Class II malocclusion is present in about 15% of the population in the United States and is often characterized by a deficient mandible, leading to a convex profile, unesthetic facial proportions, and occlusal disharmonies. Both environmental and genetic factors and their interactions have been associated with Class II malocclusions; however, the etiologic mechanisms resulting in the array of dentoskeletal combinations observed in Class II patients remain elusive.

Examples of risk factors that can act on the prenatal environment include exposure to alcohol (fetal alcohol syndrome) and preterm birth, both of which have been associated with retrognathic mandibles and a Class II malocclusion. In addition, postnatal risk factors include low socioeconomic status, caries experience, premature loss of deciduous teeth, prolonged sucking habits, and resting tongue habits that might increase susceptibility to or exacerbate a Class II malocclusion and reduce treatment effectiveness. Studies of prolonged sucking habits are the most consistent, and the results indicate associations with a Class II dental relationship, decreased overbite, increased overjet, posterior crossbites, and temporomandibular joint dysfunction. Moreover, anthropologic data from remains of aboriginal Australians and other prehistoric populations point to changes from a hard to a soft diet as an important etiologic factor for the increased prevalence of Class II malocclusion in modern humans. This is presumably due to a decrease in dental attrition and a lack of compensatory tooth mesial migration associated with modern soft diets.

Severely retrognathic profiles and Class II malocclusions are common findings among other congenital craniofacial anomalies present in patients with Pierre Robin sequence and Treacher Collins, Stickler’s, and Turner’s syndromes, supporting the role of genetics in mandibular retrognathism. The Class II malocclusion has been further subdivided into Division 1 and Division 2, depending on the maxillary incisors’ proclination or retroclination, respectively, although additional skeletal and dental differences exist between the subdivision types beyond maxillary incisor angulations. Class II Division 1 cases occur more frequently (14.9%-24%) than Class II Division 2 cases (3.4%-5.9%). Interestingly, patients with a Class II Division 2 malocclusion have a higher incidence of dental anomalies compared with the normal population, suggesting that genetic factors involved in dental development might also be etiological for maxillomandibular size discrepancies.

Human genetic mapping studies of maxillomandibular size discrepancies are scarce and have focused primarily on the Class III malocclusion. So far, mandibular height and prognathism have been associated with the genes GHR , MATRILIN-1 , EPB41 , TGFB3 , LTBP2 , and MYO1H , suggesting that molecular pathways implicated in bone ( TGFB3 , LTBP ) and cartilage ( GHR , MATRILIN-1 ) development are plausible candidates for mandibular size discrepancies. For the Class II malocclusion, the authors of a small study of 4 Colombian families with mandibular hypoplasia found that all affected individuals were homozygous for the rare allele of the polymorphism rs1348322 within the NOGGIN gene, which is essential for mandibular formation in mice. No etiologic mutations have yet been identified.

The success of genetic studies aimed at identifying causative genes for malocclusion depends greatly on a well-characterized phenotype to reduce heterogeneity and prevent misclassification of affected individuals. Many studies of cross-sectional and retrospective longitudinal Class II samples with conventional cephalometry or shape analysis methods have attempted to characterize Class II dentoskeletal morphology over different developmental stages, for varying malocclusion severities, and from across global populations. In general, most studies agree that the dentoskeletal components of Class II Division 1 malocclusion include an obtuse cranial base angle, a larger cranial base length, and a normal, protruded, or retrusive maxilla. A retrusive mandible could be both deficient in its overall size and posteriorly located in relation to the cranial base. In the vertical dimension, both anterior upward or downward tipping of the maxilla and a steep mandibular plane angle with or without increased lower face height have been described. Regarding incisor angulations, studies have reported normal, proclined, and retroclined maxillary incisors and normal or proclined mandibular incisors. In addition, studies using posteroanterior cephalograms and dental models have shown higher incidences of transverse maxillary deficiencies.

In contrast, the most common dentoskeletal features in patients with Class II Division 2 malocclusion include a larger cranial base length, a normal or retrusive maxilla, mandibular retrusion, an acute gonial angle, increased posterior facial height with marked vertical development of the mandibular ramus, decreased anterior facial height and excessive bony chin, retroclined maxillary incisors, and normal or retroclined mandibular incisors. In addition to the dentoskeletal differences, particular lip features have been found for both subdivision types. In Class II Division 1, the proclination of the maxillary incisors is usually accompanied by a short upper lip and a low lip level with flaccid tone and less lip pressure that cannot counteract maxillary incisor protrusion. Conversely, a high lip level with a thicker lip shape, yet not a hypertonic muscle, is associated with maxillary incisor retroclination commonly found in the Class II Division 2 patients.

