Identification of differentially expressed hub genes in Alzheimer’s disease using microarray dataset

Abstract

An important factor that leads to the progression of Alzheimer’s disease is the amyloid-β peptide. Improper degradation of such molecules accompanied by reduced synaptic signaling contributes to the disease. Thus, a critical understanding of proteins interacting in peptide degradation, synaptic transmission and cognition is important to understand the disease progression. In this study, a dataset from public databases was taken and differential gene expression analysis was implemented along with network construction and gene ontology. This gives us more insights into the various biological parameters that are affected and their genetic basis to understand the disease. With a cut-off in adj P-value and log 2-fold change, differentially expressed (DEG) were identified using R. The enrichment analysis resulted in three hub genes which are SST, GFAP and GABRD. These genes have been found to dysregulate crucial processes in Alzheimer’s disease etiology. These three genes are the main drivers of disease and targeting them could essentially reduce disease progression. These could also be used as markers to identify the disease and can be used in diagnostics.