Epileptic Electroencephalography Profile Associates with Attention Problems in Children with Fragile X Syndrome:

Benjamin Cowley1, Svetlana Kirjanen2, Juhani Partanen3

  • 1Brain Work Research Centre, Finnish Institute of Occupational HealthHelsinki, Finland; Cognitive Brain Research Unit, Cognitive Science, Institute of Behavioral Sciences, University of HelsinkiHelsinki, Finland.

Insights

Personalized medicine using electroencephalography (EEG) endophenotypes can improve treatment for Fragile X syndrome (FXS). Identifying specific neurophysiological profiles, like diffuse slow oscillations and epileptiform EEG, aids in managing comorbid symptoms in children with FXS.

Area of Science:

  • Neuroscience
  • Genetics
  • Developmental Pediatrics

Background:

  • Fragile X syndrome (FXS) is a leading inherited cause of intellectual disability and a form of autism spectrum disorder (ASD).
  • FXS presents significant heterogeneity in comorbidities, necessitating personalized treatment strategies.
  • Quantitative electroencephalography (EEG) endophenotypes offer potential biomarkers for tailoring interventions in FXS.

Purpose of the Study:

  • To explore the utility of EEG endophenotypes in a case series of children with FXS.
  • To correlate observed EEG patterns with comorbid symptoms and relevant literature.
  • To advocate for personalized, evidence-based treatment approaches for FXS.

Main Methods:

  • Analysis of a case series of 11 children diagnosed with FXS (ages 1-14 years).
  • Longitudinal clinical data collection focusing on comorbid symptoms and awake/asleep EEG profiles.
  • Literature review on EEG endophenotypes and their association with FXS comorbidities and treatments.

Main Results:

  • The most prevalent EEG endophenotypes identified were diffuse slow oscillations and epileptiform EEG.
  • These endophenotypes correlated with attention problems (37% prevalence) and epileptic seizures (45% prevalence) respectively.
  • Attention problems were observed to associate with the epilepsy endophenotype in this cohort.

Conclusions:

  • EEG endophenotypes provide valuable insights into the neurophysiological profiles of children with FXS.
  • Personalized treatment strategies, such as neurofeedback, guided by specific EEG characteristics can enhance clinical outcomes.
  • This approach supports evidence-based management of complex comorbid symptoms in FXS.