PhenoScore quantifies phenotypic variation for rare genetic diseases by combining facial analysis with other clinical features using a machine-learning framework

Several molecular and phenotypic algorithms exist that establish genotype-phenotype correlations, including facial recognition tools. However, no unified framework that investigates both facial data and other phenotypic data directly from individuals exists. We developed PhenoScore: an open-source, artificial intelligence-based phenomics framework, combining facial recognition technology with Human Phenotype Ontology data analysis to quantify phenotypic similarity. Here we show PhenoScore's ability to recognize distinct phenotypic entities by establishing recognizable phenotypes for 37 of 40 investigated syndromes against clinical features observed in individuals with other neurodevelopmental disorders and show it is an improvement on existing approaches. PhenoScore provides predictions for individuals with variants of unknown significance and enables sophisticated genotype-phenotype studies by testing hypotheses on possible phenotypic (sub)groups. PhenoScore confirmed previously known phenotypic subgroups caused by variants in the same gene for SATB1, SETBP1 and DEAF1 and provides objective clinical evidence for two distinct ADNP-related phenotypes, already established functionally.PhenoScore is an open-source machine-learning tool that combines facial image recognition with Human Phenotype Ontology for genetic syndrome identification without genomic data, with applications to subgroup analysis and variants of unknown significance classification.Genetics of disease, diagnosis and treatmen

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as "non-FLHS SRCAP-related NDD.'' All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations.Genetics of disease, diagnosis and treatmen

Behavior and cognitive functioning in Witteveen-Kolk syndrome

Contains fulltext : 221392.pdf (publisher's version ) (Open Access)Witteveen-Kolk syndrome (WITKOS) is a rare neurodevelopmental disorder characterized by developmental delay/intellectual disability, facial dysmorphisms, and short stature. The syndrome is caused by loss of function of switch-insensitive 3 transcription regulator family member A (SIN3A). Regarding behavioral functioning, Autism Spectrum Disorders (ASD), obsessive-compulsive behaviors, as well as Attention-Deficit/Hyperactivity Disorder symptoms (ADHD) have been suggested. The present study explores various aspects of neurocognitive functioning in five individuals (age range 10-23) with WITKOS. Medical records and results of extensive neuropsychological assessment are used to describe developmental trajectories and neurocognitive profiles. Systematic analysis of medical records displays developmental difficulties described as ASD or ADHD in childhood, sleep problems and internalizing problems during adolescence. Results of cognitive assessments indicate profoundly disabled (n = 1), mildly disabled (n = 2), borderline (n = 1), and average (n = 1) levels of intelligence. Furthermore, results indicate weaknesses in speed of information processing/sustained attention in all participants, and difficulties in planning and maintaining overview in three participants. Furthermore, parent reports of behavioral functioning primarily suggest problems in social functioning. Implications of both cognitive problems and social-emotional vulnerabilities for counseling are discussed and supplemented with suggestions for interventions.7 p

A Case Series of Familial ARID1B Variants Illustrating Variable Expression and Suggestions to Update the ACMG Criteria

Contains fulltext : 237017.pdf (Publisher’s version ) (Open Access

Phenotype based prediction of exome sequencing outcome using machine learning for neurodevelopmental disorders

Purpose: Although the introduction of exome sequencing (ES) has led to the diagnosis of a significant portion of patients with neurodevelopmental disorders (NDDs), the diagnostic yield in actual clinical practice has remained stable at approximately 30%. We hypothesized that improving the selection of patients to test on the basis of their phenotypic presentation will increase diagnostic yield and therefore reduce unnecessary genetic testing. Methods: We tested 4 machine learning methods and developed PredWES from these: a statistical model predicting the probability of a positive ES result solely on the basis of the phenotype of the patient. Results: We first trained the tool on 1663 patients with NDDs and subsequently showed that diagnostic ES on the top 10% of patients with the highest probability of a positive ES result would provide a diagnostic yield of 56%, leading to a notable 114% increase. Inspection of our model revealed that for patients with NDDs, comorbid abnormal (lower) muscle tone and microcephaly positively correlated with a conclusive ES diagnosis, whereas autism was negatively associated with a molecular diagnosis. Conclusion: In conclusion, PredWES allows prioritizing patients with NDDs eligible for diagnostic ES on the basis of their phenotypic presentation to increase the diagnostic yield, making a more efficient use of health care resources

Human disease genes website series: An international, open and dynamic library for up-to-date clinical information

Since the introduction of next-generation sequencing, an increasing number of disorders have been discovered to have genetic etiology. To address diverse clinical questions and coordinate research activities that arise with the identification of these rare disorders, we developed the Human Disease Genes website series (HDG website series): an international digital library that records detailed information on the clinical phenotype of novel genetic variants in the human genome (https://humandiseasegenes.info/). Each gene website is moderated by a dedicated team of clinicians and researchers, focused on specific genes, and provides up-to-date—including unpublished—clinical information. The HDG website series is expanding rapidly with 424 genes currently adopted by 325 moderators from across the globe. On average, a gene website has detailed phenotypic information of 14.4 patients. There are multiple examples of added value, one being the ARID1B gene website, which was recently utilized in research to collect clinical information of 81 new patients. Additionally, several gene websites have more data available than currently published in the literature. In conclusion, the HDG website series provides an easily accessible, open and up-to-date clinical data resource for patients with pathogenic variants of individual genes. This is a valuable resource not only for clinicians dealing with rare genetic disorders such as developmental delay and autism, but other professionals working in diagnostics and basic research. Since the HDG website series is a dynamic platform, its data also include the phenotype of yet unpublished patients curated by professionals providing higher quality clinical detail to improve management of these rare disorders

Establishing the phenotypic spectrum of ZTTK syndrome by analysis of 52 individuals with variants in SON

Zhu-Tokita-Takenouchi-Kim (ZTTK) syndrome, an intellectual disability syndrome first described in 2016, is caused by heterozygous loss-of-function variants in SON. Its encoded protein promotes pre-mRNA splicing of many genes essential for development. Whereas individual phenotypic traits have previously been linked to erroneous splicing of SON target genes, the phenotypic spectrum and the pathogenicity of missense variants have not been further evaluated. We present the phenotypic abnormalities in 52 individuals, including 17 individuals who have not been reported before. In total, loss-of-function variants were detected in 49 individuals (de novo in 47, inheritance unknown in 2), and in 3, a missense variant was observed (2 de novo, 1 inheritance unknown). Phenotypic abnormalities, systematically collected and analyzed in Human Phenotype Ontology, were found in all organ systems. Significant inter-individual phenotypic variability was observed, even in individuals with the same recurrent variant (n = 13). SON haploinsufficiency was previously shown to lead to downregulation of downstream genes, contributing to specific phenotypic features. Similar functional analysis for one missense variant, however, suggests a different mechanism than for heterozygous loss-of-function. Although small in numbers and while pathogenicity of these variants is not certain, these data allow for speculation whether de novo missense variants cause ZTTK syndrome via another mechanism, or a separate overlapping syndrome. In conclusion, heterozygous loss-of-function variants in SON define a recognizable syndrome, ZTTK, associated with a broad, severe phenotypic spectrum, characterized by a large inter-individual variability. These observations provide essential information for affected individuals, parents, and healthcare professionals to ensure appropriate clinical management