A common cis-regulatory variant impacts normal-range and disease-associated human facial shape through regulation of PKDCC during chondrogenesis.

Genome-wide association studies (GWAS) identified thousands of genetic variants linked to phenotypic traits and disease risk. However, mechanistic understanding of how GWAS variants influence complex morphological traits and can, in certain cases, simultaneously confer normal-range phenotypic variation and disease predisposition, is still largely lacking. Here, we focus on rs6740960, a single nucleotide polymorphism (SNP) at the 2p21 locus, which in GWAS studies has been associated both with normal-range variation in jaw shape and with an increased risk of non-syndromic orofacial clefting. Using in vitro derived embryonic cell types relevant for human facial morphogenesis, we show that this SNP resides in an enhancer that regulates chondrocytic expression of PKDCC - a gene encoding a tyrosine kinase involved in chondrogenesis and skeletal development. In agreement, we demonstrate that the rs6740960 SNP is sufficient to confer chondrocyte-specific differences in PKDCC expression. By deploying dense landmark morphometric analysis of skull elements in mice, we show that changes in Pkdcc dosage are associated with quantitative changes in the maxilla, mandible, and palatine bone shape that are concordant with the facial phenotypes and disease predisposition seen in humans. We further demonstrate that the frequency of the rs6740960 variant strongly deviated among different human populations, and that the activity of its cognate enhancer diverged in hominids. Our study provides a mechanistic explanation of how a common SNP can mediate normal-range and disease-associated morphological variation, with implications for the evolution of human facial features.

Automated 3D Landmarking of the Skull: A Novel Approach for Craniofacial Analysis.

Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising 9,999 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (>0.988), and automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.

An interactive atlas of three-dimensional syndromic facial morphology.

Craniofacial phenotyping is critical for both syndrome delineation and diagnosis because craniofacial abnormalities occur in 30% of characterized genetic syndromes. Clinical reports, textbooks, and available software tools typically provide two-dimensional, static images and illustrations of the characteristic phenotypes of genetic syndromes. In this work, we provide an interactive web application that provides three-dimensional, dynamic visualizations for the characteristic craniofacial effects of 95 syndromes. Users can visualize syndrome facial appearance estimates quantified from data and easily compare craniofacial phenotypes of different syndromes. Our application also provides a map of morphological similarity between a target syndrome and other syndromes. Finally, users can upload 3D facial scans of individuals and compare them to our syndrome atlas estimates. In summary, we provide an interactive reference for the craniofacial phenotypes of syndromes that allows for precise, individual-specific comparisons of dysmorphology.

Ulnar shape of extant primates: Functional signals and covariation with triquetrum shape.

OBJECTIVES: In this study, we investigated the shape differences of the distal ulna in a phylogenetic context among a broad range of primate taxa. Furthermore, we evaluated covariation between ulnar and triquetrum shape and a possible association between ulnar shape and locomotor behavior. MATERIALS AND METHODS: We applied 3D geometric morphometrics on a large dataset comprising the distal ulna of 124 anthropoid primate specimens belonging to 12 different genera. For each species, a mean shape was calculated using 11 Procrustes-aligned surface landmarks on the distal ulna. These mean shapes are used in a bgPCA, pPCA, and PACA and 3D morphs were used to visualize more subtle differences between taxa. A p2B-PLS analysis was performed to test the covariance between distal ulnar and triquetrum shape. RESULTS: The results show that more closely related species exhibit a similar distal ulnar shape. Overall, extant hominid ulnae show a shape shift compared to those of extant monkeys and hylobatids. This includes a shortening of the ulnar styloid process and dorspalmarly widening of the ulnar head, shape characteristics that are independent of phylogeny. Within the hominids, Pongo pygmaeus seem to possess the most plesiomorphic distal ulnar shape, while Gorilla and Homo sapiens display the most derived distal ulna. Cercopithecoids, hylobatids, and P. pygmaeus are characterized by a relatively deep ECU groove, which is a shape trait dependent of phylogeny. Although there was no significant covariation between distal ulnar shape and triquetrum shape, the shape differences of the distal ulna between the different primate taxa reveal a possible link with locomotor behavior. CONCLUSIONS: The comparative analyses of this study reveal different shape trends in a phylogenetic context. Highly arboreal primates, such as hylobatids and Ateles fusciceps, show a distal ulnar morphology that appears to be adapted to tensile and torsional forces. In primates that use their wrist under more compressive conditions, such as quadrupedal cercopithecoids and great apes, the distal ulnar morphology seems to reflect increased compressive forces. In modern humans, the distal ulnar shape can be associated to enhanced manipulative skills and power grips. There was no significant covariation between distal ulnar shape and triquetrum shape, probably due to the variation in the amount of contact between the triquetrum and ulna. In combination with future research on wrist mobility in diverse primate taxa, the results of this study will allow us to establish form-function relationships of the primate wrist and contribute towards an evidence-based interpretation of fossil remains.

