Evidence map›Paper›PMID 29547407›Full record

ArticleThe Clinical journal of pain2018

Bioinformatic Analysis of Potential Biomarkers for Spinal Cord-injured Patients with Intractable Neuropathic Pain.

Yimin Wang, Fang Ye, Chanyan Huang, Faling Xue, Yingyuan Li, Shaowei Gao, Zeting Qiu, Si Li, Qinchang Chen, Huaqiang Zhou and 4 more

Open access · hybridAbstract read
In one paragraph

Article in The Clinical journal of pain, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 32 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 3 institutions in 1 country.

Yimin WangDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Fang YeDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Chanyan HuangDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Faling XueDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Yingyuan LiDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Shaowei GaoDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Zeting QiuZhongshan School of Medicine, Sun Yat-sen University, Guangdong, China.
Si LiZhongshan School of Medicine, Sun Yat-sen University, Guangdong, China.
Qinchang ChenZhongshan School of Medicine, Sun Yat-sen University, Guangdong, China.
Huaqiang ZhouZhongshan School of Medicine, Sun Yat-sen University, Guangdong, China.
Yiyan SongZhongshan School of Medicine, Sun Yat-sen University, Guangdong, China.
Wenqi HuangDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Wulin TanDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Zhongxing WangDepartment of Anesthesiology, The First Affiliated Hospital of Sun Yat-sen University.
Sun Yat-sen University · CNGuangdong Provincial People's Hospital · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeuropathic pain is one of the common complications after spinal cord injury (SCI), affecting individuals' quality of life. The molecular mechanism for neuropathic pain after SCI is still unclear. We aimed to discover potential genes and microRNAs (miRNAs) related to neuropathic pain by the bioinformatics method.

methodsMicroarray data of GSE69901 were obtained from Gene Expression Omnibus (GEO) database. Peripheral blood samples from individuals with or without neuropathic pain after SCI were collected. Twelve samples from individuals with neuropathic pain and 13 samples from individuals without pain as controls were included in the downloaded microarray. Differentially expressed genes (DEGs) between the neuropathic pain group and the control group were detected using the GEO2R online tool. Functional enrichment analysis of DEGs was performed using the DAVID database. Protein-protein interaction network was constructed from the STRING database. MiRNAs targeting these DEGs were obtained from the miRNet database. A merged miRNA-DEG network was constructed and analyzed with Cytoscape software.

resultsIn total, 1134 DEGs were identified between individuals with or without neuropathic pain (case and control), and 454 biological processes were enriched. We identified 4 targeted miRNAs, including mir-204-5p, mir-519d-3p, mir-20b-5p, mir-6838-5p, which may be potential biomarkers for SCI patients.

conclusionProtein modification and regulation of the biological process of the central nervous system may be a risk factor in SCI. Certain genes and miRNAs may be potential biomarkers for the prediction of and potential targets for the prevention and treatment of neuropathic pain after SCI.

Indexed as

BiomarkersComputational BiologyGene ExpressionHumansIntractable PainMicroarray AnalysisMicroRNAsNeuralgiaSpinal Cord InjuriesBiomarkersMicroRNAs

Identifiers

PMID29547407
PMCPMC6078488
OpenAlexW2794337593

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.