Abstract
ObjectivesGeneral chronic periodontitis (GCP) is a bacterial inflammatory disease with complex pathology. Despite extensive studies published on the variation in the oral microbiota and metabolic profiles of GCP patients, information is lacking regarding the correlation between host-bacterial interactions and biochemical metabolism. This study aimed to analyze the oral microbiome, the oral metabolome, and the link between them and to identify potential molecules as useful biomarkers for predictive, preventive, and personalized medicine (PPPM) in GCP.MethodsIn this study, gingival crevicular fluid (GCF) samples were collected from patients with GCP (n = 30) and healthy controls (n = 28). The abundance of oral microbiota constituents was obtained by Illumina sequencing, and the relative level of metabolites was measured by gas chromatography-mass spectrometry. Full-mouth probing depth, clinical attachment loss, and bleeding on probing were recorded as indices of periodontal disease.ResultsThe relative abundances of 7 phyla and 82 genera differed significantly between the GCP and healthy groups. Seventeen differential metabolites involved in different metabolism pathways were selected based on variable influence on projection values (VIP > 1) and P values (P < 0.05). Through Spearman’s correlation analysis, microorganisms, metabolites in GCF, and clinical data together showed a clear trend, and clinical data regarding periodontitis can be reflected in the shift of the oral microbial community and the change in metabolites in GCF. A combination of citramalic acid and N-carbamylglutamate yielded satisfactory accuracy (AUC = 0.876) for the predictive diagnosis of GCP.ConclusionsDysbiosis in the polymicrobial community structure and changes in metabolism could be mechanisms underlying periodontitis. The differential microorganisms and metabolites in GCF between periodontitis patients and healthy individuals are possibly biomarkers, pointing to a potential strategy for the prediction, diagnosis, prognosis, and management of personalized periodontal therapy.
Highlights
General chronic periodontitis (GCP) is a bacterial inflammatory disease that is induced and maintained by polymicrobial biofilm in subgingival areas; intricate interactions of the microbial communities with the host subvert the host’s homeostasis, disrupting tissue attachment and destroying the supporting structures of the teeth [1, 2]
The probing depth (PD), the clinical attachment level (CAL), and the prevalence of bleeding on probing (BOP) of patients were significantly higher in the GCP group than in the control group (P < 0.01, Table 1)
Following 16S rRNA gene sequencing of 116 gingival crevicular fluid (GCF) samples from 58 individuals (60 samples from 30 chronic periodontitis individuals and 56 samples from 28 controls), 2,290,279 highquality reads were obtained after quality filtration
Summary
General chronic periodontitis (GCP) is a bacterial inflammatory disease that is induced and maintained by polymicrobial biofilm in subgingival areas; intricate interactions of the microbial communities with the host subvert the host’s homeostasis, disrupting tissue attachment and destroying the supporting structures of the teeth [1, 2]. Researchers have increasingly agreed with the hypothesis from an ecological perspective to explain the mechanism of periodontal disease occurrence and development [11], and complicated interactions between oral health and multiple diseases [12, 13]. Under this condition, next-generation sequencing (NGS) technology provides an advanced scientific technique in terms of detecting, identifying, and classifying the oral microbial community [14], and has led to the validation and enhanced understanding of periodontitis prediction conforming to the ecological plaque hypothesis
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