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1.
Hum Mol Genet ; 31(18): 3083-3094, 2022 09 10.
Article in English | MEDLINE | ID: mdl-35512351

ABSTRACT

BACKGROUND: TASP1 encodes an endopeptidase activating histone methyltransferases of the KMT2 family. Homozygous loss-of-function variants in TASP1 have recently been associated with Suleiman-El-Hattab syndrome. We report six individuals with Suleiman-El-Hattab syndrome and provide functional characterization of this novel histone modification disorder in a multi-omics approach. METHODS: Chromosomal microarray/exome sequencing in all individuals. Western blotting from fibroblasts in two individuals. RNA sequencing and proteomics from fibroblasts in one individual. Methylome analysis from blood in two individuals. Knock-out of tasp1 orthologue in zebrafish and phenotyping. RESULTS: All individuals had biallelic TASP1 loss-of-function variants and a phenotype including developmental delay, multiple congenital anomalies (including cardiovascular and posterior fossa malformations), a distinct facial appearance and happy demeanor. Western blot revealed absence of TASP1. RNA sequencing/proteomics showed HOX gene downregulation (HOXA4, HOXA7, HOXA1 and HOXB2) and dysregulation of transcription factor TFIIA. A distinct methylation profile intermediate between control and Kabuki syndrome (KMT2D) profiles could be produced. Zebrafish tasp1 knock-out revealed smaller head size and abnormal cranial cartilage formation in tasp1 crispants. CONCLUSION: This work further delineates Suleiman-El-Hattab syndrome, a recognizable neurodevelopmental syndrome. Possible downstream mechanisms of TASP1 deficiency include perturbed HOX gene expression and dysregulated TFIIA complex. Methylation pattern suggests that Suleiman-El-Hattab syndrome can be categorized into the group of histone modification disorders including Wiedemann-Steiner and Kabuki syndrome.


Subject(s)
Histone Code , Zebrafish , Abnormalities, Multiple , Animals , Endopeptidases/genetics , Face/abnormalities , Hematologic Diseases , Histone Methyltransferases/genetics , Phenotype , Transcription Factor TFIIA/genetics , Vestibular Diseases , Zebrafish/genetics
2.
Genet Med ; 25(7): 100836, 2023 Jul.
Article in English | MEDLINE | ID: mdl-37013901

ABSTRACT

PURPOSE: Rothmund-Thomson syndrome (RTS) is characterized by poikiloderma, sparse hair, small stature, skeletal defects, cancer, and cataracts, resembling features of premature aging. RECQL4 and ANAPC1 are the 2 known disease genes associated with RTS in >70% of cases. We describe RTS-like features in 5 individuals with biallelic variants in CRIPT (OMIM 615789). METHODS: Two newly identified and 4 published individuals with CRIPT variants were systematically compared with those with RTS using clinical data, computational analysis of photographs, histologic analysis of skin, and cellular studies on fibroblasts. RESULTS: All CRIPT individuals fulfilled the diagnostic criteria for RTS and additionally had neurodevelopmental delay and seizures. Using computational gestalt analysis, CRIPT individuals showed greatest facial similarity with individuals with RTS. Skin biopsies revealed a high expression of senescence markers (p53/p16/p21) and the senescence-associated ß-galactosidase activity was elevated in CRIPT-deficient fibroblasts. RECQL4- and CRIPT-deficient fibroblasts showed an unremarkable mitotic progression and unremarkable number of mitotic errors and no or only mild sensitivity to genotoxic stress by ionizing radiation, mitomycin C, hydroxyurea, etoposide, and potassium bromate. CONCLUSION: CRIPT causes an RTS-like syndrome associated with neurodevelopmental delay and epilepsy. At the cellular level, RECQL4- and CRIPT-deficient cells display increased senescence, suggesting shared molecular mechanisms leading to the clinical phenotypes.


