Facial Phenotype Research Articles

Insights into the genetic architecture of the human face.

The human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study (GWAS) meta-analysis of 8,246 European individuals, we identified 203 genome-wide significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses find that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In sum, our analyses provide insights for understanding how complex morphological traits are shaped by both individual and coordinated genetic actions.

The point‐of‐care use of a facial phenotyping tool in the genetics clinic: An ethics tête‐a‐tête

The <scp>point‐of‐care</scp> use of a facial phenotyping tool in the genetics clinic: An ethics <scp>tête‐a‐tête</scp>

Assessment of craniofacial and dental characteristics in individuals with treacher collins syndrome. A review

Treacher Collins Syndrome (TCS) is a genetic disorder with predominantly autosomal dominant inheritance, associated with different mutations in specific genes. This review aimed to evaluate the facial, temporomandibular, zygomatic and bucco-dental phenotype in TCS individuals, and describe surgical and non-surgical solutions for each case in order to improve the quality of life of these individuals. A review of the literature on the craniofacial characteristics of the TCS was carried out, using the PICO strategy, and then a systematic search method was performed in Medline, Scopus, LILACS and SCIELO databases, identifying articles of impact and relevance until 10 June 2020, 240 articles were recovered and only 35 fulfilled the selection criteria. We found the main craniofacial and oral morphological characteristics of these individuals, and the possible functional alterations inducing repercussion in the stomatognathic apparatus. Among other characteristics, the most representative include hypoplasia in the zygomatic and mandibular complex, which can cause difficulty in breathing and feeding. In some cases, cleft palate and malocclusions such as anterior open bite may lead to Angle’s Class II malocclusion, sometimes causing problems in the temporomandibular joint. In conclusion, individuals with TCS have specific craniofacial features including maxillary hypoplasia, altered orbital zones, mandibular retrognathia, and temporomandibular disorders. Oral deformities produce to a higher prevalence of caries and calculus formation because of poor hygiene due to the malformations present in these patients.

RLIM Is a Candidate Dosage-Sensitive Gene for Individuals with Varying Duplications of Xq13, Intellectual Disability, and Distinct Facial Features

Interpretation of the significance of maternally inherited X chromosome variants in males with neurocognitive phenotypes continues to present a challenge to clinical geneticists and diagnostic laboratories. Here we report 14 males from 9 families with duplications at the Xq13.2-q13.3 locus with a common facial phenotype, intellectual disability (ID), distinctive behavioral features, and a seizure disorder in two cases. All tested carrier mothers had normal intelligence. The duplication arose de novo in three mothers where grandparental testing was possible. In one family the duplication segregated with ID across three generations. RLIM is the only gene common to our duplications. However, flanking genes duplicated in some but not all the affected individuals included the brain-expressed genes NEXMIF, SLC16A2, and the long non-coding RNA gene FTX. The contribution of the RLIM-flanking genes to the phenotypes of individuals with different size duplications has not been fully resolved. Missense variants in RLIM have recently been identified to cause X-linked ID in males, with heterozygous females typically having normal intelligence and highly skewed X chromosome inactivation. We detected consistent and significant increase of RLIM mRNA and protein levels in cells derived from seven affected males from five families with the duplication. Subsequent analysis of MDM2, one of the targets of the RLIM E3 ligase activity, showed consistent downregulation in cells from the affected males. All the carrier mothers displayed normal RLIM mRNA levels and had highly skewed X chromosome inactivation. We propose that duplications at Xq13.2-13.3 including RLIM cause a recognizable but mild neurocognitive phenotype in hemizygous males.

Efficiency of Computer-Aided Facial Phenotyping (DeepGestalt) in Individuals With and Without a Genetic Syndrome: Diagnostic Accuracy Study.

