Detecting genetic association of common human facial morphological variation using high density 3D image registration

Advancement in Human Face Prediction Using DNA

The rapid improvements in identifying the genetic factors contributing to facial morphology have enabled the early identification of craniofacial syndromes. Similarly, this technology can be vital in forensic cases involving human identification from biological traces or human remains, especially when reference samples are not available in the deoxyribose nucleic acid (DNA) database. This review summarizes the currently used methods for predicting human phenotypes such as age, ancestry, pigmentation, and facial features based on genetic variations. To identify the facial features affected by DNA, various two-dimensional (2D)- and three-dimensional (3D)-scanning techniques and analysis tools are reviewed. A comparison between the scanning technologies is also presented in this review. Face-landmarking techniques and face-phenotyping algorithms are discussed in chronological order. Then, the latest approaches in genetic to 3D face shape analysis are emphasized. A systematic review of the current markers that passed the threshold of a genome-wide association (GWAS) of single nucleotide polymorphism (SNP)-face traits from the GWAS Catalog is also provided using the preferred reporting items for systematic reviews and meta-analyses (PRISMA), approach. Finally, the current challenges in forensic DNA phenotyping are analyzed and discussed.

Ocular phenotype related SNP analysis in Southern Han Chinese population from Guangdong province

Ocular phenotype is recognizable among Asians, including eyelid fold, fissure inclination, and canthal index. Here we screened 27 facial phenotype-associated SNPs and reported a preliminary study in 246 Chinese individuals of Han origin in Guangdong province. Results showed that rs17760296 could explain 6.2% of the eyelid fold variation and double eyelids were more likely to appear when one's genotype was TT. With respect to the canthal index, rs4791774 and rs642961 were significantly associated with it. However, no individual SNP was associated with fissure inclination. We further constructed two models to predict eyelid fold and canthal index and evaluated them with receiver operating characteristic (ROC) curves and support vector machine (SVM) regression, respectively. The models showed a moderate-to-high predictive capacity (AUC = 0.75, sensitivity = 76%, and specificity = 72%) for the eyelid fold while a mild performance (R² = 0.1074, MSE = 0.0005, P-value = 0.024) for the canthal index. In conclusion, our study indicates that rs17760296 could be selected into the facial phenotype prediction system for the Southern Han Chinese population. More SNPs are encouraged to improve the prediction accuracy of the canthal index besides rs4791774 and rs642961.

Landmark-based homologous multi-point warping approach to 3D facial recognition using multiple datasets

Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced methods of face recognition being proposed, and especially techniques using facial landmarks. The current facial landmark methods in 3D involve a mathematically complex and time-consuming workflow involving semi-landmark sliding tasks. This paper proposes a homologous multi-point warping for 3D facial landmarking, which is verified experimentally on each of the target objects in a given dataset using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks). This is achieved by building a template mesh as a reference object and applying this template to each of the targets in three datasets using an artificial deformation approach. The semi-landmarks are subjected to sliding along tangents to the curves or surfaces until the bending energy between a template and a target form is minimal. The results indicate that our method can be used to investigate shape variation for multiple datasets when implemented on three databases (Stirling, FRGC and Bosphorus).

3-Dimensional facial expression recognition in human using multi-points warping

Background

Expression in H-sapiens plays a remarkable role when it comes to social communication. The identification of this expression by human beings is relatively easy and accurate. However, achieving the same result in 3D by machine remains a challenge in computer vision. This is due to the current challenges facing facial data acquisition in 3D; such as lack of homology and complex mathematical analysis for facial point digitization. This study proposes facial expression recognition in human with the application of Multi-points Warping for 3D facial landmark by building a template mesh as a reference object. This template mesh is thereby applied to each of the target mesh on Stirling/ESRC and Bosphorus datasets. The semi-landmarks are allowed to slide along tangents to the curves and surfaces until the bending energy between a template and a target form is minimal and localization error is assessed using Procrustes ANOVA. By using Principal Component Analysis (PCA) for feature selection, classification is done using Linear Discriminant Analysis (LDA).

Result

The localization error is validated on the two datasets with superior performance over the state-of-the-art methods and variation in the expression is visualized using Principal Components (PCs). The deformations show various expression regions in the faces. The results indicate that Sad expression has the lowest recognition accuracy on both datasets. The classifier achieved a recognition accuracy of 99.58 and 99.32% on Stirling/ESRC and Bosphorus, respectively.

Conclusion

The results demonstrate that the method is robust and in agreement with the state-of-the-art results.

Hunting for genes that shape human faces: Initial successes and challenges for the future

There is ample evidence from heritability studies, genetic syndromes and experimental animal models that facial morphology is strongly influenced by genes. In this brief review, we present an up-to-date overview of the efforts to identify genes associated with the size and shape of human facial features. We discuss recent methodological advances that have led to breakthroughs, but also the multitude of challenges facing the field. We offer perspective on possible applications of this line of research, particularly in the context of the precision genomics movement.

