Parkinson's disease (PD) is a widespread neurodegenerative condition [1]
however, its association with glycolysis, specifically the activity of genes related to glycolysis, has not yet been explored. We downloaded 3 datasets related to PD from the GEO database and identified the glycolytic genes related to PD. Subsequently, GO and KEGG enrichment analyses were conducted. We constructed a PD diagnosis model using the SVM algorithm for differentially expressed glycolysis-related genes and verified the model with LASSO regression analysis. Next, we constructed a regulatory network of genes that were differentially expressed with respect to glycolysis. Finally, the amount of immune cell infiltration was analyzed in PD samples, and the correlation between differential genes and immune cells was calculated. A total of 64 differentially expressed glycolytic genes associated with PD were screened. Then, a GO analysis was conducted, followed by KEGG and GASE enrichment analyses. Within the established PD diagnostic model, 26 genes that were differentially expressed and linked to glycolysis showed strong statistical significance. After further screening, a diagnostic model for PD including seven key genes was established. Further analysis showed that ABHD5 most strongly correlated with neutrophils (r = 0.507). The key gene SMAD3 was strongly negatively associated with gamma delta T cells (r = -0.488). This research offered a theoretical foundation for the association between glycolysis and PD. Seven glycolytic genes were identified as significantly linked to PD and warrant additional research.