Identification of therapeutic targets for Alzheimer's disease via differentially expressed gene and weighted gene co-expression network analyses.

In order to investigate the pathogenic targets and associated biological process of Alzheimer's disease in the present study, mRNA expression profiles (GSE28146) and microRNA (miRNA) expression profiles (GSE16759) were downloaded from the Gene Expression Omnibus database. In GSE28146, eight control samples, and Alzheimer's disease samples comprising seven incipient, eight moderate, seven severe Alzheimer's disease samples, were included. The Affy package in R was used for background correction and normalization of the raw microarray data. The differentially expressed genes (DEGs) and differentially expressed miRNAs were identified using the Limma package. In addition, mRNAs were clustered using weighted gene correlation network analysis, and modules found to be significantly associated with the stages of Alzheimer's disease were screened out. The Database for Annotation, Visualization, and Integrated Discovery was used to perform Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. The target genes of the differentially expressed miRNAs were identified using the miRWalk database. Compared with the control samples, 175,59 genes and 90 DEGs were identified in the incipient, moderate and severe Alzheimer's disease samples, respectively. A module, which contained 1,592 genes was found to be closely associated with the stage of Alzheimer's disease and biological processes. In addition, pathways associated with Alzheimer's disease and other neurological diseases were found to be enriched in those genes. A total of 139 overlapped genes were identified between those genes and the DEGs in the three groups. From the miRNA expression profiles, 189 miRNAs were found differentially expressed in the samples from patients with Alzheimer's disease and 1,647 target genes were obtained. In addition, five overlapped genes were identified between those 1,647 target genes and the 139 genes, and these genes may be important pathogenic targets for Alzheimer's disease. Through bioinformatics analysis, potential therapeutic targets and associated biological processes were identified, which may assist in understanding and treatment of Alzheimer's disease.