Subject(s)
Rothmund-Thomson Syndrome , Humans , Rothmund-Thomson Syndrome/genetics , Rothmund-Thomson Syndrome/diagnosis , Rothmund-Thomson Syndrome/pathology , Cellular Senescence/genetics , DNA Damage , Hydroxyurea/metabolism , Fibroblasts , Mutation , Adaptor Proteins, Signal Transducing/metabolism
3.
J Asthma ; : 1-9, 2023 Nov 06.
Article in English | MEDLINE | ID: mdl-37930754

ABSTRACT

OBJECTIVE: This study (a) examined anxious youth with and without asthma on measures of negative self-talk, parental psychopathology, worry content, physical symptoms, panic symptoms, generalized symptoms, and separation anxiety symptoms, and (b) tested if outpatient CBT or medication were differentially effective in reducing anxiety for youth with asthma and anxiety. METHODS: This secondary analysis separated youth with an anxiety disorder into asthma and non-asthma groups. Youth were also compared on response to treatments (i.e. CBT, sertraline, combined, and placebo). RESULTS: A total of 488 participants participated in the original study, with an average age of 10 years (SD 2.87). Youth with comorbid asthma and anxiety demonstrated higher rates of negative self-talk. Youth with comorbid asthma and anxiety did not differ from the non-asthma group on measures of physical symptoms, anxiety disorder specific symptoms, parental psychopathology, or worry content. Youth with asthma and anxiety responded similarly to the non-asthma group to treatment across treatment conditions. CONCLUSIONS: Treatment was comparably effective for youth with comorbid asthma and anxiety and youth with anxiety. Future research could examine the effects of psychopharmaceuticals on asthma and anxiety comorbidity.

4.
Genet Med ; 23(2): 384-395, 2021 02.
Article in English | MEDLINE | ID: mdl-33173220

ABSTRACT

PURPOSE: We sought to delineate the genotypic and phenotypic spectrum of female and male individuals with X-linked, MSL3-related disorder (Basilicata-Akhtar syndrome). METHODS: Twenty-five individuals (15 males, 10 females) with causative variants in MSL3 were ascertained through exome or genome sequencing at ten different sequencing centers. RESULTS: We identified multiple variant types in MSL3 (ten nonsense, six frameshift, four splice site, three missense, one in-frame-deletion, one multi-exon deletion), most proven to be de novo, and clustering in the terminal eight exons suggesting that truncating variants in the first five exons might be compensated by an alternative MSL3 transcript. Three-dimensional modeling of missense and splice variants indicated that these have a deleterious effect. The main clinical findings comprised developmental delay and intellectual disability ranging from mild to severe. Autism spectrum disorder, muscle tone abnormalities, and macrocephaly were common as well as hearing impairment and gastrointestinal problems. Hypoplasia of the cerebellar vermis emerged as a consistent magnetic resonance image (MRI) finding. Females and males were equally affected. Using facial analysis technology, a recognizable facial gestalt was determined. CONCLUSION: Our aggregated data illustrate the genotypic and phenotypic spectrum of X-linked, MSL3-related disorder (Basilicata-Akhtar syndrome). Our cohort improves the understanding of disease related morbidity and allows us to propose detailed surveillance guidelines for affected individuals.


Subject(s)
Autism Spectrum Disorder , Intellectual Disability , Autism Spectrum Disorder/genetics , Chromosomal Proteins, Non-Histone , DNA-Binding Proteins , Female , Genes, X-Linked , Genotype , Humans , Intellectual Disability/genetics , Male , Phenotype , Exome Sequencing
5.
Mol Genet Metab ; 134(3): 274-280, 2021 11.
Article in English | MEDLINE | ID: mdl-34663554

ABSTRACT

Gaucher disease (GD) is a rare lysosomal storage disorder that is divided into three subtypes based on presentation of neurological manifestations. Distinguishing between the types has important implications for treatment and counseling. Yet, patients with neuronopathic forms of GD, types 2 and 3, often present at young ages and can have overlapping phenotypes. It has been shown that new technologies employing artificial intelligence and facial recognition software can assist with dysmorphology assessments. Though classically not associated nor previously described with a dysmorphic facial phenotype, this study investigated whether a facial recognition platform could distinguish between photos of patients with GD2 and GD3 and discriminate between them and photos of healthy controls. Each cohort included over 100 photos. A cross validation scheme including a series of binary comparisons between groups was used. Outputs included a composite photo of each cohort and either a receiver operating characteristic curve or a confusion matrix. Binary comparisons showed that the software could correctly group photos at least 89% of the time. Multiclass comparison between GD2, GD3, and healthy controls demonstrated a mean accuracy of 76.6%, compared to a 37.7% chance for random comparison. Both GD2 and GD3 have now been added to the facial recognition platform as established syndromes that can be identified by the algorithm. These results suggest that facial recognition and artificial intelligence, though no substitute for other diagnostic methods, may aid in the recognition of neuronopathic GD. The algorithm, in concert with other clinical features, also appears to distinguish between young patients with GD2 and GD3, suggesting that this tool can help facilitate earlier implementation of appropriate management.