BackgroundCollectively, an estimated 5% of the population have a genetic disease. Many of them feature characteristics that can be detected by facial phenotyping. Face2Gene CLINIC is an online app for facial phenotyping of patients with genetic syndromes. DeepGestalt, the neural network driving Face2Gene, automatically prioritizes syndrome suggestions based on ordinary patient photographs, potentially improving the diagnostic process. Hitherto, studies on DeepGestalt’s quality highlighted its sensitivity in syndromic patients. However, determining the accuracy of a diagnostic methodology also requires testing of negative controls.ObjectiveThe aim of this study was to evaluate DeepGestalt's accuracy with photos of individuals with and without a genetic syndrome. Moreover, we aimed to propose a machine learning–based framework for the automated differentiation of DeepGestalt’s output on such images.MethodsFrontal facial images of individuals with a diagnosis of a genetic syndrome (established clinically or molecularly) from a convenience sample were reanalyzed. Each photo was matched by age, sex, and ethnicity to a picture featuring an individual without a genetic syndrome. Absence of a facial gestalt suggestive of a genetic syndrome was determined by physicians working in medical genetics. Photos were selected from online reports or were taken by us for the purpose of this study. Facial phenotype was analyzed by DeepGestalt version 19.1.7, accessed via Face2Gene CLINIC. Furthermore, we designed linear support vector machines (SVMs) using Python 3.7 to automatically differentiate between the 2 classes of photographs based on DeepGestalt's result lists.ResultsWe included photos of 323 patients diagnosed with 17 different genetic syndromes and matched those with an equal number of facial images without a genetic syndrome, analyzing a total of 646 pictures. We confirm DeepGestalt’s high sensitivity (top 10 sensitivity: 295/323, 91%). DeepGestalt’s syndrome suggestions in individuals without a craniofacially dysmorphic syndrome followed a nonrandom distribution. A total of 17 syndromes appeared in the top 30 suggestions of more than 50% of nondysmorphic images. DeepGestalt’s top scores differed between the syndromic and control images (area under the receiver operating characteristic [AUROC] curve 0.72, 95% CI 0.68-0.76; P<.001). A linear SVM running on DeepGestalt’s result vectors showed stronger differences (AUROC 0.89, 95% CI 0.87-0.92; P<.001).ConclusionsDeepGestalt fairly separates images of individuals with and without a genetic syndrome. This separation can be significantly improved by SVMs running on top of DeepGestalt, thus supporting the diagnostic process of patients with a genetic syndrome. Our findings facilitate the critical interpretation of DeepGestalt’s results and may help enhance it and similar computer-aided facial phenotyping tools.

Coping with Wolf-Hirschhorn syndrome: quality of life and psychosocial features of family carers

BackgroundWolf-Hirschhorn Syndrome (WHS) is a rare, congenital disease characterized by a distinctive facial phenotype, seizures, intellectual disability and developmental delay, and pre and postnatal growth requiring lifelong care. The psychosocial status of the family caregivers of children diagnosed with WHS is unknown. This study aims to characterize the sociodemographic and psychosocial profile of WHS caregivers and analyze how these variables impact their quality of life (QoL) and well-being.ResultsThe sociodemographic and clinical profile of 22 Spanish caregivers of children with WHS and the characteristics of those affected have been described. Significant relationships were found between sociodemographic and psychosocial characteristics among caregivers. The impact on the parents’ QoL and negative relationship with the symptomatology were assessed. The use of engagement strategies such as problem focused coping was associated with improved psychological QoL and social support.ConclusionsWHS caregivers share similarities in their profile and needs with caregivers of children with other rare diseases. Pychosocial support groups involving parents caring for children with the same disease could improve caregivers’ well-being and QoL by strengthening their social support network and using positive coping styles.

Various haploinsufficiency mechanisms in Pitt-Hopkins syndrome

Pitt-Hopkins syndrome is a rare neurodevelopment disorder caused by haploinsufficiency of the transcription factor 4 (TCF4). The main clinical symptoms of Pitt-Hopkins syndrome are severe development delay, intellectual disability, characteristic facial phenotype, and breathing abnormalities, including episodic hyperventilation. Different pathogenic variants can lead to Pitt-Hopkins syndrome. The most common are large deletions at 18q21 encompassing the TCF4 gene and frameshifting/nonsense single nucleotide variants. However, variants in noncoding regions can also lead to Pitt-Hopkins syndrome by disrupting the normal pre-mRNA splicing machinery. Here we describe three patients with Pitt-Hopkins syndrome caused by a large deletion in chromosome 18, a nonsense variant, and a novel variant located in intron 11 of TCF4 c.922+5G > A. Using RT-PCR analysis and minigene splicing assay we showed that this intronic variant leads to exon 11 skipping resulting in a formation of a premature stop codon. To our knowledge, this is the first functional annotation of a splicing variant in Pitt-Hopkins syndrome.

