Evidence map›Paper›PMID 39762852›Full record

ArticleBMC oral health2025

Identification of core genes related to exosomes and screening of potential targets in periodontitis using transcriptome profiling at the single-cell level.

Wufanbieke Baheti, Diwen Dong, Congcong Li, Xiaotao Chen

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Wufanbieke BahetiDepartment of Stomatology, People's Hospital of Xinjiang Autonomous Region, Urumqi City, China.
Diwen DongDepartment of Stomatology, People's Hospital of Xinjiang Autonomous Region, Urumqi City, China.
Congcong LiDepartment of Stomatology, People's Hospital of Xinjiang Autonomous Region, Urumqi City, China.
Xiaotao ChenDepartment of Stomatology, People's Hospital of Xinjiang Autonomous Region, Urumqi City, China. xiaotaochen@163.com.ORCID 0000-0002-0133-215X

Funding

National Natural Science Foundation of China 82260195Science and Technology Department of Xinjiang Uygur Autonomous Region 2023D01C78
6 · The paper itself

Abstract

backgroundThe progression and severity of periodontitis (PD) are associated with the release of extracellular vesicles by periodontal tissue cells. However, the precise mechanisms through which exosome-related genes (ERGs) influence PD remain unclear. This study aimed to investigate the role and potential mechanisms of key exosome-related genes in PD using transcriptome profiling at the single-cell level.

methodsThe current study cited GSE16134, GSE10334, GSE171213 datasets and 19,643 ERGs. Initially, differential expression analysis, three machine learning (ML) models, gene expression analysis and receiver operating characteristic (ROC) analysis were proceeded to identify core genes. Subsequently, a core gene-based artificial neural network (ANN) model was built to evaluate the predictive power of core genes for PD. Gene set enrichment analysis (GSEA) and immunoinfiltration analysis were conducted based on core genes. To pinpoint key cell types influencing the progression of periodontal at the single-cell level, a series of single-cell analyses covering pseudo-time series analysis were accomplished. The expression verification of core genes was performed through quantitative reverse transcription polymerase chain reaction (qRT-PCR).

resultsCKAP2, IGLL5, MZB1, CXCL6, and AADACL2 served as core genes diagnosing PD. Four core gene were elevated in the PD group in addition to down-regulated AADACL2. The core gene-based-ANN model had AUC values of 0.909 in GSE16134 dataset, which exceeded AUC of each core gene, highlighting the accurately and credibly predictive performance of ANN model. GSEA revealed that ribosome was co-enriched by 5 core genes, manifesting the expression of these genes might be critical for protein structure or function. Immunoinfiltration analysis found that CKAP2, IGLL5, MZB1, and CXCL6 exhibited positive correlations with most discrepant immune cells/discrepant stromal cells, which were highly infiltrated in PD. B cells and T cells holding crucial parts in PD were identified as key cell types. Pseudo-time series analysis revealed that the expression of IGLL5 and MZB1 increased during T cell differentiation, increased and then decreased during B cell differentiation. The qRT-PCR proved the mRNA expression levels of CKAP2 and MZB1 were increased in the blood of PD patients compared to controls. But the mRNA expression levels of AADACL2 was decreased in the PD patients compared to controls. This is consistent with the trend in the amount of expression in the dataset.

conclusionCKAP2, IGLL5, MZB1, CXCL6 and AADACL2 were identified as core genes associated with exosomes, helping us to understand the role of these genes in PD.

Indexed as

ExosomesGene Expression ProfilingPeriodontitisSingle-Cell AnalysisHumansMachine LearningNeural Networks, ComputerCore genesExosomesMachine learningPeriodontitisScRNA-seq

Identifiers

PMID39762852
PMCPMC11706113

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