Subject(s)
Artificial Intelligence/standards , Facial Recognition , Gaucher Disease/physiopathology , Phenotype , Software/standards , Adolescent , Adult , Child , Child, Preschool , Cohort Studies , Female , Gaucher Disease/classification , Gaucher Disease/diagnosis , Humans , Infant , Infant, Newborn , Male , Musculoskeletal Abnormalities , ROC Curve , Young Adult
6.
Clin Genet ; 99(4): 547-557, 2021 04.
Article in English | MEDLINE | ID: mdl-33381861

ABSTRACT

SATB2-Associated syndrome (SAS) is an autosomal dominant, multisystemic, neurodevelopmental disorder due to alterations in SATB2 at 2q33.1. A limited number of individuals with 2q33.1 contiguous deletions encompassing SATB2 (ΔSAS) have been described in the literature. We describe 17 additional individuals with ΔSAS, review the phenotype of 33 previously published individuals with 2q33.1 deletions (n = 50, mean age = 8.5 ± 7.8 years), and provide a comprehensive comparison to individuals with other molecular mechanisms that result in SAS (non-ΔSAS). Individuals in the ΔSAS group were often underweight for age (20/41 = 49%) with a progressive decline in weight (95% CI = -2.3 to -1.1, p < 0.0001) and height (95% CI = -2.3 to -1.0, p < 0.0001) Z-score means from birth to last available measurement. ΔSAS individuals were often noted to have a broad spectrum of facial dysmorphism. A composite image of ΔSAS individuals generated by automated image analysis was distinct as compared to matched controls and non-ΔSAS individuals. We also present additional genotype-phenotype correlations for individuals in the ΔSAS group such as an increased risk for aortic root/ascending aorta dilation and primary pulmonary hypertension for those individuals with contiguous gene deletions that include COL3A1/COL5A2 and BMPR2, respectively. Based on these findings, we provide additional care recommendations for individuals with ΔSAS variants.


Subject(s)
Chromosome Deletion , Chromosomes, Human, Pair 2/genetics , Matrix Attachment Region Binding Proteins/deficiency , Transcription Factors/deficiency , Adult , Child , Child, Preschool , Chromosomes, Human, Pair 2/ultrastructure , Collagen Type III/deficiency , Collagen Type III/genetics , Collagen Type V/deficiency , Collagen Type V/genetics , Dwarfism/genetics , Face/abnormalities , Female , Genetic Association Studies , Gestational Age , Humans , Hypertension, Pulmonary/genetics , Infant , Male , Matrix Attachment Region Binding Proteins/genetics , Microcephaly/genetics , Phenotype , Thinness/genetics , Transcription Factors/genetics
7.
Am J Med Genet A ; 185(7): 2094-2101, 2021 07.
Article in English | MEDLINE | ID: mdl-33938623

ABSTRACT

3q29 deletion syndrome (3q29del) is a recurrent deletion syndrome associated with neuropsychiatric disorders and congenital anomalies. Dysmorphic facial features have been described but not systematically characterized. This study aims to detail the 3q29del craniofacial phenotype and use a machine learning approach to categorize individuals with 3q29del through analysis of 2D photos. Detailed dysmorphology exam and 2D facial photos were ascertained from 31 individuals with 3q29del. Photos were used to train the next-generation phenotyping algorithm DeepGestalt (Face2Gene by FDNA, Inc, Boston, MA) to distinguish 3q29del cases from controls and all other recognized syndromes. Area under the curve of receiver operating characteristic curves (AUC-ROC) was used to determine the capacity of Face2Gene to identify 3q29del cases against controls. In this cohort, the most common observed craniofacial features were prominent forehead (48.4%), prominent nose tip (35.5%), and thin upper lip vermillion (25.8%). The FDNA technology showed an ability to distinguish cases from controls with an AUC-ROC value of 0.873 (p = 0.006) and led to the inclusion of 3q29del as one of the supported syndromes. This study found a recognizable facial pattern in 3q29del, as observed by trained clinical geneticists and next-generation phenotyping technology. These results expand the potential application of automated technology such as FDNA in identifying rare genetic syndromes, even when facial dysmorphology is subtle.


