Candidate Gene Analyses of Skeletal Variation in Malocclusion

Author:

da Fontoura C.S.G.1,Miller S.F.1,Wehby G.L.2,Amendt B.A.3,Holton N.E.14,Southard T.E.4,Allareddy V.5,Moreno Uribe L.M.14

Affiliation:

1. Dows Institute for Research, College of Dentistry, University of Iowa, Iowa City, IA, USA

2. Department of Health Management and Policy, College of Public Health, University of Iowa, Iowa City, IA, USA

3. Department of Anatomy and Cell Biology, Carver College of Medicine, University of Iowa, Iowa City, IA, USA

4. Department of Orthodontics, College of Dentistry, University of Iowa, Iowa City, IA, USA

5. Department of Oral Pathology-Radiology and Medicine, University of Iowa, Iowa City, IA, USA

Abstract

This study evaluated associations between craniofacial candidate genes and skeletal variation in patients with malocclusion. Lateral cephalometric radiographs of 269 untreated adults with skeletal classes I, II, and III malocclusion were digitized with 14 landmarks. Two-dimensional coordinates were analyzed using Procrustes fit and principal component (PC) analysis to generate continuous malocclusion phenotypes. Skeletal class classifications (I, II, or III) were used as a categorical phenotype. Individuals were genotyped for 198 single-nucleotide polymorphisms (SNPs) in 71 craniofacial genes and loci. Phenotype-genotype associations were tested via multivariate linear regression for continuous phenotypes and multinomial logistic regression for skeletal malocclusion class. PC analysis resulted in 4 principal components (PCs) explaining 69% of the total skeletal facial variation. PC1 explained 32.7% of the variation and depicted vertical discrepancies ranging from skeletal deep to open bites. PC1 was associated with a SNP near PAX5 ( P = 0.01). PC2 explained 21.7% and captured horizontal maxillomandibular discrepancies. PC2 was associated with SNPs upstream of SNAI3 ( P = 0.0002) and MYO1H ( P = 0.006). PC3 explained 8.2% and captured variation in ramus height, body length, and anterior cranial base orientation. PC3 was associated with TWIST1 ( P = 0.000076). Finally, PC4 explained 6.6% and detected variation in condylar inclination as well as symphysis projection. PC4 was associated with PAX7 ( P = 0.007). Furthermore, skeletal class II risk increased relative to class I with the minor alleles of SNPs in FGFR2 (odds ratio [OR] = 2.1, P = 0.004) and declined with SNPs in EDN1 (OR = 0.5, P = 0.007). Conversely, skeletal class III risk increased versus class I with SNPs in FGFR2 (OR 2.2, P = 0.005) and COL1A1 (OR = 2.1, P = 0.008) and declined with SNPs in TBX5 (OR = 0.5, P = 0.014). PAX5, SNAI3, MYO1H, TWIST1, and PAX7 are associated with craniofacial skeletal variation among patients with malocclusion, while FGFR2, EDN1, TBX5, and COL1A1 are associated with type of skeletal malocclusion.

Publisher

SAGE Publications

Subject

General Dentistry

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