A Systems Biology Approach to Identifying Genetic Markers that Link Progression of Parkinson’s Disease to Risk Factors related to Ageing, Lifestyle and Type 2 Diabetes

Abstract

The processes that underlie Parkinsons disease (PD) are still unclear, but improved comprehension of genetic and environmental influences on PD, and how these influences interact will help find new approaches to reducing PD progression. We thus employed quantitative framework analysis to reveal some of the complex relationship of various genetic factors affecting PD. In this study, we analyzed gene expression microarray data from cells and tissues affected by PD, ageing (AG), type II diabetes (T2D), high body fat (HBF) and control datasets. We determined genetic associations of PD and these risk factors based on neighborhood-based benchmarking and multilayer network topology. We first identified 1343 significantly dysregulated genes in the PD patient tissues compared to healthy control, including we have 779 genes with down regulated expression and 544 genes up regulated. 45 genes were highly expressed in both for the PD and ageing; the number of shared genes for the PD and the type II diabetes is 51. Ontological and pathway analyses then identified significant gene ontology and molecular pathways that enhance our understanding of the fundamental molecular procedure of the PD progression. Therapeutic targets of the PD could be developed using these identified target genes, ontologies and pathways.