Syndrome-informed phenotyping identifies a polygenic background for achondroplasia-like facial variation in the general population.

Human craniofacial shape is highly variable yet highly heritable with genetic variants interacting through multiple layers of development. Here, we hypothesize that Mendelian phenotypes represent the extremes of a phenotypic spectrum and, using achondroplasia as an example, we introduce a syndrome-informed phenotyping approach to identify genomic loci associated with achondroplasia-like facial variation in the normal population. We compared three-dimensional facial scans from 43 individuals with achondroplasia and 8246 controls to calculate achondroplasia-like facial scores. Multivariate GWAS of the control scores revealed a polygenic basis for normal facial variation along an achondroplasia-specific shape axis, identifying genes primarily involved in skeletal development. Jointly modeling these genes in two independent control samples showed craniofacial effects approximating the characteristic achondroplasia phenotype. These findings suggest that both complex and Mendelian genetic variation act on the same developmentally determined axes of facial variation, providing new insights into the genetic intersection of complex traits and Mendelian disorders.

A statistical shape model for estimating missing soft tissues of the face in a black South African population.

PURPOSE: Facial disfigurement may affect the quality of life of many patients. Facial prostheses are often used as an adjuvant to surgical intervention and may sometimes be the only viable treatment option. Traditional methods for designing soft-tissue facial prostheses are time-consuming and subjective, while existing digital techniques are based on mirroring of contralateral features of the patient, or the use of existing feature templates/models that may not be readily available. We aim to support the objective and semi-automated design of facial prostheses with primary application to midline or bilateral defect restoration where no contralateral features are present. Specifically, we developed and validated a statistical shape model (SSM) for estimating the shape of missing facial soft tissue segments, from any intact parts of the face. MATERIALS AND METHODS: An SSM of 3D facial variations was built from meshes extracted from computed tomography and cone beam computed tomography images of a black South African sample (n = 235) without facial disfigurement. Various types of facial defects were simulated, and the missing parts were estimated automatically by a weighted fit of each mesh to the SSM. The estimated regions were compared to the original regions using color maps and root-mean-square (RMS) distances. RESULTS: Root mean square errors (RMSE) for defect estimations of one orbit, partial nose, cheek, and lip were all below 1.71 mm. Errors for the full nose, bi-orbital defects, as well as small and large composite defects were between 2.10 and 2.58 mm. Statistically significant associations of age and type of defect with RMSE were observed, but not with sex or imaging modality. CONCLUSION: This method can support the objective and semi-automated design of facial prostheses, specifically for defects in the midline, crossing the midline or bilateral defects, by facilitating time-consuming and skill-dependent aspects of prosthesis design.

Precise modulation of transcription factor levels identifies features underlying dosage sensitivity.

Transcriptional regulation exhibits extensive robustness, but human genetics indicates sensitivity to transcription factor (TF) dosage. Reconciling such observations requires quantitative studies of TF dosage effects at trait-relevant ranges, largely lacking so far. TFs play central roles in both normal-range and disease-associated variation in craniofacial morphology; we therefore developed an approach to precisely modulate TF levels in human facial progenitor cells and applied it to SOX9, a TF associated with craniofacial variation and disease (Pierre Robin sequence (PRS)). Most SOX9-dependent regulatory elements (REs) are buffered against small decreases in SOX9 dosage, but REs directly and primarily regulated by SOX9 show heightened sensitivity to SOX9 dosage; these RE responses partially predict gene expression responses. Sensitive REs and genes preferentially affect functional chondrogenesis and PRS-like craniofacial shape variation. We propose that such REs and genes underlie the sensitivity of specific phenotypes to TF dosage, while buffering of other genes leads to robust, nonlinear dosage-to-phenotype relationships.

Exploring regional aspects of 3D facial variation within European individuals.

