Your browser doesn't support javascript.
loading
Exploring the potential link between MitoEVs and the immune microenvironment of periodontitis based on machine learning and bioinformatics methods.
Yang, Haoran; Zhao, Anna; Chen, Yuxiang; Cheng, Tingting; Zhou, Jianzhong; Li, Ziliang.
Afiliação
  • Yang H; Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Zhao A; Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China.
  • Chen Y; Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Cheng T; Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China.
  • Zhou J; Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China.
  • Li Z; Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China.
BMC Oral Health ; 24(1): 169, 2024 Feb 02.
Article em En | MEDLINE | ID: mdl-38308306
ABSTRACT

BACKGROUND:

Periodontitis is a chronic inflammatory condition triggered by immune system malfunction. Mitochondrial extracellular vesicles (MitoEVs) are a group of highly heterogeneous extracellular vesicles (EVs) enriched in mitochondrial fractions. The objective of this research was to examine the correlation between MitoEVs and the immune microenvironment of periodontitis.

METHODS:

Data from MitoCarta 3.0, GeneCards, and GEO databases were utilized to identify differentially expressed MitoEV-related genes (MERGs) and conduct functional enrichment and pathway analyses. The random forest and LASSO algorithms were employed to identify hub MERGs. Infiltration levels of immune cells in periodontitis and healthy groups were estimated using the CIBERSORT algorithm, and phenotypic subgroups of periodontitis based on hub MERG expression levels were explored using a consensus clustering method.

RESULTS:

A total of 44 differentially expressed MERGs were identified. The random forest and LASSO algorithms identified 9 hub MERGs (BCL2L11, GLDC, CYP24A1, COQ2, MTPAP, NIPSNAP3A, FAM162A, MYO19, and NDUFS1). ROC curve analysis showed that the hub gene and logistic regression model presented excellent diagnostic and discriminating abilities. Immune infiltration and consensus clustering analysis indicated that hub MERGs were highly correlated with various types of immune cells, and there were significant differences in immune cells and hub MERGs among different periodontitis subtypes.

CONCLUSION:

The periodontitis classification model based on MERGs shows excellent performance and can offer novel perspectives into the pathogenesis of periodontitis. The high correlation between MERGs and various immune cells and the significant differences between immune cells and MERGs in different periodontitis subtypes can clarify the regulatory roles of MitoEVs in the immune microenvironment of periodontitis. Future research should focus on elucidating the functional mechanisms of hub MERGs and exploring potential therapeutic interventions based on these findings.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vesículas Extracelulares Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Oral Health Assunto da revista: ODONTOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Vesículas Extracelulares Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: BMC Oral Health Assunto da revista: ODONTOLOGIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China