Subject(s)
Biological Variation, Population/genetics , Craniofacial Abnormalities/genetics , Genetic Predisposition to Disease , Intellectual Disability/genetics , Adolescent , Adult , Algorithms , Child , Child, Preschool , Chromosomes, Human, Pair 3/genetics , Craniofacial Abnormalities/pathology , Face , Female , Humans , Intellectual Disability/pathology , Male , Phenotype , Sequence Deletion/genetics , Young Adult
8.
Am J Med Genet A ; 182(9): 2021-2026, 2020 09.
Article in English | MEDLINE | ID: mdl-32524756

ABSTRACT

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.


Subject(s)
Angelman Syndrome/genetics , Deep Learning , Genomic Imprinting/genetics , Uniparental Disomy/genetics , Adolescent , Adult , Angelman Syndrome/classification , Angelman Syndrome/diagnosis , Angelman Syndrome/pathology , Child , Child, Preschool , Face/pathology , Female , Humans , Infant , Male , Maternal Inheritance/genetics , Phenotype , Ubiquitin-Protein Ligases/genetics , Uniparental Disomy/diagnosis , Uniparental Disomy/pathology , Young Adult
9.
Am J Med Genet A ; 182(7): 1791-1795, 2020 07.
Article in English | MEDLINE | ID: mdl-32359026

ABSTRACT

A rare developmental delay (DD)/intellectual disability (ID) syndrome with craniofacial dysmorphisms and autistic features, termed White-Sutton syndrome (WHSUS, MIM#614787), has been recently described, identifying truncating mutations in the chromatin regulator POGZ (KIAA0461, MIM#614787). We describe a further WHSUS patient harboring a novel nonsense de novo POGZ variant, which afflicts a protein domain with transposase activity less frequently impacted by mutational events (DDE domain). This patient displays additional physical and behavioral features, these latter mimicking Smith-Magenis syndrome (SMS, MIM#182290). Considering sleep-wake cycle anomalies and abnormal behavior manifested by this boy, we reinforced the clinical resemblance between WHSUS and SMS, being both chromatinopathies. In addition, using the DeepGestalt technology, we identified a different facial overlap between WHSUS patients with mutations in the DDE domain (Group 1) and individuals harboring variants in other protein domains/regions (Group 2). This report further delineates the clinical and molecular repertoire of the POGZ-related phenotype, adding a novel patient with uncommon clinical and behavioral features and provides the first computer-aided facial study of WHSUS patients.


Subject(s)
Developmental Disabilities/genetics , Intellectual Disability/genetics , Smith-Magenis Syndrome/genetics , Transposases/genetics , Child, Preschool , Codon, Nonsense/genetics , Craniofacial Abnormalities/diagnosis , Craniofacial Abnormalities/diagnostic imaging , Craniofacial Abnormalities/genetics , Craniofacial Abnormalities/physiopathology , Developmental Disabilities/diagnosis , Developmental Disabilities/diagnostic imaging , Developmental Disabilities/physiopathology , Exome/genetics , Female , Humans , Intellectual Disability/diagnosis , Intellectual Disability/diagnostic imaging , Intellectual Disability/physiopathology , Male , Mutation/genetics , Phenotype , Smith-Magenis Syndrome/diagnosis , Smith-Magenis Syndrome/diagnostic imaging , Smith-Magenis Syndrome/physiopathology
10.
Am J Med Genet A ; 182(12): 2939-2950, 2020 12.
Article in English | MEDLINE | ID: mdl-32985117

