Identification of Key Lactylation‐Related Genes and Their Relevance to the Connection Between Parkinson's Disease and the Immune System Through Integrated Bioinformatics Analysis

Parkinson's disease (PD) is a complex neurodegenerative disorder with a growing body of evidence suggesting the involvement of immune responses. To better understand the interplay between lactylation-related genes and immune reactions in PD, we conducted an integrated bioinformatics analysis. Utilizing publicly available PD gene expression datasets, we performed a detailed analysis employing Single-sample Gene Set Enrichment Analysis and Weighted Gene Co-expression Network Analysis. Diagnostic models were constructed using Support Vector Machine (SVM) and LASSO+SVM to evaluate the performance of four candidate genes (PAK6, LMO3, SPTBN2, FA2H). We also investigated the correlations between these genes and immune cells to elucidate their roles in the immune microenvironment. Animal models and immunohistochemistry were used to validate the findings. Our analysis revealed that differentially expressed genes (DEGs) were primarily enriched in pathways associated with neurological diseases, such as Alzheimer's disease and Huntington's disease. Among the four candidate genes, PAK6 exhibited the best predictive performance. Significant correlations were found between these genes and "resting memory CD4 T cells," highlighting their potential involvement in the immune microenvironment. This study provides new insights into the roles of lactylation-related genes, specifically those involved in the biochemical process of lactylation, particularly PAK6, in the context of immune responses in PD. While our pathway enrichment analysis highlights commonalities with other neurodegenerative diseases, our focus on lactylation-related genes offers novel perspectives on how these genes might influence immune regulation in PD. The findings suggest potential therapeutic targets and open avenues for future research into the mechanisms underlying PD and its immune interactions.