Quantification of Facial Traits

Measuring facial traits by quantitative means is a prerequisite to investigate epidemiological, clinical, and forensic questions. This measurement process has received intense attention in recent years. We divided this process into the registration of the face, landmarking, morphometric quantification, and dimension reduction. Face registration is the process of standardizing pose and landmarking annotates positions in the face with anatomic description or mathematically defined properties (pseudolandmarks). Morphometric quantification computes pre-specified transformations such as distances. Landmarking: We review face registration methods which are required by some landmarking methods. Although similar, face registration and landmarking are distinct problems. The registration phase can be seen as a pre-processing step and can be combined independently with a landmarking solution. Existing approaches for landmarking differ in their data requirements, modeling approach, and training complexity. In this review, we focus on 3D surface data as captured by commercial surface scanners but also cover methods for 2D facial pictures, when methodology overlaps. We discuss the broad categories of active shape models, template based approaches, recent deep-learning algorithms, and variations thereof such as hybrid algorithms. The type of algorithm chosen depends on the availability of pre-trained models for the data at hand, availability of an appropriate landmark set, accuracy characteristics, and training complexity. Quantification: Landmarking of anatomical landmarks is usually augmented by pseudo-landmarks, i.e., indirectly defined landmarks that densely cover the scan surface. Such a rich data set is not amenable to direct analysis but is reduced in dimensionality for downstream analysis. We review classic dimension reduction techniques used for facial data and face specific measures, such as geometric measurements and manifold learning. Finally, we review symmetry registration and discuss reliability.

Association analysis between rs6184 and rs6180 polymorphisms of growth hormone receptor gene regarding skeletal-facial profile in a Colombian population

Background/Objective

There is strong evidence that genetic factors may affect the craniofacial morphology. This study aimed to examine the association between the rs6184 and rs6180 polymorphic variants of the growth hormone receptor (GHR) gene and skeletal-facial profile in a Colombian population.

Subjects/Methods

Saliva samples from 306 individuals ranging in age from 15 to 53 (mean 24.33) years were collected. Cephalometric parameters were used to categorize the participants as Class I, Class II, or Class III skeletal-facial profile. The polymerase chain reaction-restriction fragment length polymorphism method was used to identify genotypes of the rs6184 and rs6180 single nucleotide polymorphisms (SNPs). The association of polymorphisms with the skeletal-facial profile was assessed separately and adjusted for confounding using a multivariate binary logistic regression model, alongside with analysis of linkage disequilibrium and haplotype associations.

Results

Although individuals carrying the CA genotype of the rs6184 SNP showed both significantly decreased values for ANB angle and increased measures concerning mandibular body length and mandibular length, no significant differences amongst genotype groups of rs6180 SNP were observed. Moreover, chi-square test and logistic regression analysis revealed that the CA genotype of rs6184 SNP and the A-A haplotype were highly associated with Class III skeletal-facial profile.

Conclusions

Although these results do not support that rs6180 SNP could be identified as a predictor for skeletal-facial profile, they suggest that the allele A of rs6184 SNP alone or in combination with other SNPs in the GHR gene yields significant horizontal and longitudinal variations of the mandibular morphology and might be a strong/independent prognostic indicator for Class III skeletal-facial profile in the present population.

Modeling age-specific facial development in Williams-Beuren-, Noonan-, and 22q11.2 deletion syndromes in cohorts of Czech patients aged 3-18 years: A cross-sectional three-dimensional geometric morphometry analysis of their facial gestalt

Three-dimensional (3D) virtual facial models facilitate genotype-phenotype correlations and diagnostics in clinical dysmorphology. Within cross-sectional analysis of both genders we evaluated facial features in representative cohorts of Czech patients with Williams-Beuren-(WBS; 12 cases), Noonan-(NS; 14), and 22q11.2 deletion syndromes (22q11.2DS; 20) and compared their age-related developmental trajectories to 21 age, sex and ethnically matched controls in 3-18 years of age. Using geometric morphometry statistically significant differences in facial morphology were found in all cases compared to controls. The dysmorphic features observed in WBS were specific and manifested in majority of cases. During ontogenesis, dysmorphic features associated with increased facial convexity become more pronounced whereas other typical features remained relatively stable. Dysmorphic features observed in NS cases were mostly apparent during childhood and gradually diminished with age. Facial development had a similar progress as in controls, while there has been increased growth of patients' nose and chin in adulthood. Facial characteristics observed in 22q11.2DS, except for hypoplastic alae nasi, did not correspond with the standard description of its facial phenotype because of marked facial heterogeneity of this clinical entity. Because of the sensitivity of 3D facial morphometry we were able to reach statistical significance even in smaller retrospective patient cohorts, which proves its clinical utility within the routine setting.

