Bioinformatics analysis of gene and microRNA targets for fibromyalgia.

OBJECTIVES: Fibromyalgia (FM) is the most common chronic pain disease in middle-aged women. Patients may also complain of migraine, irritable bowel syndrome and depression, which seriously affect their work and life, causing huge economic losses to society. However, the pathogenesis of FM is still controversial and the effect of the current treatment is far from satisfactory. METHODS: Differentially expressed genes (DEGs) and miRNAs (DEMs) were found between FM and normal blood samples. The pathway and process enrichment analysis of the genes were performed. Protein-protein interaction network were constructed. Hub genes were found and analysed in The Comparative Toxicogenomics Database. RESULTS: A total of 102 genes were up-regulated and 46 down-regulated, 206 miRNAs down-regulated, and 15 up-regulated in FM. CD38, GATM, HDC, FOS were found as canditate genes. These genes were significantly associated with musculoskeletal disease, mental disorder, immune system disease. There was partial overlap between metformin therapy-related genes and FM-related genes. CONCLUSIONS: We found DEGs and DEMs in FM patients through bioinformatics analysis, which may be involved in the occurrence and development of FM and serve as potential targets for diagnosis and treatment.

Bioinformatics Analysis of Genes and Mechanisms in Postherpetic Neuralgia.

Objective: Elderly patients are prone to postherpetic neuralgia (PHN), which may cause anxiety, depression, and sleep disorders and reduce quality of life. As a result, the life quality of patients was seriously reduced. However, the pathogenesis of PHN has not been fully elucidated, and current treatments remain inadequate. Therefore, it is important to explore the molecular mechanism of PHN. Methods: We analyzed the GSE64345 dataset, which includes gene expression from the ipsilateral dorsal root ganglia (DRG) of PHN model rats. Differentially expressed genes (DEGs) were identified and analyzed by Gene Ontology. Protein-protein interaction (PPI) network was constructed. The miRNA associated with neuropathic pain and inflammation was found in miRNet. Hub genes were identified and analyzed in Comparative Toxicogenomics Database (CTD). miRNA-mRNA networks associated with PHN were constructed. Results: A total of 116 genes were up-regulated in the DRG of PHN rats, and 135 genes were down-regulated. Functional analysis revealed that variations were predominantly enriched for genes involved in neuroactive ligand-receptor interactions, the Jak-STAT signaling pathway, and calcium channel activity. Eleven and thirty-one miRNAs associated with neuropathic pain and inflammation, respectively, were found. Eight hub genes (S1PR1, OPRM1, PDYN, CXCL3, S1PR5, TBX5, TNNI3, MYL7, PTGDR2, and FBXW2) associated with PHN were identified. Conclusions: Bioinformatics analysis is a useful tool to explore the mechanism and pathogenesis of PHN. The identified hub genes may participate in the onset and development of PHN and serve as therapeutic targets.