This study aimed to identify potential miRNAs highly associated with the response to brain ischemic stroke. The miRNAs microarray expression profiles data were downloaded from Gene Expression Omnibus database under accession number GSE51586, including three ischemia and three ipsilateral normal samples from mouse brain tissues. Limma package was used to identify differentially expressed miRNAs between ischemia and ipsilateral normal samples. The common target genes of miRNA predicted from TargetScan, PicTar, miRanda and DIANA-microT databases were used as the candidate subset in which functional modules were identified by performing gene ontology enrichment analysis using ClusterProfile. Finally, the miRNA functional synergistic network was constructed by assembling all miRNA synergistic pairs. Fifty-one differentially expressed miRNAs were identified between ischemia and ipsilateral normal samples, including 32 up- and 19 down-regulated miRNAs. Among them, 24 miRNAs can commonly regulate at least one target gene and thus were used to construct a network, which included 274 pairs of co-regulating miRNAs. Further, 242 pairs of miRNAs interaction involving 23 miRNAs were shown to be synergetic in function. Sixteen miRNAs forming 20 miRNAs interaction pairs participated in inflammatory response, such as mir-185 and mir-674-3p. The 16 miRNAs related to inflammatory response during ischemic stroke may provide underlying targets for prevention and treatment of stroke.

Both ERS and JNK pathways are involved in the pathological process of ischemic brain injury. The JNK pathway may be involved in the process of ERS, but perhaps has more effect on the caspase-12 pathway.

Parkinson disease (PD) is one of the most frequent neurodegenerative disorders. The aim of this study was to identify blood biomarkers capable to discriminate PD patients with different progression rates. Differentially expressed genes (DEGs) were acquired by comparing the expression profiles of PD patients with rapid and slow progression rates, using an expression dataset from Gene Expression Omnibus (GEO) under accession code of GSE80599. Altered biological processes and pathways were revealed by functional annotation. Potential biomarkers of PD were identified by protein-protein interaction (PPI) network analysis. Critical transcription factors (TFs) and miRNAs regulating DEGs were predicted by TF analysis and miRNA analysis. A total of 225 DEGs were identified between PD patients with rapid and slow progression profiles. These genes were significantly enriched in biological processes and pathways related to fatty acid metabolism. Among these DEGs, ZFAND4, SRMS, UBL4B, PVALB, DIRAS1, PDP2, LRCH1, and MYL4 were potential progression rate associated biomarkers of PD. Additionally, these DEGs may be regulated by miRNAs of the miR-30 family and TFs STAT1 and GRHL3. Our results may contribute to our understanding of the molecular mechanisms underlying different PD progression profiles.

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