Clinical, Imaging, Genetic, and Disease Course Characteristics in Patients with GM2 Gangliosidosis
Multiple Sclerosis Journal(2023)SCI 2区SCI 3区
Univ Tubingen | Univ Duisburg Essen | From the Department of Neuropediatrics (J.K. | Friedrich Alexander Univ Erlangen Nurnberg | Univ Rostock | Univ Gottingen
Abstract
Background and ObjectivesGM2 gangliosidoses, a group of autosomal-recessive neurodegenerative lysosomal storage disorders, result from beta-hexosaminidase (HEX) deficiency with GM2 ganglioside as its main substrate. Historically, GM2 gangliosidoses have been classified into infantile, juvenile, and late-onset forms. With disease-modifying treatment trials now on the horizon, a more fine-grained understanding of the disease course is needed.MethodsWe aimed to map and stratify the clinical course of GM2 gangliosidoses in a multicenter cohort of pediatric and adult patients. Patients were stratified according to age at onset and age at diagnosis. The 2 resulting GM2 disease clusters were characterized in-depth for respective disease features (detailed standardized clinical, laboratory, and MRI assessments) and disease evolution.ResultsIn 21 patients with GM2 gangliosidosis (17 Tay-Sachs, 2 GM2 activator deficiency, 2 Sandhoff disease), 2 disease clusters were discriminated: an early-onset and early diagnosis cluster (type I; n = 8, including activator deficiency and Sandhoff disease) and a cluster with very variable onset and long interval until diagnosis (type II; n = 13 patients). In type I, rapid onset of developmental stagnation and regression, spasticity, and seizures dominated the clinical picture. Cherry red spot, startle reactions, and elevated AST were only seen in this cluster. In type II, problems with balance or gait, muscle weakness, dysarthria, and psychiatric symptoms were specific and frequent symptoms. Ocular signs were common, including supranuclear vertical gaze palsy in 30%. MRI involvement of basal ganglia and peritrigonal hyperintensity was seen only in type I, whereas predominant infratentorial atrophy (or normal MRI) was characteristic in type II. These types were, at least in part, associated with certain genetic variants.DiscussionAge at onset alone seems not sufficient to adequately predict different disease courses in GM2 gangliosidosis, as required for upcoming trial planning. We propose an alternative classification based on age at disease onset and dynamics, predicted by clinical features and biomarkers, into type I-an early-onset, rapid progression cluster-and type II-a variable onset, slow progression cluster. Specific diagnostic workup, including GM2 gangliosidosis, should be performed in patients with combined ataxia plus lower motor neuron weakness to identify type II patients.
MoreTranslated text
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
1984
被引用117 | 浏览
2005
被引用132 | 浏览
2012
被引用53 | 浏览
2013
被引用230 | 浏览
2019
被引用6 | 浏览
2020
被引用51 | 浏览
2006
被引用171 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper