Evidence map›Paper›PMID 30483789›Full record

ArticleMolecular medicine reports2019

Identification of potential biomarkers for differential diagnosis between rheumatoid arthritis and osteoarthritis via integrative genome‑wide gene expression profiling analysis.

Rongqiang Zhang, Xiaoli Yang, Jing Wang, Lixin Han, Aimin Yang, Jie Zhang, Dandan Zhang, Baorong Li, Zhaofang Li, Yongmin Xiong

Open access · hybridAbstract read
In one paragraph

Article in Molecular medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

24 citing papers in PubMed, 33 citations in OpenAlex.

  1. Trial
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  9. EXPLORing Arthritis with Total-body Positron Emission Tomography.Seminars in musculoskeletal radiology · 2023
    Review
  10. TheJournal of inflammation research · 2023
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  11. Article
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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

10 authors at 4 institutions in 2 countries.

Rongqiang ZhangSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Xiaoli YangSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Jing WangSchool of Public Health, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi 712046, P.R. China.
Lixin HanSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Aimin YangSchool of Public Health, Brown University, Providence, RI 02906, USA.
Jie ZhangSchool of Public Health, Brown University, Providence, RI 02906, USA.
Dandan ZhangSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Baorong LiSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Zhaofang LiSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Yongmin XiongSchool of Public Health, Xi'an Jiaotong University Health Science Center, Key Laboratory of Trace Elements and Endemic Diseases of The National Health and Family Planning Commission, Xi'an, Shaanxi 710061, P.R. China.
Xi'an Jiaotong University · CNNational Health and Family Planning Commission · CNBrown University · USShaanxi University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present study aimed to identify potential novel biomarkers in synovial tissue obtained from patients with Rheumatoid Arthritis (RA) and Osteoarthritis (OA) for differential diagnosis. The genome‑wide expression profiling datasets of synovial tissues from RA and OA cohorts, including GSE55235, GSE55457 and GSE55584 datasets, were retrieved and used to identify differentially expressed genes (DEGs; P<0.05; false discovery rate <0.05 and Fold Change >2) between RA and OA using R software. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of DEGs were performed to determine molecular and biochemical pathways associated with the identified DEGs, and a protein‑protein interaction (PPI) network of the DEGs was constructed using Cytoscape software. Significant modules in the PPI network and candidate driver genes were screened using the Molecular Complex Detection Algorithm. Potential biomarkers were evaluated by receiver operating characteristic and logistic regression analyses. Large numbers of DEGs were detected, including 273, 205 and 179 DEGs in the GSE55235, GSE55457 and GSE55584 datasets, respectively. Among them, 80 DEGs exhibited identical expression trends in all the three datasets, including 49 upregulated and 31 downregulated genes in patients with RA. DEGs in patients suffering from RA compared with patients suffering from OA were predominantly associated with the primary immunodeficiency pathway, including interleukin 7 receptor (IL7R) and signal transducer activator of transcription 1 (STAT1). The sensitivity of IL7R + STAT1 to differentiate RA from OA was 93.94% with a specificity of 80.77%. The results generated from analyses of the GSE36700 dataset were closely associated with results generated from analyses of GSE55235, GSE55457 and GSE55584 datasets, which further verified the reliability of the aforementioned results. The results of the present study suggested that increased expression of IL7R and STAT1 in synovial tissue as well as in the primary immunodeficiency may be associated with RA occurrence. These identified novel biomarkers may be used to predict disease occurrence and clinically differentiate RA from OA.

Indexed as

Arthritis, RheumatoidBiomarkersDatabases, GeneticDiagnosis, DifferentialDown-RegulationGene Expression ProfilingGene OntologyGene Regulatory NetworksGenome-Wide Association StudyHumansOsteoarthritisProtein Interaction MapsReceptors, Interleukin-7Reproducibility of ResultsSoftwareSTAT1 Transcription FactorBiomarkersReceptors, Interleukin-7STAT1 Transcription Factorosteoarthritispathwayprotein-protein interactionrheumatoid arthritissensitivityspecificity

Identifiers

PMID30483789
PMCPMC6297798
OpenAlexW2901622397

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.