Identification of potential biomarkers of long non-coding RNAs in neuropathic pain using bioinformatic analysis: A protocol for systematic review and meta-analysis

利用生物信息学分析鉴定神经性疼痛中长链非编码RNA的潜在生物标志物:系统评价和荟萃分析方案

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Abstract

BACKGROUND: Long non-coding RNAs (LncRNAs) play important roles in the regulation of neuropathic pain (NP) development. LncRNAs dysregulations are related to the development of NP. However, a comprehensive meta-analysis has never been conducted to assess the relationship between LncRNAs and NP. To combine the results of dysregulated LncRNAs in individual NP studies and to identify potential LncRNAs biomarkers. METHODS: LncRNAs profiling studies of NP were extracted from Pubmed, Web of science, Embase, Google Scholar, and Chinese National Knowledge Infrastructure, and the Chinese Biomedical Literature Database if they met the inclusion criteria. The meta-analysis was conducted using a random effects model to identify the effect of each multiple-reported LncRNAs. We also performed subgroup analysis according to LncRNAs detecting methods and sample type. Sensitivity analysis was performed on the sample size. Bioinformatic analysis was performed to identify the potential biomatic functions. All results were represented as log10 odds ratios. RESULTS: This review will be disseminated in print by peer-review. CONCLUSION: The identified LncRNAs may be closely linked with NP and may act as potentially useful biomarkers. ETHICS AND DISSEMINATION: The private information from individuals will not publish. This systematic review also will not involve endangering participant rights. Ethical approval is not available. The results may be published in a peer- reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/ZRX7C.

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