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. 2022 Sep;53(5):842-850.
doi: 10.12182/20220960207.

[Salivary Metabolic Profiling in Patients with Periodontitis]

[Article in Chinese]
Jiao Chen  1 , Yue Du  1 , Xue-Dong Zhou  1 , Ping Zhang  1
Affiliations

[Salivary Metabolic Profiling in Patients with Periodontitis]

[Article in Chinese]
Jiao Chen et al. Sichuan Da Xue Xue Bao Yi Xue Ban. 2022 Sep.

Abstract
in English, Chinese

Objective: To analyze the salivary metabolic profile of patients with periodontitis through metabolomic techniques and to explore the metabolic patterns associated with periodontal diseases.

Methods: Liquid chromatography/mass spectrometry (LC/MS) technique in conjunction with principal component analysis (PCA) analysis and orthogonal partial least squares identification (OPLS-DA) method was used to study the metabolomics of saliva samples from gingivitis patients, periodontitis patients, and healthy controls, with 10 samples for each group. We examined the correlation between migration in metabolic profile and the progression of periodontal diseases.

Results: Saliva metabolite profiles of gingivitis and periodontitis patients was significantly different from those of the healthy controls. Significant differences were identified between the different groups for eight salivary metabolites, including arachidonic acid, tyramine, L-arginine, thymine, N-acetylgalactosamine sulfate, prostaglandin E2, L-phenylalanine, and 5-aminoimidazole-4-carboxamide-riboside (AICAR). In comparison with those of the health controls, the concentration of AICAR in patients with gingivitis and periodontitis was lower and the metabolic trend was down-regulated, while the other metabolites were up-regulated.

Conclusion: Salivary metabolic profile changes along with the progression of periodontal diseases. Abnormal metabolism of the periodontal tissue and of pathogenic microorganisms related to periodontal diseases is one of the mechanisms involved in the pathogenesis, development and prognosis of periodontal diseases.

目的: 利用代谢组学研究方法分析牙周炎患者唾液代谢轮廓，探讨牙周疾病相关代谢模式。

方法: 采用液相色谱-质谱联用（LC-MS）技术结合主成分分析（PCA）法和正交偏最小二乘法-判别分析（OPLS-DA）法，分别对牙龈炎患者、牙周炎患者和健康人群各10例唾液样本进行代谢组学研究，分析代谢轮廓迁移和牙周疾病进程相关性。

结果: 牙龈炎患者、牙周炎患者和健康人群的唾液代谢轮廓存在明显差异，其中花生四烯酸、酪胺、L-精氨酸、胸腺嘧啶、N-乙酰氨基半乳糖硫酸盐、前列腺素E2、L-苯丙氨酸和5-氨基咪唑-4甲酰胺核苷酸（AICAR）等8个代谢产物在各组间差异显著。与健康人相比，AICAR在牙龈炎患者和牙周炎患者体内浓度较低，代谢趋势下调，其余代谢物的趋势均上调。

结论: 唾液代谢谱随牙周病进程而变化，牙周病相关病原微生物和牙周组织代谢异常是牙周疾病发生发展和预后的机制之一。

Keywords: Biomarkers; Metabolomics; Periodontitis; Saliva.

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Conflict of interest statement

利益冲突 所有作者均声明不存在利益冲突

Figures

图 1
图 1
The principal component analysis (PCA) score plots of samples 样本的主成分分析（PCA）图
图 2
图 2
The orthogonal partial least square discrimination analysis (OPLS-DA) score plots of gingivitis patients, periodontitis patients, and health controls and the permutation test 牙龈炎组、牙周炎组与健康组的正交偏最小二乘判别分析（OPLS-DA）得分图及置换检验图
图 3
图 3
The Venn diagram of differential metabolites 三组差异代谢产物Venn图
图 4
图 4
The heatmap analysis of differential metabolites 差异代谢产物热图
图 5
图 5
Boxplots of saliva levels of key metabolites 代谢产物箱形图
See this image and copyright information in PMC

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