OBJECTIVE: This study aims to report a severe phenotype of Arboleda-Tham syndrome in a 20-month-old girl, characterized by global developmental delay, distinct facial features, intellectual disability. Arboleda-Tham syndrome is known for its wide phenotypic spectrum and is associated with truncating variants in the KAT6A gene.
METHODS: To diagnose this case, a combination of clinical phenotype assessment and whole-exome sequencing technology was employed. The genetic analysis involved whole-exome sequencing, followed by confirmation of the identified variant through Sanger sequencing.
RESULTS: The whole-exome sequencing revealed a novel de novo frameshift mutation c.3048del (p.Leu1017Serfs*17) in the KAT6A gene, which is classified as likely pathogenic. This mutation was not found in the ClinVar and HGMD databases and was not present in her parents. The mutation leads to protein truncation or activation of nonsense-mediated mRNA degradation. The mutation is located within exon 16, potentially leading to protein truncation or activation of nonsense-mediated mRNA degradation. Protein modeling suggested that the de novo KAT6A mutation might alter hydrogen bonding and reduce protein stability, potentially damaging the protein structure and function.
CONCLUSIONS: This study expands the understanding of the genetic basis of Arboleda-Tham syndrome, highlighting the importance of whole-exome sequencing in diagnosing cases with varied clinical presentations. The discovery of the novel KAT6A mutation adds to the spectrum of known pathogenic variants and underscores the significance of this gene in the syndrome\'s pathology.

Next-generation phenotyping (NGP) can be used to compute the similarity of dysmorphic patients to known syndromic diseases. So far, the technology has been evaluated in variant prioritization and classification, providing evidence for pathogenicity if the phenotype matched with other patients with a confirmed molecular diagnosis. In a Nigerian cohort of individuals with facial dysmorphism, we used the NGP tool GestaltMatcher to screen portraits prior to genetic testing and subjected individuals with high similarity scores to exome sequencing (ES). Here, we report on two individuals with global developmental delay, pulmonary artery stenosis, and genital and limb malformations for whom GestaltMatcher yielded Cornelia de Lange syndrome (CdLS) as the top hit. ES revealed a known pathogenic nonsense variant, NM_133433.4: c.598C>T; p.(Gln200*), as well as a novel frameshift variant c.7948dup; p.(Ile2650Asnfs*11) in NIPBL. Our results suggest that NGP can be used as a screening tool and thresholds could be defined for achieving high diagnostic yields in ES. Training the artificial intelligence (AI) with additional cases of the same ethnicity might further increase the positive predictive value of GestaltMatcher.

Cri-du-chat syndrome is a rare genetic disorder, due to a deletion of the short arm of chromosome 5 (5p-). Its incidence is ranging from 1/15000 to 1/50000 live births. This was a one-day-old male newborn from a non-consanguineous marriage, the first pregnancy uncomplicated and carried to term with a birth weight of 2295g. Clinical examination revealed: craniofacial dysmorphism with hypertelorism and microcephaly, hypotonia, poor suction and clubfoot more marked on the right, the rest of the examination was unremarkable. During hospitalization, a high-pitched monochromatic cry mimicking a cat\'s meow was observed. The clinical diagnosis was confirmed by fluorescence in situ hybridization, showing a deletion of the short arm of chromosome 5 (5p15.2). The basic malformative work-up came back without any other abnormalities. The association of a high-pitched monochromatic cry with craniofacial dysmorphism in a newborn should indicate the need for cytogenetic study, in particular fluorescence in siti hybridization.

Noonan syndrome is a genetic, developmental disorder characterized by facial deformities, congenital heart defects, webbed neck, wide space nipples, and growth hormone deficiencies. We report a case of a 15-year-old female patient who presented to the outpatient department with recurrent puffiness of both eyes, easy fatiguability, and dyspnea on exertion. The condition was associated with bilateral proximal muscular weakness of lower limbs with positive Gower\'s sign. On examination, the patient had a webbed neck, hypertelorism, a shielded chest, short stature, and a high-arched palate. Thyroid function tests revealed hypothyroidism. Chromosomal analysis revealed 46 XX. After excluding Turner syndrome on karyotyping, Noonan syndrome with hypothyroidism was diagnosed. The patient was started on levothyroxine and referred to a pediatric endocrinologist for further growth and development assessment. Autoimmune hypothyroidism in a patient with Noonan Syndrome is rare; it may occur as a separate entity or have some genetic susceptibility. Further research is needed to determine the association of autoimmune hypothyroidism with Noonan syndrome.

Otofaciocervical syndrome (OTFCS) is a rare genetic disorder of both autosomal recessive and autosomal dominant patterns of inheritance. It is caused by biallelic or monoallelic mutations in PAX1 or EYA1 genes, respectively. Here, we report an OTFCS2 female patient of 1st consanguineous healthy parents. She manifested facial dysmorphism, hearing loss, intellectual disability (ID), and delayed language development (DLD) as the main clinical phenotype. The novel homozygous variant c.1212dup (p.Gly405Argfs*51) in the PAX1 gene was identified by whole exome sequencing (WES), and family segregation confirmed the heterozygous status of the mutation in the parents using the Sanger sequencing. The study recorded a novel PAX1 variant representing the sixth report of OTFCS2 worldwide and the first Egyptian study expanding the geographic area where the disorder was confined.

Neurodevelopment disorders can result in facial dysmorphisms. Therefore, the analysis of facial images using image processing and machine learning techniques can help construct systems for diagnosing genetic syndromes and neurodevelopmental disorders. The systems offer faster and cost-effective alternatives for genotyping tests, particularly when dealing with large-scale applications. However, there are still challenges to overcome to ensure the accuracy and reliability of computer-aided diagnosis systems. This article presents a systematic review of such initiatives, including 55 articles. The main aspects used to develop these diagnostic systems were discussed, namely datasets - availability, type of image, size, ethnicities and syndromes - types of facial features, techniques used for normalization, dimensionality reduction and classification, deep learning, as well as a discussion related to the main gaps, challenges and opportunities.

With recent advances in computer vision, many applications based on artificial intelligence have been developed to facilitate the diagnosis of rare genetic disorders through the analysis of patients\' two-dimensional frontal images. Some of these have been implemented on online platforms with user-friendly interfaces and provide facial analysis services, such as Face2Gene. However, users cannot run the facial analysis processes in house because the training data and the trained models are unavailable. This article therefore provides an introduction, designed for users with programming backgrounds, to the use of the open-source GestaltMatcher approach to run facial analysis in their local environment. The Basic Protocol provides detailed instructions for applying for access to the trained models and then performing facial analysis to obtain a prediction score for each of the 595 genes in the GestaltMatcher Database. The prediction results can then be used to narrow down the search space of disease-causing mutations or further connect with a variant-prioritization pipeline. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Using the open-source GestaltMatcher approach to perform facial analysis.

Laron syndrome (LS) is a rare autosomal recessively segregating disorder of severe short stature. The condition is characterized by short limbs, delayed puberty, hypoglycemia in infancy, and obesity. Mutations in growth hormone receptor (GHR) have been implicated in LS; hence, it is also known as growth hormone insensitivity syndrome (MIM-262500). Here we represent a consanguineous Pakistani family in which three siblings were afflicted with LS. Patients had rather similar phenotypic presentations marked with short stature, delayed bone age, limited extension of elbows, truncal obesity, delayed puberty, childish appearance, and frontal bossing. They also had additional features such as hypo-muscularity, early fatigue, large ears, widely-spaced breasts, and attention deficit behavior, which are rarely reported in LS. The unusual combination of the features hindered a straightforward diagnosis and prompted us to first detect the regions of shared homozygosity and subsequently the disease-causing variant by next generation technologies, like SNP genotyping and exome sequencing. A homozygous pathogenic variant c.508G>C (p.(Asp170His)) in GHR was detected. The variant is known to be implicated in LS, supporting the molecular diagnosis of LS. Also, we present detailed clinical, hematological, and hormonal profiling of the siblings.

We present a Pakistani kinship afflicted with a syndrome with features including short stature, reduced sitting height, orofacial symptoms including prominent forehead and thick eyebrows, short and broad thorax, and variable features such as long philtrum, short broad neck, barrel chest, thoracic kyphoscoliosis, hypogonadism, and hypospadias. Phenotypic variation even within different sibships was considerable. The unique combination of the phenotypic characteristics prompted us to determine the shared homozygosity regions in patient genomes and the pathogenic variants by next generation technologies like single nucleotide polymorphism (SNP) genotyping and whole exome sequencing (WES). Through these analyses, we detected homozygous OBSL1 c.848delG (p.Gly283AlafsTer54) as the causal variant. Biallelic variants in OBSL1 are known to cause Three M Syndrome 2 (3M2), a rare disorder of growth retardation with characteristic facial dysmorphism and musculoskeletal abnormalities. Affected members of the family do not have the 3M2 hallmark features of dolichocephaly, hypoplastic midface, anteverted nares, low nasal bridge, pectus excavatum, sacral hyperlordosis, spina bifida occulta, anterior wedging of thoracic vertebrae, prominent heels, and prominent talus. Moreover, they have some variable features not typical for the syndrome such as round face, disproportionate short stature, barrel chest, thoracic kyphoscoliosis, hypogonadism, and hypospadias. Our study facilitated genetic diagnosis in the family, expanded the clinical phenotype for 3M2, and unraveled the considerable clinical variation within the same kinship. We conclude that unbiased molecular analyses such as WES should be more integrated into healthcare, particularly in populations with high parental consanguinity, given the potential of such analyses to facilitate diagnosis.

With the advances in computer vision, computational facial analysis has become a powerful and effective tool for diagnosing rare disorders. This technology, also called next-generation phenotyping (NGP), has progressed significantly over the last decade. This review paper will introduce three key NGP approaches. In 2014, Ferry et al. first presented Clinical Face Phenotype Space (CFPS) trained on eight syndromes. After 5 years, Gurovich et al. proposed DeepGestalt, a deep convolutional neural network trained on more than 21,000 patient images with 216 disorders. It was considered a state-of-the-art disorder classification framework. In 2022, Hsieh et al. developed GestaltMatcher to support the ultra-rare and novel disorders not supported in DeepGestalt. It further enabled the analysis of facial similarity presented in a given cohort or multiple disorders. Moreover, this article will present the usage of NGP for variant prioritization and facial gestalt delineation. Although NGP approaches have proven their capability in assisting the diagnosis of many disorders, many limitations remain. This article will introduce two future directions to address two main limitations: enabling the global collaboration for a medical imaging database that fulfills the FAIR principles and synthesizing patient images to protect patient privacy. In the end, with more and more NGP approaches emerging, we envision that the NGP technology can assist clinicians and researchers in diagnosing patients and analyzing disorders in multiple directions in the near future.