ABSTRACT

Rubinstein-Taybi syndrome (RSTS) is an autosomal dominant disorder, caused by loss-of-function variants in CREBBP or EP300. Affected individuals present with distinctive craniofacial features, broad thumbs and/or halluces, and intellectual disability. RSTS phenotype has been well characterized in individuals of European descent but not in other populations. In this study, individuals from diverse populations with RSTS were assessed by clinical examination and facial analysis technology. Clinical data of 38 individuals from 14 different countries were analyzed. The median age was 7 years (age range: 7 months to 47 years), and 63% were females. The most common phenotypic features in all population groups included broad thumbs and/or halluces in 97%, convex nasal ridge in 94%, and arched eyebrows in 92%. Face images of 87 individuals with RSTS (age range: 2 months to 47 years) were collected for evaluation using facial analysis technology. We compared images from 82 individuals with RSTS against 82 age- and sex-matched controls and obtained an area under the receiver operating characteristic curve (AUC) of 0.99 (p < .001), demonstrating excellent discrimination efficacy. The discrimination was, however, poor in the African group (AUC: 0.79; p = .145). Individuals with EP300 variants were more effectively discriminated (AUC: 0.95) compared with those with CREBBP variants (AUC: 0.93). This study shows that clinical examination combined with facial analysis technology may enable earlier and improved diagnosis of RSTS in diverse populations.


Subject(s)
E1A-Associated p300 Protein/genetics , Ethnicity/genetics , Face/abnormalities , Genetics, Population , Mutation , Rubinstein-Taybi Syndrome/epidemiology , Adolescent , Adult , Case-Control Studies , Child , Child, Preschool , Cohort Studies , Female , Genetic Association Studies , Humans , Infant , International Agencies , Male , Middle Aged , Prognosis , Rubinstein-Taybi Syndrome/genetics , Rubinstein-Taybi Syndrome/pathology , Young Adult
11.
Am J Med Genet A ; 182(2): 303-313, 2020 02.
Article in English | MEDLINE | ID: mdl-31854143

ABSTRACT

Turner syndrome (TS) is a common multiple congenital anomaly syndrome resulting from complete or partial absence of the second X chromosome. In this study, we explore the phenotype of TS in diverse populations using clinical examination and facial analysis technology. Clinical data from 78 individuals and images from 108 individuals with TS from 19 different countries were analyzed. Individuals were grouped into categories of African descent (African), Asian, Latin American, Caucasian (European descent), and Middle Eastern. The most common phenotype features across all population groups were short stature (86%), cubitus valgus (76%), and low posterior hairline 70%. Two facial analysis technology experiments were conducted: TS versus general population and TS versus Noonan syndrome. Across all ethnicities, facial analysis was accurate in diagnosing TS from frontal facial images as measured by the area under the curve (AUC). An AUC of 0.903 (p < .001) was found for TS versus general population controls and 0.925 (p < .001) for TS versus individuals with Noonan syndrome. In summary, we present consistent clinical findings from global populations with TS and additionally demonstrate that facial analysis technology can accurately distinguish TS from the general population and Noonan syndrome.


Subject(s)
Abnormalities, Multiple/epidemiology , Face/abnormalities , Noonan Syndrome/epidemiology , Turner Syndrome/epidemiology , Abnormalities, Multiple/diagnosis , Abnormalities, Multiple/genetics , Abnormalities, Multiple/physiopathology , Adolescent , Adult , Asian People/genetics , Child , Child, Preschool , Chromosomes, Human, X/genetics , Face/pathology , Facial Recognition , Female , Hispanic or Latino/genetics , Humans , Infant , Infant, Newborn , Male , Middle Aged , Noonan Syndrome/diagnosis , Noonan Syndrome/genetics , Noonan Syndrome/physiopathology , Phenotype , Population Surveillance , Turner Syndrome/diagnosis , Turner Syndrome/genetics , Turner Syndrome/physiopathology , White People/genetics , Young Adult
12.
Hum Mutat ; 40(6): 721-728, 2019 06.
Article in English | MEDLINE | ID: mdl-30825388