An overview of the latest developments in facial imaging

Facial imaging is a term used to describe methods that use facial images to assist or facilitate human identification. This pertains to two craniofacial identification procedures that use skulls and faces-facial approximation and photographic superimposition-as well as face-only methods for age progression/regression, the construction of facial graphics from eyewitness memory (including composites and artistic sketches), facial depiction, face mapping and newly emerging methods of molecular photofitting. Given the breadth of these facial imaging techniques, it is not surprising that a broad array of subject-matter experts participate in and/or contribute to the formulation and implementation of these methods (including forensic odontologists, forensic artists, police officers, electrical engineers, anatomists, geneticists, medical image specialists, psychologists, computer graphic programmers and software developers). As they are concerned with the physical characteristics of humans, each of these facial imaging areas also falls in the domain of physical anthropology, although not all of them have been traditionally regarded as such. This too offers useful opportunities to adapt established methods in one domain to others more traditionally held to be disciplines within physical anthropology (e.g. facial approximation, craniofacial superimposition and face photo-comparison). It is important to note that most facial imaging methods are not currently used for identification but serve to assist authorities in narrowing or directing investigations such that other, more potent, methods of identification can be used (e.g. DNA). Few, if any, facial imaging approaches can be considered honed end-stage scientific methods, with major opportunities for physical anthropologists to make meaningful contributions. Some facial imaging methods have considerably stronger scientific underpinnings than others (e.g. facial approximation versus face mapping), some currently lie entirely within the artistic sphere (facial depiction), and yet others are so aspirational that realistic capacity to obtain their aims has strongly been questioned despite highly advanced technical approaches (molecular photofitting). All this makes for a broad-ranging, dynamic and energetic field that is in a constant state of flux. This manuscript provides a theoretical snapshot of the purposes of these methods, the state of science as it pertains to them, and their latest research developments.

Non-syndromic Cleft Lip and Palate Polymorphisms Affect Normal Lip Morphology

Non-syndromic cleft lip with or without palate (NSCL/P) is a frequent malformation of the facial region. Genetic variants (SNPs) within nineteen loci have been previously associated with NSCL/P in GWAS studies of European individuals. These common variant SNPs may have subtler effects on the morphology of the lip and face in unaffected individuals. Several studies have investigated the genetic influences on facial morphology using land-marking methods, but these landmarks are sparse in the lip region. The aim of this study is to assess for associations between the nineteen NSCL/P SNPs and normal lip phenotypes, using a detailed categorical scale. Three-dimensional laser scanned facial images were obtained of 4,747 subjects recruited from the Avon Longitudinal Study of Parents and Children (ALSPAC) and genetic data was available for 3,643 of them. A polygenetic risk score (PRS) combining the nineteen NSCL/P SNPs was associated with V-shaped Cupid's bow (P = 3 × 10⁻⁴) and narrow philtrum (P = 2 × 10⁻⁴) phenotypes. Analysis of individual SNPs found strong evidence for association between rs227731 and skeletal II pattern (P = 5 × 10⁻⁶). This study finds that known NSCL/P SNPs affect lip phenotypes in the general population, and an increased PRS is associated with narrow philtrum and V-shaped Cupid's bow. However, the difference in NSCL/P PRS between people with and without certain lip features is unlikely to be great enough to serve as a useful marker of NSCL/P risk.

Facial Genetics: A Brief Overview

Historically, craniofacial genetic research has understandably focused on identifying the causes of craniofacial anomalies and it has only been within the last 10 years, that there has been a drive to detail the biological basis of normal-range facial variation. This initiative has been facilitated by the availability of low-cost hi-resolution three-dimensional systems which have the ability to capture the facial details of thousands of individuals quickly and accurately. Simultaneous advances in genotyping technology have enabled the exploration of genetic influences on facial phenotypes, both in the present day and across human history. There are several important reasons for exploring the genetics of normal-range variation in facial morphology.     - Disentangling the environmental factors and relative parental biological contributions to heritable traits can help to answer the age-old question "why we look the way that we do?"     - Understanding the etiology of craniofacial anomalies; e.g., unaffected family members of individuals with non-syndromic cleft lip/palate (nsCL/P) have been shown to differ in terms of normal-range facial variation to the general population suggesting an etiological link between facial morphology and nsCL/P.     - Many factors such as ancestry, sex, eye/hair color as well as distinctive facial features (such as, shape of the chin, cheeks, eyes, forehead, lips, and nose) can be identified or estimated using an individual's genetic data, with potential applications in healthcare and forensics.     - Improved understanding of historical selection and adaptation relating to facial phenotypes, for example, skin pigmentation and geographical latitude.     - Highlighting what is known about shared facial traits, medical conditions and genes.

Genome-wide variants of Eurasian facial shape differentiation and a prospective model of DNA based face prediction

It is a long-standing question as to which genes define the characteristic facial features among different ethnic groups. In this study, we use Uyghurs, an ancient admixed population to query the genetic bases why Europeans and Han Chinese look different. Facial traits were analyzed based on high-dense 3D facial images; numerous biometric spaces were examined for divergent facial features between European and Han Chinese, ranging from inter-landmark distances to dense shape geometrics. Genome-wide association studies (GWAS) were conducted on a discovery panel of Uyghurs. Six significant loci were identified, four of which, rs1868752, rs118078182, rs60159418 at or near UBASH3B, COL23A1, PCDH7 and rs17868256 were replicated in independent cohorts of Uyghurs or Southern Han Chinese. A prospective model was also developed to predict 3D faces based on top GWAS signals and tested in hypothetic forensic scenarios.

Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology

There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 2x10-5). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.

