Multi-omics analysis reveals the genetic aging landscape of Parkinson's disease

Parkinson's disease (PD) is the second most common age-related neurodegenerative disease after Alzheimer's disease. Despite numerous studies, specific age-related factors remain unidentified. This study employed a multi-omics approach to investigate the link between PD and aging. We integrated blood gene expression profiles, expression quantitative trait loci, genome-wide association studies, predictive models, and conducted clinical validation.By analyzing PD datasets, a total of 953 differentially expressed genes (DEGs) and 10 intersecting aging differentially expressed genes (ADEGs) were identified. Enrichment analysis revealed that the regulatory pathways of these ADEGs involve the classical Wnt signaling pathway, endoplasmic reticulum stress, and neuronal apoptosis. Mendelian randomization (MR) analysis showed that the MAP3K5 gene significantly reduces the risk of PD. Multivariate regression analysis identified MXD1, CREB1, and SIRT3 as key diagnostic genes and constructed a predictive model to aid clinical decision-making. Enzyme-linked immunosorbent assay experiments validated the expression levels of these genes in the serum of PD patients.This study utilized a multi-omics approach to identify key ADEGs and their regulatory mechanisms in PD, leading to the establishment of a diagnostic model. The resource is accessible at this link: https://yunhaihupo.shinyapps.io/DynNomapp. This web application can be used as a standalone resource to explore changes in blood transcription profiles in PD and their relationship to clinical and aging aspects, generating new research hypotheses.