Facial ancestry can be described as variation that exists in facial features that are shared amongst members of a population due to environmental and genetic effects. Even within Europe, faces vary among subregions and may lead to confounding in genetic association studies if unaccounted for. Genetic studies use genetic principal components (PCs) to describe facial ancestry to circumvent this issue. Yet the phenotypic effect of these genetic PCs on the face has yet to be described, and phenotype-based alternatives compared. In anthropological studies, consensus faces are utilized as they depict a phenotypic, not genetic, ancestry effect. In this study, we explored the effects of regional differences on facial ancestry in 744 Europeans using genetic and anthropological approaches. Both showed similar ancestry effects between subgroups, localized mainly to the forehead, nose, and chin. Consensus faces explained the variation seen in only the first three genetic PCs, differing more in magnitude than shape change. Here we show only minor differences between the two methods and discuss a combined approach as a possible alternative for facial scan correction that is less cohort dependent, more replicable, non-linear, and can be made open access for use across research groups, enhancing future studies in this field.

Influence of age and diet consistency on the oral muscle pressure of orthodontically treated and untreated subjects with normal occlusion and comparison of their 3D facial shape.

OBJECTIVES: (1) To investigate the effect of age and diet consistency on maximum lips, tongue and cheek pressure of orthodontically treated and untreated subjects with normal, Class I dental occlusion, (2) to find out whether there is a muscle imbalance between anterior tongue and lip pressure in the same subjects at different ages and (3) to compare the 3D facial shape of treated and untreated individuals. MATERIAL AND METHODS: Subjects with normal occlusion were prospectively grouped into orthodontically treated/untreated and in children/adolescents/adults. Iowa Oral Performance Instrument was used to record the maximum muscle pressure. Two-way ANOVA and Tukey post hoc test analysed age-specific differences in muscle pressure. Two-way ANCOVA analysed the effect of diet consistency on muscle pressure. Lips and tongue imbalance was analysed using z-scores and 3D faces using a generalized Procrustes analysis. RESULTS: One hundred thirty-five orthodontically untreated and 114 treated participants were included. Muscle pressure was found to increase with age in both groups, except for the tongue in treated subjects. No differences in the balance between lips and tongue muscle pressure were found, but a higher cheek pressure in untreated adults (p<0.05) was observed. 3D facial shapes showed subtle differences. Untreated subjects with soft diet consistency showed lower lip pressure (p<0.05). CONCLUSION: Oral muscle pressure of orthodontically treated patients without relapse does not differ from that of untreated patients with Class-I occlusion. CLINICAL RELEVANCE: This study provides normative lip, tongue and cheek muscle pressure in subjects with normal occlusion, which can be used for diagnosis, treatment planning and stability.

Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology.

The effects of sex on human facial morphology have been widely documented. Because sexual dimorphism is relevant to a variety of scientific and applied disciplines, it is imperative to have a complete and accurate account of how and where male and female faces differ. We apply a comprehensive facial phenotyping strategy to a large set of existing 3D facial surface images. We investigate facial sexual dimorphism in terms of size, shape, and shape variance. We also assess the ability to correctly assign sex based on shape, both for the whole face and for subregions. We applied a predefined data-driven segmentation to partition the 3D facial surfaces of 2446 adults into 63 hierarchically linked regions, ranging from global (whole face) to highly localized subparts. Each facial region was then analyzed with spatially dense geometric morphometrics. To describe the major modes of shape variation, principal components analysis was applied to the Procrustes aligned 3D points comprising each of the 63 facial regions. Both nonparametric and permutation-based statistics were then used to quantify the facial size and shape differences and visualizations were generated. Males were significantly larger than females for all 63 facial regions. Statistically significant sex differences in shape were also seen in all regions and the effects tended to be more pronounced for the upper lip and forehead, with more subtle changes emerging as the facial regions became more granular. Males also showed greater levels of shape variance, with the largest effect observed for the central forehead. Classification accuracy was highest for the full face (97%), while most facial regions showed an accuracy of 75% or greater. In summary, sex differences in both size and shape were present across every part of the face. By breaking the face into subparts, some shape differences emerged that were not apparent when analyzing the face as a whole. The increase in facial shape variance suggests possible evolutionary origins and may offer insights for understanding congenital facial malformations. Our classification results indicate that a high degree of accuracy is possible with only parts of the face, which may have implications for biometrics applications.

Quantification and visualization of the tooth extraction effects on face with spatially dense geometric morphometrics.

PURPOSE: To apply geometric morphometrics and multivariate statistics to evaluate changes of the face for female Chinese patients who underwent orthodontic treatment with different type of anchorage control. METHODS: Forty-six adult female patients were enrolled including 33 four first premolar extraction cases (17 patients with mini-implants for maximum anchorage control and 16 patients without mini-implants) and 13 non-extraction cases with minimum treatment duration of 15 months. Spatially dense correspondence was established among all the images The pre-and post-treatment average faces of the two extraction groups and the non-extraction group were generated. Partial least squares regression was used to test the statistical significance of the effects of treatment for different anchorage choice. RESULTS: The upper and lower lips were retruded significantly after treatment in the extraction groups. In the maximum anchorage control group, the temple and cheek were depressed by approximately 1 mm, and the zygomatic regions were increased in the mid-face. However, these changes were not statistically significant. In comparison, no statistically significant facial changes occurred in the non-extraction group. CONCLUSIONS: The anchorage choice and the removal of four first premolar extraction influence lip shape as well as the perioral regions. However, extraction treatment does not impact the appearance of the cheeks and temples on a statistically level, as compared to orthodontic treatment without premolar extractions. Spatially dense geometric morphometric facilitates comprehensive treatment effect quantification and visualization on the full facial changes for improving orthodontic outcome evaluation.

Age- and sex-related differences in 3D facial shape and muscle pressure in subjects with normal occlusion.

BACKGROUND AND OBJECTIVE(S): (1) To derive descriptive statistics of three-dimensional (3D) facial shape, lip and cheek muscle pressure in subjects of European descent with normal dental occlusion. (2) To analyse the effect of age and sex on 3D-facial soft tissue morphology and muscle pressure in the same sample. (3) To assess the independent effect of muscle pressure on face shape. METHOD: 129 subjects with normal occlusion were cross-sectionally recruited and divided into: children (mixed dentition), adolescents and adults (permanent dentition, < and ≥18 years respectively). Muscle pressure was recorded using the Iowa Oral Performance Instrument. MeshLab, MeVisLab and Meshmonk tool box were used to clean, annotate landmarks and generate the 3D images. Two-way analysis of variance and post-hoc tests were used to analyse age and sex differences in face shape and muscle pressure. The effect of muscle pressure on face shape was analysed by Pearson correlation and Partial Least Square regression. RESULTS: Significant facial differences were observed between adults and adolescents and adults and children in both sexes, showing flattening of cheeks and lips and protrusion of nose and chin. Significant cheek protrusion and retrusion of the vertical midface were found in adult women compared to men. Lip and cheek pressure increased with age, but their effect on face shape was not significant. CONCLUSIONS: This study provides 3D age- and sex-specific facial models and muscle pressure of subjects without malocclusion. These can be used as a reference for clinicians focused on facial assessment in treatment planning and follow-up.

Nasal characteristics in patients with asymmetric mandibular prognathism.

INTRODUCTION: To objectively quantify nasal characteristics of patients with asymmetric mandibular prognathism and to evaluate the association between nasal asymmetry and dentofacial abnormalities. METHODS: Ninety adult patients with asymmetric mandibular prognathism were included. Images were captured during pretreatment using 3-dimensional stereophotogrammetry. A total of 7160 uniformly sampled quasi-landmarks were automatically identified on each facial image to establish correspondence using a template mapping technique. Fifteen commonly used anatomic landmarks were automatically located on each image through barycentric to Cartesian coordinate conversion. Nasal characteristics and asymmetry were quantified by anthropometric linear distances, angular measurements, and surface-based analysis. The degree of the nasal, chin, and periorbital asymmetry in a patient was scored using a root-mean-squared error between the left and right sides. The correlations among these regional asymmetries were evaluated. RESULTS: The nasal tip was significantly shifted to the deviated side of the chin, and the nostrils were asymmetrical. The location and degree of nasal asymmetry varied among patients with asymmetric mandibular prognathism. The level of nasal asymmetry was significantly and positively correlated with chin and periorbital asymmetry. CONCLUSIONS: Nasal asymmetry is present in asymmetric mandibular prognathism patients. Furthermore, it is positively associated with periorbital deviation and chin deviation. Individualized nasal asymmetry evaluation should be performed, and clinicians should inform patients about preexisting nasal asymmetry.

Refining nosology by modelling variation among facial phenotypes: the RASopathies.