Mechanobehavior and mandibular ramus length in different facial phenotypes.

To test the hypotheses that mechanobehavior scores (MBS) were correlated with mandibular ramus lengths (Co-Go) and differed between facial phenotypes. Subjects gave informed consent to participate. Co-Go (mm), mandibular plane angles (SN-GoGn, °), and three-dimensional anatomy were derived from cephalometric radiography or cone beam computed tomography. Temporomandibular joint (TMJ) energy densities (ED) (mJ/mm3) were measured using dynamic stereometry and duty factors (DF) (%) were measured from electromyography, to calculate MBS (= ED2 × DF,) for each TMJ. Polynomial regressions, K-means cluster analysis, and analysis of variance (ANOVA) with Tukey post-hoc tests were employed. Fifty females and 23 males produced replete data. Polynomial regressions showed MBS were correlated with Co-Go (females, R2 = 0.57; males, R2 = 0.81). Cluster analysis identified three groups (P < .001). Dolichofacial subjects, with shorter normalized Co-Go, clustered into two subgroups with low and high MBS compared to brachyfacial subjects with longer Co-Go. SN-GoGn was significantly larger (P < .03) in the dolichofacial subgroups combined (33.0 ± 5.9°) compared to the brachyfacial group (29.8 ± 5.5°). MBS correlated with Co-Go within sexes and differed significantly between brachyfacial and dolichofacial subjects.

A Preliminary Study on Cranio-Facial Characteristics Associated with Minor Neurological Dysfunctions (MNDs) in Children with Autism Spectrum Disorders (ASD).

Background. Craniofacial anomalies and minor neurological dysfunction (MNDs) have been identified, in literature, as risk factors for neurodevelopmental disorders. They represent physical indicators of embryonic development suggesting a possible contributory role of complications during early, even pre-conceptional, phases of ontogeny in autism spectrum disorders (ASD). Limited research has been conducted about the co-occurrence of the two biomarkers in children with ASD. This study investigates the associative patterns of cranio-facial anomalies and MNDs in ASD children, and whether these neurodevelopmental markers correlate with intensity of ASD symptoms and overall functioning. Methods. Caucasian children with ASD (n = 33) were examined. Measures were based on five anthropometric cranio-facial indexes and a standardized and detailed neurological examination according to Touwen. Relationships between anthropometric z-scores, MNDs and participant characteristics (i.e., age, cognitive abilities, severity of autistic symptoms measured using the Childhood Autism Rating Scale (CARS) checklist) were assessed. Results. With respect to specific MNDs, significant positive correlations were found between Cephalic Index and Sensory deficits (p-value < 0.001), which did not correlate with CARS score. Importantly, CARS score was positively linked with Intercanthal Index (p-value < 0.001), and negatively associated with posture and muscle tone (p-value = 0.027) and Facial Index (p-value = 0.004). Conclusion. Our data show a link between a specific facial phenotype and anomalies in motor responses, suggesting early brain dysmaturation involving subcortical structures in cerebro-craniofacial development of autistic children. This research supports the concept of a “social brain functional morphology” in autism spectrum disorders.

