The facial evolution: looking backward and moving forward

An investigation of a novel broad autism phenotype: increased facial masculinity among parents of children on the autism spectrum

The broad autism phenotype commonly refers to sub-clinical levels of autistic-like behaviour and cognition presented in biological relatives of autistic people. In a recent study, we reported findings suggesting that the broad autism phenotype may also be expressed in facial morphology, specifically increased facial masculinity. Increased facial masculinity has been reported among autistic children, as well as their non-autistic siblings. The present study builds on our previous findings by investigating the presence of increased facial masculinity among non-autistic parents of autistic children. Using a previously established method, a 'facial masculinity score' and several facial distances were calculated for each three-dimensional facial image of 192 parents of autistic children (58 males, 134 females) and 163 age-matched parents of non-autistic children (50 males, 113 females). While controlling for facial area and age, significantly higher masculinity scores and larger (more masculine) facial distances were observed in parents of autistic children relative to the comparison group, with effect sizes ranging from small to medium (0.16 ≤ d ≤ .41), regardless of sex. These findings add to an accumulating evidence base that the broad autism phenotype is expressed in physical characteristics and suggest that both maternal and paternal pathways are implicated in masculinized facial morphology.

Ethical dangers of facial phenotyping through photography in psychiatric genomics studies

Psychiatric genomics research protocols are increasingly incorporating tools of deep phenotyping to observe and examine phenotypic abnormalities among individuals with neurodevelopmental disorders. In particular, photography and the use of two-dimensional and three-dimensional facial analysis is thought to shed further light on the phenotypic expression of the genes underlying neurodevelopmental disorders, as well as provide potential diagnostic tools for clinicians. In this paper, I argue that the research use of photography to aid facial phenotyping raises deeply fraught issues from an ethical point of view. First, the process of objectification through photographic imagery and facial analysis could potentially worsen the stigmatisation of persons with neurodevelopmental disorders. Second, the use of photography for facial phenotyping has worrying parallels with the historical misuse of photography to advance positive and negative eugenics around race, ethnicity and intellectual disability. The paper recommends ethical caution in the use of photography and facial phenotyping in psychiatric genomics studies exploring neurodevelopmental disorders, outlining certain necessary safeguards, such as a critical awareness of the history of anthropometric photography use among scientists, as well as the exploration of photographic methodologies that could potentially empower individuals with disabilities.

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

Spatially Dense 3D Facial Heritability and Modules of Co-heritability in a Father-Offspring Design

Introduction: The human face is a complex trait displaying a strong genetic component as illustrated by various studies on facial heritability. Most of these start from sparse descriptions of facial shape using a limited set of landmarks. Subsequently, facial features are preselected as univariate measurements or principal components and the heritability is estimated for each of these features separately. However, none of these studies investigated multivariate facial features, nor the co-heritability between different facial features. Here we report a spatially dense multivariate analysis of facial heritability and co-heritability starting from data from fathers and their children available within ALSPAC. Additionally, we provide an elaborate overview of related craniofacial heritability studies.

Methods: In total, 3D facial images of 762 father-offspring pairs were retained after quality control. An anthropometric mask was applied to these images to establish spatially dense quasi-landmark configurations. Partial least squares regression was performed and the (co-)heritability for all quasi-landmarks (∼7160) was computed as twice the regression coefficient. Subsequently, these were used as input to a hierarchical facial segmentation, resulting in the definition of facial modules that are internally integrated through the biological mechanisms of inheritance. Finally, multivariate heritability estimates were obtained for each of the resulting modules.

Results: Nearly all modular estimates reached statistical significance under 1,000,000 permutations and after multiple testing correction (p ≤ 1.3889 × 10^-3), displaying low to high heritability scores. Particular facial areas showing the greatest heritability were similar for both sons and daughters. However, higher estimates were obtained in the former. These areas included the global face, upper facial part (encompassing the nasion, zygomas and forehead) and nose, with values reaching 82% in boys and 72% in girls. The lower parts of the face only showed low to moderate levels of heritability.

Conclusion: In this work, we refrain from reducing facial variation to a series of individual measurements and analyze the heritability and co-heritability from spatially dense landmark configurations at multiple levels of organization. Finally, a multivariate estimation of heritability for global-to-local facial segments is reported. Knowledge of the genetic determination of facial shape is useful in the identification of genetic variants that underlie normal-range facial variation.

