and after treatment with empagliflozin. HFrEF-related hub genes were identified through bioinformatics analyses including differential gene expression analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, immune infiltration analysis, machine learning, immune cell correlation analysis and clinical indicator correlation analysis. Results: The nine patients included in this study completed a two-month treatment regimen, with an average age of 62.11 ± 6.36 years. By performing bioinformatics analysis on the transcriptome from the treatment groups, 42 differentially expressed genes were identified, with six being up-regulated and 36 being down-regulated (|log2FC|>1 and adj.pvalue<0.05). Immune infiltration analysis of these genes demonstrated a significant difference in the proportion of plasma between the pre-treatment and post-treatment groups (p<0.05). Two hub genes, GTF2IP14 and MTLN, were finally identified through machine learning. Further analysis of the correlation between the hub genes and immune cells suggested a negative correlation between GTF2IP14 and naive B cells, and a positive correlation between MTLN and regulatory T cells and resting memory CD4+ T cells (p<0.05). Conclusion: Through RNA-seq and bioinformatics analysis, this study identified GTF2IP14 and MTLN as the hub genes of HFrEF, and their mechanisms may be related to immune inflammatory responses and various immune cells.
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Purpose: Heart failure is a serious complication after acute myocardial infarction (AMI). It is crucial to investigate the mechanism of action of empagliflozin in the treatment of heart failure. Methods: A total of 20 wild type (WT) male C57BL6/J mice were used to establish a model of heart failure after myocardial infarction and randomly divided into 2 groups: treatment group and control group. The treatment group was treated with empagliflozin, and the control group was treated with placebo. After 8 weeks of treatment, mouse heart tissues were collected for next generation sequencing. Bioinformatics methods were used to screen the key genes. Finally, the correlation between clinical data and gene expression was analyzed. Quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the expression of key genes. Results: A mouse model of heart failure was successfully constructed. By DEG analysis, a total of 740 DEGs in the treatment group vs the control group were obtained. Dendritic cells, granulocytes, follicular B, plasma cell, cDC1, cDC2, pDC and neutrophils were 8 different immune cells identified by immunoinfiltration analysis. Through WGCNA, the turquoise module with the highest correlation with the above differential immune cells was selected. One hundred and forty-two immune-related DEGs were obtained by taking intersection of the DEGs and the genes of the turquoise module. Col17a1 and Gria4 were finally screened out as key immune-related genes via PPI analysis and machine learning. Col17a1 was significantly up-regulated, while Gria4 was significantly down-regulated in the treatment group. At the same time, the expression level of Col17a1 was significantly correlated with left ventricular ejection fraction (LVEF), left ventricular fraction shortening (LVFS) and left ventricular internal dimension systole (LVIDs). Conclusion: Col17a1 and Gria4 are key immune-related genes of empagliflozin in the treatment of heart failure after myocardial infarction. This study provides a scientific basis for elucidating the mechanism of action of empagliflozin in treating heart failure after myocardial infarction.
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Purpose: The purpose was to identify shared immune cells and co-disease genes in chronic heart failure (HF) and systemic lupus erythematosus (SLE), as well as explore the potential mechanisms of action between HF and SLE. Methods: A collection of peripheral blood mononuclear cells (PBMCs) from ten patients with HF and SLE and ten normal controls (NC) was used for transcriptome sequencing. Differentially expressed genes (DEGs) analysis, enrichment analysis, immune infiltration analysis, weighted gene co-expression network analysis (WGCNA), protein-protein interaction (PPI) analysis, and machine learning were applied for the screening of shared immune cells and co-disease genes in HF and SLE. Gene expression analysis and correlation analysis were used to explore the potential mechanisms of co-disease genes and immune cells in HF and SLE. Results: In this study, it was found that two immune cells, T cells CD4 naïve and Monocytes, displayed similar expression patterns in HF and SLE at the same time. By taking intersection of the above immune cell-associated genes with the DEGs common to both HF and SLE, four immune-associated co-disease genes, CCR7, RNASE2, RNASE3 and CXCL10, were finally identified. CCR7, as one of the four key genes, was significantly down-regulated in HF and SLE, while the rest three key genes were all significantly up-regulated in both diseases. Conclusion: T cells CD4 naïve and Monocytes were first revealed as possible shared immune cells of HF and SLE, and CCR7, RNASE2, RNASE3 and CXCL10 were identified as possible key genes common to HF and SLE as well as potential biomarkers or therapeutic targets for HF and SLE.