Abstract
The present bioinformatics analysis was performed using a multi‑step approach to identify a microRNA (miR)‑mRNA regulatory network in Down syndrome. miR (GSE69210) and mRNA (GSE70573) data was downloaded and collected from the thymic tissues of both Down syndrome and karyotypically normal subjects and placed in a public repository. Then, weighted gene co‑expression network analysis (WGCNA) was performed to screen for miRs and mRNAs associated with Down syndrome. Subsequently, differentially expressed miRs (DEmiRs) and mRNAs/differentially expressed genes (DEGs) were identified following screening and mapping to RNA data. Bidirectional hierarchical clustering analysis was then performed to distinguish DEmiRs and DEGs between Down syndrome samples and normal control samples. DEmiR targets were retrieved using the miRanda database and mapped to the mRNA module screen by WGCNA. A gene co‑expression network was constructed and subjected to functional enrichment analysis. During WGCNA, a total of 6 miR modules and 20 mRNA modules associated with Down syndrome were identified. Following mapping of these miRs and mRNAs to the miR and mRNA modules screened using WGNCA, a total of 12 DEmiRs and 237 DEGs were collected. Following comparison with DEmiR targets retrieved from the miRanda database, a total of 255 DEmiR‑DEG pairs, including 6 DEmiRs and 106 DEGs were obtained. At expression correlation coefficient >0.9, a total of 231 gene pairs were selected. These gene pairs were enriched in response to stress and response to stimuli following functional annotation and module division. An integrated analysis of miR and mRNA expression in the thymus in Down syndrome is reported in the present study. miR‑30c, miR‑145, miR‑183 and their targets may serve important roles in the pathogenesis and development of complications in Down syndrome. However, further experimental studies are required to verify these results.