Computer face-matching technology using two-dimensional photographs accurately matches the facial gestalt of unrelated individuals with the same syndromic form of intellectual disability

Background

Massively parallel genetic sequencing allows rapid testing of known intellectual disability (ID) genes. However, the discovery of novel syndromic ID genes requires molecular confirmation in at least a second or a cluster of individuals with an overlapping phenotype or similar facial gestalt. Using computer face-matching technology we report an automated approach to matching the faces of non-identical individuals with the same genetic syndrome within a database of 3681 images [1600 images of one of 10 genetic syndrome subgroups together with 2081 control images]. Using the leave-one-out method, two research questions were specified:

Using two-dimensional (2D) photographs of individuals with one of 10 genetic syndromes within a database of images, did the technology correctly identify more than expected by chance: i) a top match? ii) at least one match within the top five matches? or iii) at least one in the top 10 with an individual from the same syndrome subgroup?

Was there concordance between correct technology-based matches and whether two out of three clinical geneticists would have considered the diagnosis based on the image alone?

Results

The computer face-matching technology correctly identifies a top match, at least one correct match in the top five and at least one in the top 10 more than expected by chance (P < 0.00001). There was low agreement between the technology and clinicians, with higher accuracy of the technology when results were discordant (P < 0.01) for all syndromes except Kabuki syndrome.

Conclusions

Although the accuracy of the computer face-matching technology was tested on images of individuals with known syndromic forms of intellectual disability, the results of this pilot study illustrate the potential utility of face-matching technology within deep phenotyping platforms to facilitate the interpretation of DNA sequencing data for individuals who remain undiagnosed despite testing the known developmental disorder genes.

Electronic supplementary material

The online version of this article (10.1186/s12896-017-0410-1) contains supplementary material, which is available to authorized users.

3-Dimensional Facial Analysis-Facing Precision Public Health

Precision public health is a new field driven by technological advances that enable more precise descriptions and analyses of individuals and population groups, with a view to improving the overall health of populations. This promises to lead to more precise clinical and public health practices, across the continuum of prevention, screening, diagnosis, and treatment. A phenotype is the set of observable characteristics of an individual resulting from the interaction of a genotype with the environment. Precision (deep) phenotyping applies innovative technologies to exhaustively and more precisely examine the discrete components of a phenotype and goes beyond the information usually included in medical charts. This form of phenotyping is a critical component of more precise diagnostic capability and 3-dimensional facial analysis (3DFA) is a key technological enabler in this domain. In this paper, we examine the potential of 3DFA as a public health tool, by viewing it against the 10 essential public health services of the “public health wheel,” developed by the US Centers for Disease Control. This provides an illustrative framework to gage current and emergent applications of genomic technologies for implementing precision public health.

Indigenous Genetics and Rare Diseases: Harmony, Diversity and Equity

Advances in our understanding of genetic and rare diseases are changing the face of healthcare. Crucially, the global community must implement these advances equitably to reduce health disparities, including between Indigenous and non-Indigenous peoples. We take an Australian perspective to illustrate some key areas that are fundamental to the equitable translation of new knowledge for the improved diagnosis of genetic and rare diseases for Indigenous people. Specifically, we focus on inequalities in access to clinical genetics services and the lack of genetic and phenomic reference data to inform diagnoses. We provide examples of ways in which these inequities are being addressed through Australian partnerships to support a harmonious and inclusive approach to ensure that benefits from traditional wisdom, community knowledge and shared experiences are interwoven to support and inform implementation of new knowledge from genomics and precision public health. This will serve to deliver benefits to all of our diverse citizens, including Indigenous populations.

Improved Diagnosis and Care for Rare Diseases through Implementation of Precision Public Health Framework

