Toward 3D facial analysis for recognizing Mendelian causes of autism spectrum disorder.

Recognizing Mendelian causes is crucial in molecular diagnostics and counseling for patients with autism spectrum disorder (ASD). We explored facial dysmorphism and facial asymmetry in relation to genetic causes in ASD patients and studied the potential of objective facial phenotyping in discriminating between Mendelian and multifactorial ASD. In a cohort of 152 ASD patients, 3D facial images were used to calculate three metrics: a computational dysmorphism score, a computational asymmetry score, and an expert dysmorphism score. High scores for each of the three metrics were associated with Mendelian causes of ASD. The computational dysmorphism score showed a significant correlation with the average expert dysmorphism score. However, in some patients, different dysmorphism aspects were captured making the metrics potentially complementary. The computational dysmorphism and asymmetry scores both enhanced the individual expert dysmorphism scores in differentiating Mendelian from non-Mendelian cases. Furthermore, the computational asymmetry score enhanced the average expert opinion in predicting a Mendelian cause. By design, our study does not allow to draw conclusions on the actual point-of-care use of 3D facial analysis. Nevertheless, 3D morphometric analysis is promising for developing clinical dysmorphology applications in diagnostics and training.

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.

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.

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.

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.

Large-scale open-source three-dimensional growth curves for clinical facial assessment and objective description of facial dysmorphism.

Craniofacial dysmorphism is associated with thousands of genetic and environmental disorders. Delineation of salient facial characteristics can guide clinicians towards a correct clinical diagnosis and understanding the pathogenesis of the disorder. Abnormal facial shape might require craniofacial surgical intervention, with the restoration of normal shape an important surgical outcome. Facial anthropometric growth curves or standards of single inter-landmark measurements have traditionally supported assessments of normal and abnormal facial shape, for both clinical and research applications. However, these fail to capture the full complexity of facial shape. With the increasing availability of 3D photographs, methods of assessment that take advantage of the rich information contained in such images are needed. In this article we derive and present open-source three-dimensional (3D) growth curves of the human face. These are sequences of age and sex-specific expected 3D facial shapes and statistical models of the variation around the expected shape, derived from 5443 3D images. We demonstrate the use of these growth curves for assessing patients and show that they identify normal and abnormal facial morphology independent from age-specific facial features. 3D growth curves can facilitate use of state-of-the-art 3D facial shape assessment by the broader clinical and biomedical research community. This advance in phenotype description will support clinical diagnosis and the understanding of disease pathogenesis including genotype-phenotype relations.

Pitfalls and Promise of 3-dimensional Image Comparison for Craniofacial Surgical Assessment.

Three-dimensional (3D) photography is becoming widely used in plastic surgery. It provides an accurate and reproducible record of the facial surface anatomy and could be a versatile tool for treatment planning and assessment. However, the existing software tools available for the assessment of 3D facial imaging often give highly misleading results. The goal of this special topic article is to give clinicians an insight into methods of 3D image assessment and explain the reasons why results may be misleading. We point toward the advantages of an alternative approach using "nonrigid surface registration" for the comparison of pre- and postsurgical images. This approach is compared with the regular rigid surface registration, and this is illustrated by the assessment of a child with Crouzon syndrome before and after LeFort III osteotomy and distraction. Findings of the standard method imply that changes have occurred that are anatomically not possible, whereas the alternative approach indicates realistic changes. Furthermore, we demonstrate an exciting capacity of 3D image analysis to construct reference populations of normal head size and shape. These can be used to assess the parts of the head that are normal and abnormal pre- and posttreatment of the same child. We conclude that, while 3D image analysis has great potential in surgical assessment, existing software does not always give an adequate assessment. Collaboration among surgeons and engineering and computer science specialists should be encouraged. This way, more comprehensive and accurate techniques in patient assessment and surgical planning can be developed and applied in clinical practice.

Modelling 3D craniofacial growth trajectories for population comparison and classification illustrated using sex-differences.

Many disorders present with characteristic abnormalities of the craniofacial complex. Precise descriptions of how and when these abnormalities emerge and change during childhood and adolescence can inform our understanding of their underlying pathology and facilitate diagnosis from craniofacial shape. In this paper we develop a framework for analysing how anatomical differences between populations emerge and change over time, and for binary group classification that adapts to the age of each participant. As a proxy for a disease-control comparison we use a database of 3D photographs of normally developing boys and girls to examine emerging sex-differences. Essentially we define 3D craniofacial 'growth curves' for each sex. Differences in the forehead, upper lip, chin and nose emerge primarily from different growth rates between the groups, whereas differences in the buccal region involve different growth directions. Differences in the forehead, buccal region and chin are evident before puberty, challenging the view that sex differences result from pubertal hormone levels. Classification accuracy was best for older children. This paper represents a significant methodological advance for the study of facial differences between growing populations and comprehensively describes developing craniofacial sex differences.