The 81st Annual Meeting of the American Association of Physical Anthropologists (2012)


Caries in the primary and permanent dentitions

MARY L. MARAZITA1,2, JOHN R. SHAFFER2, ELEANOR FEINGOLD2, XIAOJING WANG1 and STEVEN M. LEVY3.

1Center for Craniofacial and Dental Genetics, Dept of Oral Biology, University of Pittsburgh, 2Dept of Human Genetics, University of Pittsburgh, 3Pediatric Dentistry, University of Iowa

Saturday 1:15-1:30, Galleria South Add to calendar

Motivation: A major challenge in studies of dental caries is defining the phenotype. Clinically relevant measures, such as the DMFS index, may not be optimal for identifying risk factors that lead to specific decay patterns, especially if the risk factors (such as genetic susceptibility loci) have small individual effects. We modeled surface-level caries data using hierarchical clustering methods to combine surfaces with similar caries risk into novel phenotypes (clusters). We then explored genetic and non-genetic risk factors for the dental caries clusters. Methods: Hierarchical clustering yielded 6 clusters of permanent dentition surfaces (from 1,069 adults): (cluster 1) occlusal surfaces of molars, (2) mandibular anterior surfaces (incisors + canines), (3) molar and premolar surfaces, (4) maxillary incisor surfaces, (5) maxillary canine and premolar surfaces, and (6) mandibular premolar surfaces. The clusters were used as phenotypes to assess the effects of environmental risk factors, estimate heritability, and perform genome-wide association scans (GWAS). Similar methods were used for surface-level caries data in the primary dentition of 561 children aged 5 years. Results: Some clusters were under genetic control (heritabilities: 31%-54%). Certain caries clusters were associated with environmental and/or genetic risk factors that were not detected using traditional caries phenotypes (DMFS) in this sample. Results of GWAS of cluster phenotypes in the permanent and primary dentitions will be presented. Conclusions: These results support the hypothesis that genetic and non-genetic risk factors lead to specific patterns of decay, and that modeling these patterns improves our efforts to identify the contributors to disease risk.

These studies were funded by NIH grants, U01-DE018903 and R01-DE014899.

Tweet
comments powered by Disqus