Co-expression Network Analysis of Down's Syndrome Based on Microarray Data

Down's syndrome (DS) is a type of chromosome disease. The present study aimed to explore the underlying molecular mechanisms of DS. GSE5390 microarray data downloaded from the gene expression omnibus database was used to identify differentially expressed genes (DEGs) in DS. Pathway enrichment analysis of the DEGs was performed, followed by co-expression network construction. Significant differential modules were mined by mutual information, followed by functional analysis. The accuracy of sample classification for the significant differential modules of DEGs was evaluated by leave-one-out cross-validation. A total of 997 DEGs, including 638 upregulated and 359 downregulated genes, were identified. Upregulated DEGs were enriched in 15 pathways, such as cell adhesion molecules, whereas downregulated DEGs were enriched in maturity onset diabetes of the young. Three significant differential modules with the highest discriminative scores (mutual information>0.35) were selected from a co-expression network. The classification accuracy of GSE16677 expression profile samples was 54.55% and 72.73% when characterized by 12 DEGs and 3 significant differential modules, respectively. Genes in significant differential modules were significantly enriched in 5 functions, including the endoplasmic reticulum (P=0.018) and regulation of apoptosis (P=0.061). The identified DEGs, in particular the 12 DEGs in the significant differential modules, such as B-cell lymphoma 2-associated transcription factor 1, heat shock protein 90 kDa beta member 1, UBX domain-containing protein 2 and transmembrane protein 50B, may serve important roles in the pathogenesis of DS.