In silico analysis of gene expression data from bald frontal and haired occipital scalp to identify candidate genes in male androgenetic alopecia.

Abstract

Androgenetic alopecia (AGA) is a progressive dermatological disorder of frontal and vertex scalp hair loss leading to baldness in men. This study aimed to identify candidate genes involved in AGA through an in silico search strategy. The gene expression profile GS36169, which contains microarray gene expression data from bald frontal and haired occipital scalps of five men with AGA, was downloaded from the Gene Expression Omnibus (GEO) database. The differential gene expression analysis for all five subjects was carried out separately by PUMA package in R and identified 32 differentially expressed genes (DEGs) common to all five subjects. Gene ontology (GO) biological process and pathway- enrichment analyses of the DEGs were conducted separately for the up-regulated and down-regulated genes. ReactomeFIViz app was utilized to construct the protein functional interaction network for the DEGs. Through GO biological process and pathway analysis on the clusters of the Reactome FI network, we found that the down-regulated DEGs participate in Wnt signaling, TGF-beta signaling, and up-regulated DEGs participate in oxidative-stress- related pathways.