Tan Harold H G, Westeneng Henk-Jan, Nitert Abram D, van Veenhuijzen Kevin, Meier Jil M, van der Burgh Hannelore K, van Zandvoort Martine J E, van Es Michael A, Veldink Jan H, van den Berg Leonard H
Department of Neurology, UMC Utrecht Brain Center University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Department of Experimental Psychology, Utrecht University, Utrecht, The Netherlands.
Ann Neurol. 2022 Dec;92(6):1030-1045. doi: 10.1002/ana.26488. Epub 2022 Sep 20.
The purpose of this study was to identify subtypes of amyotrophic lateral sclerosis (ALS) by comparing patterns of neurodegeneration using brain magnetic resonance imaging (MRI) and explore their phenotypes.
We performed T1-weighted and diffusion tensor imaging in 488 clinically well-characterized patients with ALS and 338 control subjects. Measurements of whole-brain cortical thickness and white matter connectome fractional anisotropy were adjusted for disease-unrelated variation. A probabilistic network-based clustering algorithm was used to divide patients into subgroups of similar neurodegeneration patterns. Clinical characteristics and cognitive profiles were assessed for each subgroup. In total, 512 follow-up scans were used to validate clustering results longitudinally.
The clustering algorithm divided patients with ALS into 3 subgroups of 187, 163, and 138 patients. All subgroups displayed involvement of the precentral gyrus and are characterized, respectively, by (1) pure motor involvement (pure motor cluster [PM]), (2) orbitofrontal and temporal involvement (frontotemporal cluster [FT]), and (3) involvement of the posterior cingulate cortex, parietal white matter, temporal operculum, and cerebellum (cingulate-parietal-temporal cluster [CPT]). These subgroups had significantly distinct clinical profiles regarding male-to-female ratio, age at symptom onset, and frequency of bulbar symptom onset. FT and CPT revealed higher rates of cognitive impairment on the Edinburgh cognitive and behavioral ALS screen (ECAS). Longitudinally, clustering remained stable: at 90.4% of their follow-up visits, patients clustered in the same subgroup as their baseline visit.
ALS can manifest itself in 3 main patterns of cerebral neurodegeneration, each associated with distinct clinical characteristics and cognitive profiles. Besides the pure motor and frontotemporal dementia (FTD)-like variants of ALS, a new neuroimaging phenotype has emerged, characterized by posterior cingulate, parietal, temporal, and cerebellar involvement. ANN NEUROL 2022;92:1030-1045.
本研究旨在通过比较脑磁共振成像（MRI）的神经退行性变模式来识别肌萎缩侧索硬化症（ALS）的亚型，并探索其表型。
我们对488例临床特征明确的ALS患者和338例对照者进行了T1加权成像和弥散张量成像。对全脑皮质厚度和白质连接组分数各向异性的测量进行了与疾病无关的变异校正。使用基于概率网络的聚类算法将患者分为神经退行性变模式相似的亚组。对每个亚组的临床特征和认知概况进行评估。总共使用512次随访扫描对聚类结果进行纵向验证。
聚类算法将ALS患者分为3个亚组，分别有187例、163例和138例患者。所有亚组均显示中央前回受累，其特征分别为：（1）单纯运动受累（纯运动簇[PM]）；（2）眶额和颞叶受累（额颞簇[FT]）；（3）后扣带回皮质、顶叶白质、颞叶岛盖和小脑受累（扣带回-顶叶-颞叶簇[CPT]）。这些亚组在男女比例、症状发作年龄和延髓症状发作频率方面具有明显不同的临床特征。FT和CPT在爱丁堡认知和行为性ALS筛查（ECAS）中显示出较高的认知障碍发生率。纵向来看，聚类保持稳定：在90.4%的随访中，患者聚类于与基线访视相同的亚组。
ALS可表现为3种主要的脑神经元退行性变模式，每种模式都与不同的临床特征和认知概况相关。除了ALS的纯运动型和额颞叶痴呆（FTD）样变体之外，一种新的神经影像表型已经出现，其特征是后扣带回、顶叶、颞叶和小脑受累。《神经病学纪事》2022年；92:1030 - 1045。
