Facial biometry of Amazon indigenous people of the Xingu River - Perspectives on genetic and environmental contributions to variation in human facial morphology

Correlation Between Maxillary Anterior Teeth and Common Facial Measurements

Background

The symmetry between maxillary anterior teeth and the face holds significant importance. This study assessed and analyzed the relationship between facial parameters and anterior teeth in the maxillary arch of male and female subjects. Specifically, individual width and combined width (CW) measurements of the maxillary anterior teeth were investigated.

Methods

This study involved a total of 150 dentate Yemeni subjects (74 men and 76 women), whose ages ranged from 18 years old to 30 years old. A maxillary cast was created, and two digital photographs of the face of each subject were taken and analyzed. Digital calipers and AutoCAD were used to gather measurement data of the dental parameters (intercanthal distance [ICD], interpupillary distance [IPD], interalar width [IAW], intercommissural width [ICW], and bizygomatic width [BZW]) and facial parameters (profile distance).

Results

Significant correlations were found for the following: IPD and width of six maxillary anterior teeth of each of the study subjects; ICD and their central incisors; and BZW and their canine width measurements. In contrast, IAW and ICW were not correlated with all tooth measurements. Linear regression findings showed that the CW measurement of the four incisors was significantly correlated with all facial parameter measurements, excluding the ICW and IAW in females and the IAW, ICW, and profile distance in males.

Conclusion

The IPD and ICD of males and females may be used to determine their CW measurements. The BZW and IPD of males can be used to take precise anthropological measurements of the width of the central canines and incisors. Meanwhile, the IPD distance of females can be used to assess the central and lateral incisor widths.

Three-dimensional phenotype characteristics of skeletal class III malocclusion in adult Chinese: a principal component analysis-based cluster analysis

BACKGROUND

Skeletal class III malocclusion has a diverse and complicated aetiology involving environmental and genetic factors. It is critical to correctly classify and define this malocclusion to be diagnosed and treated on a clinically sound basis. Thus, this study aimed to provide reliable and detailed measurements in a large ethnically homogeneous sample of Chinese adults to generate an adequate phenotypic clustering model to identify and describe the skeletal variation present in skeletal class III malocclusion.

MATERIALS AND METHODS

This is a retrospective cross-sectional study in which 500 pre-treatments cone-beam computed tomography (CBCT) scans of patients with skeletal class III malocclusion (250 males and 250 females) were selected following specific selection criteria. Seventy-six linear, angular, and ratios measurements were three-dimensionally analysed using InVivo 6.0.3 software. These measurements were categorised into 47 skeletal, 18 dentoalveolar, and 11 soft tissue variables. Multivariate reduction methods: principal component analyses and cluster analyses were used to present the most common phenotypic groupings of skeletal class III malocclusion in Han ethnic group of Chinese adults.

RESULTS

The principal component analysis revealed eight principal components accounted for 72.9% of the overall variation of the data produced from the seventy-six variables. The first four principal components accounted for 53.37% of the total variations. They explained the most variation in data and consisted mainly of anteroposterior and vertical skeletal relationships. The cluster analysis identified four phenotypes of skeletal class III malocclusion: C1, 34%; C2, 11.4%; C3, 26.4%; and C4, 28.2%.

CONCLUSION

Based on three-dimensional analyses, four skeletal class III malocclusion distinct phenotypic variations were defined in a large sample of the adult Chinese population, showing the occurrence of phenotypic variation between identified clusters in the same ethnic group. These findings might serve as a foundation for accurate diagnosis and treatment planning of each cluster and future genetic studies to determine the causative gene(s) of each cluster.

Sub-clustering in skeletal class III malocclusion phenotypes via principal component analysis in a southern European population

The main aim of this study was to generate an adequate sub-phenotypic clustering model of class III skeletal malocclusion in an adult population of southern European origin. The study design was conducted in two phases, a preliminary cross-sectional study and a subsequent discriminatory evaluation by main component and cluster analysis to identify differentiated skeletal sub-groups with differentiated phenotypic characteristics. Radiometric data from 699 adult patients of southern European origin were analyzed in 212 selected subjects affected by class III skeletal malocclusion. The varimax rotation was used with Kaiser normalization, to prevent variables with more explanatory capacity from affecting the rotation. A total of 21,624 radiographic measurements were obtained as part of the cluster model generation, using a total set of 55 skeletal variables for the subsequent analysis of the major component and cluster analyses. Ten main axes were generated representing 92.7% of the total variation. Three main components represented 58.5%, with particular sagittal and vertical variables acting as major descriptors. Post hoc phenotypic clustering retrieved six clusters: C1:9.9%, C2:18.9%, C3:33%, C4:3.77%, C5:16%, and C6:16%. In conclusion, phenotypic variation was found in the southern European skeletal class III population, demonstrating the existence of phenotypic variations between identified clusters in different ethnic groups.

Subclustering in Skeletal Class III Phenotypes of Different Ethnic Origins: A Systematic Review

OBJECTIVE

We aimed to systematically review articles investigating the efficiency of the clustering of skeletal class III malocclusion phenotypic subtypes of different ethnic origins as a diagnostic tool.

METHODS

The review protocol was structured in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and registered in Prospero (CRD42016053865). A survey of articles published up to March 2018 investigating the identification of different subgroups of skeletal class III malocclusion via cluster analysis was performed using 11 electronic databases. Any type of study design that addressed the classification of subclusters of class III malocclusion was considered. The Newcastle-Ottawa scale for cohort and cross-sectional (modified) studies was used for quality assessment.

RESULTS

The final selection included 7 studies that met all the criteria for eligibility (% overall agreement 0.889, free marginal kappa 0.778). All studies identified at least 3 different types of class III clusters (ranging from 3 to 14 clusters; the total variation of the prevalence of each cluster ranged from 0.2% to 36.0%). The main shared variables used to describe the more prevalent clusters in the studies included were vertical measurements (Ar-Go-Me: 117.51°-135.8°); sagittal measurements: maxilla (SNA: 75.3°-82.95°), mandible (SNB: 77.03°-85.0°). With regard to ethnicity, a mean number of 8.5 and 3.5 clusters of class III were retrieved for Asian and Caucasian population, respectively.

CONCLUSIONS

The total number of clusters identified varied from 3 to 14 to explain all the variability in the phenotype class III malocclusions. Although each extreme may be too simple or complex to facilitate an exhaustive but useful classification for clinical use, a classification system including 4 to 7 clusters may prove to be efficient for clinical use in conjunction with complete and meticulous subgrouping.

CLINICAL SIGNIFICANCE

The identification and description of a subclustering classification system may constitute an additional step toward more precise orthodontic/orthopedic diagnosis and treatment of skeletal class III malocclusion.