Selenomonas sputigena acts as a pathobiont mediating spatial structure and biofilm virulence in early childhood caries.

Streptococcus mutans has been implicated as the primary pathogen in childhood caries (tooth decay). While the role of polymicrobial communities is appreciated, it remains unclear whether other microorganisms are active contributors or interact with pathogens. Here, we integrate multi-omics of supragingival biofilm (dental plaque) from 416 preschool-age children (208 males and 208 females) in a discovery-validation pipeline to identify disease-relevant inter-species interactions. Sixteen taxa associate with childhood caries in metagenomics-metatranscriptomics analyses. Using multiscale/computational imaging and virulence assays, we examine biofilm formation dynamics, spatial arrangement, and metabolic activity of Selenomonas sputigena, Prevotella salivae and Leptotrichia wadei, either individually or with S. mutans. We show that S. sputigena, a flagellated anaerobe with previously unknown role in supragingival biofilm, becomes trapped in streptococcal exoglucans, loses motility but actively proliferates to build a honeycomb-like multicellular-superstructure encapsulating S. mutans, enhancing acidogenesis. Rodent model experiments reveal an unrecognized ability of S. sputigena to colonize supragingival tooth surfaces. While incapable of causing caries on its own, when co-infected with S. mutans, S. sputigena causes extensive tooth enamel lesions and exacerbates disease severity in vivo. In summary, we discover a pathobiont cooperating with a known pathogen to build a unique spatial structure and heighten biofilm virulence in a prevalent human disease.

Guardians' Self-Reported Fair/Poor Oral Health Is Associated with Their Young Children's Fair/Poor Oral Health and Clinically Determined Dental Caries Experience.

In this cross-sectional, community-based study among a multi-ethnic sample of preschool-age children in North Carolina, United States, we sought to quantify the association between guardians' self-reported oral health and their children's oral health and determine whether race/ethnicity and education level modify these associations. We used questionnaire (n = 7852) responses about caregivers' and their children's oral health and clinical examination-derived (n = 6243) early childhood caries (ECC) status defined at the ICDAS ≥ 3 caries lesion detection threshold. We used multi-level mixed-effects generalized linear models to examine the associations between the guardians' reported oral health and their children's reported and clinically determined oral health among the entire sample and within strata of race/ethnicity, guardians' education, and children's dental home. The guardians' and their children's reported fair/poor oral health (FPOH) were 32% and 15%, respectively, whereas 54% of the children had ECC and 36% had unrestored disease. The guardians' FPOH was strongly associated with their children's FPOH (average marginal effect (AME) = +19 percentage points (p.p.); 95% CI = 17-21), and this association was most pronounced among Hispanics, lower-educated guardians, and children without a dental home. Similar patterns, but smaller-in-magnitude associations, were found for the guardians' FPOH and their children's clinically determined ECC (AME = +9 p.p.; 95% CI = 6-12) and unrestored disease (AME = +7 p.p.; 95% CI = 4-9). The study's findings support a strong association between guardians' and their children's reported and clinically determined oral health and implicate ethnicity, education, and having a dental home as factors possibly modifying the magnitude of these associations.

PARTITIONING AROUND MEDOIDS CLUSTERING AND RANDOM FOREST CLASSIFICATION FOR GIS-INFORMED IMPUTATION OF FLUORIDE CONCENTRATION DATA.

Community water fluoridation is an important component of oral health promotion, as fluoride exposure is a well-documented dental caries-preventive agent. Direct measurements of domestic water fluoride content provide valuable information regarding individuals' fluoride exposure and thus caries risk; however, they are logistically challenging to carry out at a large scale in oral health research. This article describes the development and evaluation of a novel method for the imputation of missing domestic water fluoride concentration data informed by spatial autocorrelation. The context is a state-wide epidemiologic study of pediatric oral health in North Carolina, where domestic water fluoride concentration information was missing for approximately 75% of study participants with clinical data on dental caries. A new machine-learning-based imputation method that combines partitioning around medoids clustering and random forest classification (PAMRF) is developed and implemented. Imputed values are filtered according to allowable error rates or target sample size, depending on the requirements of each application. In leave-one-out cross-validation and simulation studies, PAMRF outperforms four existing imputation approaches-two conventional spatial interpolation methods (i.e., inverse-distance weighting, IDW and universal kriging, UK) and two supervised learning methods (k-nearest neighbors, KNN and classification and regression trees, CART). The inclusion of multiply imputed values in the estimation of the association between fluoride concentration and dental caries prevalence resulted in essentially no change in PAMRF estimates but substantial gains in precision due to larger effective sample size. PAMRF is a powerful new method for the imputation of missing fluoride values where geographical information exists.

