A graph-clustering approach to search important molecular markers and pathways of Parkinson’s disease

Abstract

Parkinson disease is the second most common neurodegenerative disorder. Therefore, it is worthwhile to search for important molecular markers and pathways that hold great promise for further treatment of patients with Parkinson’s disease. DNA-microarray-based technologies allow simultaneous analysis of expression of thousands of genes. Here, we performed a comprehensive gene level assessment of Parkinson’s disease using 16 colorectal cancer samples and nine normal samples. The results show that SLC6A3, SLC18A2, and EN1, etc., are related to Parkinson’s disease. Besides, we further mined the underlying molecular mechanism within these different genes. The results indicate that tyrosine metabolism pathway and Parkinson's disease pathway were two significant pathways, with hope to provide insights into the development of novel therapeutic targets and pathways. Key words: Microarrays, graph-cluster, Parkinson’s disease, gene ontology (GO), pathway.