Genome-wide mapping of global-to-local genetic effects on human facial shape

Genome-wide association scans of complex multipartite traits like the human face typically use preselected phenotypic measures. Here we report a data-driven approach to phenotyping facial shape at multiple levels of organization, allowing for an open-ended description of facial variation while preserving statistical power. In a sample of 2,329 persons of European ancestry, we identified 38 loci, 15 of which replicated in an independent European sample (n = 1,719). Four loci were completely new. For the others, additional support (n = 9) or pleiotropic effects (n = 2) were found in the literature, but the results reported here were further refined. All 15 replicated loci highlighted distinctive patterns of global-to-local genetic effects on facial shape and showed enrichment for active chromatin elements in human cranial neural crest cells, suggesting an early developmental origin of the facial variation captured. These results have implications for studies of facial genetics and other complex morphological traits.

A PCA-Based method for determining craniofacial relationship and sexual dimorphism of facial shapes

Previous studies have used principal component analysis (PCA) to investigate the craniofacial relationship, as well as sex determination using facial factors. However, few studies have investigated the extent to which the choice of principal components (PCs) affects the analysis of craniofacial relationship and sexual dimorphism. In this paper, we propose a PCA-based method for visual and quantitative analysis, using 140 samples of 3D heads (70 male and 70 female), produced from computed tomography (CT) images. There are two parts to the method. First, skull and facial landmarks are manually marked to guide the model's registration so that dense corresponding vertices occupy the same relative position in every sample. Statistical shape spaces of the skull and face in dense corresponding vertices are constructed using PCA. Variations in these vertices, captured in every principal component (PC), are visualized to observe shape variability. The correlations of skull- and face-based PC scores are analysed, and linear regression is used to fit the craniofacial relationship. We compute the PC coefficients of a face based on this craniofacial relationship and the PC scores of a skull, and apply the coefficients to estimate a 3D face for the skull. To evaluate the accuracy of the computed craniofacial relationship, the mean and standard deviation of every vertex between the two models are computed, where these models are reconstructed using real PC scores and coefficients. Second, each PC in facial space is analysed for sex determination, for which support vector machines (SVMs) are used. We examined the correlation between PCs and sex, and explored the extent to which the choice of PCs affects the expression of sexual dimorphism. Our results suggest that skull- and face-based PCs can be used to describe the craniofacial relationship and that the accuracy of the method can be improved by using an increased number of face-based PCs. The results show that the accuracy of the sex classification is related to the choice of PCs. The highest sex classification rate is 91.43% using our method.

Interferon regulatory factor 6 variants affect nasolabial morphology in East Asian populations

OBJECTIVE

The interferon regulatory factor 6 gene (IRF6) is one of the most conspicuous genes among a large number of candidate risk genes for non-syndromic cleft lip with or without cleft palate, which is considered to be a multifactorial defect. Variants of IRF6 are also suggested to affect normal craniofacial variations, especially in the area of the nose and the upper lip. In the present study, we used lateral cephalograms to establish the relationship between IRF6 and sagittal nasolabial morphology in healthy East Asian subjects.

DESIGN

Genomic DNA was extracted from 215 Japanese and 226 Korean individuals, and genotyped for five IRF6 single nucleotide polymorphisms (SNPs): rs17389541, rs642961, rs2013162, rs2235371, and rs7802. These SNPs were tested by multiple regression analyses for their association with craniofacial measurements obtained from lateral cephalometrics.

RESULTS

We detected a significant association between the derived variants, rs2013162 and rs2235371 and the distances between a facial bone plane indicated by distance from Nasion and Point A (NA plane) to soft tissue landmarks; the Subalare (NA-Sbal) and the Subnasale (NA-Sn) in the sagittal plane.

CONCLUSION

Our results indicate that IRF6 variants play an important role in the normal range of variation in nasolabial soft-tissue morphology.

Effects of Objective 3-Dimensional Measures of Facial Shape and Symmetry on Perceptions of Facial Attractiveness

PURPOSE

Meeting patient desires for enhanced facial esthetics requires that providers have standardized and objective methods to measure esthetics. The authors evaluated the effects of objective 3-dimensional (3D) facial shape and asymmetry measurements derived from 3D facial images on perceptions of facial attractiveness.

MATERIALS AND METHODS

The 3D facial images of 313 adults in Iowa were digitized with 32 landmarks, and objective 3D facial measurements capturing symmetric and asymmetric components of shape variation, centroid size, and fluctuating asymmetry were obtained from the 3D coordinate data using geo-morphometric analyses. Frontal and profile images of study participants were rated for facial attractiveness by 10 volunteers (5 women and 5 men) on a 5-point Likert scale and a visual analog scale. Multivariate regression was used to identify the effects of the objective 3D facial measurements on attractiveness ratings.

RESULTS

Several objective 3D facial measurements had marked effects on attractiveness ratings. Shorter facial heights with protrusive chins, midface retrusion, faces with protrusive noses and thin lips, flat mandibular planes with deep labiomental folds, any cants of the lip commissures and floor of the nose, larger faces overall, and increased fluctuating asymmetry were rated as significantly (P < .001) less attractive.

CONCLUSION

Perceptions of facial attractiveness can be explained by specific 3D measurements of facial shapes and fluctuating asymmetry, which have important implications for clinical practice and research.

