Immuno-Metabolic Reprogramming in Metabolic Syndrome and Its Cardiovascular Complications: An Integrative Bioinformatics Study
Year: 2026
Type: article
Abstract: Background: Metabolic syndrome (MeS) is a multifactorial metabolic disorder characterized by obesity, dyslipidemia, insulin resistance, and hypertension, and is strongly associated with an increased risk of cardiovascular diseases (CVDs) and type-2 diabetes mellitus (T2DM)-related complications. Chronic low-grade inflammation and immune dysregulation are increasingly recognized as central contributors to metabolic and cardiovascular pathogenesis. However, the molecular mechanisms linking MeS-related etiologies to coronary artery disease (CAD) remain incompletely understood. The present study aimed to identify shared inflammatory and immuno-metabolic transcriptional signatures associated with MeS and its cardiovascular complications using an integrative bioinformatics approach. Methods: Three publicly available peripheral blood mononuclear cell (PBMC) microarray datasets from the Gene Expression Omnibus (GEO) database, including metabolic syndrome (GSE98895), recent-onset type 1 diabetes (GSE193273), and diabetes mellitus with coronary artery disease (GSE250283), were analyzed using R-based bioinformatics pipelines. Differentially expressed genes (DEGs) were identified using the limma package, followed by Gene Set Enrichment Analysis (GSEA) using MSigDB Gene Ontology Biological Process C5 gene sets. Shared DEGs were subjected to protein-protein interaction (PPI) network construction using STRING and Cytoscape http://www.cytoscape.org/. Hub genes were identified using the CytoHubba MCC algorithm, and associated miRNAs were predicted using miRNet. Functional enrichment analysis of candidate miRNAs was performed using TAM 2.0. Results: GSEA demonstrated prominent enrichment of inflammatory, immune-regulatory, cytokine-mediated, oxidative stress, and metabolic pathways across the datasets. T1D samples exhibited enrichment of interferon-mediated signaling, cytokine responses, and proliferative cellular programs. MeS samples showed activation of adaptive immune responses, leukocyte-mediated immunity, and inflammatory signaling pathways. DMCAD samples demonstrated strong enrichment of inflammatory cytokine production, oxidative phosphorylation, mitochondrial metabolism, reactive oxygen species pathways, and leukocyte activation. Comparative analysis identified 19 shared DEGs between MeS and DMCAD, including CXCL16, CCR1, FPR1, C5AR1, CD86, and TNFRSF21, which formed a significantly interconnected inflammatory interaction network. Functional enrichment analyses revealed enrichment of chemotaxis, complement signaling, immune receptor activity, interferon gamma response, inflammatory response, and IL6-JAK-STAT3 signaling pathways. miRNA interaction analysis identified candidate regulatory miRNAs, including miR-146a-5p, miR-21-5p, miR-155-5p, and members of the miR-17-92 cluster, which were enriched in inflammatory, cardiovascular, and metabolic disease-associated pathways. Conclusions: The present integrative bioinformatics analysis demonstrates that MeS and DMCAD share common inflammatory and immuno-metabolic transcriptional programs characterized by immune activation, cytokine signaling, oxidative stress, and vascular-inflammatory regulatory networks. The identified hub genes and candidate miRNAs may represent potential biomarkers and therapeutic targets associated with inflammation-driven cardiovascular complications in metabolic disorders.
DOI: 10.3390/ijms27135923
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,499
OpenAlex ID: W7166735514
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