Evidence map›Paper›PMID 40539067›Full record

ArticleFrontiers in immunology2025

Integrated machine learning and single-cell RNA sequencing reveal COL4A2 and CXCL6 as oxidative stress-associated biomarkers in periodontitis.

Siyu Sun, Jing Ren, Xiujuan Zeng, Yanbin Chen, Qianbing Zhou, Junying Yang, Shan Chen

Abstract read
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Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

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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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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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.

Siyu SunDepartment of Stomatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Jing RenDepartment of Stomatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xiujuan ZengDepartment of Stomatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yanbin ChenDepartment of Stomatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Qianbing ZhouDepartment of Stomatology, The First Affiliated Hospital of Guangdong Pharmaceutical University, Guangzhou, China.
Junying YangDepartment of Stomatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Shan ChenDepartment of Stomatology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Periodontitis, recognized as the second most prevalent oral disease globally, is strongly linked to systemic disorders like diabetes and cardiovascular diseases, highlighting the critical need for effective prevention and treatment strategies. Oxidative stress plays an important role in periodontitis pathogenesis and progression, yet their specific association remains unclear. This study aims to explore the association between oxidative stress and periodontitis pathogenesis while identifying potential diagnostic biomarkers and therapeutic targets for this condition. Methods: Transcriptomic data from gingival tissues of periodontitis patients and controls were obtained from the Gene Expression Omnibus (GEO) database. Key genes linked to oxidative stress in periodontitis were identified through a comprehensive analytical approach, including differential expression analysis, weighted gene co-expression network analysis (WGCNA), gene set enrichment analysis (GSEA), and functional enrichment analyses (GO and KEGG). Machine learning algorithms were subsequently employed to refine the selection of key genes. The relationship between oxidative stress and the expression of these key genes was validated using external datasets and a periodontitis rat model. Additionally, single-cell RNA sequencing (scRNA-seq) data were interrogated to delineate the cellular subpopulations expressing the key genes, leveraging clustering and annotation approaches. Results: Comprehensive bioinformatics analysis identified COL4A2, CYR61, and CXCL6 as key genes associated with oxidative stress in periodontitis. Among these genes, COL4A2 and CXCL6 showed elevated expression levels in the gingival tissues of periodontitis rats. Single-cell RNA-seq analysis further demonstrated that COL4A2 exhibited predominant expression within endothelial and stromal cell clusters, whereas CXCL6 was predominantly localized to epithelial cell clusters. Conclusions: This study demonstrates a correlation between oxidative stress and the progression of periodontitis. COL4A2 and CXCL6 were identified as potential therapeutic targets for the treatment of periodontitis.

Indexed as

Chemokine CXCL6Collagen Type IVMachine LearningOxidative StressPeriodontitisAnimalsbeta-ThromboglobulinBiomarkersComputational BiologyGene Expression ProfilingGene Regulatory NetworksHumansMaleRatsSequence Analysis, RNASingle-Cell Analysisbeta-ThromboglobulinBiomarkersChemokine CXCL6Collagen Type IVCXCL6 protein, humanPPBP protein, humanCOL4A2CXCL6oxidative stressperiodontitissingle-cell RNA sequencing

Identifiers

PMID40539067
PMCPMC12176571

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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.