To expand our understanding of the HADDS phenotypic spectrum and co-morbid conditions to advance diagnosis and guide clinical management.

Hypotonia, Ataxia, and Delayed Development Syndrome (HADDS) is a neurodevelopmental disorder caused by heterozygous Early B-Cell Factor 3 (EBF3) loss-of-function variants. Discovered in 2016, this disorder is associated with its namesake features, but the full spectrum of clinical findings and the relationship between the EBF3 genotype and clinical outcomes remains unclear.

We combined a deep phenotypic assessment of 33 individuals diagnosed with pathogenic EBF3 variants with a meta-analysis of 34 previously reported individuals. A total of 62 unique individuals with pathogenic EBF3 variants are assessed, which allows for comparative phenotype and genotype analysis in a large clinical cohort of affected individuals with EBF3 variants. To understand the relationship between the EBF3 molecular phenotype and clinical outcome, we designed two assessment scales that determine an individual’s risk for having a pathogenic EBF3 variant and their degree of functional impairments.

Using the largest set of clinically annotated EBF3 pathogenic variants examined to date, we identified features that facilitate phenotypic stratification for diagnosis, and developed a diagnostic scale to identify individuals with pathogenic EBF3 variants, stratified the clinical severity, and connected variant-specific molecular phenotypes to clinical outcomes. Our findings reveal that a class of EBF3 variants affecting the conserved Zinc Finger (ZNF) motif, which stabilizes the protein interaction with the DNA target sequence, is associated with an increased risk of persistent motor and language impairments.

Our comprehensive clinical phenotyping in a large cohort of individuals molecularly diagnosed with pathogenic EBF3 variants allows for an expanded understanding of the variation in clinical outcomes and guides clinical management. These findings highlight the potential impact of combining variant-specific molecular phenotypes with comprehensive clinical data to predict neurodevelopmental outcomes and potentially guide personalized decisions for therapeutic interventions.