ArticlePloS one2024
Role of immune-related endoplasmic reticulum stress genes in sepsis-induced cardiomyopathy: Novel insights from bioinformatics analysis.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe current study aims to elucidate the key molecular mechanisms linked to endoplasmic reticulum stress (ERS) in the pathogenesis of sepsis-induced cardiomyopathy (SIC) and offer innovative therapeutic targets for SIC.
methodsThe study downloaded dataset GSE79962 from the Gene Expression Omnibus database and acquired the ERS-related gene set from GeneCards. It utilized weighted gene co-expression network analysis (WGCNA) and conducted differential expression analysis to identify key modules and genes associated with SIC. The SIC hub genes were determined by the intersection of WGCNA-based hubs, DEGs, and ERS-related genes, followed by protein-protein interaction (PPI) network construction. Enrichment analyses, encompassing GO, KEGG, GSEA, and GSVA, were performed to elucidate potential biological pathways. The CIBERSORT algorithm was employed to analyze immune infiltration patterns. Diagnostic and prognostic models were developed to assess the clinical significance of hub genes in SIC. Additionally, in vivo experiments were conducted to validate the expression of hub genes.
resultsDifferential analysis revealed 1031 differentially expressed genes (DEGs), while WGCNA identified a hub module with 1327 key genes. Subsequently, 13 hub genes were pinpointed by intersecting with ERS-related genes. NOX4, PDHB, SCP2, ACTC1, DLAT, EDN1, and NSDHL emerged as hub ERS-related genes through the protein-protein interaction network, with their diagnostic values confirmed via ROC curves. Diagnostic models incorporating five genes (NOX4, PDHB, ACTC1, DLAT, NSDHL) were validated using the LASSO algorithm, highlighting only the prognostic significance of serum PDHB levels in predicting the survival of septic patients. Additionally, decreased PDHB mRNA and protein expression levels were observed in the cardiac tissue of septic mice compared to control mice.
conclusionsThis study elucidated the interplay between metabolism and the immune microenvironment in SIC, providing fresh perspectives on the investigation of potential SIC pathogenesis. PDHB emerged as a significant biomarker of SIC, with implications on its progression through the regulation of ERS and metabolism.
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