In vivo (Athens, Greece) · 2025
Age- and Periodontal Disease Independent Correlation of Salivary Amino Acids.
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Tanaka Shoji, Sakagami Hiroshi, Sugimoto Masahiro
Аннотация
BACKGROUND/AIM: This study explored the relationship between salivary metabolomic profiles, periodontal diseases, and age.
PATIENTS AND METHODS: Resting whole saliva samples were collected from a cohort comprising 21 women and 30 men aged 20 to 70 years, including healthy volunteers and patients with different stages of periodontal diseases. Hydrophilic metabolites were analyzed using capillary electrophoresis-mass spectrometry. The concentrations were quantified and analyzed using multivariable analysis with or without normalization to eliminate overall differences in salivary concentrations across the samples.
RESULTS: Metabolomic analysis quantified the absolute concentration of 248 metabolites in saliva samples. The unnormalized metabolomic profiles formed large clusters, with more than half of the detected metabolites showing positive correlations with each other. The absence of such clusters in the normalized data suggests the presence of individual differences in the processed data. The presence of urea, whose concentration increased gradually with the degree of progression of periodontal disease, and leucine, whose concentration decreased gradually, was identified. Highly positive correlations were observed between proline and glycine, which remained consistent regardless of normalization, age, or disease progression.
CONCLUSION: The metabolomic profiles of salivary samples revealed unique correlations between amino acids that were independent of age and periodontal disease.
PATIENTS AND METHODS: Resting whole saliva samples were collected from a cohort comprising 21 women and 30 men aged 20 to 70 years, including healthy volunteers and patients with different stages of periodontal diseases. Hydrophilic metabolites were analyzed using capillary electrophoresis-mass spectrometry. The concentrations were quantified and analyzed using multivariable analysis with or without normalization to eliminate overall differences in salivary concentrations across the samples.
RESULTS: Metabolomic analysis quantified the absolute concentration of 248 metabolites in saliva samples. The unnormalized metabolomic profiles formed large clusters, with more than half of the detected metabolites showing positive correlations with each other. The absence of such clusters in the normalized data suggests the presence of individual differences in the processed data. The presence of urea, whose concentration increased gradually with the degree of progression of periodontal disease, and leucine, whose concentration decreased gradually, was identified. Highly positive correlations were observed between proline and glycine, which remained consistent regardless of normalization, age, or disease progression.
CONCLUSION: The metabolomic profiles of salivary samples revealed unique correlations between amino acids that were independent of age and periodontal disease.