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

Content Provider	Springer Nature : BioMed Central
Author	Baheti, Wufanbieke Dong, Diwen Li, Congcong Chen, Xiaotao
Abstract	Background The 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. Methods The 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). Results CKAP2, 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. Conclusion CKAP2, IGLL5, MZB1, CXCL6 and AADACL2 were identified as core genes associated with exosomes, helping us to understand the role of these genes in PD.
Related Links	https://bmcoralhealth.biomedcentral.com/counter/pdf/10.1186/s12903-024-05409-w.pdf
Ending Page	19
Page Count	19
Starting Page	1
File Format	HTM / HTML
ISSN	14726831
DOI	10.1186/s12903-024-05409-w
Journal	BMC Oral Health
Issue Number	1
Volume Number	25
Language	English
Publisher	BioMed Central
Publisher Date	2025-01-06
Access Restriction	Open
Subject Keyword	Dentistry Oral and Maxillofacial Surgery Periodontitis Exosomes ScRNA-seq Machine learning Core genes
Content Type	Text
Resource Type	Article
Subject	Dentistry
Journal Impact Factor	2.6/2023
5-Year Journal Impact Factor	3.2/2023

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