Children's oral health-related behaviours and early childhood caries: A latent class analysis.

OBJECTIVE: In this cross-sectional study in a large community-based sample of preschool-age children, we sought to identify distinct clusters of modifiable early childhood oral health-related behaviours (OHBs) and quantify their association with clinical and parent-reported measures of early childhood oral health. METHODS: We relied upon a questionnaire (n = 8033; 11% in Spanish) and clinical oral health data (n = 6404; early childhood caries [ECC] prevalence = 54%] collected in the context of an epidemiologic study of early childhood oral health among 3- to 5-year-old children in North Carolina. Latent class analysis was used to identify clusters of modifiable OHBs based on parents' responses to 6 questionnaire items pertaining to their children's oral hygiene, diet and dental home. The optimal number of clusters was determined based on measures of model fit and interpretability. We examined associations of OHB clusters with clinical and parent-reported child oral health status (ie, ECC prevalence, severity and proportion with untreated disease) using bivariate association tests and multivariable regression modelling with marginal effects estimation accounting for clustered data. We used Mplus v.8.6 (Muthén & Muthén, Los Angeles, CA, USA) and Stata v.16.1 (StataCorp, College Station, TX, USA) for data analyses. RESULTS: We identified 2 OHB clusters, a favourable (74%) and an unfavourable (26%) one. Children in the favourable OHB cluster had better oral hygiene practices (ie, tooth brushing frequency and fluoridated toothpaste use), lower consumption frequency of sugar-containing snacks and beverages, less frequent reports of night-time bottle-feeding history and a higher likelihood of a dental home. Children in the unfavourable cluster had significantly higher ECC prevalence (57% vs 53%), caries burden (mean dmfs = 9.3 vs 7.6), untreated disease (43% vs 33%) and worse parent-reported oral health status than the favourable cluster. CONCLUSIONS: Our findings demonstrate the importance and utility of clustering common, modifiable ECC risk factors in population studies - health promotion efforts may centre on groups of people rather than individual behavioural risk factors.

Guardian Reports of Children's Sub-optimal Oral Health Are Associated With Clinically Determined Early Childhood Caries, Unrestored Caries Lesions, and History of Toothaches.

Background: Parents'/guardians' perceptions of their children's oral health are useful proxies of their clinically determined caries status and are known to influence dental care-seeking behavior. In this study, we sought to examine (1) the social and behavioral correlates of fair/poor child oral health reported by guardians and (2) quantify the association of these reports with the prevalence of early childhood caries (ECC), unrestored caries lesions and toothaches. Methods: We used guardian-reported child oral health information (dichotomized as fair/poor vs. excellent/very good/good) obtained via a parent questionnaire that was completed for n = 7,965 participants (mean age = 52 months; range = 36-71 months) of a community-based, cross-sectional epidemiologic study of early childhood oral health in North Carolina between 2016 and 2019. Social, demographic, oral health-related behavioral data, and reports on children's history of toothaches (excluding teething) were collected in the same questionnaire. Unrestored ECC (i.e., caries lesions) was measured via clinical examinations in a subset of n = 6,328 children and was defined as the presence of one or more tooth surfaces with an ICDAS ≥ 3 caries lesion. Analyses relied on descriptive and bivariate methods, and multivariate modeling with average marginal effect (A.M.E.) estimation accounting for the clustered nature of the data. Estimates of association [prevalence ratios (PR) and adjusted marginal effects (AME) with 95% confidence intervals (CI)] were obtained via multilevel generalized linear models using Stata's svy function and accounting for the clustered nature of the data. Results: The prevalence of fair/poor oral health in this sample was 15%-it increased monotonically with children's age, was inversely associated with parents' educational attainment, and was higher among Hispanics (21%) and African Americans (15%) compared to non-Hispanic whites (11%). Brushing less than twice a day, not having a dental home, and frequently consuming sugar-containing snacks and beverages were significantly associated with worse reports (P < 0.0005). Children with fair/poor reported oral health were twice as likely to have unrestored caries lesions [prevalence ratio (PR) = 2.0; 95% confidence interval (CI) = 1.8-2.1] and 3.5 times as likely to have experienced toothaches [PR = 3.5; 95% CI = 3.1-3.9] compared to those with better reported oral health. Conclusions: Guardian reports of their children's oral health are valuable indicators of clinical and public health-important child oral health status. Those with fair/poor guardian-reported child oral health have distinguishing characteristics spanning socio-demographics, oral-health related practices, diet, and presence of a dental home.

