Evidence map›Paper›PMID 32788627›Full record

ArticleScientific reports2020

Identification of potential diagnostic gene biomarkers in patients with osteoarthritis.

Xinling Wang, Yang Yu, Yong Huang, Mingshuang Zhu, Rigao Chen, Zhanghui Liao, Shipeng Yang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.5field-weighted citation impact, top 10% 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, 24 citations in OpenAlex.

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  10. Identification of potential pathogenic genes related to osteoporosis and osteoarthritis.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
    Article
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  14. Maternal caffeine intake and DNA methylation in newborn cord blood.The American journal of clinical nutrition · 2022
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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

7 authors at 1 institution in 1 country.

Xinling WangHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China.
Yang YuHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China. wangxinling@cdutcm.edu.cn.
Yong HuangHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China.
Mingshuang ZhuHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China.
Rigao ChenHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China.
Zhanghui LiaoHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China.
Shipeng YangHospital of Chengdu University of Traditional Chinese Medicine, No. 39, Shierqiao road, Jinniu District, Chengdu City, 610075, Sichuan Province, China.
Chengdu University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current study was aimed to identify diagnostic gene signature for osteoarthritis (OA). The differentially expressed genes (DEGs) in synovial membrane samples and blood samples were respectively identified from the GEO dataset. The intersection DEGs between synovial membrane and blood were further screened out, followed by the functional annotation of these common DEGs. The optimal intersection gene biomarkers for OA diagnostics were determined. The GSE51588 dataset of articular cartilage was used for expression validation and further diagnostic analysis validation of identified gene biomarkers for OA diagnostics. There were 379 intersection DEGs were obtained between the synovial membrane and blood samples of OA. 22 DEGs had a diagnostic value for OA. After further screening, a total of 9 DEGs including TLR7, RTP4, CRIP1, ZNF688, TOP1, EIF1AY, RAB2A, ZNF281 and UIMC1 were identified for OA diagnostic. The identified DEGs could be considered as potential diagnostic biomarkers for OA.

Indexed as

BiomarkersCluster AnalysisDatabases, GeneticFemaleGene Expression ProfilingGene OntologyGenetic Predisposition to DiseaseHumansMaleOsteoarthritisReproducibility of ResultsSensitivity and SpecificitySignal TransductionSynovial MembraneBiomarkers

Identifiers

PMID32788627
PMCPMC7424510
OpenAlexW3048952321

What OpenQuestion holds

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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.