Identification of Blood Based biomarker for Huntington's disease using in-silico gene expression analysis

Abstract

Huntingtons disease (HD) is an autosomal dominant neurodegenerative disorder with profound phenotypic characters. HD is at present incurable and there are several trials going on to find a cure. HD is caused when there is a mutation in the Huntingtin gene which is found to be associated with axonal transport. Diagnosis is based on the signs and symptoms of the patients but by that time the psychomotor problems have already reached the level from where reversing the disease is impossible. Blood based biomarkers can be used for the diagnosis of the disease at an early stage. In this study several gene expression study data were analyzed and there were 329 Differentially Expressed Genes (DEGs) in all the three chosen datasets. Protein protein interaction network was created using STRING and CytoHubba plug-in was used to identify top ten hub genes which are CXCL8, PSMC6, UBE2D1, UBE2D1, CD27, UBE2D3, SF3B1, CASP3, EIF4E, BIRC2 and PTEN. Online software Enrichr was used for Gene Ontology and KEGG pathway enrichment analysis to find out the biological process, molecular function, cellular component and the pathways that were enriched in HD. This study finds out that those genes which were present in all the three datasets namely FNDC3A, BCLAF1 and ALCAM were not the hub genes. So further studies are required for identifying a potential biomarker of HD.