Microbial and metabolomic analysis of gingival crevicular fluid in general chronic periodontitis patients: lessons for a predictive, preventive, and personalized medical approach

Jun Pei; Fei Li; Youhua Xie; Jing Liu; Tian Yu; Xiping Feng

doi:10.1007/s13167-020-00202-5

Microbial and metabolomic analysis of gingival crevicular fluid in general chronic periodontitis patients: lessons for a predictive, preventive, and personalized medical approach

EPMA J. 2020 Apr 16;11(2):197-215. doi: 10.1007/s13167-020-00202-5. eCollection 2020 Jun.

Authors

Jun Pei^#^{1

2

3}, Fei Li^#^{1

2

3}, Youhua Xie⁴, Jing Liu⁴, Tian Yu^{1

2

3}, Xiping Feng^{1

2

3}

Affiliations

¹ Department of Preventive Dentistry, Shanghai Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200000 China.
² National Clinical Research Center for Oral Diseases, Shanghai, 200000 China.
³ Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, 200000 China.
⁴ Key Lab of Medical Molecular Virology, School of Basic Medical Sciences, Fudan University, Shanghai, 200000 China.

^# Contributed equally.

Abstract

Objectives: General 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.

Methods: In 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.

Results: The 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.

Conclusions: Dysbiosis 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.

Keywords: Gingival crevicular fluid; Metabolites; Microbial communities; Molecular biomarkers; Multi-level diagnostics; Multi-omics; Periodontitis; Predictive preventive personalized medicine; Therapeutic targets.