Evidence map›Paper›PMID 35967352›Full record

ArticleFrontiers in immunology2022

Six macrophage-associated genes in synovium constitute a novel diagnostic signature for osteoarthritis.

Yiying Liu, Taoyuan Lu, Zaoqu Liu, Wenhua Ning, Siying Li, Yanru Chen, Xiaoyong Ge, Chunguang Guo, Youyang Zheng, Xiangyang Wei and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
7.5field-weighted citation impact, top 2% 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

28 citing papers in PubMed, 45 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

11 authors at 3 institutions in 1 country.

Yiying LiuAcademy of Medical Sciences, Zhengzhou University, Zhengzhou, China.
Taoyuan LuDepartment of Cerebrovascular Disease, Zhengzhou University People's Hospital, Henan Provincial People's Hospital, Zhengzhou, China.
Zaoqu LiuDepartment of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Wenhua NingDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Siying LiAcademy of Medical Sciences, Zhengzhou University, Zhengzhou, China.
Yanru ChenAcademy of Medical Sciences, Zhengzhou University, Zhengzhou, China.
Xiaoyong GeDepartment of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Chunguang GuoDepartment of Endovascular Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Youyang ZhengDepartment of Cardiovascular Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Xiangyang WeiDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Haiming WangDepartment of Rehabilitation Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
First Affiliated Hospital of Zhengzhou University · CNZhengzhou University · CNHenan Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Synovial macrophages play important roles in the formation and progression of osteoarthritis (OA). This study aimed to explore the biological and clinical significance of macrophage-associated genes (MAGs) in OA. Methods: The OA synovial gene expression profiles GSE89408 and GSE82107 were obtained from the GEO database. Single-sample gene set enrichment analysis (ssGSEA) and GSEA were employed to decipher differences in immune infiltration and macrophage-associated biological pathways, respectively. Protein-protein interaction (PPI) network analysis and machine learning were utilized to establish a macrophage-associated gene diagnostic signature (MAGDS). RT-qPCR was performed to test the expression of key MAGs in murine models. Results: OA synovium presented high levels of immune infiltration and activation of macrophage-associated biological pathways. A total of 55 differentially expressed MAGs were identified. Using PPI analysis and machine learning, a MAGDS consisting of IL1B, C5AR1, FCGR2B, IL10, IL6, and TYROBP was established for OA diagnosis (AUC = 0.910) and molecular pathological evaluation. Patients with high MAGDS scores may possess higher levels of immune infiltration and expression of matrix metalloproteinases (MMPs), implying poor biological alterations. The diagnostic value of MAGDS was also validated in an external cohort (AUC = 0.886). The expression of key MAGs was validated in a murine model using RT-qPCR. Additionally, a competitive endogenous RNA network was constructed to reveal the potential posttranscriptional regulatory mechanisms. Conclusions: We developed and validated a MAGDS model with the ability to accurately diagnose and characterize biological alterations in OA. The six key MAGs may also be latent targets for immunoregulatory therapy.

Indexed as

Gene Regulatory NetworksOsteoarthritisAnimalsGene Expression ProfilingHumansMacrophagesMiceSynovial Membranediagnostic signatureimmunopathologymachine learningmacrophage-associated genesOsteoarthritissynovial macrophages

Identifiers

PMID35967352
PMCPMC9368762
OpenAlexW4288441241

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.