Project description:Background: Inflammatory activation and immune infiltration play important roles in the pathologic process of heart failure (HF). The current study is designed to investigate the immune infiltration and identify related biomarkers in heart failure patients due to ischemic cardiomyopathy. Methods: Expression data of HF due to ischemic cardiomyopathy (CM) samples and non-heart failure (NF) samples were downloaded from gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) between CM and NF samples were identified. Single sample gene set enrichment analysis (ssGSEA) was performed to explore the landscape of immune infiltration. Weighted gene co-expression network analysis (WGCNA) was applied to screen the most relevant module associated with immune infiltration. The diagnostic values of candidate genes were evaluated by receiver operating curves (ROC) curves. The mRNA levels of potential biomarkers in the peripheral blood mononuclear cells (PBMCs) isolated from 10 CM patients and 10 NF patients were analyzed to further assess their diagnostic values. Results: A total of 224 DEGs were identified between CM and NF samples in GSE5406, which are mainly enriched in the protein processing and extracellular matrix related biological processes and pathways. The result of ssGSEA showed that the abundance of dendritic cells (DC), mast cells, natural killer (NK) CD56dim cells, T cells, T follicular helper cells (Tfh), gammadelta T cells (Tgd) and T helper 2 (Th2) cells were significantly higher, while the infiltration of eosinophils and central memory T cells (Tcm) were lower in CM samples compared to NF ones. Correlation analysis revealed that Calumenin (CALU) and palladin (PALLD) were negatively correlated with the abundance of DC, NK CD56dim cells, T cells, Tfh, Tgd and Th2 cells, but positively correlated with the level of Tcm. More importantly, CALU and PALLD were significantly lower in PBMCs from CM patients compared to NF ones. Conclusion: Our study revealed that CALU and PALLD are potential biomarkers associated with immune infiltration in heart failure due to ischemic cardiomyopathy.

Project description:Heart failure (HF) and osteoarthritis (OA) are medical conditions that can significantly impact daily activities. Evidence has shown that HF and OA may share some pathogenic mechanisms. However, the underlying genomic mechanisms remain unclear. This study aimed to explore the underlying molecular mechanism and identify diagnostic biomarkers for HF and OA. With the cutoff criteria of fold change (FC) > 1.3 and P < .05, 920, 1500, 2195, and 2164 differentially expressed genes (DEGs) were identified in GSE57338, GSE116250, GSE114007, and GSE169077, respectively. After making the intersection of DEGs, we obtained 90 upregulated DEGs and 51 downregulated DEGs in HF datasets and 115 upregulated DEGs and 75 downregulated DEGs in OA datasets. Afterward, we conducted genome ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, protein-protein interaction (PPI) networks, and hub genes screening based on DEGs. Then, 4 common DEGs (fibroblast activation protein alpha [FAP], secreted frizzled-related protein 4 (SFRP4), Thy-1 cell surface antigen (THY1), matrix remodeling associated 5 [MXRA5]) between HF and OA were screened and validated in GSE5406 and GSE113825 datasets, based on which we established the support vector machine (SVM) models. The combined area under the receiver operating characteristic curve (AUC) of THY1, FAP, SFRP4, and MXRA5 in the HF training and test sets reached 0.949 and 0.928. While in the OA training set and test set, the combined AUC of THY1, FAP, SFRP4, and MXRA5 reached 1 and 1, respectively. The analysis of immune cells in HF revealed high levels of dendritic cell (DC), B cells, natural killer T cell (NKT), Type 1 regulatory T cell (Tr1), cytotoxic T cell (Tc), exhausted T cell (Tex), and mucosal-associated invariant T cell (MAIT), while displaying lower levels of monocytes, macrophages, NK, CD4 + T, gamma delta T (γδ T), T helper type 1 (Th1), T helper type 2 (Th2), and effector memory T cell (Tem). Moreover, the 4 common DEGs were positively correlated with DCs and B cells and negatively correlated with γδ T. In OA patients, the abundance of monocyte, macrophage, CD4 + naïve, and natural T regulatory cell (nTreg) was higher, while the infiltration of CD8 + T, γδ T, CD8 + naïve, and MAIT was lower. The expression of THY1 and FAP was significantly correlated with macrophage, CD8 + T, nTreg, and CD8 + naïve. SFRP4 was correlated with monocyte, CD8 + T, γδ T, CD4 + naïve, nTreg, CD8 + naïve and MAIT. MXRA5 was correlated with macrophage, CD8 + T, nTreg and CD8 + naïve. FAP, THY1, MXRA5, and SFRP4 may be diagnostic biomarkers for both HF and OA, and their correlation with immune cell infiltrations suggests shared immune pathogenesis.

