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Metabolomics Insights in Early Childhood Caries.
Heimisdottir, L H; Lin, B M; Cho, H; Orlenko, A; Ribeiro, A A; Simon-Soro, A; Roach, J; Shungin, D; Ginnis, J; Simancas-Pallares, M A; Spangler, H D; Zandoná, A G Ferreira; Wright, J T; Ramamoorthy, P; Moore, J H; Koo, H; Wu, D; Divaris, K.
Afiliación
  • Heimisdottir LH; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
  • Lin BM; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
  • Cho H; Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
  • Orlenko A; Department of Biostatistics, Epidemiology and Informatics, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA.
  • Ribeiro AA; Division of Diagnostic Sciences, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
  • Simon-Soro A; 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.
  • Roach J; Department of Orthodontics and Divisions of Pediatric Dentistry and Community Oral Health, School of Dental Medicine, University of Pennsylvania, Philadelphia, PA, USA.
  • Shungin D; Department of Stomatology, School of Dentistry, University of Sevilla, Sevilla, Spain.
  • Ginnis J; Research Computing, University of North Carolina, Chapel Hill, NC, USA.
  • Simancas-Pallares MA; Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Spangler HD; Department of Odontology, Umeå University, Umeå, Sweden.
  • Zandoná AGF; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
  • Wright JT; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
  • Ramamoorthy P; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
  • Moore JH; Department of Comprehensive Care, School of Dental Medicine, Tufts University, Boston, MA, USA.
  • Koo H; Division of Pediatric and Public Health, Adams School of Dentistry, University of North Carolina, Chapel Hill, NC, USA.
  • Wu D; Metabolon, Inc., Durham, NC, USA.
  • Divaris K; Department of Biostatistics, Epidemiology and Informatics, Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA.
J Dent Res ; 100(6): 615-622, 2021 06.
Article en En | MEDLINE | ID: mdl-33423574
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Caries Dental Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Child / Child, preschool / Humans País/Región como asunto: America do norte Idioma: En Revista: J Dent Res Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Caries Dental Tipo de estudio: Diagnostic_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Child / Child, preschool / Humans País/Región como asunto: America do norte Idioma: En Revista: J Dent Res Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos