Causal effects between circulating immune cells and heart failure: evidence from a bidirectional Mendelian randomization study.

BACKGROUND: Heart failure (HF) is a prevalent cardiac condition characterized by high mortality and morbidity rates. Immune cells play a pivotal role as crucial biomarkers in assessing the overall immune status of individuals. However, the causal relationship between circulating immune cells and the pathogenesis of HF remains an area requiring further investigation. OBJECTIVES: The aim of this study was to investigate the genetic interactions between circulating immune cells and HF, and to further elucidate the genetic associations between different lymphocyte subsets and HF. METHODS: We obtained genetic variants associated with circulating immune cells as instrumental variables (IVs) from the Blood Cell Consortium and publicly available HF summary data. We conducted additional subsets analyses on lymphocyte counts. Our study utilized two-sample and multivariate Mendelian randomization (MVMR) analysis to investigate the causal effect of immune cells on HF. The primary analysis employed inverse variance weighting (IVW) and was complemented by a series of sensitivity analyses. RESULTS: The findings of the study showed that the IVW model demonstrated a significant correlation between an elevation in lymphocyte count and a decreased risk of HF (OR = 0.97, 95% CI, 0.94 - 1.00, P = 0.032). However, no such correlation was evident in the MVMR analysis for lymphocytes and HF. Furthermore, the examination of the lymphocyte subsets indicated that an increase in CD39+ CD4+ T-cell counts was notably linked to a reduced risk of HF (OR = 0.96, 95% CI, 0.95 - 0.98, P = 0.0002). The MVMR results confirmed that the association between CD39+ CD4+ T-cell counts and HF remained significant. There was no substantial evidence of reverse causality observed between circulating immune cells and HF. CONCLUSION: Our MR research provided evidence for a causal relationship between lymphocyte cell and HF. Subsets analyses revealed a causal relationship between CD39+ CD4+ T lymphocytes and HF. These findings will facilitate a future understanding of the mechanisms underlying HF.

Application and mechanisms of Sanhua Decoction in the treatment of cerebral ischemia-reperfusion injury.

Cerebral ischemia-reperfusion is a process in which the blood supply to the brain is temporarily interrupted and subsequently restored. However, it is highly likely to lead to further aggravation of pathological damage to ischemic tissues or the nervous system., and has accordingly been a focus of extensive clinical research. As a traditional Chinese medicinal formulation, Sanhua Decoction has gradually gained importance in the treatment of cerebrovascular diseases. Its main constituents include Citrus aurantium, Magnolia officinalis, rhubarb, and Qiangwu, which are primarily used to regulate qi. In the treatment of neurological diseases, the therapeutic effects of the Sanhua Decoction are mediated via different pathways, including antioxidant, anti-inflammatory, and neurotransmitter regulatory pathways, as well as through the protection of nerve cells and a reduction in cerebral edema. Among the studies conducted to date, many have found that the application of Sanhua Decoction in the treatment of neurological diseases has clear therapeutic effects. In addition, as a natural treatment, the Sanhua Decoction has received widespread attention, given that it is safer and more effective than traditional Western medicines. Consequently, research on the mechanisms of action and efficacy of the Sanhua Decoctions in the treatment of cerebral ischemia-reperfusion injury is of considerable significance. In this paper, we describe the pathogenesis of cerebral ischemia-reperfusion injury and review the current status of its treatment to examine the therapeutic mechanisms of action of the Sanhua Decoction. We hope that the findings of the research presented herein will contribute to a better understanding of the efficacy of this formulation in the treatment of cerebral ischemia-reperfusion, and provide a scientific basis for its application in clinical practice.

Potential Value of Probiotics on Lipid Profiles in Hyperlipidemia and Healthy Participants: Systematic Review and Meta-Analysis.