Child Nutrition Patterns Are Associated with Primary Dentition Dental Caries.

Purpose: Diet is a well-established, modifiable factor influencing dental caries risk. However, evidence regarding its association with distinct clinical patterns of dental caries is lacking. The purpose of this study was to identify the association of child nutrition patterns with two distinct clinical presentations (subtypes) of childhood dental caries. Methods: The study sample comprised 120 children who were patients of a private pediatric dental practice: 30 ages one to three years (mean equals 2.2 years) with anterior carious lesions; 30 ages four to 12 years (mean equals six years) with posterior-only carious lesions; and 60 age-, gender-, and payment method-matched caries-free controls. Participants underwent dental examinations, and their guardians completed a 17-item nutrition frequency questionnaire. A latent profile analysis was used to define distinct dietary patterns and, subsequently, test their association with dental caries subtypes. Results: Dietary patterns were differentiated by consumption frequencies of water and cariogenic solid, soft, and liquid food items; a diet cluster characterized by frequent consumption of fruit juice, cereal bars, and daily vitamins was more common (P<0.05) among one- to three-year-old patients with anterior carious lesions compared to matched caries-free controls. Conclusions: These results affirm the key role of dietary patterns in childhood oral health and demonstrate the influence of fermentable carbohydrates on specific clinical subtypes of caries.

A Web-Based Rendering Application for Communicating Dental Conditions.

The importance of visual aids in communicating clinical examination findings or proposed treatments in dentistry cannot be overstated. Similarly, communicating dental research results with tooth surface-level precision is impractical without visual representations. Here, we present the development, deployment, and two real-life applications of a web-based data visualization informatics pipeline that converts tooth surface-level information to colorized, three-dimensional renderings. The core of the informatics pipeline focuses on texture (UV) mapping of a pre-existing model of the human primary dentition. The 88 individually segmented tooth surfaces receive independent inputs that are represented in colors and textures according to customizable user specifications. The web implementation SculptorHD, deployed on the Google Cloud Platform, can accommodate manually entered or spreadsheet-formatted tooth surface data and allows the customization of color palettes and thresholds, as well as surface textures (e.g., condition-free, caries lesions, stainless steel, or ceramic crowns). Its current implementation enabled the visualization and interpretation of clinical early childhood caries (ECC) subtypes using latent class analysis-derived caries experience summary data. As a demonstration of its potential clinical utility, the tool was also used to simulate the restorative treatment presentation of a severe ECC case, including the use of stainless steel and ceramic crowns. We expect that this publicly available web-based tool can aid clinicians and investigators deliver precise, visual presentations of dental conditions and proposed treatments. The creation of rapidly adjustable lifelike dental models, integrated to existing electronic health records and responsive to new clinical findings or planned for future work, is likely to boost two-way communication between clinicians and their patients.

An Automated Machine Learning Classifier for Early Childhood Caries.