Public health relies on technologies to produce and analyse data, as well as effectively develop and implement policies and practices. An example is the public health practice of epidemiology, which relies on computational technology to monitor the health status of populations, identify disadvantaged or at risk population groups and thereby inform health policy and priority setting. Critical to achieving health improvements for the underserved population of people living with rare diseases is early diagnosis and best care. In the rare diseases field, the vast majority of diseases are caused by destructive but previously difficult to identify protein-coding gene mutations. The reduction in cost of genetic testing and advances in the clinical use of genome sequencing, data science and imaging are converging to provide more precise understandings of the 'person-time-place' triad. That is: who is affected (people); when the disease is occurring (time); and where the disease is occurring (place). Consequently we are witnessing a paradigm shift in public health policy and practice towards 'precision public health'.Patient and stakeholder engagement has informed the need for a national public health policy framework for rare diseases. The engagement approach in different countries has produced highly comparable outcomes and objectives. Knowledge and experience sharing across the international rare diseases networks and partnerships has informed the development of the Western Australian Rare Diseases Strategic Framework 2015-2018 (RD Framework) and Australian government health briefings on the need for a National plan.The RD Framework is guiding the translation of genomic and other technologies into the Western Australian health system, leading to greater precision in diagnostic pathways and care, and is an example of how a precision public health framework can improve health outcomes for the rare diseases population.Five vignettes are used to illustrate how policy decisions provide the scaffolding for translation of new genomics knowledge, and catalyze transformative change in delivery of clinical services. The vignettes presented here are from an Australian perspective and are not intended to be comprehensive, but rather to provide insights into how a new and emerging 'precision public health' paradigm can improve the experiences of patients living with rare diseases, their caregivers and families.The conclusion is that genomic public health is informed by the individual and family needs, and the population health imperatives of an early and accurate diagnosis; which is the portal to best practice care. Knowledge sharing is critical for public health policy development and improving the lives of people living with rare diseases.

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.

A germline MTOR mutation in Aboriginal Australian siblings with intellectual disability, dysmorphism, macrocephaly, and small thoraces

We report on three Aboriginal Australian siblings with a unique phenotype which overlaps with known megalencephaly syndromes and RASopathies, including Costello syndrome. A gain-of-function mutation in MTOR was identified and represents the first reported human condition due to a germline, familial MTOR mutation. We describe the findings in this family to highlight that (i) the path to determination of pathogenicity was confounded by the lack of genomic reference data for Australian Aboriginals and that (ii) the disease biology, functional analyses in this family, and studies on the tuberous sclerosis complex support consideration of an mTOR inhibitor as a therapeutic agent.

A Pilot Study on the Influence of Facial Expression on Measurements in Three-Dimensional Digital Surfaces of the Face in Infants With Cleft Lip and Palate

OBJECTIVE

Three-dimensional surface imaging is an increasingly popular modality for face measurements in infants with cleft lip and palate. Infants are noncompliant toward producing specific facial expressions, and selecting the appropriate moment of acquisition is challenging. The objective was to estimate amount and spatial distribution of deformation of the face due to facial expression in infants with cleft lip and palate and provide recommendations for an improved acquisition protocol, including a method of quality control in terms of obtaining images with true neutral expression.

MATERIAL AND METHODS

Three-dimensional surface images of ten 4-month-old infants with unrepaired cleft lip and palate were obtained using a 3dMDface stereophotogrammetric system. For each subject, five surface images judged as representing a neutral expression were obtained during the same photo session. Mean and maximum deformations were calculated. A formalized review was performed, allowing the image exhibiting the "best" neutral expression to be selected, thus decreasing errors due to residual facial expression.

RESULTS

Deformation due to facial expression generally increased from forehead to chin. The amount of deformation in three selected regions were determined: nose (mean, 1 mm; maximum = 3 mm); cleft region (mean, 2 mm; maximum = 5 mm); chin region (mean, 5 mm; maximum = 12 mm). Analysis indicated that introduction of a formalized review of images could reduce these errors by a factor of 2.

CONCLUSIONS

The continuous change of facial expression in infants represents a substantial source of error; however, this may be reduced by incorporating a formalized review into the acquisition protocol.

Phenotyping: targeting genotype's rich cousin for diagnosis

There are many current and evolving tools to assist clinicians in their daily work of phenotyping. In medicine, the term 'phenotype' is usually taken to mean some deviation from normal morphology, physiology and behaviour. It is ascertained via history, examination and investigations, and a primary aim is diagnosis. Therefore, doctors are, by necessity, expert 'phenotypers'. There is an inherent and partially realised power in phenotypic information that when harnessed can improve patient care. Furthermore, phenotyping developments are increasingly important in an era of rapid advances in genomic technology. Fortunately, there is an expanding network of phenotyping tools that are poised for clinical translation. These tools will preferentially be implemented to mirror clinical workflows and to integrate with advances in genomic and information-sharing technologies. This will synergise with and augment the clinical acumen of medical practitioners. We outline key enablers of the ascertainment, integration and interrogation of clinical phenotype by using genetic diseases, particularly rare ones, as a theme. Successes from the test bed or rare diseases will support approaches to common disease.

