Integrating and Analyzing Genetic Data Across Angelman Syndrome Databases
Enhancing Research and Clinical Insight
Niki Armstrong, Meagan Cross, Amanda Moore, Megan Tones, Anne C. Wheeler, and Katie Garbarini
Published November 1, 2025
https://doi.org/10.65856/MXHH8236
KEYWORDS: UBE3A, Angelman syndrome, paternal allele, maternal deletion, hippocampus, synaptic plasticity, neuronal activation, imprinting, Western blot, mouse model.
ABSTRACT: Angelman syndrome (AS) is a neurogenetic condition caused by loss of maternally expressed UBE3A in neurons, resulting in developmental delay, cognitive impairment, ataxia, seizures, and minimal to absent speech. AS is caused by multiple genetic mechanisms, and data remain limited for the less common non-deletion subtypes. To better characterize genetic subtypes, we undertook systematic review and curation of genetic test reports within two databases: the Linking Angelman and Dup15q Data for Expanded Research (LADDER) Database and the Global Angelman Syndrome Registry (GASR).
Reports from LADDER (n=194) and GASR (n=447) were reviewed by genetic counselors using a standardized extraction template. This process enabled validation of caregiver-reported genotype and detailed categorization of genotype and UBE3A variants. Caregiver report was generally concordant with genetic confirmation; misclassification was most often associated with language-related issues. Variant characterization across LADDER, GASR, and Aggregate external datasets (ClinVar, LOVD, Invitae/Labcorp) indicated that small deletions or duplications leading to frameshift were the most common variant type. Across the Aggregate dataset, most variants were predicted to result in truncated protein, while subsets of missense and late frameshift variants may yield mutant UBE3A protein. These findings show that curated registry data strengthens opportunities for subtype-specific analyses and highlight areas where clarification is needed for families, particularly around terminology and translation. As therapeutic strategies advance toward restoring functional UBE3A, understanding variant effects will be important for anticipating potential differences in treatment response. Future directions include harmonization of datasets and expanded functional studies of UBE3A variants to refine genotype–phenotype correlations and inform clinical trial design.