DNA methylation episignature in Gabriele-de Vries syndrome

International audiencePURPOSE: Gabriele-de Vries syndrome (GADEVS) is a rare genetic disorder characterized by developmental delay and/or intellectual disability, hypotonia, feeding difficulties, and distinct facial features. To refine the phenotype and to better understand the molecular basis of the syndrome, we analyzed clinical data and performed genome-wide DNA methylation analysis of a series of individuals carrying a YY1 variant. METHODS: Clinical data were collected for 13 individuals not yet reported through an international call for collaboration. DNA was collected for 11 of these individuals and 2 previously reported individuals in an attempt to delineate a specific DNA methylation signature in GADEVS. RESULTS: Phenotype in most individuals overlapped with the previously described features. We described 1 individual with atypical phenotype, heterozygous for a missense variant in a domain usually not involved in individuals with YY1 pathogenic missense variations. We also described a specific peripheral blood DNA methylation profile associated with YY1 variants. CONCLUSION: We reported a distinct DNA methylation episignature in GADEVS. We expanded the clinical profile of GADEVS to include thin/sparse hair and cryptorchidism. We also highlighted the utility of DNA methylation episignature analysis for classification of variants of unknown clinical significance

New insights into genotype-phenotype correlation for GLI3 mutations

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Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction.

Whereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability

Mutation-specific pathophysiological mechanisms define different neurodevelopmental disorders associated with SATB1 dysfunction

International audienceWhereas large-scale statistical analyses can robustly identify disease-gene relationships, they do not accurately capture genotype-phenotype correlations or disease mechanisms. We use multiple lines of independent evidence to show that different variant types in a single gene, SATB1, cause clinically overlapping but distinct neurodevelopmental disorders. Clinical evaluation of 42 individuals carrying SATB1 variants identified overt genotype-phenotype relationships, associated with different pathophysiological mechanisms, established by functional assays. Missense variants in the CUT1 and CUT2 DNA-binding domains result in stronger chromatin binding, increased transcriptional repression, and a severe phenotype. In contrast, variants predicted to result in haploinsufficiency are associated with a milder clinical presentation. A similarly mild phenotype is observed for individuals with premature protein truncating variants that escape nonsense-mediated decay, which are transcriptionally active but mislocalized in the cell. Our results suggest that in-depth mutation-specific genotype-phenotype studies are essential to capture full disease complexity and to explain phenotypic variability