BACKGROUND: In clinical genetics, establishing an accurate nosology requires analysis of variations in both aetiology and the resulting phenotypes. At the phenotypic level, recognising typical facial gestalts has long supported clinical and molecular diagnosis; however, the objective analysis of facial phenotypic variation remains underdeveloped. In this work, we propose exploratory strategies for assessing facial phenotypic variation within and among clinical and molecular disease entities and deploy these techniques on cross-sectional samples of four RASopathies: Costello syndrome (CS), Noonan syndrome (NS), cardiofaciocutaneous syndrome (CFC) and neurofibromatosis type 1 (NF1). METHODS: From three-dimensional dense surface scans, we model the typical phenotypes of the four RASopathies as average 'facial signatures' and assess individual variation in terms of direction (what parts of the face are affected and in what ways) and severity of the facial effects. We also derive a metric of phenotypic agreement between the syndromes and a metric of differences in severity along similar phenotypes. RESULTS: CFC shows a relatively consistent facial phenotype in terms of both direction and severity that is similar to CS and NS, consistent with the known difficulty in discriminating CFC from NS based on the face. CS shows a consistent directional phenotype that varies in severity. Although NF1 is highly variable, on average, it shows a similar phenotype to CS. CONCLUSIONS: We established an approach that can be used in the future to quantify variations in facial phenotypes between and within clinical and molecular diagnoses to objectively define and support clinical nosologies.

Static and Motion Facial Analysis for Craniofacial Assessment and Diagnosing Diseases.

Deviation from a normal facial shape and symmetry can arise from numerous sources, including physical injury and congenital birth defects. Such abnormalities can have important aesthetic and functional consequences. Furthermore, in clinical genetics distinctive facial appearances are often associated with clinical or genetic diagnoses; the recognition of a characteristic facial appearance can substantially narrow the search space of potential diagnoses for the clinician. Unusual patterns of facial movement and expression can indicate disturbances to normal mechanical functioning or emotional affect. Computational analyses of static and moving 2D and 3D images can serve clinicians and researchers by detecting and describing facial structural, mechanical, and affective abnormalities objectively. In this review we survey traditional and emerging methods of facial analysis, including statistical shape modeling, syndrome classification, modeling clinical face phenotype spaces, and analysis of facial motion and affect.

Automated assessment of mandibular shape asymmetry in 3-dimensions.

INTRODUCTION: This study aimed to develop an automatic pipeline for analyzing mandibular shape asymmetry in 3-dimensions. METHODS: Forty patients with skeletal Class I pattern and 80 patients with skeletal Class III pattern were used. The mandible was automatically segmented from the cone-beam computed tomography images using a U-net deep learning network. A total of 17,415 uniformly sampled quasi-landmarks were automatically identified on the mandibular surface via a template mapping technique. After alignment with the robust Procrustes superimposition, the pointwise surface-to-surface distance between original and reflected mandibles was visualized in a color-coded map, indicating the location of asymmetry. The degree of overall mandibular asymmetry and the asymmetry of subskeletal units were scored using the root-mean-squared-error between the left and right sides. These asymmetry parameters were compared between the skeletal Class I and skeletal Class III groups. RESULTS: The mandible shape was significantly more asymmetrical in patients with skeletal Class III pattern with positional asymmetry. The condyles were identified as the most asymmetric region in all groups, followed by the coronoid process and the ramus. CONCLUSIONS: This automated approach to quantify mandibular shape asymmetry will facilitate high-throughput image processing for big data analysis. The spatially-dense landmarks allow for evaluating mandibular asymmetry over the entire surface, which overcomes the information loss inherent in conventional linear distance or angular measurements. Precise quantification of the asymmetry can provide important information for individualized diagnosis and treatment planning in orthodontics and orthognathic surgery.

Facial asymmetry assessment in skeletal Class III patients with spatially-dense geometric morphometrics.

OBJECTIVE: Quantification and visualization of the location and magnitude of facial asymmetry is important for diagnosis and treatment planning. The objective of this study was to analyze the asymmetric features of the face for skeletal Class III patients using spatially-dense geometric morphometrics. METHODS: Three-dimensional facial images were obtained for 86 skeletal Class III patients. About 7160 uniformly sampled quasi-landmarks were automatically identified on each face using template mapping technique. The pointwise surface-to-surface distance between original and mirror face was measured and visualized for the whole face after robust Procrustes superimposition. The degree of overall asymmetry in an individual was scored using a root-mean-squared-error. Automatic partitioning of the face was obtained, and the severity of the asymmetry compared among seven facial regions. RESULTS: Facial asymmetry was mainly located on, but not limited to, the lower two-thirds of the face in skeletal Class III patients. The lower cheek and nose asymmetry were detected to have more extensive and of a greater magnitude of asymmetry than other facial anatomical regions but with various individual variations. The overall facial asymmetry index and the regional facial asymmetry indices were higher in males and patients with chin deviation. CONCLUSIONS: Soft tissue asymmetry is predominately presented in the lower-third of the face in skeletal Class III patients and with various variations on other facial anatomical regions. Morphometric techniques and computer intensive analysis have allowed sophisticated quantification and visualization of the pointwise asymmetry on the full face.