Facial Port-Wine Stain Phenotypes Associated with Glaucoma Risk in Neonates

To determine if the size and location of facial port-wine stains (PWS) can predict glaucoma risk in neonates. Retrospective cohort study. Children with facial PWS who had undergone ophthalmologic examination within 4weeks of their birth were included. Clinical information, including facial photographs, intraocular pressure, corneal diameter, optic disc cup-to-disc ratio, and Sturge-Weber syndrome (SWS) diagnoses were collected. Based on facial photographs, PWS distribution, eyelid involvement, and PWS scores according to degree of involvement in each embryonic facial vasculature distribution (segment [S]1, S2 and S3) were evaluated. Among the 34 patients, 7 (21%) had bilateral PWS lesions. Eighteen (53%) had diagnoses of glaucoma. The proportion of eyes showing PWS involving both S1 and S2 was the highest (n= 15, 37%), and the frequency of glaucoma diagnosis (n= 9, 60%) was also the greatest. In eyelid involvement analysis, among the 7 eyes with only lower-eyelid lesions, 5 (83%) had glaucoma. Among the 11 eyes with only upper-eyelid lesions, however, 2 (18%) had diagnoses of glaucoma. A logistic regression model showed that the significant factors associated with glaucoma risk were greater PWS scores in S2 (odds ratio [OR]: 3.604; 95% confidence interval: 1.078-12.050; P= .037) or lower-eyelid involvement (OR: 12.816; 95% CI: 1.698-96.744; P= .013). Among the newborns with facial PWS, 1) a greater extent of birthmarks involving the S2 area, and 2) lesions including the lower eyelid were associated with higher risk of glaucoma development within the neonatal period.

Human facial shape related SNP analysis in Han Chinese populations

Human facial morphology is one of the important visible biological characteristics. Understanding the genetic basis underlying facial shape traits has important implications in population genetics, developmental biology, and forensic science. This study extracted 136 Euclidean distance phenotypes from 17 facial features of high-resolution 3D facial images in 1177 Chinese Han adult males. Based on 3× low-depth sequencing data, linear regression was used to analyze the correlation between 125 reported SNPs significantly associated with facial morphology and 136 facial phenotypes. As a result, a total of twelve SNPs from ten genes demonstrated significant association with one or more facial shape traits after adjusting for multiple testing (significance threshold P < 1.35 × 10 -3 ), together explaining up to 3.89% of age-, and BMI-adjusted facial phenotype variance. These included TEX41 rs17479393, PAX3 rs974448, RAB7A/ACAD9 rs2977562, DCHS2 rs9995821, DCHS2 rs2045323, C5orf50 rs6555969, SUPT3H/RUNX2 rs1852985, MSRA rs11782517, EYA1 rs10504499, GSC rs2224309, DICER1 rs7161418 and DHX35 rs2206437.These results revealed the genetics basis of facial morphology of Han Chinese population, and provided reference data for DNA-based face prediction.

Diagnostic performance of artificial intelligence to detect genetic diseases with facial phenotypes: A protocol for systematic review and meta analysis.

Background:Many genetic diseases are known to have distinctive facial phenotypes, which are highly informative to provide an opportunity for automated detection. However, the diagnostic performance of artificial intelligence to identify genetic diseases with facial phenotypes requires further investigation. The objectives of this systematic review and meta-analysis are to evaluate the diagnostic accuracy of artificial intelligence to identify the genetic diseases with face phenotypes and then find the best algorithm.Methods:The systematic review will be conducted in accordance with the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols” guidelines. The following electronic databases will be searched: PubMed, Web of Science, IEEE, Ovid, Cochrane Library, EMBASE and China National Knowledge Infrastructure. Two reviewers will screen and select the titles and abstracts of the studies retrieved independently during the database searches and perform full-text reviews and extract available data. The main outcome measures include diagnostic accuracy, as defined by accuracy, recall, specificity, and precision. The descriptive forest plot and summary receiver operating characteristic curves will be used to represent the performance of diagnostic tests. Subgroup analysis will be performed for different algorithms aided diagnosis tests. The quality of study characteristics and methodology will be assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data will be synthesized by RevMan 5.3 and Meta-disc 1.4 software.Results:The findings of this systematic review and meta-analysis will be disseminated in a relevant peer-reviewed journal and academic presentations.Conclusion:To our knowledge, there have not been any systematic review or meta-analysis relating to diagnosis performance of artificial intelligence in identifying the genetic diseases with face phenotypes. The findings would provide evidence to formulate a comprehensive understanding of applications using artificial intelligence in identifying the genetic diseases with face phenotypes and add considerable value in the future of precision medicine.OSF Registration:DOI 10.17605/OSF.IO/P9KUH.