Genome-wide association study of facial morphology reveals novel associations with FREM1 and PARK2

Several studies have now shown evidence of association between common genetic variants and quantitative facial traits in humans. The reported associations generally involve simple univariate measures and likely represent only a small fraction of the genetic loci influencing facial morphology. In this study, we applied factor analysis to a set of 276 facial linear distances derived from 3D facial surface images of 2187 unrelated individuals of European ancestry. We retained 23 facial factors, which we then tested for genetic associations using a genome-wide panel of 10,677,593 single nucleotide polymorphisms (SNPs). In total, we identified genome-wide significant (p < 5 × 10⁻⁸) associations in three regions, including two that are novel: one involving measures of midface height at 6q26 within an intron of PARK2 (lead SNP rs9456748; p = 4.99 × 10⁻⁸) and another involving measures of central upper lip height at 9p22 within FREM1 (lead SNP rs72713618; p = 2.02 × 10⁻⁸). In both cases, the genetic association was stronger with the composite facial factor phenotype than with any of the individual linear distances that comprise those factors. While the biological role of PARK2 in the craniofacial complex is currently unclear, there is evidence from both mouse models and Mendelian syndromes that FREM1 may influence facial variation. These results highlight the potential value of data-driven multivariate phenotyping for genetic studies of human facial morphology.

Correlation between facial morphology and gene polymorphisms in the Uygur youth population

Human facial morphology varies considerably among individuals and can be influenced by gene polymorphisms. We explored the effects of single nucleotide polymorphisms (SNPs) on facial features in the Uygur youth population of the Kashi area in Xinjiang, China. Saliva samples were collected from 578 volunteers, and 10 SNPs previously associated with variations in facial physiognomy were genotyped. In parallel, 3D images of the subjects’ faces were obtained using grating facial scanning technology. After delimitation of 15 salient landmarks, the correlation between SNPs and the distances between facial landmark pairs was assessed. Analysis of variance revealed that ENPP1 rs7754561 polymorphism was significantly associated with RAla-RLipCn and RLipCn-Sbn linear distances (p = 0.044 and p = 0.012, respectively) as well as RLipCn-Stm curve distance (p = 0.042). The GHR rs6180 polymorphism correlated with RLipCn-Stm linear distance (p = 0.04), while the GHR rs6184 polymorphism correlated with RLipCn-ULipP curve distance (p = 0.047). The FGFR1 rs4647905 polymorphism was associated with LLipCn-Nsn linear distance (p = 0.042). These results reveal that ENPP1 and FGFR1 influence lower anterior face height, the distance from the upper lip to the nasal floor, and lip shape. FGFR1 also influences the lower anterior face height, while GHR is associated with the length and width of the lip.

Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping

The human face is a complex trait under strong genetic control, as evidenced by the striking visual similarity between twins. Nevertheless, heritability estimates of facial traits have often been surprisingly low or difficult to replicate. Furthermore, the construction of facial phenotypes that correspond to naturally perceived facial features remains largely a mystery. We present here a large-scale heritability study of face geometry that aims to address these issues. High-resolution, three-dimensional facial models have been acquired on a cohort of 952 twins recruited from the TwinsUK registry, and processed through a novel landmarking workflow, GESSA (Geodesic Ensemble Surface Sampling Algorithm). The algorithm places thousands of landmarks throughout the facial surface and automatically establishes point-wise correspondence across faces. These landmarks enabled us to intuitively characterize facial geometry at a fine level of detail through curvature measurements, yielding accurate heritability maps of the human face (www.heritabilitymaps.info).

Signatures of personality on dense 3D facial images

It has long been speculated that cues on the human face exist that allow observers to make reliable judgments of others' personality traits. However, direct evidence of association between facial shapes and personality is missing from the current literature. This study assessed the personality attributes of 834 Han Chinese volunteers (405 males and 429 females), utilising the five-factor personality model ('Big Five'), and collected their neutral 3D facial images. Dense anatomical correspondence was established across the 3D facial images in order to allow high-dimensional quantitative analyses of the facial phenotypes. In this paper, we developed a Partial Least Squares (PLS) -based method. We used composite partial least squares component (CPSLC) to test association between the self-tested personality scores and the dense 3D facial image data, then used principal component analysis (PCA) for further validation. Among the five personality factors, agreeableness and conscientiousness in males and extraversion in females were significantly associated with specific facial patterns. The personality-related facial patterns were extracted and their effects were extrapolated on simulated 3D facial models.

Contribution of FGFR1 Variants to Craniofacial Variations in East Asians

FGFR1 plays an important role in the development of the nervous system as well as the regulation of the skeletal development and bone homeostasis. Mutations in FGFR1 genes affect skull development, specifically suture and synchondrosis, resulting in craniosynostosis and facial abnormalities. We examined subjects with normal skull morphology for genetic polymorphisms that might be associated with normal craniofacial variations. Genomic DNA was obtained from 216 Japanese and 227 Korean subjects. Four FGFR1 SNPs, namely, rs881301, rs6996321, rs4647905, and rs13317, were genotyped. These SNPs were tested for association with craniofacial measurements obtained from lateral and posteroanterior cephalometries, in which principle component analysis was performed to compress the data of the craniofacial measurements. We observed that SNPs rs13317 and rs6996321 were correlated with the overall head size and midfacial development, indicating that FGFR1 SNPs played crucial roles in the normal variation of human craniofacial morphology. Subjects with the derived alleles of SNPs rs13317 and rs6996321 had a small face and a facial pattern associated with a retruded midface and relatively wide-set eyes. These facial features were similar to but were milder than those of individuals with Pfeiffer syndrome, which is caused by a dysfunctional mutation in FGFR1.