ABSTRACT

The pathogenic variants in the neuroblastoma-amplified sequence (NBAS) are associated with a clinical spectrum involving the hepatic, skeletal, ocular, and immune systems. Here, we report on two unrelated subjects with a complex phenotype solved by whole-exome sequencing, who shared a synonymous change in NBAS that was documented to affect the transcript processing and co-occurring with a truncating change. Starting from these two cases, we systematically assessed the clinical information available for all subjects with biallelic NBAS pathogenic variants (73 cases in total). We revealed a recognizable facial profile (hypotelorism, thin lips, pointed chin, and "progeroid" appearance) determined by using DeepGestalt facial recognition technology, and we provide evidence for the occurrence of genotype-phenotype correlations. Notably, severe hepatic involvement was associated with variants affecting the NBAS-Nter and Sec39 domains, whereas milder liver involvement and immunodeficiency were generally associated with variants located at the N-terminus and C-terminus of the protein. Remarkably, no patient was reported to carry two nonsense variants, suggesting lethality of complete NBAS loss-of-function.


Subject(s)
Abnormalities, Multiple/genetics , Exome Sequencing/methods , Neoplasm Proteins/genetics , Silent Mutation , Child , Child, Preschool , Female , Genetic Association Studies , Humans , Loss of Function Mutation , Male , Neoplasm Proteins/chemistry , Pedigree , Protein Domains
13.
Genet Med ; 21(12): 2807-2814, 2019 12.
Article in English | MEDLINE | ID: mdl-31164752

ABSTRACT

PURPOSE: Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. METHODS: Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. RESULTS: The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20-89% and the top 10 accuracy rate by more than 5-99% for the disease-causing gene. CONCLUSION: Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis.


Subject(s)
Computational Biology/methods , Image Processing, Computer-Assisted/methods , Sequence Analysis, DNA/methods , Algorithms , Databases, Genetic , Deep Learning , Exome/genetics , Female , Genomics , Humans , Male , Phenotype , Software
14.
J Hum Genet ; 64(8): 721-728, 2019 Aug.
Article in English | MEDLINE | ID: mdl-31086247

ABSTRACT

Genetic syndromes are frequently associated with Intellectual Disability (ID), as well as craniofacial dysmorphisms. A group of ID syndromes with typical abnormal face related to chromatin remodeling defects, have been recognized, coining the term chromatinopathies. This is a molecular heterogeneous subset of congenital disorders caused by mutations of the various components of the Chromatin-Marking System (CMS), including modifiers of DNA and chromatin remodelers. We performed a phenotypic study on a sample of 120 individuals harboring variants in genes codifying for the histones enzymes, using the DeepGestalt technology. Three experiments (two multiclass comparison experiments and a frontal face-crop analysis) were conducted, analyzing respectively a total of 181 pediatric images in the first comparison experiment and 180 in the second, all individuals belonging predominantly to Caucasian population. The classification results were expressed in terms of the area under the curve (AUC) of the receiver-operating-characteristic curve (ROC). Significant values of AUC and low p-values were registered for all syndromes in the three experiments, in comparison with each other, with other ID syndromes characterized by recognizable craniofacial dysmorphisms and with unaffected controls. Final findings indicated that this group of diseases is characterized by distinctive dysmorphisms, which result pathognomonic. A correct interrogation and use of adequate informatics aids, could become a valid support for clinicians.


Subject(s)
Facies , Genetic Association Studies , Genetic Predisposition to Disease , Intellectual Disability/diagnosis , Intellectual Disability/genetics , Phenotype , Child , Child, Preschool , Cohort Studies , Diagnostic Imaging , Female , Genetic Association Studies/methods , Humans , Image Processing, Computer-Assisted , Male , ROC Curve
15.
Am J Med Genet A ; 179(10): 2075-2082, 2019 10.
Article in English | MEDLINE | ID: mdl-31361404

