Scholarlink

Objective <p>Saliva, which is a critical component of the oral ecosystem, undergoes dynamic changes, particularly during the onset and progression of periodontitis.</p> Subjects and methods <p>This study used Gas Chromatography-Mass Spectrometry (GC-MS), a reliable and high-throughput tool for metabolomic analysis, to detect salivary metabolic shifts across various stages of periodontitis (T1-T4). We compared differential changes in metabolites between the HC and T1 groups, the T1 and T2 groups, the T2 and T3 groups, and the T3 and T4 groups.</p> Results <p>By analysing saliva samples from 116 individuals-10 healthy controls (HC) and 106 patients with periodontitis across stages T1 (22 individuals) to T4 (28 individuals), we identified differential metabolites including Glucose, 3-Aminobutanoic Acid, N-(1-Cyclopropylethyl) Aniline, and Methylmalonic Acid. Compared to HC, the metabolites in patients with periodontitis exhibited progressive concentration changes correlating with the severity of the disease. Furthermore, KEGG pathway analysis was used to elucidate the metabolic pathways involved in the development of periodontitis.</p> Conclusions <p>Our findings demonstrate the potential of salivary metabolites as biomarkers for monitoring periodontitis progression and offer valuable insights into its pathogenesis and potential therapeutic targets.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The salivary metabolomics analyses reveal the variable metabolites in distinct staging of periodontitis

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年4月3日

查看全文
  • Lijun Wang,
  • Wen Lu,
  • Wei Ju,
  • Wenxin Yao,
  • Chaowen Shi,
  • Xihu Yang,
  • Wenhao Qian

摘要

Objective

Saliva, which is a critical component of the oral ecosystem, undergoes dynamic changes, particularly during the onset and progression of periodontitis.

Subjects and methods

This study used Gas Chromatography-Mass Spectrometry (GC-MS), a reliable and high-throughput tool for metabolomic analysis, to detect salivary metabolic shifts across various stages of periodontitis (T1-T4). We compared differential changes in metabolites between the HC and T1 groups, the T1 and T2 groups, the T2 and T3 groups, and the T3 and T4 groups.

Results

By analysing saliva samples from 116 individuals-10 healthy controls (HC) and 106 patients with periodontitis across stages T1 (22 individuals) to T4 (28 individuals), we identified differential metabolites including Glucose, 3-Aminobutanoic Acid, N-(1-Cyclopropylethyl) Aniline, and Methylmalonic Acid. Compared to HC, the metabolites in patients with periodontitis exhibited progressive concentration changes correlating with the severity of the disease. Furthermore, KEGG pathway analysis was used to elucidate the metabolic pathways involved in the development of periodontitis.

Conclusions

Our findings demonstrate the potential of salivary metabolites as biomarkers for monitoring periodontitis progression and offer valuable insights into its pathogenesis and potential therapeutic targets.