Project description:Cardiovascular diseases are a leading cause of death worldwide. After an ischemic injury, the myocardium undergoes severe necrosis and apoptosis, leading to a dramatic degradation of function. Numerous studies have reported that cardiac fibroblasts (CFs) play a critical role in heart function even after injury. However, CFs present heterogeneous characteristics according to their development stage (i.e., fetal or adult), and the molecular mechanisms by which they maintain heart function are not fully understood. The aim of this study is to explore the hypothesis that a specific population of CFs can repair the injured myocardium in heart failure following ischemic infarction, and lead to a significant recovery of cardiac function. Flow cytometry analysis of CFs defined two subpopulations according to their relative expression of vascular cell adhesion molecule 1 (VCAM1). Whole-transcriptome analysis described distinct profiles for these groups, with a correlation between VCAM1 expression and lymphangiogenesis-related genes up-regulation. Vascular formation assays showed a significant stimulation of lymphatic cells network complexity by VCFs. Injection of human VCAM1-expressing CFs (VCFs) in postinfarct heart failure rat models (ligation of the left anterior descending artery) led to a significant restoration of the left ventricle contraction. Over the course of the experiment, left ventricular ejection fraction and fractional shortening increased by 16.65% ± 5.64% and 10.43% ± 6.02%, respectively, in VCF-treated rats. Histological examinations revealed that VCFs efficiently mobilized the lymphatic endothelial cells into the infarcted area. In conclusion, human CFs present heterogeneous expression of VCAM1 and lymphangiogenesis-promoting factors. VCFs restore the mechanical properties of ventricular walls by mobilizing lymphatic endothelial cells into the infarct when injected into a rat heart failure model. These results suggest a role of this specific population of CFs in the homeostasis of the lymphatic system in cardiac regeneration, providing new information for the study and therapy of cardiac diseases.

Project description:Both oxidative stress and the immune response are associated with heart failure (HF). In this study, our aim was to identify the hub genes associated with oxidative stress andimmune infiltration of HF by bioinformatics analysis and experimental verification. The expression profile of GSE36074 was obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were screened by GEO2R. The genes related to oxidative stress were extracted from GeneCards websites. Then, the functional enrichment analysis of oxidative stress-related DEGs (OSRDEGs) was performed using DAVID. In addition, we constructed a protein-protein interaction (PPI) network using the STRING database and screened for hub genes with Cytoscape software. We also used CIBERSORTx to analyze immune infiltration in mice heart tissues between the TAC and Sham groups and explored the correlation between immune cells and hub genes. Finally, the hub genes were carried out using reverse transcription quantitative PCR (RT-qPCR), immunohistochemistry (IHC) and western blot. A total of 136 OSRDEGs were found in GSE36074. Enrichment analysis revealed that these OSRDEGs were enriched in the mitochondrion, HIF-1, FoxO, MAPK and TNF signaling pathway. The five hub genes (Mapk14, Hif1a, Myc, Hsp90ab1, and Hsp90aa1) were screened by the cytoHubba plugin. The correlation analysis between immune cells and hub genes showed that Mapk14 was positively correlated with Th2 Cells, while Hif1a and Hsp90ab1exhibited a negative correlation with Th2 Cells; Myc exhibited a negative correlation with Monocytes; whereas, Hsp90aa1 was negatively correlated with NK Resting. Finally, five hub genes were validated by RT-qPCR, IHC and western blot. Mapk14, Hif1a, Myc, Hsp90ab1, and Hsp90aa1 are hub genes of HF and may play a critical role in the oxidative stress of HF. This study may provide new targets for the treatment of HF, and the potential immunotherapies are worthy of further study.

Project description:ObjectiveInflammation and immune cells are closely intertwined mechanisms that contribute to the progression of heart failure (HF). Nonetheless, there is a paucity of information regarding the distinct features of dysregulated immune cells and efficient diagnostic biomarkers linked with HF. This study aims to explore diagnostic biomarkers related to immune cells in HF to gain new insights into the underlying molecular mechanisms of HF and to provide novel perspectives for the detection and treatment of HF.MethodThe CIBERSORT method was employed to quantify 22 types of immune cells in HF and normal subjects from publicly available GEO databases (GSE3586, GSE42955, GSE57338, and GSE79962). Machine learning methods were utilized to screen for important cell types. Single-cell RNA sequencing (GSE145154) was further utilized to identify important cell types and hub genes. WGCNA was employed to screen for immune cell-related genes and ultimately diagnostic models were constructed and evaluated. To validate these predictive results, blood samples were collected from 40 normal controls and 40 HF patients for RT-qPCR analysis. Lastly, key cell clusters were divided into high and low biomarker expression groups to identify transcription factors that may affect biomarkers.ResultsThe study found a noticeable difference in immune environment between HF and normal subjects. Macrophages were identified as key immune cells by machine learning. Single-cell analysis further showed that macrophages differed dramatically between HF and normal subjects. This study revealed the existence of five subsets of macrophages that have different differentiation states. Based on module genes most relevant to macrophages, macrophage differentiation-related genes (MDRGs), and DEGs in HF and normal subjects from GEO datasets, four genes (CD163, RNASE2, LYVE1, and VSIG4) were identified as valid diagnostic markers for HF. Ultimately, a diagnostic model containing two hub genes was constructed and then validated with a validation dataset and clinical samples. In addition, key transcription factors driving or maintaining the biomarkers expression programs were identified.ConclusionThe analytical results and diagnostic model of this study can assist clinicians in identifying high-risk individuals, thereby aiding in guiding treatment decisions for patients with HF.

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VCAM1 expression in the myocardium is associated with the risk of heart failure and immune cell infiltration in myocardium.

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