Morphometric studies of Class II samples have found mostly large differences in the size and shape of the mandible between Class II and control subjects, corroborating previous reports More sophisticated multivariate methods for cephalometric data analysis such as cluster procedures and principal components analysis have also been used to provide further insight and facilitate data interpretation beyond univariate methods. Moyers et al had the largest sample (n = 697) and applied a clustering procedure that produced 6 horizontal (A-F) and 5 vertical (1-5) overlapping subgroups ( Table I ). Among the horizontal subgroups, 4 were considered severe (B, C, D, and E), and 2 others (A and F) were mild, including maxillary dental protrusion in group A and slight mandibular retrognathism in group F. The 5 vertical subgroups were less well defined, and some occurred in 1 particular horizontal subgroup more frequently. Moyers et al classified 610 subjects in horizontal subgroups and 495 subjects into both vertical and horizontal subgroups, yet failed to classify 87 subjects. Although the methods in that study were not detailed and much of the variation remained unexplained, important Class II clinical features were visualized.

Kasai et al used a sample of 46 adult Japanese men with Class I and Class II crania to investigate the relationships between the cranial base and facial morphology and to examine differences between both malocclusion groups. A principal component analyses was done separately for the linear and angular craniofacial measurements. The authors found that 5 linear and 3 angular components explained 73% and 78.6% of the variations, respectively. The linear components depicted variations in overall facial size; negative correlations between mandibular size vs facial height, and mandibular width vs ramus height; and variations in cranial base and palatal width. In contrast, the 3 angular principal components represented variations in anteroposterior jaw relationships, horizontal discrepancies between both jaws, and variations in the symphysis and gonial angle. This study also showed that both cranial base size and angulation were accurate predictors of anteroposterior and vertical maxillomandibular relationships.

Burke et al used multivariate reduction methods to predict facial and horizontal facial morphology and established correlations with condylar head inclinations. The results showed that patients with horizontal facial morphology had anterior condylar head inclination and more superior joint space, whereas patients with vertical facial morphology showed posterior condylar head inclination and less superior condylar space, leading to a possible reduction in condylar soft tissues and less growth potential. Thus, condylar head inclination is an important aspect in the evaluation of growth potential in Class II patients.

Finally, longitudinal studies of Class II patients indicate that Class II dentoskeletal characteristics can appear as early as the deciduous dentition. Although growth curve profiles are similar between Class II and Class I subjects and catch-up growth can occur in some Class II patients, growth magnitudes and directions are different. This indicates an overall tendency for Class II discrepancies not to self-correct and instead be maintained into adulthood.

In summary, previous studies have shown large variation in the dentoskeletal features for both subdivision types of Class II malocclusion. Yet, the causes of such unfavorable dentoskeletal combinations are still unknown. To an extent, the most common components observed in Class II subjects have been described, leading to improved orthodontic diagnostics and treatment planning. However, most studies to date have limitations in sample sizes, sample selection criteria (eg, including growing subjects and not excluding other genetic or environmental traits such as missing or impacted teeth), heterogeneity due to race or ethnicity, and lack of or limited standardization of data with respect to key variables such as age and sex before applying the data reduction methods. Therefore, there is uncertainty regarding the extent to which the results from previous studies are generalizable to other samples and populations, and whether one can identify additional phenotypic variations in other samples.

The goals of this study were to extract phenotypes that can best capture the variations in a large sample of white adults with Class II malocclusion using multivariate data reduction methods and to investigate whether the identified patterns would replicate those of previous studies. We also investigated the details of age and sex effects during our attempts to carry out rigorous data standardization before application of the data reduction methods to increase the precision of the estimation. Additional goals of this study were to determine whether we could explain meaningful additional variation in this sample and to provide an improvement for the assignment of qualitative phenotypic classification for each subject in this sample. Such improvement in phenotypic classification can be important both clinically and for increasing the power of genetic studies. This study resulted in a comprehensive set of Class II phenotypes that can be used on the unbiased phenotypic characterization of additional Class II patients to increase the power of future genetic studies by strengthening the phenotype-genotype correlations.