Developmental outcome of electroencephalographic findings in SYNGAP1 encephalopathy

Juliana Ribeiro-Constante1, Alba Tristán-Noguero2,3, Fernando Francisco Martínez Calvo4

  • 1Pediatric Neurology Department Sant Joan de Déu (SJD) Children's Hospital, Barcelona, Spain.

Insights

SYNGAP1 haploinsufficiency, a cause of developmental and epileptic encephalopathy, shows worsening EEG abnormalities with age. This highlights SYNGAP1

Area of Science:

  • Neuroscience
  • Genetics
  • Clinical Neurology

Background:

  • SYNGAP1 haploinsufficiency causes developmental and epileptic encephalopathy (DEE) with diverse neurodevelopmental symptoms and generalized epilepsies.
  • Interictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are potential biomarkers for DEE, with fixation-off sensitivity (FOS) and eye closure sensitivity (ECS) being areas of interest.

Purpose of the Study:

  • To clinically evaluate a cohort of 36 SYNGAP1-DEE individuals.
  • To investigate electroencephalographic (EEG) findings and their age-related changes in SYNGAP1-DEE.
  • To identify potential EEG biomarkers for SYNGAP1-DEE.

Main Methods:

  • Clinical evaluation of 36 SYNGAP1-DEE individuals using standardized questionnaires.
  • Collection of clinical, electroencephalographic (EEG), and genetic data.
  • Revision of 63 VEEGs to analyze cortical distribution of interictal abnormalities and age-related changes.

Main Results:

  • A disorganized EEG background was observed in all age groups, more prevalent in older individuals.
  • Bilateral synchronous and asynchronous posterior discharges were the most frequent IEDs (≥50%).
  • Generalized anterior region IEDs (≥15%) and diffuse fast activity (in cases ≥6 years) increased with age.

Conclusions:

  • SYNGAP1 haploinsufficiency leads to complex effects on human brain development, with some manifestations changing across developmental stages.
  • EEG features, particularly interictal abnormalities, show an increase from infancy to adolescence in SYNGAP1-DEE.
  • Baseline EEG analysis across age groups is crucial for identifying biomarkers and advancing natural history studies for targeted therapies.

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