Genome scans of facial features in East Africans and cross-population comparisons reveal novel associations.

Facial morphology is highly variable, both within and among human populations, and a sizable portion of this variation is attributable to genetics. Previous genome scans have revealed more than 100 genetic loci associated with different aspects of normal-range facial variation. Most of these loci have been detected in Europeans, with few studies focusing on other ancestral groups. Consequently, the degree to which facial traits share a common genetic basis across diverse sets of humans remains largely unknown. We therefore investigated the genetic basis of facial morphology in an East African cohort. We applied an open-ended data-driven phenotyping approach to a sample of 2,595 3D facial images collected on Tanzanian children. This approach segments the face into hierarchically arranged, multivariate features that capture the shape variation after adjusting for age, sex, height, weight, facial size and population stratification. Genome scans of these multivariate shape phenotypes revealed significant (p < 2.5 × 10-8) signals at 20 loci, which were enriched for active chromatin elements in human cranial neural crest cells and embryonic craniofacial tissue, consistent with an early developmental origin of the facial variation. Two of these associations were in highly conserved regions showing craniofacial-specific enhancer activity during embryological development (5q31.1 and 12q21.31). Six of the 20 loci surpassed a stricter threshold accounting for multiple phenotypes with study-wide significance (p < 6.25 × 10-10). Cross-population comparisons indicated 10 association signals were shared with Europeans (seven sharing the same associated SNP), and facilitated fine-mapping of causal variants at previously reported loci. Taken together, these results may point to both shared and population-specific components to the genetic architecture of facial variation.

Exploring palatal and dental shape variation with 3D shape analysis and geometric deep learning.

OBJECTIVES: Palatal shape contains a lot of information that is of clinical interest. Moreover, palatal shape analysis can be used to guide or evaluate orthodontic treatments. A statistical shape model (SSM) is a tool that, by means of dimensionality reduction, aims at compactly modeling the variance of complex shapes for efficient analysis. In this report, we evaluate several competing approaches to constructing SSMs for the human palate. SETTING AND SAMPLE POPULATION: This study used a sample comprising digitized 3D maxillary dental casts from 1,324 individuals. MATERIALS AND METHODS: Principal component analysis (PCA) and autoencoders (AE) are popular approaches to construct SSMs. PCA is a dimension reduction technique that provides a compact description of shapes by uncorrelated variables. AEs are situated in the field of deep learning and provide a non-linear framework for dimension reduction. This work introduces the singular autoencoder (SAE), a hybrid approach that combines the most important properties of PCA and AEs. We assess the performance of the SAE using standard evaluation tools for SSMs, including accuracy, generalization, and specificity. RESULTS: We found that the SAE obtains equivalent results to PCA and AEs for all evaluation metrics. SAE scores were found to be uncorrelated and provided an optimally compact representation of the shapes. CONCLUSION: We conclude that the SAE is a promising tool for 3D palatal shape analysis, which effectively combines the power of PCA with the flexibility of deep learning. This opens future AI driven applications of shape analysis in orthodontics and other related clinical disciplines.

Automated landmarking for palatal shape analysis using geometric deep learning.

OBJECTIVES: To develop and evaluate a geometric deep-learning network to automatically place seven palatal landmarks on digitized maxillary dental casts. SETTINGS AND SAMPLE POPULATION: The sample comprised individuals with permanent dentition of various ethnicities. The network was trained from manual landmark annotations on 732 dental casts and evaluated on 104 dental casts. MATERIALS AND METHODS: A geometric deep-learning network was developed to hierarchically learn features from point-clouds representing the 3D surface of each cast. These features predict the locations of seven palatal landmarks. RESULTS: Repeat-measurement reliability was <0.3 mm for all landmarks on all casts. Accuracy is promising. The proportion of test subjects with errors less than 2 mm was between 0.93 and 0.68, depending on the landmark. Unusually shaped and large palates generate the highest errors. There was no evidence for a difference in mean palatal shape estimated from manual compared to the automatic landmarking. The automatic landmarking reduces sample variation around the mean and reduces measurements of palatal size. CONCLUSIONS: The automatic landmarking method shows excellent repeatability and promising accuracy, which can streamline patient assessment and research studies. However, landmark indications should be subject to visual quality control.