SYNGAP1-related developmental and epileptic encephalopathy: Genotypic and phenotypic characteristics and longitudinal insights.
Hye Jin KimMinhye KimSeoyun JangJae So ChoSoo Yeon KimAnna ChoHunmin KimByung Chan LimJong-Hee ChaeJieun ChoiKi Joong KimWooJoong KimPublished in: American journal of medical genetics. Part A (2024)
The clinical and genetic characteristics of SYNGAP1 mutations in Korean pediatric patients are not well understood. We retrospectively analyzed 13 individuals with SYNGAP1 mutations from a longitudinal aspect. Clinical data, genetic profiles, and electroencephalography (EEG) patterns were examined. Genotypic analyses included gene panels and whole-exome sequencing. All patients exhibited global developmental delay from early infancy, with motor development eventually reaching independent ambulation by 3 years of age. Language developmental delay varied significantly from nonverbal to simple sentences, which plateaued in all patients. Patients with the best language outcomes typically managed 2-3-word sentences, corresponding to a developmental age of 2-3 years. Epilepsy developed in 77% of patients, with onset consistently following developmental delays at a median age of 31 months. Longitudinal EEG data revealed a shift from occipital to frontal epileptiform discharges with age, suggesting a correlation with synaptic maturation. These findings suggest that the critical developmental plateau occurs between the ages of 2 and 5 years and is potentially influenced by epilepsy. By analyzing longitudinal data, our study contributes to a deeper understanding of SYNGAP1-related DEE, provides potential EEG biomarkers, and underlines the importance of early diagnosis and intervention to address this complex disorder.
Keyphrases
- end stage renal disease
- newly diagnosed
- functional connectivity
- chronic kidney disease
- ejection fraction
- electronic health record
- big data
- cross sectional
- metabolic syndrome
- copy number
- randomized controlled trial
- autism spectrum disorder
- early onset
- peritoneal dialysis
- risk assessment
- weight loss
- artificial intelligence
- weight gain
- high density
- data analysis
- single cell
- transcription factor
- genome wide identification