Socioeconomic Status Is Not Related with Facial Fluctuating Asymmetry: Evidence from Latin-American Populations

The expression of facial asymmetries has been recurrently related with poverty and/or disadvantaged socioeconomic status. Departing from the developmental instability theory, previous approaches attempted to test the statistical relationship between the stress experienced by individuals grown in poor conditions and an increase in facial and corporal asymmetry. Here we aim to further evaluate such hypothesis on a large sample of admixed Latin Americans individuals by exploring if low socioeconomic status individuals tend to exhibit greater facial fluctuating asymmetry values. To do so, we implement Procrustes analysis of variance and Hierarchical Linear Modelling (HLM) to estimate potential associations between facial fluctuating asymmetry values and socioeconomic status. We report significant relationships between facial fluctuating asymmetry values and age, sex, and genetic ancestry, while socioeconomic status failed to exhibit any strong statistical relationship with facial asymmetry. These results are persistent after the effect of heterozygosity (a proxy for genetic ancestry) is controlled in the model. Our results indicate that, at least on the studied sample, there is no relationship between socioeconomic stress (as intended as low socioeconomic status) and facial asymmetries.

Exploring the Underlying Genetics of Craniofacial Morphology through Various Sources of Knowledge

The craniofacial complex is the billboard of sorts containing information about sex, health, ancestry, kinship, genes, and environment. A thorough knowledge of the genes underlying craniofacial morphology is fundamental to understanding craniofacial biology and evolution. These genes can also provide an important foundation for practical efforts like predicting faces from DNA and phenotype-based facial diagnostics. In this work, we focus on the various sources of knowledge regarding the genes that affect patterns of craniofacial development. Although tremendous successes recently have been made using these sources in both methodology and biology, many challenges remain. Primary among these are precise phenotyping techniques and efficient modeling methods.

Genetic and Environmental Contributions to Facial Morphological Variation: A 3D Population-Based Twin Study

INTRODUCTION

Facial phenotype is influenced by genes and environment; however, little is known about their relative contributions to normal facial morphology. The aim of this study was to assess the relative genetic and environmental contributions to facial morphological variation using a three-dimensional (3D) population-based approach and the classical twin study design.

MATERIALS AND METHODS

3D facial images of 1380 female twins from the TwinsUK Registry database were used. All faces were landmarked, by manually placing 37 landmark points, and Procrustes registered. Three groups of traits were extracted and analysed: 19 principal components (uPC) and 23 principal components (sPC), derived from the unscaled and scaled landmark configurations respectively, and 1275 linear distances measured between 51 landmarks (37 manually identified and 14 automatically calculated). The intraclass correlation coefficients, rMZ and rDZ, broad-sense heritability (h2), common (c2) and unique (e2) environment contributions were calculated for all traits for the monozygotic (MZ) and dizygotic (DZ) twins.

RESULTS

Heritability of 13 uPC and 17 sPC reached statistical significance, with h2 ranging from 38.8% to 78.5% in the former and 30.5% to 84.8% in the latter group. Also, 1222 distances showed evidence of genetic control. Common environment contributed to one PC in both groups and 53 linear distances (4.3%). Unique environment contributed to 17 uPC and 20 sPC and 1245 distances.

CONCLUSIONS

Genetic factors can explain more than 70% of the phenotypic facial variation in facial size, nose (width, prominence and height), lips prominence and inter-ocular distance. A few traits have shown potential dominant genetic influence: the prominence and height of the nose, the lower lip prominence in relation to the chin and upper lip philtrum length. Environmental contribution to facial variation seems to be the greatest for the mandibular ramus height and horizontal facial asymmetry.

Genome-Wide Association Study Reveals Multiple Loci Influencing Normal Human Facial Morphology

Numerous lines of evidence point to a genetic basis for facial morphology in humans, yet little is known about how specific genetic variants relate to the phenotypic expression of many common facial features. We conducted genome-wide association meta-analyses of 20 quantitative facial measurements derived from the 3D surface images of 3118 healthy individuals of European ancestry belonging to two US cohorts. Analyses were performed on just under one million genotyped SNPs (Illumina OmniExpress+Exome v1.2 array) imputed to the 1000 Genomes reference panel (Phase 3). We observed genome-wide significant associations (p < 5 x 10⁻⁸) for cranial base width at 14q21.1 and 20q12, intercanthal width at 1p13.3 and Xq13.2, nasal width at 20p11.22, nasal ala length at 14q11.2, and upper facial depth at 11q22.1. Several genes in the associated regions are known to play roles in craniofacial development or in syndromes affecting the face: MAFB, PAX9, MIPOL1, ALX3, HDAC8, and PAX1. We also tested genotype-phenotype associations reported in two previous genome-wide studies and found evidence of replication for nasal ala length and SNPs in CACNA2D3 and PRDM16. These results provide further evidence that common variants in regions harboring genes of known craniofacial function contribute to normal variation in human facial features. Improved understanding of the genes associated with facial morphology in healthy individuals can provide insights into the pathways and mechanisms controlling normal and abnormal facial morphogenesis.

