Kabuki syndrome (KS) is a neurodevelopmental disorder characterized by hypotonia, intellectual disability, skeletal anomalies, and postnatal growth restriction. The characteristic facial appearance is not pathognomonic for KS as several other conditions demonstrate overlapping features. For 20-30% of children with a clinical diagnosis of KS, no causal variant is identified by conventional genetic testing of the two associated genes, KMT2D and KDM6A. Here, we describe two cases of suspected KS that met clinical diagnostic criteria and had a high gestalt match on the artificial intelligence platform Face2Gene. Although initial KS testing was negative, genome-wide DNA methylation (DNAm) was instrumental in guiding genome sequencing workflow to establish definitive molecular diagnoses. In one case, a positive DNAm signature for KMT2D led to the identification of a cryptic variant in KDM6A by genome sequencing; for the other case, a DNAm signature different from KS led to the detection of another diagnosis in the KS differential, CDK13-related disorder. This approach illustrates the clinical utility of DNAm signatures in the diagnostic workflow for the genome analyst or clinical geneticist-especially for disorders with overlapping clinical phenotypes.
Keywords: CDK13; DNA methylation signature; KDM6A; KMT2D; Kabuki syndrome.
© 2022 The Authors. American Journal of Medical Genetics Part A published by Wiley Periodicals LLC.