Prediction of Future Caries in 1-Year-Old Children via the Salivary Microbiome. (June 2023)
- Record Type:
- Journal Article
- Title:
- Prediction of Future Caries in 1-Year-Old Children via the Salivary Microbiome. (June 2023)
- Main Title:
- Prediction of Future Caries in 1-Year-Old Children via the Salivary Microbiome
- Authors:
- Raksakmanut, R.
Thanyasrisung, P.
Sritangsirikul, S.
Kitsahawong, K.
Seminario, A.L.
Pitiphat, W.
Matangkasombut, O. - Abstract:
- Dental caries is the most common chronic disease in children that causes negative effects on their health, development, and well-being. Early preventive interventions are key to reduce early childhood caries prevalence. An efficient strategy is to provide risk-based targeted prevention; however, this requires an accurate caries risk predictor, which is still lacking for infants before caries onset. We aimed to develop a caries prediction model based on the salivary microbiome of caries-free 1-y-old children. Using a nested case-control design within a prospective cohort study, we selected 30 children based on their caries status at 1-y follow-up (at 2 y old): 10 children who remained caries-free, 10 who developed noncavitated caries, and 10 who developed cavitated caries. Saliva samples collected at baseline before caries onset were analyzed through 16S rRNA gene sequencing. The results of β diversity analysis showed a significant difference in salivary microbiome composition between children who remained caries-free and those who developed cavitated caries at 2 y old (analysis of similarities, Benjamini-Hochberg corrected, P = 0.042). The relative abundance of Prevotella nanceiensis, Leptotrichia sp. HMT 215, Prevotella melaninogenica, and Campylobacter concisus in children who remained caries-free was significantly higher than in children who developed cavitated caries (Wilcoxon rank sum test, P = 0.024, 0.040, 0.049, and 0.049, respectively). These taxa were alsoDental caries is the most common chronic disease in children that causes negative effects on their health, development, and well-being. Early preventive interventions are key to reduce early childhood caries prevalence. An efficient strategy is to provide risk-based targeted prevention; however, this requires an accurate caries risk predictor, which is still lacking for infants before caries onset. We aimed to develop a caries prediction model based on the salivary microbiome of caries-free 1-y-old children. Using a nested case-control design within a prospective cohort study, we selected 30 children based on their caries status at 1-y follow-up (at 2 y old): 10 children who remained caries-free, 10 who developed noncavitated caries, and 10 who developed cavitated caries. Saliva samples collected at baseline before caries onset were analyzed through 16S rRNA gene sequencing. The results of β diversity analysis showed a significant difference in salivary microbiome composition between children who remained caries-free and those who developed cavitated caries at 2 y old (analysis of similarities, Benjamini-Hochberg corrected, P = 0.042). The relative abundance of Prevotella nanceiensis, Leptotrichia sp. HMT 215, Prevotella melaninogenica, and Campylobacter concisus in children who remained caries-free was significantly higher than in children who developed cavitated caries (Wilcoxon rank sum test, P = 0.024, 0.040, 0.049, and 0.049, respectively). These taxa were also identified as biomarkers for children who remained caries-free (linear discriminant analysis effect size, linear discriminant analysis score = 3.69, 3.74, 3.53, and 3.46). A machine learning model based on these 4 species distinguished between 1-y-old children who did and did not develop cavitated caries at 2 y old, with an accuracy of 80%, sensitivity of 80%, and specificity of 80% (area under the curve, 0.8; 95% CI, 44.4 to 97.5). Our findings suggest that these salivary microbial biomarkers could assist in predicting future caries in caries-free 1-y-old children and, upon validation, are promising for development into an adjunctive tool for caries risk prediction for prevention and monitoring. … (more)
- Is Part Of:
- Journal of dental research. Volume 102:Number 6(2023)
- Journal:
- Journal of dental research
- Issue:
- Volume 102:Number 6(2023)
- Issue Display:
- Volume 102, Issue 6 (2023)
- Year:
- 2023
- Volume:
- 102
- Issue:
- 6
- Issue Sort Value:
- 2023-0102-0006-0000
- Page Start:
- 626
- Page End:
- 635
- Publication Date:
- 2023-06
- Subjects:
- dental caries -- biomarkers -- microbiota -- machine learning -- infant -- saliva
Dentistry -- Periodicals
Dentistry -- Social aspects -- Periodicals
Dentistry -- Periodicals
Research -- Periodicals
617.6005 - Journal URLs:
- http://jdr.sagepub.com/ ↗
http://www.sagepublications.com/ ↗
http://www.dentalresearch.org/Publications/JournalDentalRsrch/default.htm ↗ - DOI:
- 10.1177/00220345231152802 ↗
- Languages:
- English
- ISSNs:
- 0022-0345
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 27127.xml