Evidence map›Paper›PMID 37594094›Full record

ArticleCurrent computer-aided drug design2024

The Diagnostic Features of Peripheral Blood Biomarkers in Identifying Osteoarthritis Individuals: Machine Learning Strategies and Clinical Evidence.

Qiao Zhou, Jian Liu, Ling Xin, Yuedi Hu, Yajun Qi

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In one paragraph

Article in Current computer-aided drug design, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 32% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

5 authors at 2 institutions in 1 country.

Qiao ZhouDepartment of Rheumatism Immunity, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, 230031, China.ORCID 0000-0001-6568-0260
Jian LiuDepartment of Rheumatism Immunity, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, 230031, China.
Ling XinInstitute of Rheumatism Prevention and Treatment of Traditional Chinese Medicine, Anhui Academy of Chinese Medicine Sciences, Hefei, Anhui, 230031, China.
Yuedi HuInstitute of Rheumatism Prevention and Treatment of Traditional Chinese Medicine, Anhui Academy of Chinese Medicine Sciences, Hefei, Anhui, 230031, China.
Yajun QiInstitute of Rheumatism Prevention and Treatment of Traditional Chinese Medicine, Anhui Academy of Chinese Medicine Sciences, Hefei, Anhui, 230031, China.
Anhui University of Traditional Chinese Medicine · CNAnhui University · CN

Funding

Anhui Province Traditional Chinese Medicine Leading Talent Project (Traditional Chinese Medicine Development Secret (2018) 23CSRD VA 1Famous Traditional Chinese Medicine Liu Jian Studio Construction Project (Traditional Chinese Medicine Development Secret (2018) 11Key Project of Natural Science Research in the Anhui University 2022AH050449
6 · The paper itself

Abstract

backgroundPeople with osteoarthritis place a huge burden on society. Early diagnosis is essential to prevent disease progression and to select the best treatment strategy more effectively. In this study, the aim was to examine the diagnostic features and clinical value of peripheral blood biomarkers for osteoarthritis.

objectiveThe goal of this project was to investigate the diagnostic features of peripheral blood and immune cell infiltration in osteoarthritis (OA).

methodsTwo eligible datasets (GSE63359 and GSE48556) were obtained from the GEO database to discern differentially expressed genes (DEGs). The machine learning strategy was employed to filtrate diagnostic biomarkers for OA. Additional verification was implemented by collecting clinical samples of OA. The CIBERSORT website estimated relative subsets of RNA transcripts to evaluate the immune-inflammatory states of OA. The link between specific DEGs and clinical immune-inflammatory markers was found by correlation analysis.

resultsOverall, 67 robust DEGs were identified. The nuclear receptor subfamily 2 group C member 2 (NR2C2), transcription factor 4 (TCF4), stromal antigen 1 (STAG1), and interleukin 18 receptor accessory protein (IL18RAP) were identified as effective diagnostic markers of OA in peripheral blood. All four diagnostic markers showed significant increases in expression in OA. Analysis of immune cell infiltration revealed that macrophages are involved in the occurrence of OA. Candidate diagnostic markers were correlated with clinical immune-inflammatory indicators of OA patients.

conclusionWe highlight that DEGs associated with immune inflammation (NR2C2, TCF4, STAG1, and IL18RAP) may be potential biomarkers for peripheral blood in OA, which are also associated with clinical immune-inflammatory indicators.

Indexed as

BiomarkersMachine LearningOsteoarthritisDatabases, GeneticHumansBiomarkersdiagnostic markersimmune-inflammatorymachine learning strategiesOsteoarthritisperipheral bloodtranscription factor 4 (TCF4).

Identifiers

PMID37594094
OpenAlexW4385969418

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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.