Down syndrome is the most common cause of cognitive impairment and presents clinically with universally recognizable signs and symptoms. In this study, we focus on exam findings and digital facial analysis technology in individuals with Down syndrome in diverse populations. Photos and clinical information were collected on 65 individuals from 13 countries, 56.9% were male and the average age was 6.6 years (range 1 month to 26 years; SD ¼ 6.6 years). Subjective 42findings showed that clinical features were different across ethnicities (Africans, Asians, and Latin Americans), including brachycephaly, ear anomalies, clinodactyly, sandal gap, and abundant neck skin, which were all significantly less frequent in Africans (P < 0.001, P < 0.001, P < 0.001, P < 0.05, and P < 0.05, respectively). Evaluation using a digital facial analysis technology of a larger diverse cohort of newborns to adults (n ¼ 129 cases; n ¼ 132 controls) was able to diagnose Down syndrome with a sensitivity of 0.961, specificity of 0.924, and accuracy of 0.943. Only the angles at medial canthus and ala of the nose were common significant findings amongst different ethnicities (Caucasians, Africans, and Asians) when compared to ethnically matched controls. The Asian group had the least number of significant digital facial biometrics at 4, compared to Caucasians at 8 and Africans at 7. In conclusion, this study displays the wide variety of findings across different geographic populations in Down syndrome and demonstrates the accuracy and promise of digital facial analysis technology in the diagnosis of Down syndrome internationally.
Rett syndrome (RTT) is a clinically defined disorder that describes a subset of patients with mutations in the X-linked MECP2 gene. However, there is a high degree of variability in the clinical phenotypes produced by mutations in MECP2, even amongst classical RTT patients. In a large-scale screening project, this variability has been examined by looking at the effects of mutation type, functional domain affected and X-inactivation. Mutations have been identified in 60% of RTT patients in this study (25% of whom were atypical), including 23 novel mutations and polymorphisms. More mutations were found in classical patients (63%) compared to atypical patients (44%). All of the pathogenic mutations were de novo in patients for whom parent DNA was available for screening. A composite phenotype score was developed, based on the recommendations for reporting clinical features in RTT of an international collaborative group. This score proved useful for summarising phenotypic severity, but did not correlate with mutation type, domain affected or X-inactivation, probably due to complex interactions between all three. Other correlations suggested that truncating mutations and mutations affecting the methyl-CpG-binding domain tend to lead to a more severe phenotype. Skewed X-inactivation was found in a large proportion (43%) of our patients, particularly in those with truncating mutations and mutations affecting the MBD. It is therefore likely that X-inactivation does modulate the phenotype in RTT.
22q11.2 deletion syndrome (22q11.2 DS) is the most common microdeletion syndrome and is underdiagnosed in diverse populations. This syndrome has a variable phenotype and affects multiple systems, making early recognition imperative. In this study, individuals from diverse populations with 22q11.2 DS were evaluated clinically and by facial analysis technology. Clinical information from 106 individuals and images from 101 were collected from individuals with 22q11.2 DS from 11 countries; average age was 11.7 and 47% were male. Individuals were grouped into categories of African descent (African), Asian, and Latin American. We found that the phenotype of 22q11.2 DS varied across population groups. Only two findings, congenital heart disease and learning problems, were found in greater than 50% of participants. When comparing the clinical features of 22q11.2 DS in each population, the proportion of individuals within each clinical category was statistically different except for learning problems and ear anomalies (P<0.05). However, when Africans were removed from analysis, six additional clinical features were found to be independent of ethnicity (P≥0.05). Using facial analysis technology, we compared 156 Caucasians, Africans, Asians, and Latin American individuals with 22q11.2 DS with 156 age and gender matched controls and found that sensitivity and specificity were greater than 96% for all populations. In summary, we present the varied findings from global populations with 22q11.2 DS and demonstrate how facial analysis technology can assist clinicians in making accurate 22q11.2 DS diagnoses. This work will assist in earlier detection and in increasing recognition of 22q11.2 DS throughout the world.
Congenital contractural arachnodactyly (CCA) is an autosomal dominant condition that shares skeletal features with Marfan syndrome (MFS), but does not have the ocular and cardiovascular complications that characterize MFS. CCA and MFS result from mutations in highly similar genes, FBN2 and FBN1, respectively. All the identified CCA mutations in FBN2 cluster in a limited region similar to where severe MFS mutations cluster in FBN1, specifically between exons 23 and 34. We screened exons 22 through 36 of FBN2 for mutations in 13 patients with classic CCA by single stranded conformational polymorphism analysis (SSCP) and then by direct sequencing. We successfully identified 10 novel mutations in this critical region of FBN2 in these patients, indicating a mutation detection rate of 75% in this limited region. Interestingly, none of these identified FBN2 mutations alter amino acids in the calcium binding consensus sequence in the EGF-like domains, whereas many of the FBN1 mutations alter the consensus sequence. Furthermore, analysis of the clinical data of the CCA patients with characterized FBN2 mutation indicate that CCA patients have aortic root dilatation and the vast majority lack evidence of congenital heart disease. These studies have implications for our understanding of the molecular basis of CCA, along with the diagnosis and genetic counseling of CCA patients.
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