Exploration of potential therapeutic targets for stroke based on the GEO database

BACKGROUND: This study aimed to analyze non-coding RNA sequencing results, screen differentially expressed long non-coding RNAs (lncRNAs), and predict lncRNA target genes. It further clarifies the potential functions of lncRNAs, thus exploring potential biomarkers and therapeutic targets for stroke. METHODS: LncRNA sequencing data of blood samples from stroke patients and healthy subjects (GSE102541 and GSE140275) were downloaded from the Gene Expression Omnibus (GEO) database. This study used R software and related R packages to conduct a batch correction and differential analysis of sequencing results. It also screened differentially expressed lncRNAs and visualized the correlations between significantly different lncRNAs. Target genes of differential lncRNAs were predicted by the StarBase database. Gene ontology (GO) functional enrichment analysis of related target genes was performed using the DAVID database. Principal component analysis was performed based on the expression levels of lncRNAs with the most significant differences in stroke blood samples. RESULTS: A total of 239 differentially expressed lncRNAs were screened out in this study, of which 146 were upregulated and 93 were downregulated. According to |log2FC| values from highest to lowest, the top 10 lncRNAs with the most significant differences were selected. The upregulated lncRNAs were LINC02334, TARID, MRGPRF-AS1, CAI2, LINC00189, TUG1, and RNF5P1. The downregulated lncRNAs included AC005180.2, ADAMTS9-AS1, and AC036108.3. TARID was strongly correlated with MRGPRF-AS1. Meanwhile, LINC02334 was strongly correlated with TUG1. CAI2, LINC00189, and RNF5P1 were at the core of the correlation network and may therefore be the critical lncRNAs in stroke pathogenesis. GO functional enrichment results indicated that genes were significantly enriched in muscle contraction, RNA polymerase II promoter transcription regulation, muscle structure composition, focal adhesion, endothelial cell chemotaxis, actin, actin cytoskeleton, actin filament binding, blood lipid regulation, smooth muscle contraction regulation, skeletal muscle cell differentiation, and other functions. Principal component analysis showed that the 10 lncRNAs with significant differences could significantly distinguish stroke blood samples from healthy control blood samples, and could characterize the essential characteristics of stroke. CONCLUSIONS: LINC02334, TARID, MRGPRF-AS1, CAI2, LINC00189, TUG1, RNF5P1, AC005180.2, ADAMTS9-AS1, and AC036108.3 play an essential role in the pathogenesis of stroke, and may be potential therapeutic targets.