Craniofacial allometry in the OIM-/- mouse model of osteogenesis imperfecta.

Osteogenesis imperfecta (OI) is a skeletal disorder characterized by the impaired synthesis of type I collagen (Col1). This study tests the hypothesis that the craniofacial phenotype of severe OI is linked to an overall reduction in body size. 3D landmark data were collected from µCT scans of adult OIM-/- and wild-type (WT) mice and used to calculate centroid sizes (CS) and interlandmark distances (ILDs). To remove the effect of body size, ILDs were scaled against craniomandibular lengths and CS. Mann-Whitney U tests were used to compare CS and absolute/scaled ILDs between genotypes. OIM-/- mice are smaller than their WT littermates in body mass, craniomandibular CS, and absolute ILDs including skull, basicranial, palatal, mandibular, and toothrow lengths. When linear distances are scaled to CS, OIM-/- mice have a relatively short midface, short nasal bones, tall mandibular corpora, and long mandibular toothrows. Results underscore the importance of size and scaling in morphometric analyses. The deleterious effect of Col1 mutations on global skeletal dimensions combined with localized morphometric changes may underlie the facial phenotype seen in human patients with severe OI. Attempts to identify these localized changes should first account for the restricted growth and small body sizes present in individuals with OI.

Differentiating molecular etiologies of Angelman syndrome through facial phenotyping using deep learning.

Angelman syndrome (AS) is caused by several genetic mechanisms that impair the expression of maternally-inherited UBE3A through deletions, paternal uniparental disomy (UPD), UBE3A pathogenic variants, or imprinting defects. Current methods of differentiating the etiology require molecular testing, which is sometimes difficult to obtain. Recently, computer-based facial analysis systems have been used to assist in identifying genetic conditions based on facial phenotypes. We sought to understand if the facial-recognition system DeepGestalt could find differences in phenotype between molecular subtypes of AS. Images and molecular data on 261 individuals with AS ranging from 10 months through 32 years were analyzed by DeepGestalt in a cross-validation model with receiver operating characteristic (ROC) curves generated. The area under the curve (AUC) of the ROC for each molecular subtype was compared and ranked from least to greatest differentiable phenotype. We determined that DeepGestalt demonstrated a high degree of discrimination between the deletion subtype and UPD or imprinting defects, and a lower degree of discrimination with the UBE3A pathogenic variants subtype. Our findings suggest that DeepGestalt can recognize subclinical differences in phenotype based on etiology and may provide decision support for testing.

Unique skeletal manifestations in patients with Primrose syndrome

Primrose syndrome (OMIM 259050) is a rare disorder characterised by macrocephaly with developmental delay, a recognisable facial phenotype, altered glucose metabolism, and other features such as sensorineural hearing loss, short stature, and calcification of the ear cartilage. It is caused by heterozygous variants in ZBTB20, a member of the POK family of transcription repressors. Recently, this gene was shown to have a role in skeletal development through its action on chondrocyte differentiation by repression of SOX9. We describe five unrelated patients with Primrose syndrome and distinct skeletal features including multiple Wormian bones, platybasia, bitemporal bossing, bathrocephaly, slender bones, epiphyseal and spondylar dysplasia. The radiological abnormalities of the skull and the epiphyseal dysplasia were the most consistent findings. This novel constellation of skeletal features expands the phenotypic spectrum of the disorder.

Treacher Collins syndrome: A novel TCOF1 mutation and monopodial stapes.