Purpose: The purpose of the study was to develop and evaluate an automated machine learning algorithm (AutoML) for children's classification according to early childhood caries (ECC) status. Methods: Clinical, demographic, behavioral, and parent-reported oral health status information for a sample of 6,404 three- to five-year-old children (mean age equals 54 months) participating in an epidemiologic study of early childhood oral health in North Carolina was used. ECC prevalence (decayed, missing, and filled primary teeth surfaces [dmfs] score greater than zero, using an International Caries Detection and Assessment System score greater than or equal to three caries lesion detection threshold) was 54 percent. Ten sets of ECC predictors were evaluated for ECC classification accuracy (i.e., area under the ROC curve [AUC], sensitivity [Se], and positive predictive value [PPV]) using an AutoML deployment on Google Cloud, followed by internal validation and external replication. Results: A parsimonious model including two terms (i.e., children's age and parent-reported child oral health status: excellent/very good/good/fair/poor) had the highest AUC (0.74), Se (0.67), and PPV (0.64) scores and similar performance using an external National Health and Nutrition Examination Survey (NHANES) dataset (AUC equals 0.80, Se equals 0.73, PPV equals 0.49). Contrarily, a comprehensive model with 12 variables covering demographics (e.g., race/ethnicity, parental education), oral health behaviors, fluoride exposure, and dental home had worse performance (AUC equals 0.66, Se equals 0.54, PPV equals 0.61). Conclusions: Parsimonious automated machine learning early childhood caries classifiers, including single-item self-reports, can be valuable for ECC screening. The classifier can accommodate biological information that can help improve its performance in the future.

Cohort Profile: ZOE 2.0-A Community-Based Genetic Epidemiologic Study of Early Childhood Oral Health.

Early childhood caries (ECC) is an aggressive form of dental caries occurring in the first five years of life. Despite its prevalence and consequences, little progress has been made in its prevention and even less is known about individuals' susceptibility or genomic risk factors. The genome-wide association study (GWAS) of ECC ("ZOE 2.0") is a community-based, multi-ethnic, cross-sectional, genetic epidemiologic study seeking to address this knowledge gap. This paper describes the study's design, the cohort's demographic profile, data domains, and key oral health outcomes. Between 2016 and 2019, the study enrolled 8059 3-5-year-old children attending public preschools in North Carolina, United States. Participants resided in 86 of the state's 100 counties and racial/ethnic minorities predominated-for example, 48% (n = 3872) were African American, 22% white, and 20% (n = 1611) were Hispanic/Latino. Seventy-nine percent (n = 6404) of participants underwent clinical dental examinations yielding ECC outcome measures-ECC (defined at the established caries lesion threshold) prevalence was 54% and the mean number of decayed, missing, filled surfaces due to caries was eight. Nearly all (98%) examined children provided sufficient DNA from saliva for genotyping. The cohort's community-based nature and rich data offer excellent opportunities for addressing important clinical, epidemiologic, and biological questions in early childhood.

Measurement of Early Childhood Oral Health for Research Purposes: Dental Caries Experience and Developmental Defects of the Enamel in the Primary Dentition.

Epidemiological investigations of early childhood oral health rely upon the collection of high-quality clinical measures of health and disease. However, ascertainment of valid and accurate clinical measures presents unique challenges among young, preschool-age children. The paper presents a clinical research protocol for the conduct of oral epidemiological examinations among children, implemented in ZOE 2.0, a large-scale population-based genetic epidemiologic study of early childhood caries (ECC). The protocol has been developed for the collection of information on tooth surface-level dental caries experience and tooth-level developmental defects of the enamel in the primary dentition. Dental caries experience is recorded using visual criteria modified from the International Caries Detection and Assessment System (ICDAS), and measurement of developmental defects is based upon the modified Clarkson and O'Mullane Developmental Defects of the Enamel Index. After a dental prophylaxis (toothbrushing among all children and flossing as needed), children's teeth are examined by trained and calibrated examiners in community locations, using portable dental equipment, compressed air, and uniform artificial light and magnification conditions. Data are entered directly onto a computer using a custom Microsoft Access-based data entry application. The ZOE 2.0 clinical protocol has been implemented successfully for the conduct of over 6000 research examinations to date, contributing phenotype data to downstream genomics and other "omics" studies of ECC and DDE, as well as traditional clinical and epidemiologic dental research.