Metabolomics Insights in Early Childhood Caries

Author:

Heimisdottir L.H.1ORCID,Lin B.M.2,Cho H.2,Orlenko A.3,Ribeiro A.A.4,Simon-Soro A.567,Roach J.8,Shungin D.910,Ginnis J.1,Simancas-Pallares M.A.1,Spangler H.D.1,Zandoná A.G. Ferreira11,Wright J.T.1,Ramamoorthy P.12,Moore J.H.3,Koo H.56,Wu D.213,Divaris K.114ORCID

Affiliation:

1. Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA

2. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA

3. Department of Biostatistics, Epidemiology and Informatics, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA

4. Division of Diagnostic Sciences, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA

5. Biofilm Research Labs, Center for Innovation and Precision Dentistry, School of Dental Medicine and School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA, USA

6. Department of Orthodontics and Divisions of Pediatric Dentistry and Community Oral Health, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA

7. Department of Stomatology, School of Dentistry, University of Sevilla, Sevilla, Spain

8. Research Computing, University of North Carolina, Chapel Hill, NC, USA

9. Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA

10. Department of Odontology, Umeå University, Umeå, Sweden

11. Department of Comprehensive Care, School of Dental Medicine, Tufts University, Boston, MA, USA

12. Metabolon, Inc., Durham, NC, USA

13. Division of Oral & Craniofacial Health Sciences, School of Dentistry, University of North Carolina, Chapel Hill, NC, USA

14. Department of Epidemiology, Gillings School of Public Health, University of North Carolina, Chapel Hill, NC, USA

Abstract

Dental caries is characterized by a dysbiotic shift at the biofilm–tooth surface interface, yet comprehensive biochemical characterizations of the biofilm are scant. We used metabolomics to identify biochemical features of the supragingival biofilm associated with early childhood caries (ECC) prevalence and severity. The study’s analytical sample comprised 289 children ages 3 to 5 (51% with ECC) who attended public preschools in North Carolina and were enrolled in a community-based cross-sectional study of early childhood oral health. Clinical examinations were conducted by calibrated examiners in community locations using International Caries Detection and Classification System (ICDAS) criteria. Supragingival plaque collected from the facial/buccal surfaces of all primary teeth in the upper-left quadrant was analyzed using ultra-performance liquid chromatography–tandem mass spectrometry. Associations between individual metabolites and 18 clinical traits (based on different ECC definitions and sets of tooth surfaces) were quantified using Brownian distance correlations (dCor) and linear regression modeling of log2-transformed values, applying a false discovery rate multiple testing correction. A tree-based pipeline optimization tool (TPOT)–machine learning process was used to identify the best-fitting ECC classification metabolite model. There were 503 named metabolites identified, including microbial, host, and exogenous biochemicals. Most significant ECC-metabolite associations were positive (i.e., upregulations/enrichments). The localized ECC case definition (ICDAS ≥1 caries experience within the surfaces from which plaque was collected) had the strongest correlation with the metabolome (dCor P = 8 × 10−3). Sixteen metabolites were significantly associated with ECC after multiple testing correction, including fucose ( P = 3.0 × 10−6) and N-acetylneuraminate (p = 6.8 × 10−6) with higher ECC prevalence, as well as catechin ( P = 4.7 × 10−6) and epicatechin ( P = 2.9 × 10−6) with lower. Catechin, epicatechin, imidazole propionate, fucose, 9,10-DiHOME, and N-acetylneuraminate were among the top 15 metabolites in terms of ECC classification importance in the automated TPOT model. These supragingival biofilm metabolite findings provide novel insights in ECC biology and can serve as the basis for the development of measures of disease activity or risk assessment.

Funder

National Institute of Dental and Craniofacial Research

Publisher

SAGE Publications

Subject

General Dentistry

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