Study of microarray data to identify putative risk genes in Parkinson’s disease

Abstract

This study focussed on identification of risk genes involved in PD.We used three methods namely WGCNA, DEGs Analysis and PPI to identify such important downregulated and upregulated genes. The three methods show high agreement with each other and also with the available biomedical literature on this neurodegenerative disease. In this study, 20 significantly (p-value) upregulated and 19 significantly (p-value) downregulated genes have been found to have notable contribution in the manifestation of motor and non motor symptoms of the disease as interpreted from the enrichment analysis. Gene expression dataset of Parkinson’s Disease (PD) obtained from the Gene Expression Omnibus (GEO), a free public functional genomics data repository of an array and sequence-based data. In this study, three gene expression profiles/datasets GSE8397, GSE20164, and GSE20295 are used, which are obtained using Affymetrix Human Genome U133A Array chip. This study shows a promise in identifying potential biomarkers that would enable in the early diagnosis of Parkinson’s Disease prior to the onset of disease symptoms.