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1.
J Inherit Metab Dis ; 2023 Nov 06.
Artigo em Inglês | MEDLINE | ID: mdl-37932875

RESUMO

The study of inborn errors of neurotransmission has been mostly focused on monoamine disorders, GABAergic and glycinergic defects. The study of the glutamatergic synapse using the same approach than classic neurotransmitter disorders is challenging due to the lack of biomarkers in the CSF. A metabolomic approach can provide both insight into their molecular basis and outline novel therapeutic alternatives. We have performed a semi-targeted metabolomic analysis on CSF samples from 25 patients with neurogenetic disorders with an important expression in the glutamatergic synapse and 5 controls. Samples from patients diagnosed with MCP2, CDKL5-, GRINpathies and STXBP1-related encephalopathies were included. We have performed univariate (UVA) and multivariate statistical analysis (MVA), using Wilcoxon rank-sum test, principal component analysis (PCA), and OPLS-DA. By using the results of both analyses, we have identified the metabolites that were significantly altered and that were important in clustering the respective groups. On these, we performed pathway- and network-based analyses to define which metabolic pathways were possibly altered in each pathology. We have observed alterations in the tryptophan and branched-chain amino acid metabolism pathways, which interestingly converge on LAT1 transporter-dependency to cross the blood-brain barrier (BBB). Analysis of the expression of LAT1 transporter in brain samples from a mouse model of Rett syndrome (MECP2) revealed a decrease in the transporter expression, that was already noticeable at pre-symptomatic stages. The study of the glutamatergic synapse from this perspective advances the understanding of their pathophysiology, shining light on an understudied feature as is their metabolic signature.

2.
Front Cell Dev Biol ; 12: 1321282, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38505260

RESUMO

SYNGAP1 haploinsufficiency results in a developmental and epileptic encephalopathy (DEE) causing generalized epilepsies accompanied by a spectrum of neurodevelopmental symptoms. Concerning interictal epileptiform discharges (IEDs) in electroencephalograms (EEG), potential biomarkers have been postulated, including changes in background activity, fixation-off sensitivity (FOS) or eye closure sensitivity (ECS). In this study we clinically evaluate a new cohort of 36 SYNGAP1-DEE individuals. Standardized questionnaires were employed to collect clinical, electroencephalographic and genetic data. We investigated electroencephalographic findings, focusing on the cortical distribution of interictal abnormalities and their changes with age. Among the 36 SYNGAP1-DEE cases 18 presented variants in the SYNGAP1 gene that had never been previously reported. The mean age of diagnosis was 8 years and 8 months, ranging from 2 to 17 years, with 55.9% being male. All subjects had global neurodevelopmental/language delay and behavioral abnormalities; 83.3% had moderate to profound intellectual disability (ID), 91.7% displayed autistic traits, 73% experienced sleep disorders and 86.1% suffered from epileptic seizures, mainly eyelid myoclonia with absences (55.3%). A total of 63 VEEGs were revised, observing a worsening of certain EEG findings with increasing age. A disorganized background was observed in all age ranges, yet this was more common among older cases. The main IEDs were bilateral synchronous and asynchronous posterior discharges, accounting for ≥50% in all age ranges. Generalized alterations with maximum amplitude in the anterior region showed as the second most frequent IED (≥15% in all age ranges) and were also more common with increasing age. Finally, diffuse fast activity was much more prevalent in cases with 6 years or older. To the best of our knowledge, this is the first study to analyze EEG features across different age groups, revealing an increase in interictal abnormalities over infancy and adolescence. Our findings suggest that SYNGAP1 haploinsufficiency has complex effects in human brain development, some of which might unravel at different developmental stages. Furthermore, they highlight the potential of baseline EEG to identify candidate biomarkers and the importance of natural history studies to develop specialized therapies and clinical trials.

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