Exploring the Potential Value of Lactylation and Macrophage Polarization-Related Genes as Biomarkers for TNF-α Inhibitor Response in Inflammatory Bowel Disease.

Background: Lactylation has emerged as a novel post-translational modification, and genes linked to both lactylation and macrophage polarization may play a role in inflammatory bowel disease (IBD). However, the connection between these genes and TNF-α inhibitor response in IBD remained unclear. Methods: This study used bioinformatic tools including weighted gene co-expression network analysis (WGCNA), immune infiltration analysis, and machine learning algorithms to identify correlations between lactylation and macrophage-related genes and TNF-α inhibitor response in IBD. Results: Significant differential expression of MNDA, CALD1, RECQL, and RBM10 was identified between the remission and non-remission groups in the pre-treatment data. Based on these findings, we established a predictive model for TNF-α inhibitor response, achieving an ROC performance with training AUC reaching 0.894 and validation AUC reaching 0.883. Furthermore, MNDA, LGALS1, ZYX, ADAR, and WAS were significantly elevated in the non-remission group 4-6 weeks after initial treatment. Immune infiltration analysis further indicated strong correlations between hub genes expression and immune cell proportions. In addition, GSEA identified signaling pathways associated with TNF-α inhibitor response. To validate these observations, TNF-α inhibitor was administered to mice with TNBS-induced colitis, and the expression of hub genes was confirmed by RT-qPCR. Importantly, combination therapy with lactate supplementation enhanced the efficacy of TNF-α inhibitor treatment compared with monotherapy. Finally, analysis of lactylation levels indicated intergroup differences associated with TNF-α inhibitor treatment in IBD. Conclusion: Overall, we identified lactylation and macrophage-related genes as potential biomarkers for TNF-α inhibitor response. Lactate supplementation was found to enhance the efficacy of TNF-α inhibitor based on animal experimental validation. Nevertheless, the findings were based on secondary analyses of public datasets, and the animal experiments remained preliminary. Further studies should be conducted to validate these findings and explore the molecular pathways involved.