Objective: Many randomized controlled trials (RCTs) have reported the effect of probiotics on reducing plasma lipids with inconsistent results. An explicit systematic review and meta-analysis were conducted in this study to evaluate the effect of probiotics on the lipid profile of healthy and hyperlipidemia participants. Methods: A comprehensive literature search of RCTs was conducted using PubMed, Embase, World Health Organization (WHO) Global Index Medicus, WHO clinical trial registry, and Clinicaltrials.gov. Inclusion criteria included RCTs comparing the use of any strain of a specified probiotic with the placebo control group. The change in lipid profiles was analyzed. Results: The probiotics can decrease the total cholesterol (TC) level in hyperlipidemia participants but not healthy persons (MD = -0.43, 95% CI -0.60 - -0.25, P < .01; MD = -0.09, 95% CI -0.26 - 0.08, P > .05). Probiotics did not reduce high-density lipoprotein cholesterol (HDL-C) in patients with hyperlipidemia or healthy people (MD = -0.01, 95% CI -0.09 - 0.07, P > .05; MD = 0.02, 95% CI -0.04 - 0.09, P > .05). Furthermore, probiotics can reduce the low-density lipoprotein cholesterol (LDL-C) level both in hyperlipidemia and healthy persons (MD = -0.34, 95% CI -0.43 - -0.26, P < .01; MD = -0.15, 95% CI -0.28 - -0.02, P < .05). Lastly, the effect of probiotics on reducing triglyceride (TG) levels was significant in hyperlipidemia persons but not in the healthy population (MD = -0.20, 95% CI -0.37 - -0.04, P < .01; MD = -0.01, 95% CI -0.02 - 0.04, P > .05). Conclusions: Through our analysis, the effect of probiotics on lowering plasma lipid was more obvious in hyperlipidemia participants than healthy population. However, further studies are required to confirm the findings due to pronounced clinical heterogeneity.

Identification of cuproptosis-related biomarkers in dilated cardiomyopathy and potential therapeutic prediction of herbal medicines.

Background: Dilated cardiomyopathy (DCM) is one of the significant causes of heart failure, and the mechanisms of metabolic ventricular remodelling due to disturbances in energy metabolism are still poorly understood in cardiac pathology. Understanding the biological mechanisms of cuproptosis in DCM is critical for drug development. Methods: The DCM datasets were downloaded from Gene Expression Omnibus, their relationships with cuproptosis-related genes (CRGs) and immune signatures were analyzed. LASSO, RF, and SVM-RFE machine learning algorithms were used to identify signature genes and the eXtreme Gradient Boosting (XGBoost) model was used to assess diagnostic efficacy. Molecular clusters of CRGs were identified, and immune Infiltration analysis was performed. The WGCNA algorithm was used to identify specific genes in different clusters. In addition, AUCell was used to analyse the cuproptosis scores of different cell types in the scRNA-seq dataset. Finally, herbal medicines were predicted from an online database, and molecular docking and molecular dynamics simulations were used to support the confirmation of the potential of the selected compounds. Results: We identified dysregulated cuproptosis genes and activated immune responses between DCM and healthy controls. Two signature genes (FDX1, SLC31A1) were identified and performed well in an external validation dataset (AUC = 0.846). Two molecular clusters associated with cuproptosis were further defined in DCM, and immune infiltration analysis showed B-cell naive, Eosinophils, NK cells activated and T-cell CD4 memory resting is significant immune heterogeneity in the two clusters. AUCell analysis showed that cardiomyocytes had a high cuproposis score. In addition, 19 and 3 herbal species were predicted based on FDX1 and SLC31A1. Based on the molecular docking model, the natural compounds Rutin with FDX1 (-9.3 kcal/mol) and Polydatin with SLC31A1 (-5.5 kcal/mol) has high stability and molecular dynamics simulation studies further validated this structural stability. Conclusion: Our study systematically illustrates the complex relationship between cuproptosis and the pathological features of DCM and identifies two signature genes (FDX1 and SLC31A1) and two natural compounds (Rutin and Polydatin). This may enhance our diagnosis of the disease and facilitate the development of clinical treatment strategies for DCM.

Uncovering the molecular mechanisms between heart failure and end-stage renal disease via a bioinformatics study.

