Evidence map›Paper›PMID 35379209›Full record

ArticleBMC musculoskeletal disorders2022

Potential biomarkers that discriminate rheumatoid arthritis and osteoarthritis based on the analysis and validation of datasets.

Le Kang, Chengqian Dai, Lihong Wang, Xinling Pan

Open access · goldAbstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

10 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Rheumatoid Arthritis: Biomarkers and the Latest Breakthroughs.International journal of molecular sciences · 2025
    Review
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
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

4 authors at 1 institution in 1 country.

Le KangDepartment of Biomedical Sciences Laboratory, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.
Chengqian DaiDepartment of Orthopedics, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.
Lihong WangDepartment of Orthopedics, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China.
Xinling PanDepartment of Biomedical Sciences Laboratory, Affiliated Dongyang Hospital of Wenzhou Medical University, Dongyang, Zhejiang, China. panfengyuwuzu@163.com.
Wenzhou Medical University · CN

Funding

Science and Technology Bureau of Jinhua 2021-4-135
6 · The paper itself

Abstract

backgroundRheumatoid arthritis (RA) and osteoarthritis (OA) share some similar arthritic symptoms, but different mechanisms underlie the pathogenesis of these two diseases. Analysis of differentially expressed molecules in rheumatoid arthritis and osteoarthritis may assist in improving diagnosis and treatment strategies in clinical practice.

methodsMicroarray and RNA-seq data were acquired from the gene expression omnibus database. Differentially expressed genes (DEGs) were identified using Bioconductor packages. Receiver operating characteristic curves were plotted to assess performance. Gene ontology enrichment analysis was conducted using the clusterProfiler application. During validation, synovial fluid was harvested from patients who had undergone in-hospital joint replacement, in which the expression of proteins was measured using enzyme-linked immunosorbent assays.

resultsCompared with OA samples, RA samples showed 14 genes to be upregulated and 3 to be downregulated. Gene ontology analysis indicated that DEGs principally included molecules responsible for the regulation of a synovial tissue inflammatory response. Seven genes displayed a good discriminatory power with an AUC higher than 0.90. ADAMDEC1 was the biomarker that most clearly discriminated RA from OA in the database, exhibiting an AUC of 0.999, a sensitivity of 100%, and a specificity of 97.8%. Following validation, the expression levels of ADAMDEC1 in the synovial fluid from RA patients were significantly higher than those in the synovial fluid from OA patients (P < 0.05). At the cut-off value of 1957 pg/mL, ADAMDEC1 expression in the synovial fluid discriminated RA from OA with an AUC of 0.951, a specificity of 88.6%, and a sensitivity of 92.9%.

conclusionThe differential expression of genes in RA compared with OA indicates potential targets for molecular diagnosis and treatment. The presence of ADAMDEC1 in synovial fluid is a good biomarker of RA.

Indexed as

Arthritis, RheumatoidOsteoarthritisBiomarkersHumansSynovial FluidSynovial MembraneBiomarkersDifferentially expressed genesOsteoarthritisRheumatoid arthritis

Identifiers

PMID35379209
PMCPMC8978354
OpenAlexW4225769991

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.