Abstract
Parkinson’s disease (PD) is a progressive neurodegenerative disorder, in which ferroptosis and dysregulation of lipid metabolism are believed to play critical roles. However, the key genes and molecular mechanisms underlying these processes remain to be fully elucidated. We combined bioinformatics analyses with experimental validation to identify and characterize central genes involved in ferroptosis and lipid metabolism in PD. Integrated bioinformatics analysis identified 44 candidate genes associated with ferroptosis and lipid metabolism in PD. Machine learning refined these to three core genes: CBS, PRKAR2B, and RELA. Expression analysis revealed significant upregulation of CBS and RELA and downregulation of PRKAR2B in PD samples. Receiver Operating Characteristic (ROC) analysis indicated strong diagnostic potential for all three genes. Functional enrichment suggested their involvement in neuroinflammation, energy metabolism, and neuroprotective pathways. Immune infiltration analysis revealed significant correlations between these genes and specific immune cell types. In cellular models, knockdown of RELA attenuated MPP(+)-induced oxidative stress, ferroptosis, and inflammatory activation, while also restoring dopaminergic neuronal function. ELISA results from PD patient cerebrospinal fluid (CSF) samples further confirmed the dysregulation of these genes, supporting their clinical relevance. This study identifies CBS, PRKAR2B, and RELA as key genes linking ferroptosis and lipid metabolism in Parkinson’s disease. These genes demonstrate strong diagnostic value and are closely associated with neuroinflammation and immune responses. Experimental validation underscores the protective effect of RELA knockdown against ferroptosis and inflammatory damage. Our findings suggest that RELA(p65) may serve as a promising diagnostic biomarker and therapeutic target for PD.