Abstract
BackgroundDental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies. Therefore, global measures of decay, such as the DMFS index, may not be optimal for identifying risk factors that manifest as specific decay patterns, especially if the risk factors such as genetic susceptibility loci have small individual effects. We used two methods to extract patterns of decay from surface-level caries data in order to generate novel phenotypes with which to explore the genetic regulation of caries.MethodsThe 128 tooth surfaces of the permanent dentition were scored as carious or not by intra-oral examination for 1,068 participants aged 18 to 75 years from 664 biological families. Principal components analysis (PCA) and factor analysis (FA), two methods of identifying underlying patterns without a priori surface classifications, were applied to our data.ResultsThe three strongest caries patterns identified by PCA recaptured variation represented by DMFS index (correlation, r = 0.97), pit and fissure surface caries (r = 0.95), and smooth surface caries (r = 0.89). However, together, these three patterns explained only 37% of the variability in the data, indicating that a priori caries measures are insufficient for fully quantifying caries variation. In comparison, the first pattern identified by FA was strongly correlated with pit and fissure surface caries (r = 0.81), but other identified patterns, including a second pattern representing caries of the maxillary incisors, were not representative of any previously defined caries indices. Some patterns identified by PCA and FA were heritable (h2 = 30-65%, p = 0.043-0.006), whereas other patterns were not, indicating both genetic and non-genetic etiologies of individual decay patterns.ConclusionsThis study demonstrates the use of decay patterns as novel phenotypes to assist in understanding the multifactorial nature of dental caries.
Highlights
Dental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies
Separating the global level of caries into components or patterns with distinct etiologies may be critical for identifying risk factors of modest effect sizes, such as specific genetic loci contributing to tooth decay
Principal components analysis PCA was performed on the surface-level data in order to extract the underlying patterns of caries
Summary
Dental caries is the result of a complex interplay among environmental, behavioral, and genetic factors, with distinct patterns of decay likely due to specific etiologies. Global measures of decay, such as the DMFS index, may not be optimal for identifying risk factors that manifest as specific decay patterns, especially if the risk factors such as genetic susceptibility loci have small individual effects. As global measures of tooth decay, DMFT and DMFS indices may not be optimal for investigating genetic and environmental factors that manifest as specific patterns of caries across the dentition. Separating the global level of caries into components or patterns with distinct etiologies may be critical for identifying risk factors of modest effect sizes, such as specific genetic loci contributing to tooth decay. A few studies have modeled the patterns of childhood tooth decay without a priori assumptions and have identified distinct patterns reflecting caries of the maxillary incisor surfaces and pit and fissure surfaces, among others [13,23,24]
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