Exploring the Association Between Rheumatoid Arthritis and Parkinson's Disease: Evidence from 2001-2016 NHANES,...

Parkinson's disease (PD) and rheumatoid arthritis (RA) are two common chronic diseases, but the potential links between them and the common molecular mechanisms remain largely unknown. The purpose of this study was to explore the potential association and common genetic signatures between RA and PD.

Based on the data from NHANES 2001-2016 (n=27,215) and real-world clinical setting (n=209), logistic regression analysis was used to evaluate the association between PD and RA. Subsequently, the potential molecular mechanisms linking between PD and RA were explored based on transcriptomic data.

Based on data from NHANES and real-world clinical settings, this study confirmed that RA was significantly associated with an increased risk of PD. Based on the transcriptome data, 79 common DEGs and three key genes (GNB2L1, HSPA9, RPA1) were identified. Functional enrichment analysis revealed that common DEGs were significantly enriched in multiple immune-related biological pathways, activation of innate immune response, T cell receptor signaling pathway, and PI3K-Akt signaling pathway. Based on GSVA and GSEA analysis, this study also identified three signaling pathways (MTORC1_SIGNALING, OXIDATIVE_PHOSPHORYLATION and MYC_TARGETS_V1) that may play a key role in the occurrence and development of PD and RA, and are regulated by GNB2L1, HSPA9 and RPA1. Regulatory network analysis identified key miRNAs (for example, hsa-miR-143-3p, hsa-miR-128-3p) and TFs (for example, MYB) that may coregulate these key genes. The nomogram model constructed based on these genes showed favorable predictive performance for both disease.

The results of this study showed a significant association between PD and RA. Furthermore, it was revealed that GNB2L1, HSPA9, and RPA1 may have complex regulatory mechanisms in PD and RA, providing new insights into the common molecular basis and therapeutic targets of these two different diseases. Notably, these associative findings from epidemiological and transcriptomic analyses require further experimental validation.