Analysis of multiple transcriptome data to determine age-associated genes for the progression of Parkinson's disease

Abstract

Transcriptome data analysis between ageing Parkinson's disease and healthy individuals were conducted. Network-based approach and correlation measure were employed to find the significant genes followed by pathway enrichment analysis. Significant differentially expressed genes (DEGs) were identified using ANOVA from microarray datasets specifically sorted for substantia nigra pars compacta region of the brain and a protein-protein interaction network (DEGs-PPIN) was developed using HIPPIE database. The network was subdivided into two sub-networks; where the sub-network for control set was developed based on the gene pair having high correlation in healthy ageing and low or negative correlation in diseased condition and vice-a-versa for patient sub-network. 74 highly correlated gene pairs were identified for control sub-network and 191 pairs for patient, followed by pathway enrichment analysis. Here, we have discussed the role of specific genes along with their pathways, which were not reported earlier, thereby opening the vista for characterizing novel targets for PD.