To investigate four Treacher Collins syndrome patients of the Sgaw Karen family living in Thailand. Clinical examination, hearing tests, lateral cephalometric analyses, Computed tomography, whole exome sequencing and Sanger direct sequencing were performed. All of the patients affected with Treacher Collins syndrome carried a novel TCOF1 mutation (c.4138_4142del; p.Lys1380GlufsTer12), but clinically they did not have the typical facial gestalt of Treacher Collins syndrome, which includes downward-slanting palpebral fissures, colobomas of the lower eyelids, absence of eyelashes medial to the colobomas, malformed pinnae, hypoplastic zygomatic bones and mandibular hypoplasia. Lateral cephalometric analyses identified short anterior and posterior cranial bases, and hypoplastic maxilla and mandible. Computed tomography showed fusion of malleus and incus, sclerotic mastoid, hypoplastic middle ear space with a soft tissue remnant, dehiscence of facial nerve and monopodial stapes. Treacher Collins syndrome in Sgaw Karen patients has not been previously documented. This is the first report of monopodial stapes in a TCS patient who had a TCOF1 mutation. The absence of a common facial phenotype and/or the presence of monopodial stapes may be the effects of this novel TCOF1 mutation.

Shared facial phenotype of patients with mucolipidosis type IV: A clinical observation reaffirmed by next generation phenotyping.

Mucolipidosis type IV (ML-IV) is a rare autosomal-recessive lysosomal storage disease, caused by mutations in MCOLN1. ML-IV manifests with developmental delay, esotropia and corneal clouding. While the clinical phenotype is well-described, the diagnosis of ML-IV is often challenging and elusive. Our experience with ML-IV patients brought to the clinical observation that they share common and identifiable facial features, not yet described in the literature to date. Here, we utilized a computerized facial analysis tool to establish this association. Using the DeepGestalt algorithm, 50 two-dimensional facial images of ten ML-IV patients were analyzed, and compared to unaffected controls (n=98) and to individuals affected with other genetic disorders (n=99). Results were expressed in terms of the area-under-the-curve (AUC) of the receiver-operating-characteristic curve (ROC). When compared to unaffected cases and to cases diagnosed with syndromes other than ML-IV, the ML-IV cohort showed an AUC of 0.822 (p value < 0.01) and an AUC of 0.885 (p value < 0.001), respectively. We describe recognizable facial features typical in patients with ML-IV. Reaffirmed by the DeepGestalt technology, the described common facial phenotype adds to the tools currently available for clinicians and may thus assist in reaching an earlier diagnosis of this rare and underdiagnosed disorder.

Bi-allelic Loss-of-Function Variants in NUP188 Cause a Recognizable Syndrome Characterized by Neurologic, Ocular, and Cardiac Abnormalities

Nucleoporins (NUPs) are an essential component of the nuclear-pore complex, which regulates nucleocytoplasmic transport of macromolecules. Pathogenic variants in NUP genes have been linked to several inherited human diseases, including a number with progressive neurological degeneration. We present six affected individuals with bi-allelic truncating variants in NUP188 and strikingly similar phenotypes and clinical courses, representing a recognizable genetic syndrome; the individuals are from four unrelated families. Key clinical features include congenital cataracts, hypotonia, prenatal-onset ventriculomegaly, white-matter abnormalities, hypoplastic corpus callosum, congenital heart defects, and central hypoventilation. Characteristic dysmorphic features include small palpebral fissures, a wide nasal bridge and nose, micrognathia, and digital anomalies. All affected individuals died as a result of respiratory failure, and five of them died within the first year of life. Nuclear import of proteins was decreased in affected individuals' fibroblasts, supporting a possible disease mechanism. CRISPR-mediated knockout of NUP188 in Drosophila revealed motor deficits and seizure susceptibility, partially recapitulating the neurological phenotype seen in affected individuals. Removal of NUP188 also resulted in aberrant dendrite tiling, suggesting a potential role of NUP188 in dendritic development. Two of the NUP188 pathogenic variants are enriched in the Ashkenazi Jewish population in gnomAD, a finding we confirmed with a separate targeted population screen of an international sampling of 3,225 healthy Ashkenazi Jewish individuals. Taken together, our results implicate bi-allelic loss-of-function NUP188 variants in a recessive syndrome characterized by a distinct neurologic, ophthalmologic, and facial phenotype.

