@article{Chen_Wang_Na_Yu_Sui_Cui_Wang_2022, title={Bioinformatic Prediction of Depression-Related Signaling Pathways Regulated by miR-146a in Peripheral Blood of Patients with Post-Stroke Depression: Depression-Related Signaling Pathways Regulated by miR-146a}, volume={68}, url={https://cellmolbiol.org/index.php/CMB/article/view/4423}, DOI={10.14715/cmb/2022.68.6.7}, abstractNote={<p>It was aimed to explore the differential expression of miR-146a-5p in peripheral blood of patients with post-stroke depression (PSD), and to analyze its mechanism using bioinformatics. Stroke patients were selected as the research objects, and were divided into PSD ones and non-post-stroke depression (N-PSD) ones with the National Institutes of Health stroke scale (NHISS) and Hamilton Depression Scale-17 terms (HAMD-17) scores. Peripheral blood of patients was collected for serum miR-146a-5p detection. Targetscan7.1, miRDB, DIANA TOOLS, and more databases were used to predict the target genes of miR-146a-5p. String11.0 was applied to construct a protein interaction network, and GO and KEGG pathway enrichment analysis of target genes was performed. Compared with that of N-PSD patients, serum miR-146a-5p levels in PSD patients were significantly increased (<em>P</em><0.05). The receiver operator characteristic (ROC) curve suggested that the sensitivity and specificity of miR-146a-5p in predicting PSD were 0.703 and 0.811, respectively. The human miR-146a-5p sequence was highly conserved, with a total of 43 target genes. It involved analysis of activity, signaling pathways, and transcriptional regulation, as well as related signaling pathways such as Toll-like receptors (TLR), neurotrophic factors, and nuclear factor kappa-B (NF-κB). In conclusion, the expression level of miR-146a-5p was abnormally increased in PSD patients, and it could be taken as a candidate marker for the diagnosis of PSD. miR-146a-5p could affect PSD through signaling pathways of TLRs, neurotrophic factors, and NF-κB.</p>}, number={6}, journal={Cellular and Molecular Biology}, author={Chen, Zhimin and Wang, Na and Na, Risu and Yu, Haiyan and Sui, Dan and Cui, Bing and Wang, Lihua}, year={2022}, month={Jun.}, pages={40–47} }