OBJECTIVES: To characterize soft-tissue facial height and width variation in Class II malocclusion and test for correlations with genes HMGA2, AJUBA, and ADK. SETTING AND SAMPLE POPULATION: Nine facial proportions were estimated from 2D frontal repose photographs of 330 Caucasian adults with Class II malocclusion. MATERIAL AND METHODS: After adjustments for age and gender, the facial proportions were submitted to a principal component analyses (PCA). The most meaningful phenotypic variations were correlated with SNPs rs7924176 (ADK), rs17101923 (HMGA2), and rs997154 (AJUBA) genotyped in 106 individuals. RESULTS: Principal component analyses resulted in four principal components (PCs), which explained 75% of total variation. PC1 captured variation in the intercanthus distance and explained 28% of total variation. PC2 explained 21% of the variations in facial taper and facial index. PC3 explained 14% and reflected variations in the vertical dimension of the lower face. PC4 explained 12% and captured variations in distance between the eyes, width of the commissures, and the length of the superior aspect of the lower face height corresponding to the vertical dimension of the philtrum of the upper lip. A suggestive association (p<0.05) was observed between PC4 and rs997154 corroborating the role of AJUBA in variation of facial dimensions. CONCLUSION: 2D frontal photographs can be used to derive quantitative measures of soft-tissue phenotypes that are of clinical relevance. The methods described are suitable for discovery and replication of associations between genotypes and malocclusion phenotypes.
OBJECTIVES: To characterize soft-tissue facial height and width variation in Class II malocclusion and test for correlations with genes HMGA2, AJUBA, and ADK. SETTING AND SAMPLE POPULATION: Nine facial proportions were estimated from 2D frontal repose photographs of 330 Caucasian adults with Class II malocclusion. MATERIAL AND METHODS: After adjustments for age and gender, the facial proportions were submitted to a principal component analyses (PCA). The most meaningful phenotypic variations were correlated with SNPs rs7924176 (ADK), rs17101923 (HMGA2), and rs997154 (AJUBA) genotyped in 106 individuals. RESULTS: Principal component analyses resulted in four principal components (PCs), which explained 75% of total variation. PC1 captured variation in the intercanthus distance and explained 28% of total variation. PC2 explained 21% of the variations in facial taper and facial index. PC3 explained 14% and reflected variations in the vertical dimension of the lower face. PC4 explained 12% and captured variations in distance between the eyes, width of the commissures, and the length of the superior aspect of the lower face height corresponding to the vertical dimension of the philtrum of the upper lip. A suggestive association (p<0.05) was observed between PC4 and rs997154 corroborating the role of AJUBA in variation of facial dimensions. CONCLUSION: 2D frontal photographs can be used to derive quantitative measures of soft-tissue phenotypes that are of clinical relevance. The methods described are suitable for discovery and replication of associations between genotypes and malocclusion phenotypes.
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