Integrated multi-omics profiling of the early post-infarct heart reveals a hub gene network associated with myeloid-driven inflammation

S100A8/S100A9 Links Diabetic Stress to Cardiac Progenitor Cell Dysfunction and Fibrotic Heart Failure: An Integrated Transcriptomic, Single‐Cell, and Functional Study

Background Diabetes markedly increases the risk of heart failure, yet the molecular signals connecting metabolic stress, myocardial fibrosis, and impaired cardiac repair remain incompletely understood. Methods We integrated bulk transcriptomic data from postischemic hearts (GSE26887), fibrosis‐related genes from the CTD database, protein–protein interaction (PPI) analysis, and pathway enrichment (GO, KEGG, GSEA, and GSVA) to identify candidate mediators in diabetic versus nondiabetic heart failure. Single‐cell RNA‐sequencing datasets were analyzed with Seurat to map the cellular distribution of key genes. Pan‐cancer analyses using TCGA cohorts were performed to evaluate prognostic, immune, and tumor mutation burden (TMB) correlations. Mechanistic validation was conducted in human cardiac progenitor cells (CPCs) exposed to normoglycemia or high glucose with S100A9 knockdown or overexpression, recombinant S100A8/A9, and a neutralizing S100A9 antibody. Cell viability (CCK‐8); qPCR panels for fibrosis, inflammation, and metabolic genes; ROS production (DCF‐DA and MitoSOX); and mitochondrial respiration were quantified. Results Differential expression and PPI network analyses identified S100A8 as a fibrosis‐related hub specifically enriched in diabetic heart failure. Single‐cell mapping revealed predominant S100A8 expression in CPCs rather than mature cardiomyocytes. Pathway analyses linked S100A8 to collagen fibril organization, ECM–receptor interaction, oxidative phosphorylation, and fatty acid β‐oxidation. Functionally, high glucose upregulated S100A8/S100A9 and profibrotic and proinflammatory genes in CPCs, increased total and mitochondrial ROS, and reduced basal, ATP‐linked, and maximal respiration and spare capacity. S100A9 knockdown partially restored CPC proliferation, redox balance, and mitochondrial function, whereas S100A9 overexpression or recombinant S100A8/A9 further exacerbated oxidative stress and bioenergetic failure; S100A9 neutralization attenuated these effects. Pan‐cancer analyses showed that high S100A8 expression was associated with adverse prognosis, altered immune infiltration, and increased TMB in several TCGA cohorts. Conclusions S100A8/S100A9 emerges as a central mediator linking hyperglycemia‐induced oxidative stress, metabolic inflexibility, and fibrotic reprogramming of CPCs, thereby promoting diabetic heart failure. S100A8/S100A9 may serve as a biomarker and therapeutic target at the interface of immunometabolism, cardiac regeneration, and cardio‐oncology.

Multi-layer network biology combined with single-cell evidence reveals core regulatory nodes in atherosclerotic plaques and potential drug-targeting directions.

Shared immune signatures in acute myocardial infarction and periodontitis: the role of FCN1 and LYN as potential biomarkers

Integrated Bulk and Single-Cell Transcriptomic Analyses Identify a FOLR2+ Tissue-Resident Macrophage-Associated Lysophagy Gene Module in Heart Failure

Objectives: Heart failure (HF) arises from multiple interrelated pathological processes. Among these, lysosomal impairment and loss of autophagic homeostasis are increasingly recognized as important contributors to myocardial damage and ventricular remodeling. This study sought to identify lysophagy-associated signature genes in HF and to define their biological roles, cellular origins, and potential diagnostic relevance. Methods: Bulk myocardial transcriptome datasets, including GSE16499, GSE57338, and GSE76701, were integrated with the human cardiac single-cell dataset GSE145154. Differential expression analysis was first performed to identify lysophagy-related differentially expressed genes (DEGs). Candidate hub genes were then screened using support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression. Functional enrichment analysis, Gene Set Enrichment Analysis (GSEA), immune infiltration assessment, single-cell transcriptomic mapping, and regulatory network analysis were subsequently conducted. The expression profiles of the selected genes were validated in a murine HF model, and VAMP8 overexpression assays were performed in H9c2 cells. Results: Five hub genes, namely VAMP8, STX2, MCOLN1, DERL1, and PTP4A2, were consistently and markedly decreased in failing myocardial tissue. These genes were mainly linked to SNARE-dependent vesicle trafficking and lysophagy regulation. A diagnostic model incorporating these hub genes demonstrated good discriminatory performance in both the training dataset and a small independent validation cohort, supporting further evaluation of their potential diagnostic value. Single-cell analysis further indicated that these genes were primarily enriched in cardiac FOLR2+ tissue-resident macrophages (TRMs). Pseudotime and cell–cell communication analyses associated this module with FOLR2+ TRM cell states and predicted interactions with cardiac stromal cells. In the HF mouse model, the mRNA levels of all five hub genes were decreased, with concurrent reductions in VAMP8, MCOLN1 and DERL1 protein expression. In Ang II/LLOMe-induced H9c2 cells, VAMP8 overexpression was associated with reduced cardiomyocyte injury, attenuation of changes in the abundance of lysosome- and autophagy-related proteins, and fewer ultrastructural abnormalities, suggesting a potential cardioprotective effect. Conclusions: VAMP8, STX2, MCOLN1, DERL1, and PTP4A2 were identified as candidate molecular markers of HF that reflect alterations in a lysophagy- and vesicular-transport-related program associated with FOLR2+ tissue-resident macrophages. These findings provide new insights into immune-microenvironment remodeling in HF and suggest potential directions for mechanistic and therapeutic investigations.

Integrated Bioinformatics and Experimental Validation of Post-Translational Modification-Related Biomarkers in Myocardial Ischemia-Reperfusion Injury

Integrating Bulk and Single-Cell RNA Sequencing Identifies and Validates Lactylation-Related Signatures in Acute Kidney Injury

Background: Acute kidney injury (AKI) is a severe clinical syndrome characterized by metabolic stress and profound inflammation. However, the landscape of lactylation-associated molecular alterations and their potential relevance in AKI remain incompletely understood. Methods: Bulk transcriptomes (GSE30718) were analyzed using the limma package, weighted gene co-expression network analysis (WGCNA), and consensus clustering to characterize AKI-associated molecular patterns linked to lactylation-associated signatures. Hub genes, prioritized through least absolute shrinkage and selection operator (LASSO) regression and the random forest algorithm, were integrated into a diagnostic nomogram and evaluated in an external cohort (GSE139061). Immune infiltration analysis was performed, and single-cell RNA sequencing data (GSE183276) were used to resolve cell-type-specific expression patterns of the hub genes. A cisplatin-induced murine AKI model validated global protein lactylation and hub gene expression by immunohistochemistry and Western blot. Results: Three hub genes (CKLF, ACLY, and SLC13A3) reliably discriminated AKI from controls (training AUC = 0.897). Their diagnostic performance varied in the external validation cohort. These genes correlated significantly with diverse immune infiltrates. Single-cell analysis localized CKLF predominantly to immune cells, ACLY broadly across renal populations, and SLC13A3 to proximal tubules. In vivo validation demonstrated increased global protein lysine lactylation levels in injured kidneys and confirmed expression alterations of CKLF, ACLY, and SLC13A3 consistent with transcriptomic observations. Conclusions: Integrating transcriptomic analysis with in vivo experimental validation, this study identified CKLF, ACLY, and SLC13A3 as candidate lactylation-associated signatures linked to immune and metabolic alterations in AKI.