Department of Neurology and Neurological Science, Graduate School, Tokyo Medical and Dental University, 1-5-45, Yushima, Bunkyo-Ku, Tokyo, 113-8510, Japan.
Basic Technology Research Center, Tokyo Metropolitan Institute of Medical Science, 2-1-6 Kamikitazawa, Setagaya-Ku, Tokyo, 156-8506, Japan.
Cerebellum. 2024 Aug;23(4):1280-1292. doi: 10.1007/s12311-023-01545-1. Epub 2023 Apr 28.
Ataxia and impaired motor learning are both fundamental features in diseases affecting the cerebellum. However, it remains unclarified whether motor learning is impaired only when ataxia clearly manifests, nor it is known whether the progression of ataxia, the speed of which often varies among patients with the same disease, can be monitored by examining motor learning. We evaluated motor learning and ataxia at intervals of several months in 40 patients with degenerative conditions [i.e., multiple system atrophy (MSA), Machado-Joseph disease (MJD)/spinocerebellar ataxia type 3 (SCA3), SCA6, and SCA31]. Motor learning was quantified as the adaptability index (AI) in the prism adaptation task and ataxia was scored using the Scale for the Assessment and Rating of Ataxia (SARA). We found that AI decreased most markedly in both MSA-C and MSA-P, moderately in MJD, and mildly in SCA6 and SCA31. Overall, the AI decrease occurred more rapidly than the SARA score increase. Interestingly, AIs remained normal in purely parkinsonian MSA-P patients (n = 4), but they dropped into the ataxia range when these patients started to show ataxia. The decrease in AI during follow-up (dAI/dt) was significant in patients with SARA scores < 10.5 compared with patients with SARA scores ≥ 10.5, indicating that AI is particularly useful for diagnosing the earlier phase of cerebellar degeneration. We conclude that AI is a useful marker for progressions of cerebellar diseases, and that evaluating the motor learning of patients can be particularly valuable for detecting cerebellar impairment, which is often masked by parkinsonisms and other signs.
在影响小脑的疾病中，共济失调和运动学习障碍都是基本特征。然而，目前尚不清楚运动学习是否仅在明显出现共济失调时受到损害，也不知道小脑退行性疾病（如多系统萎缩症（MSA）、Machado-Joseph 病（MJD）/脊髓小脑性共济失调 3 型（SCA3）、SCA6 和 SCA31）患者的共济失调进展速度是否可以通过检查运动学习来监测。我们在 40 例退行性疾病患者中每隔几个月评估一次运动学习和共济失调[即多系统萎缩症（MSA）、Machado-Joseph 病（MJD）/脊髓小脑性共济失调 3 型（SCA3）、SCA6 和 SCA31]。在棱镜适应任务中，我们将运动学习量化为适应性指数（AI），并使用共济失调评估和评分量表（SARA）对共济失调进行评分。我们发现，MSA-C 和 MSA-P 患者的 AI 下降最明显，MJD 患者中度下降，SCA6 和 SCA31 患者轻度下降。总的来说，AI 的下降速度比 SARA 评分的增加速度更快。有趣的是，在仅有帕金森症状的 MSA-P 患者（n=4）中，AI 仍然正常，但当这些患者开始出现共济失调时，AI 则降至共济失调范围。与 SARA 评分≥10.5 的患者相比，SARA 评分<10.5 的患者在随访期间的 AI 下降（dAI/dt）更显著，表明 AI 对于诊断小脑退行性病变的早期阶段特别有用。我们的结论是，AI 是小脑疾病进展的有用标志物，评估患者的运动学习对于检测小脑损伤特别有价值，因为小脑损伤常常被帕金森症状和其他体征所掩盖。
