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Introduction and aim: Oculo-auriculo-vertebral spectrum (OAVS) is a congenital complex of extremely variable phenotypes. Typically, unilaterally affected structuresare facial structures developing from the first and second branchial arches and first pharyngeal pouch and first branchial cleft and the basis of temporal bone. The aim is to introduce the clinical conditions of the disease whose facial asymmetry is accompanied by a number of functional disorders. Moreover, it presents non-invasive 3D morphometry, that enables evaluation of the morphological deviation of the affected area. Methods: An accurate geometric 3D image of the patient's face was created by the optical method – stereophotogrammetry in six patients (age from 6 to 15; 5 , 1) with OAVS. Using the construction of dense correspondence mapping by CPD-DCA (coherent point drift – dense correspondence analysis) method between facial meshes, model registration were performed. A perfectly symmetrical face was constructed for each patient. The differences between the constructed symmetrical face and the real patient's face were shown using a color map. The individual asymmetry thus displayed was quantitatively processed and analyzed over a period of nine to 23 months. Results: Only minor differences in facial asymmetry of OAVS patients have been demonstrated, suggesting an insignificant dynamics in the development of facial malformations in patients with this disease. We did not find a dependence between face relief changes and patient age during the reference period. There was also no correlation between the severity of the defect and the development of asymmetry. Conclusion: Significant worsening of facial morphology in growing OAVS patients has not been confirmed as supposed. That allows satisfactory compensation of defects by early orthodontic treatment. Non-invasive 3D morphometric facial scanning is an optimal method for monitoring the development of facial asymmetries. [ABSTRACT FROM AUTHOR]

Aim: To utilize three-dimensional (3D) geometric morphometry for visualization of the level of facial asymmetry in patients with the oculo-auriculo-vertebral spectrum (OAVS)., Materials and Methods: Three-dimensional facial scans of 25 Czech patients with OAVS were processed. The patients were divided into subgroups according to Pruzansky classification. For 13 of them, second 3D facial scans were obtained. The 3D facial scans were processed using geometric morphometry. Soft tissue facial asymmetry in the sagittal plane and its changes in two time spots were visualized using colour-coded maps with a thermometre-like scale., Results: Individual facial asymmetry was visualized in all patients as well as the mean facial asymmetry for every Pruzansky subgroup. The mean colour-coded maps of type I and type IIA subgroups showed no differences in facial asymmetry, more pronounced asymmetry in the middle and the lower facial third was found between type IIA and type IIB (maximum 1.5 mm) and between type IIB and type III (maximum 2 mm). The degree of intensity facial asymmetry in affected middle and lower facial thirds did not change distinctly during the two time spots in all subgroups., Conclusions: The 3D geometric morphometry in OAVS patients could be a useful tool for objective facial asymmetry assessment in patients with OAVS. The calculated colour-coded maps are illustrative and useful for clinical evaluation., (© 2024 The Author(s). Orthodontics & Craniofacial Research published by John Wiley & Sons Ltd.)

Cluster analyzes of facial models of autistic patients aim to clarify whether it is possible to diagnose autism on the basis of facial features and further to stratify the autism spectrum disorder. We performed a cluster analysis of sets of 3D scans of ASD patients (116) and controls (157) using Euclidean and geodesic distances in order to recapitulate the published results on the Czech population. In the presented work, we show that the major factor determining the clustering structure and consequently also the correlation of resulting clusters with autism severity degree is body mass index corrected for age (BMIFA). After removing the BMIFA effect from the data in two independent ways, both the cluster structure and autism severity correlations disappeared. Despite the fact that the influence of body mass index (BMI) on facial dimensions was studied many times, this is the first time to our knowledge when BMI was incorporated into the faces clustering study and it thereby casts doubt on previous results. We also performed correlation analysis which showed that the only correction used in the existing clustering studies-dividing the facial distance by the average value within the face-is not eliminating correlation between facial distances and BMIFA within the facial cohort., (© 2024. The Author(s).)

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs., (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Zimmermann-Laband syndrome is a rare, heterogeneous disorder characterized by gingival hypertrophy or fibromatosis, aplastic/hypoplastic nails, hypoplasia of the distal phalanges, hypertrichosis, various degrees of intellectual disability, and distinctive facial features. Three genes are considered causative for ZLS: KCNH1, KCNN3, and ATP6V1B2. We report on a pair of female concordant monozygotic twins, both carrying a novel pathogenic variant in the KCNN3 gene, identified using exome sequencing. Only six ZLS patients with the KCNN3 pathogenic variant have been reported so far. The twins show facial dysmorphism, hypoplastic distal phalanges, aplasia or hypoplasia of nails, and hypertrichosis. During infancy, they showed mild developmental delays, mainly speech. They successfully completed secondary school education and are socio-economically independent. Gingival overgrowth is absent in both individuals. Our patients exhibited an unusually mild phenotype compared to published cases, which is an important diagnostic finding for proper genetic counseling for Zimmermann-Laband syndrome patients and their families., (© 2021 Wiley Periodicals LLC.)

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.

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., (© 2018 Wiley Periodicals, Inc.)

Objectives: To evaluate facial asymmetry changes in pre-school patients with orofacial clefts after neonatal cheiloplasty and to compare facial asymmetry with age-matched healthy controls., Methods and Materials: The sample consisted of patients with unilateral cleft lip (UCL), unilateral cleft lip and palate (UCLP), and bilateral cleft lip and palate (BCLP). The patients were divided in two age groups with a mean age of 3 years (n = 51) and 4.5 years (n = 45), respectively, and 78 age-matched individuals as controls. Three-dimensional (3D) facial scans were analyzed using geometric morphometry and multivariate statistics., Results: Geometric morphometry showed positive deviations from perfect symmetry on the right side of the forehead in the intervention groups and the controls. The UCL groups showed the greatest asymmetric nasolabial area on the cleft-side labia and the contralateral nasal tip. The UCLP group showed, moreover, asymmetry in buccal region due to typical maxillar hypoplasia, which was accentuated in the older group. The BCLP groups showed slightly similar but greater asymmetry than the control groups, except for the philtrum region., Conclusions: Asymmetry of each of the cleft groups significantly differed from the controls. Except for the buccal region in the UCLP and BCLP groups, asymmetry did not significantly increase with age., (Copyright © 2018 Elsevier B.V. All rights reserved.)