Identification of a lncRNA/circRNA-miRNA-mRNA ceRNA Network in Alzheimer's Disease

Background: Alzheimer's disease (AD) occurs in the elderly and pre-elderly, characterized by decline of memory, cognitive dysfunction, impairment of learning capacity, and motor dysfunction. Recently a competitive endogenous RNA (ceRNA) network has been found to be related to AD progression, but there is still little understanding of the ceRNA regulatory network in AD. This study aims to explore the important regulatory mechanisms of ceRNA regulatory networks containing long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) in AD. Methods: Data from the gene expression omnibus (GEO) database were used for the analysis. To study enrichment function for the upregulated and downregulated mRNAs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using the Metascape database, respectively. Based on the STRING database and Cytoscape software 3.9.1, a protein-protein interaction (PPI) network was constructed. The hub genes in this network were identified utilizing the CytoHubba plugin in Cytoscape. The TargetScan, miRWalk, and miRDB were selected to calculate the regulatory interaction between miRNAs and the hub genes. LncRNAs were predicted using RNA22. Additionally, circRNA prediction was executed using the circBank database. Results: 711 downregulated and 670 upregulated overlapping mRNAs were identified between AD and control samples. 32 downregulated and 340 upregulated miRNAs were obtained from AD samples compared with control samples. 78 upregulated and 205 downregulated circRNAs were screened. 275 upregulated lncRNAs and 209 downregulated lncRNAs were found between AD samples and control samples. The PPI network constructed consists of 1016 nodes and 13,946 edges. Ten hub genes were selected to identify target miRNAs and ceRNAs. On the basis of the ceRNA hypothesis, a circRNA/lncRNA-miRNA-mRNA network was established. It included five lncRNAs (TRHDE-AS1, SNHG10, OIP5-AS, LINC00926 and LINC00662), 26 circRNAs, five miRNAs (hsa-miR-3158-3p, hsa-miR-4435, hsa-let-7d-3p, hsa-miR-330-5p and hsa-miR-3605-3p), and ten mRNAs (RPL11, RPL34, RPL21, RPL22, RPL6, RPL32, RPL24, RPL35, RPL31, and RPL35A). RPL35 and RPL35A were found to be significantly associated with AD pathology in tau and Aβ line AD models by the AlzData database. The study discovered the significance of several lncRNA-miRNA-mRNA axes and circRNA-miRNA-mRNA axes that included RPL35A and RPL35. Conclusions: ceRNAs were found to be important regulators in the development of AD and provide potential biological therapy targets for AD management.