Lactate-Associated Gene Signatures as Predictors: A Comprehensive Analysis of Immune Profiles in Sepsis

Background Sepsis is a complex disorder characterized by a dysregulated immune response to infection. Elevated lactic acid levels and lactylation modification may induce changes in gene expression and immune cell infiltration in sepsis. Methods RNA-seq data and clinical information related to sepsis were obtained from GEO datasets. Differential expression analysis identified genes that are differentially expressed between sepsis patients and healthy controls. The lactylation-related genes were then integrated with the differential expressed genes to classify genes as Sepsis-related differentially expressed lactylation-related genes (Sepsis-DELRGs). Mendelian randomization analysis was performed to assess the causal relationship between Sepsis-DELRGs and the two groups. Machine learning algorithms predicted potential Sepsis-DELRGs, and immune infiltration analysis examined the relationships between these genes and immune cell types. Finally, we examined the expression of MDC1 and LYRM4 within the GSE131761 and GSE80496 datasets and in sepsis patients from our hospital. Results A total of 1356 differentially expressed genes were identified between sepsis patients and healthy controls. From these, 138 Sepsis-DELRGs associated with sepsis were isolated. Mendelian randomization identified LYRM4 and MDC1 as protective factors against sepsis. Both genes positively influence CD8 + T cells and negatively affect activated mast cells and neutrophils. The expression levels of LYRM4 and MDC1 in CD8 + T cells from sepsis patients were low. ROC curve analysis demonstrated that both genes have strong predictive power for sepsis onset. Conclusions LYRM4 and MDC1 could serve as potential biomarkers for differentiating sepsis patients from healthy individuals. Their functions are closely linked to changes in inflammatory cell populations in sepsis.