There is a great deal of evidence that genes influence facial appearance. This is perhaps most apparent when we look at our own families, since we are more likely to share facial features in common with our close relatives than with unrelated individuals. Nevertheless, little is known about how variation in specific regions of the genome relates to the kinds of distinguishing facial characteristics that give us our unique identities, e.g., the size and shape of our nose or how far apart our eyes are spaced. In this paper, we investigate this question by examining the association between genetic variants across the whole genome and a set of measurements designed to capture key aspects of facial form. We found evidence of genetic associations involving measures of eye, nose, and facial breadth. In several cases, implicated regions contained genes known to play roles in embryonic face formation or in syndromes in which the face is affected. Our ability to connect specific genetic variants to ubiquitous facial traits can inform our understanding of normal and abnormal craniofacial development, provide potential predictive models of evolutionary changes in human facial features, and improve our ability to create forensic facial reconstructions from DNA.

Genomewide Association Study of African Children Identifies Association of SCHIP1 and PDE8A with Facial Size and Shape

The human face is a complex assemblage of highly variable yet clearly heritable anatomic structures that together make each of us unique, distinguishable, and recognizable. Relatively little is known about the genetic underpinnings of normal human facial variation. To address this, we carried out a large genomewide association study and two independent replication studies of Bantu African children and adolescents from Mwanza, Tanzania, a region that is both genetically and environmentally relatively homogeneous. We tested for genetic association of facial shape and size phenotypes derived from 3D imaging and automated landmarking of standard facial morphometric points. SNPs within genes SCHIP1 and PDE8A were associated with measures of facial size in both the GWAS and replication cohorts and passed a stringent genomewide significance threshold adjusted for multiple testing of 34 correlated traits. For both SCHIP1 and PDE8A, we demonstrated clear expression in the developing mouse face by both whole-mount in situ hybridization and RNA-seq, supporting their involvement in facial morphogenesis. Ten additional loci demonstrated suggestive association with various measures of facial shape. Our findings, which differ from those in previous studies of European-derived whites, augment understanding of the genetic basis of normal facial development, and provide insights relevant to both human disease and forensics.

The human face is made up of distinct yet related anatomic structures that together make both individuals and families recognizable. It is clear there is a strong genetic component to the human face, and though the genetics of the face have been studied for several years, there are relatively few genes known to impact normal human facial development and facial shape. We report here a large-scale human genetic study in which we successfully identify and replicate genetic markers associated with normal facial variation using advanced 3D facial imaging in African children. We identified two significant replicated genes associated with measures of human facial size, SCHIP1 and PDE8A, demonstrated their clear expression in the developing face in the mouse, and identified 10 additional candidate genetic loci for human facial shape. Gene discovery for human facial development is an important first step for both diagnosing and treating craniofacial syndromes and for developing forensic modeling of the human face.

Phenotype-genotype correlations of facial width and height proportions in patients with Class II malocclusion

OBJECTIVES

To characterize soft-tissue facial height and width variation in Class II malocclusion and test for correlations with genes HMGA2, AJUBA, and ADK.

SETTING AND SAMPLE POPULATION

Nine facial proportions were estimated from 2D frontal repose photographs of 330 Caucasian adults with Class II malocclusion.

MATERIAL AND METHODS

After adjustments for age and gender, the facial proportions were submitted to a principal component analyses (PCA). The most meaningful phenotypic variations were correlated with SNPs rs7924176 (ADK), rs17101923 (HMGA2), and rs997154 (AJUBA) genotyped in 106 individuals.

RESULTS

Principal component analyses resulted in four principal components (PCs), which explained 75% of total variation. PC1 captured variation in the intercanthus distance and explained 28% of total variation. PC2 explained 21% of the variations in facial taper and facial index. PC3 explained 14% and reflected variations in the vertical dimension of the lower face. PC4 explained 12% and captured variations in distance between the eyes, width of the commissures, and the length of the superior aspect of the lower face height corresponding to the vertical dimension of the philtrum of the upper lip. A suggestive association (p<0.05) was observed between PC4 and rs997154 corroborating the role of AJUBA in variation of facial dimensions.

CONCLUSION

2D frontal photographs can be used to derive quantitative measures of soft-tissue phenotypes that are of clinical relevance. The methods described are suitable for discovery and replication of associations between genotypes and malocclusion phenotypes.

Genetics of the dentofacial variation in human malocclusion

Malocclusions affect individuals worldwide, resulting in compromised function and esthetics. Understanding the etiological factors contributing to the variation in dentofacial morphology associated with malocclusions is the key to develop novel treatment approaches. Advances in dentofacial phenotyping, which is the comprehensive characterization of hard and soft tissue variation in the craniofacial complex, together with the acquisition of large-scale genomic data have started to unravel genetic mechanisms underlying facial variation. Knowledge on the genetics of human malocclusion is limited even though results attained thus far are encouraging, with promising opportunities for future research. This review summarizes the most common dentofacial variations associated with malocclusions and reviews the current knowledge of the roles of genes in the development of malocclusions. Lastly, this review will describe ways to advance malocclusion research, following examples from the expanding fields of phenomics and genomic medicine, which aim to better patient outcomes.