ABSTRACT

Zinc finger protein 462 (ZNF462) is a relatively newly discovered vertebrate specific protein with known critical roles in embryonic development in animal models. Two case reports and a case series study have described the phenotype of 10 individuals with ZNF462 loss of function variants. Herein, we present 14 new individuals with loss of function variants to the previous studies to delineate the syndrome of loss of function in ZNF462. Collectively, these 24 individuals present with recurring phenotypes that define a multiple congenital anomaly syndrome. Most have some form of developmental delay (79%) and a minority has autism spectrum disorder (33%). Characteristic facial features include ptosis (83%), down slanting palpebral fissures (58%), exaggerated Cupid's bow/wide philtrum (54%), and arched eyebrows (50%). Metopic ridging or craniosynostosis was found in a third of study participants and feeding problems in half. Other phenotype characteristics include dysgenesis of the corpus callosum in 25% of individuals, hypotonia in half, and structural heart defects in 21%. Using facial analysis technology, a computer algorithm applying deep learning was able to accurately differentiate individuals with ZNF462 loss of function variants from individuals with Noonan syndrome and healthy controls. In summary, we describe a multiple congenital anomaly syndrome associated with haploinsufficiency of ZNF462 that has distinct clinical characteristics and facial features.


Subject(s)
DNA-Binding Proteins/genetics , Nerve Tissue Proteins/genetics , Transcription Factors/genetics , Adolescent , Adult , Child , Child, Preschool , Facies , Female , Humans , Infant , Male , Phenotype , Syndrome
16.
J Inherit Metab Dis ; 41(3): 533-539, 2018 05.
Article in English | MEDLINE | ID: mdl-29623569

ABSTRACT

Significant improvements in automated image analysis have been achieved in recent years and tools are now increasingly being used in computer-assisted syndromology. However, the ability to recognize a syndromic facial gestalt might depend on the syndrome and may also be confounded by severity of phenotype, size of available training sets, ethnicity, age, and sex. Therefore, benchmarking and comparing the performance of deep-learned classification processes is inherently difficult. For a systematic analysis of these influencing factors we chose the lysosomal storage diseases mucolipidosis as well as mucopolysaccharidosis type I and II that are known for their wide and overlapping phenotypic spectra. For a dysmorphic comparison we used Smith-Lemli-Opitz syndrome as another inborn error of metabolism and Nicolaides-Baraitser syndrome as another disorder that is also characterized by coarse facies. A classifier that was trained on these five cohorts, comprising 289 patients in total, achieved a mean accuracy of 62%. We also developed a simulation framework to analyze the effect of potential confounders, such as cohort size, age, sex, or ethnic background on the distinguishability of phenotypes. We found that the true positive rate increases for all analyzed disorders for growing cohorts (n = [10...40]) while ethnicity and sex have no significant influence. The dynamics of the accuracies strongly suggest that the maximum distinguishability is a phenotype-specific value, which has not been reached yet for any of the studied disorders. This should also be a motivation to further intensify data sharing efforts, as computer-assisted syndrome classification can still be improved by enlarging the available training sets.


Subject(s)
Image Processing, Computer-Assisted/methods , Image Processing, Computer-Assisted/trends , Metabolism, Inborn Errors/diagnosis , Adolescent , Algorithms , Child , Facies , Female , Foot Deformities, Congenital/diagnosis , Foot Deformities, Congenital/metabolism , Humans , Hypotrichosis/diagnosis , Hypotrichosis/metabolism , Intellectual Disability/diagnosis , Intellectual Disability/metabolism , Male , Metabolism, Inborn Errors/metabolism , Metabolism, Inborn Errors/pathology , Molecular Diagnostic Techniques/methods , Molecular Diagnostic Techniques/trends , Phenotype , Smith-Lemli-Opitz Syndrome/diagnosis , Smith-Lemli-Opitz Syndrome/metabolism , Syndrome
18.
Article in English | MEDLINE | ID: mdl-38466512

ABSTRACT

BACKGROUND: Research in health disparities and how they affect underserved populations continues to grow and expand. However, the experiences of Arab/Middle Eastern and North African (MENA) Americans often go unnoticed, and yet, preliminary data suggests there are significant disparities between this population and other groups. The purpose of this scoping review is to examine and synthesize the extent of available literature on health disparities and outcomes for this group. METHODS: A scoping review was conducted to investigate the current state of research on health disparities and outcomes among Arab/MENA individuals within the USA. The PRISMA protocol for scoping reviews was utilized. RESULTS: Through the use of PubMed and PsychInfo databases, the search identified 43 articles that were eligible for inclusion in the final review. Five themes emerged: prevalence and health outcomes, factors impacting health, comparison studies, barriers, and health literacy and beliefs. Extant data was equivocal, suggesting the need for further research. CONCLUSIONS: Research on Arab/MENA health disparities and outcomes is in the detection phase, indicating that more research is needed to elucidate the state of Arab/MENA health in the USA. These findings can help healthcare professionals and researchers understand the emerging literature on health disparities within the Arab/MENA community and inform further research and clinical practice within this population.

