Affiliated Stomatology Hospital of Kunming Medical University, Kunming, Yunnan, China.
Yunnan Provincial Key Laboratory of Stomatology, Kunming, Yunnan, China.
BMC Oral Health. 2024 Feb 2;24(1):169. doi: 10.1186/s12903-024-03912-8.
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.
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.
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.
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.
牙周炎是一种由免疫系统功能障碍引发的慢性炎症性疾病。线粒体细胞外囊泡（MitoEVs）是一组富含线粒体部分的高度异质性细胞外囊泡（EVs）。本研究旨在探讨 MitoEVs 与牙周炎免疫微环境的相关性。
利用 MitoCarta 3.0、GeneCards 和 GEO 数据库中的数据来鉴定差异表达的 MitoEV 相关基因（MERGs），并进行功能富集和途径分析。采用随机森林和 LASSO 算法来识别枢纽 MERGs。利用 CIBERSORT 算法估计牙周炎和健康组中免疫细胞的浸润水平，并利用共识聚类方法基于枢纽 MERG 表达水平探索牙周炎的表型亚群。
共鉴定出 44 个差异表达的 MERGs。随机森林和 LASSO 算法识别出 9 个枢纽 MERGs（BCL2L11、GLDC、CYP24A1、COQ2、MTPAP、NIPSNAP3A、FAM162A、MYO19 和 NDUFS1）。ROC 曲线分析表明，枢纽基因和逻辑回归模型具有出色的诊断和区分能力。免疫浸润和共识聚类分析表明，枢纽 MERGs 与多种类型的免疫细胞高度相关，并且在不同牙周炎亚型中免疫细胞和枢纽 MERGs 存在显著差异。
基于 MERGs 的牙周炎分类模型表现出色，为牙周炎的发病机制提供了新的视角。MERGs 与各种免疫细胞之间的高度相关性以及不同牙周炎亚型中免疫细胞和 MERGs 之间的显著差异，可以阐明 MitoEVs 在牙周炎免疫微环境中的调节作用。未来的研究应侧重于阐明枢纽 MERGs 的功能机制，并基于这些发现探索潜在的治疗干预措施。
