Evidence map›Paper›PMID 37547319›Full record

ArticleFrontiers in endocrinology2023

Verification of cuproptosis-related diagnostic model associated with immune infiltration in rheumatoid arthritis.

Mingyang Jiang, Kaicheng Liu, Shenyi Lu, Yue Qiu, Xiaochong Zou, Ke Zhang, Chuanliang Chen, Yiji Jike, Mingjing Xie, Yongheng Dai and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.5field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 21 citations in OpenAlex.

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  14. Cuproptosis and its potential role in musculoskeletal disease.Frontiers in cell and developmental biology · 2025
    Review
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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

11 authors at 2 institutions in 1 country.

Mingyang JiangDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Kaicheng LiuDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Shenyi LuDepartment of Rehabilitation, The Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China.
Yue QiuDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Xiaochong ZouDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Ke ZhangDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Chuanliang ChenDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Yiji JikeDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Mingjing XieDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Yongheng DaiDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Zhandong BoDepartment of Bone and Joint Surgery, Guangxi Medical University First Affiliated Hospital, Nanning, China.
Guangxi Medical University · CNAffiliated Hospital of Youjiang Medical University for Nationalities · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Rheumatoid arthritis (RA) is a chronic autoimmune disease closely related to inflammation. Cuproptosis is a newly discovered unique type of cell death, and it has been found that it may play an essential role in the occurrence and development of RA. Therefore, we intend to explore the potential association between cuproptosis-related genes (CRGs) and RA to provide a new biomarker for the treatment and prognosis of RA. Methods: Download GSE93777 datasets from the GEO database. Variance analysis was performed on the CRGs that had been reported. Then, the random forest (RF) model and nomogram of differentially expressed CRGs were constructed, and the ROC curve was used to evaluate the accuracy of the diagnostic model. Next, RA patients were subtyped by consensus clustering, and immune infiltration was analyzed in each subgroup to confirm the correlation between CRGs and abundance of immune cells. The expression levels of CRGs were verified by qRT-PCR. Results: Eight differentially expressed CRGs (DLST, DLD, PDHB, PDHA1, ATP7A, CDKN2A, LIAS, DLAT) were screened out by differential analysis to construct an RF model. The ROC curve proved that this model had good diagnostic accuracy. Based on the above eight significant CRGs, a nomogram was built to predict effective and high-precision results. The consensus clustering method identified two CRG patterns. Most of the immune cells were enriched in cluster A, indicating that cluster A may be related to the development of RA. Finally, qRT-PCR verified the expression of eight key genes, further confirming our findings. Conclusion: The diagnosis model of RA based on the above eight CRGs has excellent diagnostic potential. Based on these, patients can be divided into two different molecular subtypes; it is expected to develop a new treatment strategy for RA.

Indexed as

ApoptosisArthritis, RheumatoidAutoimmune DiseasesCell DeathCluster AnalysisCopperHumansInflammationCoppercuproptosisdiagnostic modeldiagnosticsimmune infiltrationrheumatoid arthritis

Identifiers

PMID37547319
PMCPMC10399571
OpenAlexW4385067870

What OpenQuestion holds

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LicenceCC BY
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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.