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Funder: Ultragenyx Pharmaceutical Inc.; Id: http://dx.doi.org/10.13039/100013220, OBJECTIVE: This study was undertaken to evaluate efficacy and long-term safety of triheptanoin in patients >1 year old, not on a ketogenic diet, with drug-resistant seizures associated with glucose transporter 1 deficiency syndrome (Glut1DS). METHODS: UX007G-CL201 was a randomized, double-blind, placebo-controlled trial. Following a 6-week baseline period, eligible patients were randomized 3:1 to triheptanoin or placebo. Dosing was titrated to 35% of total daily calories over 2 weeks. After an 8-week placebo-controlled period, all patients received open-label triheptanoin through Week 52. RESULTS: The study included 36 patients (15 children, 13 adolescents, eight adults). A median 12.6% reduction in overall seizure frequency was observed in the triheptanoin arm relative to baseline, and a 13.5% difference was observed relative to placebo (p = .58). In patients with absence seizures only (n = 9), a median 62.2% reduction in seizure frequency was observed in the triheptanoin arm relative to baseline. Only one patient with absence seizures only was present in the control group, preventing comparison. No statistically significant differences in seizure frequency were observed. Common treatment-emergent adverse events included diarrhea, vomiting, abdominal pain, and nausea, mostly mild or moderate in severity. No serious adverse events were considered to be treatment related. One patient discontinued due to status epilepticus. SIGNIFICANCE: Triheptanoin did not significantly reduce seizure frequency in patients with Glut1DS not on the ketogenic diet. Treatment was associated with mild to moderate gastrointestinal treatment-related events; most resolved following dose reduction or interruption and/or medication for treatment. Triheptanoin was not associated with any long-term safety concerns when administered at dose levels up to 35% of total daily caloric intake for up to 1 year.

Funder: National Institute for Health Research (NIHR) GOSH BRC, OBJECTIVE: Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS: The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS: FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE: FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.