Novel Genetic Determinants of Dental Maturation in Children

Abstract

Dental occlusion requires harmonious development of teeth, jaws, and other elements of the craniofacial complex, which are regulated by environmental and genetic factors. We performed the first genome-wide association study (GWAS) on dental development (DD) using the Demirjian radiographic method. Radiographic assessments from participants of the Generation R Study (primary study population, N1 = 2,793; mean age of 9.8 y) were correlated with ~30 million genetic variants while adjusting for age, sex, and genomic principal components (proxy for population stratification). Variants associated with DD at genome-wide significant level ( P < 5 × 10−8) mapped to 16q12.2 ( IRX5) (lead variant rs3922616, B = 0.16; P = 2.2 × 10−8). We used Fisher’s combined probability tests weighted by sample size to perform a meta-analysis ( N = 14,805) combining radiographic DD at a mean age of 9.8 y from Generation R with data from a previous GWAS ( N2 = 12,012) on number of teeth (NT) in infants used as proxy of DD at a mean age of 9.8 y (including the ALSPAC and NFBC1966). This GWAS meta-analysis revealed 3 novel loci mapping to 7p15.3 ( IGF2BP3: P = 3.2 × 10−8), 14q13.3 ( PAX9: P = 1.9 × 10−8), and 16q12.2 ( IRX5: P = 1.2 × 10−9) and validated 8 previously reported NT loci. A polygenic allele score constructed from these 11 loci was associated with radiographic DD in an independent Generation R set of children ( N = 703; B = 0.05, P = 0.004). Furthermore, profiling of the identified genes across an atlas of murine and human stem cells observed expression in the cells involved in the formation of bone and/or dental tissues (>0.3 frequency per kilobase of transcript per million mapped reads), likely reflecting functional specialization. Our findings provide biological insight into the polygenic architecture of the pediatric dental maturation process.

Identification of disease-associate variants of aggressive periodontitis using genome-wide association studies

“…In dental studies, GWAS have been employed to identify genetic factors associated with various oral health conditions and traits [12] . These conditions include periodontal disease [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , dental caries [21] , [22] , [23] , [24] , [25] , [26] , [27] , dental abnormalities [25] , [28] , [29] , [30] , and craniofacial abnormalities [31] , [32] , [33] , [34] , [35] , [36] . By analyzing a large cohort of individuals, GWAS can identify common genetic variants, including SNPs that are significantly associated with the risk or susceptibility to the dental diseases.…”