Meo Giuseppe, Ferraro Pilar M, Cillerai Marta, Gemelli Chiara, Cabona Corrado, Zaottini Federico, Roccatagliata Luca, Villani Flavio, Schenone Angelo, Caponnetto Claudia
Department of Neurology, IRCCS Ospedale Policlinico San Martino, 16132 Genoa, Italy.
Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16126 Genoa, Italy.
Life (Basel). 2022 Sep 27;12(10):1506. doi: 10.3390/life12101506.
Pure/predominant upper motor neuron (pUMN) and lower motor neuron (pLMN) diseases have significantly better prognosis compared to amyotrophic lateral sclerosis (ALS), but their early differentiation is often challenging. We therefore tested whether a multimodal characterization approach embedding clinical, cognitive/behavioral, genetic, and neurophysiological data may improve the differentiation of pUMN and pLMN from ALS already by the time of diagnosis. Dunn’s and chi-squared tests were used to compare data from 41 ALS, 34 pLMN, and 19 pUMN cases with diagnoses confirmed throughout a 2-year observation period. Area under the curve (AUC) analyses were implemented to identify the finest tools for phenotypes discrimination. Relative to ALS, pLMN showed greater lower limbs weakness, lower UMN burden, and progression rate (p < 0.001−0.04). PUMN showed a greater frequency of lower limbs onset, higher UMN burden, lower ALSFRS-r and MRC progression rates (p < 0.001−0.03), and greater ulnar compound muscle action potential (CMAP) amplitude and tibial central motor conduction time (CMCT) (p = 0.05−0.03). The UMN progression rate was the finest measure to identify pLMN cases (AUC = 90%), while the MRC progression rate was the finest tool to identify pUMN (AUC = 82%). Detailed clinical and neurophysiological examinations may significantly improve MNDs differentiation, facilitating prognosis estimation and ameliorating stratification strategies for clinical trials enrollment.
与肌萎缩侧索硬化症（ALS）相比，单纯/主要为上运动神经元（pUMN）和下运动神经元（pLMN）疾病的预后明显更好，但它们的早期鉴别往往具有挑战性。因此，我们测试了一种嵌入临床、认知/行为、遗传和神经生理学数据的多模态特征分析方法是否可以在诊断时就改善pUMN和pLMN与ALS的鉴别。使用邓恩检验和卡方检验来比较41例ALS、34例pLMN和19例pUMN病例的数据，这些病例的诊断在2年观察期内得到确认。进行曲线下面积（AUC）分析以确定区分表型的最佳工具。相对于ALS，pLMN表现出更严重的下肢无力、更低的上运动神经元负荷和进展率（p<0.001 - 0.04）。pUMN表现出下肢起病频率更高、上运动神经元负荷更高、更低的ALS功能评定量表修订版（ALSFRS-r）和医学研究委员会（MRC）进展率（p<0.001 - 0.03），以及更大的尺神经复合肌肉动作电位（CMAP）幅度和胫神经中枢运动传导时间（CMCT）（p = 0.05 - 0.03）。上运动神经元进展率是识别pLMN病例的最佳指标（AUC = 90%），而MRC进展率是识别pUMN的最佳工具（AUC = 82%）。详细的临床和神经生理学检查可能会显著改善运动神经元疾病（MNDs）的鉴别，有助于预后评估并改善临床试验入组的分层策略。
