Integrative Analysis Identifies Lactylation-Associated Hub Genes in Septic Cardiomyopathy

Septic Cardiomyopathy (SCM) is a critical complication contributing to high mortality in septic patients, yet its precise molecular mechanisms remain incompletely elucidated.

Publicly available human transcriptomic data for SCM were obtained from the Gene Expression Omnibus (GEO) database (GSE79962). Our integrated analytical workflow consisted of several steps. First, Weighted Gene Co-expression Network Analysis (WGCNA) pinpointed key co-expression modules. Subsequently, a consensus approach combining three machine learning algorithms, Boruta, Random Forest (RF), and Support Vector Machine-Recursive Feature Elimination (SVM-RFE), was used to screen for hub genes. The diagnostic potential of these genes was then assessed using Receiver Operating Characteristic (ROC) curves. Further investigations included functional pathway enrichment via Gene Set Enrichment Analysis (GSEA), immune infiltration profiling with CIBERSORT, and the construction of a Protein-Protein Interaction (PPI) network using the STRING database. To validate the bioinformatic findings, key results were experimentally confirmed in a lipopolysaccharide (LPS)-induced septic mouse model.

Our analysis identified three hub genes (GADD45B, STAT3, SLC7A5) that were significantly dysregulated in SCM. These genes demonstrated exceptional diagnostic power, with area under the curve (AUC) values exceeding 0.95. GSEA indicated a pronounced activation of innate immune and inflammatory pathways. Concurrently, we observed a sustained suppression of critical cardiac energy metabolic pathways. The hub genes were also closely linked to the cS-STING signaling pathway. Their expression levels showed significant correlations with the infiltration of specific immune cell subsets, including resting NK cells, M0 and M2 macrophages, and resting CD4+ memory T cells.Critically, the dysregulation of these hub genes was successfully corroborated in heart tissues from the LPS-induced mouse model.

This study, through integrated bioinformatics and initial experimental validation, identifies GADD45B, STAT3, and SLC7A5 as central hub genes in SCM and proposes their potential regulation by lactylation as a novel hypothesis for future mechanistic investigation.