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.

Diagnostically relevant facial gestalt information from ordinary photos

Craniofacial characteristics are highly informative for clinical geneticists when diagnosing genetic diseases. As a first step towards the high-throughput diagnosis of ultra-rare developmental diseases we introduce an automatic approach that implements recent developments in computer vision. This algorithm extracts phenotypic information from ordinary non-clinical photographs and, using machine learning, models human facial dysmorphisms in a multidimensional 'Clinical Face Phenotype Space'. The space locates patients in the context of known syndromes and thereby facilitates the generation of diagnostic hypotheses. Consequently, the approach will aid clinicians by greatly narrowing (by 27.6-fold) the search space of potential diagnoses for patients with suspected developmental disorders. Furthermore, this Clinical Face Phenotype Space allows the clustering of patients by phenotype even when no known syndrome diagnosis exists, thereby aiding disease identification. We demonstrate that this approach provides a novel method for inferring causative genetic variants from clinical sequencing data through functional genetic pathway comparisons.DOI: http://dx.doi.org/10.7554/eLife.02020.001.

Diagnostically relevant facial gestalt information from ordinary photos

Craniofacial characteristics are highly informative for clinical geneticists when diagnosing genetic diseases. As a first step towards the high-throughput diagnosis of ultra-rare developmental diseases we introduce an automatic approach that implements recent developments in computer vision. This algorithm extracts phenotypic information from ordinary non-clinical photographs and, using machine learning, models human facial dysmorphisms in a multidimensional 'Clinical Face Phenotype Space'. The space locates patients in the context of known syndromes and thereby facilitates the generation of diagnostic hypotheses. Consequently, the approach will aid clinicians by greatly narrowing (by 27.6-fold) the search space of potential diagnoses for patients with suspected developmental disorders. Furthermore, this Clinical Face Phenotype Space allows the clustering of patients by phenotype even when no known syndrome diagnosis exists, thereby aiding disease identification. We demonstrate that this approach provides a novel method for inferring causative genetic variants from clinical sequencing data through functional genetic pathway comparisons.DOI: http://dx.doi.org/10.7554/eLife.02020.001.

Objective monitoring of mTOR inhibitor therapy by three-dimensional facial analysis

With advances in therapeutics for rare, genetic and syndromic diseases, there is an increasing need for objective assessments of phenotypic endpoints. These assessments will preferentially be high precision, non-invasive, non-irradiating, and relatively inexpensive and portable. We report a case of a child with an extensive lymphatic vascular malformation of the head and neck, treated with an mammalian target of Rapamycin (mTOR) inhibitor that was assessed using 3D facial analysis. This case illustrates that this technology is prospectively a cost-effective modality for treatment monitoring, and it supports that it may also be used for novel explorations of disease biology for conditions associated with disturbances in the mTOR, and interrelated, pathways.

Quantitative three-dimensional assessment of port-wine stain clearance after laser treatments

BACKGROUND AND OBJECTIVE

Outcomes analysis of laser treatment for port-wine stains has been hampered by the lack of an objective measure of surface area and volume; moreover, treatment success is often gauged by clinician subjective assessment. Three-dimensional (3D) surface imaging has been applied in several medical disciplines to quantify surface changes, with promising results. We hypothesized that 3D surface imaging could be used to objectively measure changes in area and volume of port-wine stains following laser treatment.

STUDY DESIGN/MATERIALS AND METHODS

We performed a retrospective review of consecutive patients with port-wine stains treated over a 20-month time period. Area and volume of the lesions were measured using 3dMD photogrammetric software (3dMD, Atlanta, GA) before and after a series of sequential pulsed dye laser and/or alexandrite laser treatments.

RESULTS

Fifty-five patients with 59 port-wine stains were included in the study. The initial average measured area was 44.3 cm(2) ; final average measured area decreased to 36.9 cm(2) (P < 0.001). The average volume change was 1.20 cc for all PWS included in the study and 1.90 cc for lesions that received at least 5 laser treatments within the study period.

CONCLUSION

Three-dimensional photography demonstrated area and volume changes in patients with port-wine stains after laser treatments. Future studies to determine if statistically significant changes correlate with clinically appreciable changes are warranted.