Dataset Information

A missense mutation in SLC6A1 associated with Lennox-Gastaut syndrome impairs GABA transporter 1 protein trafficking and function.

ABSTRACT:

Background

Mutations in SLC6A1 have been associated mainly with myoclonic atonic epilepsy (MAE) and intellectual disability. We identified a novel missense mutation in a patient with Lennox-Gastaut syndrome (LGS) characterized by severe seizures and developmental delay.

Methods

Exome Sequencing was performed in an epilepsy patient cohort. The impact of the mutation was evaluated by ³H γ-aminobutyric acid (GABA) uptake, structural modeling, live cell microscopy, cell surface biotinylation and a high-throughput assay flow cytometry in both neurons and non neuronal cells.

Results

We discovered a heterozygous missense mutation (c700G to A [pG234S) in the SLC6A1 encoding GABA transporter 1 (GAT-1). Structural modeling suggests the mutation destabilizes the global protein conformation. With transient expression of enhanced yellow fluorescence protein (YFP) tagged rat GAT-1 cDNAs, we demonstrated that the mutant GAT-1(G234S) transporter had reduced total protein expression in both rat cortical neurons and HEK 293 T cells. With a high-throughput flow cytometry assay and live cell surface biotinylation, we demonstrated that the mutant GAT-1(G234S) had reduced cell surface expression. ³H radioactive labeling GABA uptake assay in HeLa cells indicated a reduced function of the mutant GAT-1(G234S).

Conclusions

This mutation caused instability of the mutant transporter protein, which resulted in reduced cell surface and total protein levels. The mutation also caused reduced GABA uptake in addition to reduced protein expression, leading to reduced GABA clearance, and altered GABAergic signaling in the brain. The impaired trafficking and reduced GABA uptake function may explain the epilepsy phenotype in the patient.

SUBMITTER: Cai K

PROVIDER: S-EPMC6849469 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Publications

A missense mutation in SLC6A1 associated with Lennox-Gastaut syndrome impairs GABA transporter 1 protein trafficking and function.

Cai Kefu K Wang Jie J Eissman Jaclyn J Wang Juexin J Nwosu Gerald G Shen Wangzhen W Liang Hui-Ci HC Li Xiao-Jing XJ Zhu Hai-Xia HX Yi Yong-Hong YH Song Jeffrey J Xu Dong D Delpire Eric E Liao Wei-Ping WP Shi Yi-Wu YW Kang Jing-Qiong JQ

Experimental neurology 20190606

<h4>Background</h4>Mutations in SLC6A1 have been associated mainly with myoclonic atonic epilepsy (MAE) and intellectual disability. We identified a novel missense mutation in a patient with Lennox-Gastaut syndrome (LGS) characterized by severe seizures and developmental delay.<h4>Methods</h4>Exome Sequencing was performed in an epilepsy patient cohort. The impact of the mutation was evaluated by <sup>3</sup>H γ-aminobutyric acid (GABA) uptake, structural modeling, live cell microscopy, cell sur ...[more]

PMID: 31176687

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Project description:BackgroundLennox-Gastaut syndrome (LGS) is a severe developmental and epileptic encephalopathy characterized by drug-resistant epilepsy with multiple seizure types starting in childhood, a typical slow spike-wave pattern on electroencephalogram, and cognitive dysfunction.MethodsWe performed a systematic literature review according to the PRISMA guidelines to identify, synthesize and appraise the burden of illness in LGS (including "probable" LGS). Studies were identified by searching MEDLINE, Embase and APA PsychInfo, Cochrane's database of systematic reviews, and Epistemonikos. The outcomes were epidemiology (incidence, prevalence or mortality), direct and indirect costs, healthcare resource utilization, and patient and caregiver health-related quality of life (HRQoL).ResultsThe search identified 22 publications evaluating the epidemiology (n = 10), direct costs and resource (n = 10) and/or HRQoL (n = 5). No studies reporting on indirect costs were identified. With no specific ICD code for LGS in many regions, several studies had to rely upon indirect methods to identify their patient populations (e.g., algorithms to search insurance claims databases to identify "probable" LGS). There was heterogeneity between studies in how LGS was defined, the size of the populations, ages of the patients and length of the follow-up period. The prevalence varied from 4.2 to 60.8 per 100,000 people across studies for probable LGS and 2.9-28 per 100,000 for a confirmed/narrow definition of LGS. LGS was associated with high mortality rates compared to the general population and epilepsy population. Healthcare resource utilization and direct costs were substantial across all studies. Mean annual direct costs per person varied from $24,048 to $80,545 across studies, and home-based care and inpatient care were significant cost drivers. Studies showed that the HRQoL of patients and caregivers was adversely affected, although only a few studies were identified. In addition, studies suggested that seizure events were associated with higher costs and worse HRQoL. The risk of bias was low or moderate in most studies.ConclusionsLGS is associated with a significant burden of illness featuring resistant seizures associated with higher costs and worse HRQoL. More research is needed, especially in evaluating indirect costs and caregiver burden, where there is a notable lack of studies.

Project description:ObjectiveThe discovery and validation of electroencephalography (EEG) biomarkers often rely on visual identification of waveforms. However, bias toward visually striking events restricts the search space for new biomarkers, and low interrater reliability can limit rigorous validation. We present a data-driven approach to biomarker discovery called scalp EEG Pattern Identification and Categorization (s-EPIC), which enables automated, unsupervised identification of EEG waveforms. S-EPIC is validated on Lennox-Gastaut syndrome (LGS), an epilepsy that is difficult to diagnose and assess due to its variable presentation and insidious evolution of symptoms.MethodsWe retrospectively collected 10-min scalp EEG clips during non-rapid eye movement (NREM) sleep from 20 subjects with LGS and 20 approximately age-matched healthy controls. For s-EPIC, EEG events of interest (EOIs) were detected in all subjects using time-frequency analysis. The 11 705 EOIs were characterized based on 11 features and were collectively grouped using both k-means clustering and feature categorization. To provide clinical context, 1350 EOIs were visually reviewed and classified by three epileptologists.Resultss-EPIC identified four clusters as candidate biomarkers of LGS, each having significantly more LGS EOIs than control EOIs. Two clusters contained EOIs resembling known LGS biomarkers such as interictal epileptiform discharges and generalized paroxysmal fast activity. The other two LGS-associated EEG clusters contained short bursts of power in beta and gamma frequency bands that were primarily unrecognized by epileptologists. This approach also uncovered significant differences in sleep spindles between LGS and control cohorts.Significances-EPIC provides a quantitative approach to waveform identification that could be broadly applied to EEG from both healthy subjects and those with suspected pathology. s-EPIC can objectively identify and characterize relevant EEG waveforms without visual review or assumptions about the waveform's morphology and could therefore be a powerful tool for the discovery and refinement of EEG biomarkers.

Dataset Information

A missense mutation in SLC6A1 associated with Lennox-Gastaut syndrome impairs GABA transporter 1 protein trafficking and function.

Background

Methods

Results

Conclusions

Publications

A missense mutation in SLC6A1 associated with Lennox-Gastaut syndrome impairs GABA transporter 1 protein trafficking and function.

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