Background: Heart failure (HF) is not only a common complication in patients with end-stage renal disease (ESRD) but also a major cause of death. Although clinical studies have shown that there is a close relationship between them, the mechanism of its occurrence is unclear. The aim of this study is to explore the molecular mechanisms between HF and ESRD through comprehensive bioinformatics analysis, providing a new perspective on the crosstalk between these two diseases. Methods: The HF and ESRD datasets were downloaded from the Gene Expression Omnibus (GEO) database; we identified and analyzed common differentially expressed genes (DEGs). First, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set variation analyses (GSVA) were applied to explore the potential biological functions and construct protein-protein interaction (PPI) networks. Also, four algorithms, namely, random forest (RF), Boruta algorithm, logical regression of the selection operator (LASSO), and support vector machine-recursive feature elimination (SVM-RFE), were used to identify the candidate genes. Subsequently, the diagnostic efficacy of hub genes for HF and ESRD was evaluated using eXtreme Gradient Boosting (XGBoost) algorithm. CIBERSORT was used to analyze the infiltration of immune cells. Thereafter, we predicted target microRNAs (miRNAs) using databases (miRTarBase, TarBase, and ENOCRI), and transcription factors (TFs) were identified using the ChEA3 database. Cytoscape software was applied to construct mRNA-miRNA-TF regulatory networks. Finally, the Drug Signatures Database (DSigDB) was used to identify potential drug candidates. Results: A total of 68 common DEGs were identified. The enrichment analysis results suggest that immune response and inflammatory factors may be common features of the pathophysiology of HF and ESRD. A total of four hub genes (BCL6, CCL5, CNN1, and PCNT) were validated using RF, LASSO, Boruta, and SVM-RFE algorithms. Their AUC values were all greater than 0.8. Immune infiltration analysis showed that immune cells such as macrophages, neutrophils, and NK cells were altered in HF myocardial tissue, while neutrophils were significantly correlated with all four hub genes. Finally, 11 target miRNAs and 10 TFs were obtained, and miRNA-mRNA-TF regulatory network construction was performed. In addition, 10 gene-targeted drugs were discovered. Conclusion: Our study revealed important crosstalk between HF and ESRD. These common pathways and pivotal genes may provide new ideas for further clinical treatment and experimental studies.

Immunoadsorption treatment for dilated cardiomyopathy: A PRISMA-compliant systematic review and meta-analysis.

BACKGROUND: As one of the leading causes of heart failure, dilated cardiomyopathy (DCM) is characterized by dysfunctional muscle contraction and enlarged ventricular chamber. Patients with DCM have been shown to respond well to immunoadsorption (IA) therapies. However, the efficacy and safety of IA treatment for DCM patients remained to be evaluated. METHODS: This study was designed in accordance with the Preferred Reporting Items for Systematic Review and Meta-analysis. We searched the databases such as Cochrane library, Cochrane Central Register of Controlled Trials, Embase, OVID, and Web of Science from January 1990 to March 20, 2020, and performed meta-analysis using Stata MP Version 13.0. RESULTS: We performed meta-analysis on 12 studies that included a total of 395 patients with DCM. Overall, IA treatment significantly improved the left ventricular ejection fraction (6.01, 95% confidence interval [CI] [4.84-7.19]), reduced the left ventricular end diastolic diameter (-3.62, 95% CI [-4.06 to -3.19]), reduced severity of symptoms according to the New York Heart Association (NYHA) functional classification (-1.37, 95% CI [-1.73 to -1.02]) as compared with the controls, but had no effect on values for safety parameters (1.13, 95% CI [0.58-2.19]). CONCLUSIONS: Results of this meta-analysis indicated that the IA treatment can improve the left ventricular ejection fraction, reduce left ventricular end diastolic diameter, and thus improve clinical outcome in DCM patients. However, further evidence are required to validate the relative safety of IA treatment. Multi-center, double blind studies should be conducted to elucidate the precise effect of IA treatment in DCM patients.