Journal of Clinical Medicine (Jun 2024)

Exploring the Clinical and Genetic Landscape of Angelman Syndrome: Patient-Reported Insights from an Italian Registry

  • Pier Luigi Carriero,
  • Rosalia Zangari,
  • Eleonora Sfreddo,
  • Arianna Ghirardi,
  • Arrigo Schieppati,
  • Tiziano Barbui,
  • Francesco Biroli

DOI
https://doi.org/10.3390/jcm13123520
Journal volume & issue
Vol. 13, no. 12
p. 3520

Abstract

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Background: The Angelman Syndrome Registry (RISA) was developed as a retrospective study with the following objectives: to evaluate the clinical history of individuals with Angelman Syndrome (AS) in Italy and compare it with the existing literature; to investigate the feasibility of gathering data by directly involving participants in the data collection process; and to explore the relationship between different symptoms and genotypes. Methods: Established in 2018, RISA enrolled a total of 82 participants, with 62 (75.6%) providing complete data. Demographic, clinical, and genetic information was collected using electronic case report forms. Descriptive statistics characterized the sample, while associations between genotype and clinical characteristics were examined. Results: Descriptive analysis revealed a median participant age of 8.0 years, with males comprising 48.8% of the sample. Deletion (58.1%) was the most common genotype. The majority (82.2%) experienced epilepsy, with seizures typically onset before 3 years of age. Most patients (86.2%) required multiple anti-epileptic drugs for control, with generalized tonic–clonic seizures and atypical absence seizures being most prevalent. The deletion group exhibited more severe developmental delays and a trend towards higher seizure severity. Sleep problems affected 69.4% of participants, characterized by difficulties in sleep onset and maintenance. Conclusions: This study offers valuable insights into the clinical history and genetic characteristics of AS in Italy, consistent with the prior literature. Additionally, it underscores the efficacy of patient registries in capturing comprehensive data on rare diseases such as AS, highlighting their potential to advance research and enhance patient care.

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