19.
J Neurodev Disord ; 16(1): 35, 2024 Jun 25.
Article in English | MEDLINE | ID: mdl-38918700

ABSTRACT

BACKGROUND: Minor physical anomalies (MPAs) are congenital morphological abnormalities linked to disruptions of fetal development. MPAs are common in 22q11.2 deletion syndrome (22q11DS) and psychosis spectrum disorders (PS) and likely represent a disruption of early embryologic development that may help identify overlapping mechanisms linked to psychosis in these disorders. METHODS: Here, 2D digital photographs were collected from 22q11DS (n = 150), PS (n = 55), and typically developing (TD; n = 93) individuals. Photographs were analyzed using two computer-vision techniques: (1) DeepGestalt algorithm (Face2Gene (F2G)) technology to identify the presence of genetically mediated facial disorders, and (2) Emotrics-a semi-automated machine learning technique that localizes and measures facial features. RESULTS: F2G reliably identified patients with 22q11DS; faces of PS patients were matched to several genetic conditions including FragileX and 22q11DS. PCA-derived factor loadings of all F2G scores indicated unique and overlapping facial patterns that were related to both 22q11DS and PS. Regional facial measurements of the eyes and nose were smaller in 22q11DS as compared to TD, while PS showed intermediate measurements. CONCLUSIONS: The extent to which craniofacial dysmorphology 22q11DS and PS overlapping and evident before the impairment or distress of sub-psychotic symptoms may allow us to identify at-risk youths more reliably and at an earlier stage of development.


Subject(s)
Craniofacial Abnormalities , DiGeorge Syndrome , Psychotic Disorders , Humans , DiGeorge Syndrome/genetics , DiGeorge Syndrome/physiopathology , Psychotic Disorders/genetics , Female , Male , Adolescent , Child , Craniofacial Abnormalities/genetics , Young Adult , Adult , Machine Learning , Image Processing, Computer-Assisted
20.
Front Genet ; 13: 991721, 2022.
Article in English | MEDLINE | ID: mdl-36204321

ABSTRACT

Introduction: Vici Syndrome is a rare, severe, neurodevelopmental/neurodegenerative disorder with multi-systemic manifestations presenting in infancy. It is mainly characterized by global developmental delay, seizures, agenesis of the corpus callosum, hair and skin hypopigmentation, bilateral cataract, and varying degrees of immunodeficiency, among other features. Vici Syndrome is caused by biallelic pathogenic variants in EPG5, resulting in impaired autophagy. Thus far, the condition has been reported in less than a hundred individuals. Objective and Methods: We aimed to characterize the clinical and molecular findings in individuals harboring biallelic EPG5 variants, recruited from four medical centers in Israel. Furthermore, we aimed to utilize a machine learning-based tool to assess facial features of Vici syndrome. Results: Eleven cases of Vici Syndrome from five unrelated families, one of which was diagnosed prenatally with subsequent termination of pregnancy, were recruited. A total of five disease causing variants were detected in EPG5: two novel: c.2554-5A>G and c.1461delC; and 3 previously reported: c.3447G>A, c.5993C>G, and c.1007A>G, the latter previously identified in several patients of Ashkenazi-Jewish (AJ) descent. Amongst 140,491 individuals screened by the Dor Yeshorim Program, we show that the c.1007A>G variant has an overall carrier frequency of 0.45% (1 in 224) among AJ individuals. Finally, based on two-dimensional facial photographs of individuals with Vici syndrome (n = 19), a composite facial mask was created using the DeepGestalt algorithm, illustrating facial features typical of this disorder. Conclusion: We report on ten children and one fetus from five unrelated families, affected with Vici syndrome, and describe prenatal and postnatal characteristics. Our findings contribute to the current knowledge regarding the molecular basis and phenotypic features of this rare syndrome. Additionally, the deep learning-based facial gestalt adds to the clinician's diagnostic toolbox and may aid in facilitating identification of affected individuals.

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