A computational approach to study age-related modifications of the genes involved in Parkinson's disease

Aging represents a relevant contributing factor to the development of diseases, in-cluding Parkinson's Disease (PD). Recent researchs on the origin of PD underscored the significant role of genomic and proteomic approaches in examining molecular alterations in the brains. Specifically, the shifts in gene expression patterns asso-ciated with processes like neuroinflammation, oxidative damage, and mitochondrial impairments have been observed. Nevertheless, the intricate connections between aging and this neurodegenerative condition remain partially understood. Recognizing that pinpointing specific genes and pathways involved in this pro-cess could transform these discoveries into potential treatments, we have devised a network-based strategy to explore how baseline gene expression in brain tissues af-fected by PD evolves with age. For this purpose, data on genes and their expression levels were obtained from the Gene4PD and GTEx databases, allowing us to create distinct gene expression datasets for each brain tissue type across six age groups. In detail, we identified a set of genes exhibiting significant expression changes in certain tissues over time. Additionally, we constructed a related set of protein interaction networks corresponding based on these tissues and age groups. Results revealed six genes with age-dependent expression variations across four brain regions, suggesting their potential involvement in PD progression. Further findings suggest that both age and sex may impact the likelihood of developing PD, emphasizing the need for more studies to unravel the biological mechanisms that contribute to the increased risk of PD associated with aging.