A genome-wide association scan implicates DCHS2, RUNX2, GLI3, PAX1 and EDAR in human facial variation

We report a genome-wide association scan for facial features in ∼6,000 Latin Americans. We evaluated 14 traits on an ordinal scale and found significant association (P values<5 × 10⁻⁸) at single-nucleotide polymorphisms (SNPs) in four genomic regions for three nose-related traits: columella inclination (4q31), nose bridge breadth (6p21) and nose wing breadth (7p13 and 20p11). In a subsample of ∼3,000 individuals we obtained quantitative traits related to 9 of the ordinal phenotypes and, also, a measure of nasion position. Quantitative analyses confirmed the ordinal-based associations, identified SNPs in 2q12 associated to chin protrusion, and replicated the reported association of nasion position with SNPs in PAX3. Strongest association in 2q12, 4q31, 6p21 and 7p13 was observed for SNPs in the EDAR, DCHS2, RUNX2 and GLI3 genes, respectively. Associated SNPs in 20p11 extend to PAX1. Consistent with the effect of EDAR on chin protrusion, we documented alterations of mandible length in mice with modified Edar funtion.

Humans show great diversity in facial appearance and this variation is highly heritable. Here, Andres Ruiz-Linares and colleagues examined facial features in admixed Latin Americans and identify genome-wide associations for 14 facial traits, including four gene loci (RUNX2, GLI3, DCHS2 and PAX1) influencing nose morphology.

An Automatic 3D Facial Landmarking Algorithm Using 2D Gabor Wavelets

In this paper, we present a novel approach to automatic 3D facial landmarking using 2D Gabor wavelets. Our algorithm considers the face to be a surface and uses map projections to derive 2D features from raw data. Extracted features include texture, relief map, and transformations thereof. We extend an established 2D landmarking method for simultaneous evaluation of these data. The method is validated by performing landmarking experiments on two data sets using 21 landmarks and compared with an active shape model implementation. On average, landmarking error for our method was 1.9 mm, whereas the active shape model resulted in an average landmarking error of 2.3 mm. A second study investigating facial shape heritability in related individuals concludes that automatic landmarking is on par with manual landmarking for some landmarks. Our algorithm can be trained in 30 min to automatically landmark 3D facial data sets of any size, and allows for fast and robust landmarking of 3D faces.

Three-dimensional human facial morphologies as robust aging markers

Aging is associated with many complex diseases. Reliable prediction of the aging process is important for assessing the risks of aging-associated diseases. However, despite intense research, so far there is no reliable aging marker. Here we addressed this problem by examining whether human 3D facial imaging features could be used as reliable aging markers. We collected > 300 3D human facial images and blood profiles well-distributed across ages of 17 to 77 years. By analyzing the morphological profiles, we generated the first comprehensive map of the aging human facial phenome. We identified quantitative facial features, such as eye slopes, highly associated with age. We constructed a robust age predictor and found that on average people of the same chronological age differ by ± 6 years in facial age, with the deviations increasing after age 40. Using this predictor, we identified slow and fast agers that are significantly supported by levels of health indicators. Despite a close relationship between facial morphological features and health indicators in the blood, facial features are more reliable aging biomarkers than blood profiles and can better reflect the general health status than chronological age.

Toward DNA-based facial composites: preliminary results and validation

The potential of constructing useful DNA-based facial composites is forensically of great interest. Given the significant identity information coded in the human face these predictions could help investigations out of an impasse. Although, there is substantial evidence that much of the total variation in facial features is genetically mediated, the discovery of which genes and gene variants underlie normal facial variation has been hampered primarily by the multipartite nature of facial variation. Traditionally, such physical complexity is simplified by simple scalar measurements defined a priori, such as nose or mouth width or alternatively using dimensionality reduction techniques such as principal component analysis where each principal coordinate is then treated as a scalar trait. However, as shown in previous and related work, a more impartial and systematic approach to modeling facial morphology is available and can facilitate both the gene discovery steps, as we recently showed, and DNA-based facial composite construction, as we show here. We first use genomic ancestry and sex to create a base-face, which is simply an average sex and ancestry matched face. Subsequently, the effects of 24 individual SNPs that have been shown to have significant effects on facial variation are overlaid on the base-face forming the predicted-face in a process akin to a photomontage or image blending. We next evaluate the accuracy of predicted faces using cross-validation. Physical accuracy of the facial predictions either locally in particular parts of the face or in terms of overall similarity is mainly determined by sex and genomic ancestry. The SNP-effects maintain the physical accuracy while significantly increasing the distinctiveness of the facial predictions, which would be expected to reduce false positives in perceptual identification tasks. To the best of our knowledge this is the first effort at generating facial composites from DNA and the results are preliminary but certainly promising, especially considering the limited amount of genetic information about the face contained in these 24 SNPs. This approach can incorporate additional SNPs as these are discovered and their effects documented. In this context we discuss three main avenues of research: expanding our knowledge of the genetic architecture of facial morphology, improving the predictive modeling of facial morphology by exploring and incorporating alternative prediction models, and increasing the value of the results through the weighted encoding of physical measurements in terms of human perception of faces.