Screening of SLC2A1 in a large cohort of patients suspected for Glut1 deficiency syndrome: identification of novel variants and associated phenotypes.
Barbara CastellottiFrancesca RagonaElena FreriRoberta SolazziStefano CiardulloGiovanni TricomiAnna VenerandoBarbara SalisLaura CanafogliaFlavio VillaniSilvana FranceschettiNardo NardocciCinzia GelleraDiFrancesco Jacopo CosimoTiziana GranataPublished in: Journal of neurology (2019)
Glucose transporter type 1 deficiency syndrome (Glut1 DS) is a rare neurological disorder caused by impaired glucose delivery to the brain. The clinical spectrum of Glut1 DS mainly includes epilepsy, paroxysmal dyskinesia (PD), developmental delay and microcephaly. Glut1 DS diagnosis is based on the identification of hypoglycorrhachia and pathogenic mutations of the SLC2A1 gene. Here, we report the molecular screening of SLC2A1 in 354 patients clinically suspected for Glut1 DS. From this cohort, we selected 245 patients for whom comprehensive clinical and laboratory data were available. Among them, we identified 19 patients carrying nucleotide variants of pathological significance, 5 of which were novel. The symptoms of onset, which varied from neonatal to adult age, included epilepsy, PD or non-epileptic paroxysmal manifestations. The comparison of the clinical features between the 19 SLC2A1 mutated and the 226 non-mutated patients revealed that the onset of epilepsy within the first year of life (when associated with developmental delay or other neurological manifestations), the association of epilepsy with PD and acquired microcephaly are more common in mutated subjects. Taken together, these data confirm the variability of expression of the phenotypes associated with mutation of SLC2A1 and provide useful clinical tools for the early identification of subjects highly suspected for the disease.
Keyphrases
- end stage renal disease
- newly diagnosed
- ejection fraction
- prognostic factors
- peritoneal dialysis
- pulmonary embolism
- adipose tissue
- zika virus
- atrial fibrillation
- metabolic syndrome
- intellectual disability
- physical activity
- multiple sclerosis
- blood pressure
- insulin resistance
- electronic health record
- depressive symptoms
- young adults
- deep learning