Analyzing Facial Asymmetry in Children as a Function of BMI

Childhood obesity is a major public health concern in the US with a prevalence of nearly 19% for all children and adolescents. During growth, environmental factors such as poor diet can result in increased developmental stress. Given the symmetric patterning of facial growth in humans, any random deviations from symmetry, referred to as fluctuating asymmetry (FA), are considered a reflection of stress during growth. In this study, we examine whether childhood obesity serves as a source of developmental stress resulting in increased facial asymmetry. We hypothesize that a significant relationship between facial asymmetry and BMI exists, with higher BMI individuals demonstrating increased levels of facial asymmetry.To test our hypothesis, we obtained n=354 3D facial scans of children (age 3–19) from the University of Pittsburgh Center for Craniofacial and Dental Genetics. A total of n=286 facial scans represented children with a normal weight and n=68 faces were from children with obesity. Obesity status was determined using BMI values at or above the 95th percentile. Facial scans were digitized using 34 coordinate landmarks to capture asymmetry in the eyes, nose, mouth, and lower jaw. Coordinate data was submitted to a Generalized Procrustes Analysis (GPA) to align the facial landmarks and geometric morphometrics (GM) was then employed to quantify facial shape phenotypes in MorphoJ. Principal Component Analysis (PCA) was used to identify patterns of facial asymmetry throughout the entire sample. Canonical Variate Analysis (CVA) was then employed to identify differences in facial shape due to BMI. Lastly, a Procrustes ANOVA was ran to quantify levels of fluctuating asymmetry in the sample and the resulting FA scores were regressed against BMI percentile to test for a significant relationship.The results from the PCA identified 43 principal components (PCs), with the first three PCs accounting for 44.3% of total facial asymmetry. PC1 (accounting for 20.6% of facial asymmetry) identified asymmetry in the position of the eyes and a slight deviation of the nose, mouth and lower jaw to the left or right. PC2 (12.9%) demonstrated asymmetry primarily between the jaw and nose. PC3 (10.7%) further illustrated asymmetries through the eyes and jaw. The results of the CVA showed a significant difference (p=0.023) in overall asymmetry between normal weight children with children with obesity. Normal weight children demonstrated a trend toward facial symmetry while obese children showed marked asymmetry with respect to the eyes, nose, and chin. Finally, the results of the regression between FA scores and BMI percentile did not produce any significant association (p=0.72).While these results indicate a significant difference in the patterning of facial asymmetry between normal and obese children, evidence for increased FA levels (and therefore developmental instability) was not observed. Although we reject our hypothesis, the results demonstrate interesting facial asymmetries between BMI groups that may be promising for future analysis with longitudinal data.Support or Funding InformationGrant support: R01‐DE016148

Understanding Brain/Face Integration from Neuropsychiatric Disorders

Understanding how genetic and environmental variation alter the integrated development of the face and the brain has important implications for medicine and human evolution. Neuropsychiatric disorders offer an ideal model for investigating the association between facial and brain phenotypes with their underlying genotype. Schizophrenia (SZ) and Bipolar Disorder (BD) are severe psychiatric disorders caused by pathological processes occurring early in neurodevelopment. Disruptions in signaling pathways that are common to brain and face development may explain why these disorders are associated with abnormalities of brain structure and a high prevalence of minor facial dysmorphologies. We assessed facial shape with its neuroanatomical and genetic correlates in a sample with magnetic resonances and genetic data available for 188 subjects (75 healthy controls, 67 SZ and 46 BP patients). Geometric Morphometrics revealed that facial shape variation assessed from 3D facial reconstructions significantly differentiated between SZ/BP patients and controls with moderate accuracy (60–65%). ANOVA tests detected a significant association between facial shape and specific measures of the brain superior frontal regions (thickness, volume and area), whereas the explained facial shape variation increased from 1% to 4.8% in SZ and 6.5% in BD when we included in the model the interaction between a SNP in GLI3 gene and these brain measures. We conclude that facial shape may be considered as an indirect marker of deviances in brain development, and GLI3 as a modulator of brain‐face relationships; probably due to the key role of this gene in the Shh signaling pathway regulating brain and face development.Support or Funding InformationMinisterio de Ciencia, Innovación y Universidades, Proyectos I+D+i «Retos Investigación» RTI2018‐097845‐J‐I00; 2017SGR1630; 2017SGR1271; CD16/00264.