Williams–Beuren syndrome: pitfalls for diagnosis in limited resources setting

Abstract

Key Clinical MessagePatients with Williams–Beuren Syndrome can be recognized clinically, given the characteristic dysmorphism, intellectual disability, and behavior. We report on a Congolese boy with typical WBS facial characteristics. He suffered meningitis and coma at the age of 2 years then subsequently presented with profound intellectual disability and atypical behavior. The WBS was only made at age 8.2 years and confirmed with FISH testing and microarray‐CGH. The present report aims to warn clinicians that infections may associate and/or modify a genetic disease as this may be observed in developing countries given the prevalence of infectious diseases.

Next generation phenotyping in Emanuel and Pallister‐Killian syndrome using computer‐aided facial dysmorphology analysis of 2D photos

“…In this study, we sought to use the FDNA technology to automatically identify facial phenotypes associated with 2 of the yet 6 known sSMC syndromes, that is, ES and PKS. The here presented results support the evidence, that computer aided facial recognition can help in the clinic and could possibly reduce the time patients spend in the diagnostic odyssey in general . Specifically, the FDNA technology may now also help to differentiate ES or PKS from each other and from other patients with sSMCs.…”

“…As a form of NGP, we used in this study the facial dysmorphology novel analysis (Face2Gene; FDNA inc., Boston, MA, USA) technology to automatically identify facial phenotypes associated with ES and PKS from 2D facial photos. The discriminatory power of such technology to recognize the phenotype of patients was recently and repeatedly described …”

Computer-Aided Recognition of Facial Attributes for Fetal Alcohol Spectrum Disorders

“…This could prove to be particularly important in developing nations where access to molecular testing is limited. 22 Although promising as a detection system, clinical assessment must be used adjunctively with FDNA when characterizing other domains within FASD diagnostic criteria. For example, clinical judgment is needed when assessing the significance of neurodevelopmental delays, the veracity of alcohol exposure reports, and in ruling out other possible genetic or teratogenic causes of the phenotypes identified.…”

Automatic recognition of the XLHED phenotype from facial images

“…This deep phenotyping technology is trained to identify specific syndromes from a patient's facial photo and may be helpful for medical professionals who work in clinical genetics (Basel‐Vanagaite et al, ; Lumaka et al, ) as well as in complementing exome analysis by inferring causative genetic variants from sequencing data (Gripp, Baker, Telegrafi, & Monaghan, ).…”