Beichert Lukas, Seemann Jens, Kessler Christoph, Traschütz Andreas, Müller Doreen, Dillmann-Jehn Katrin, Ricca Ivana, Satolli Sara, Basak Nazli A, Coarelli Giulia, Timmann Dagmar, Gagnon Cynthia, van de Warrenburg Bart P C, Ilg Winfried, Synofzik Matthis, Schüle Rebecca
Division Translational Genomics of Neurodegenerative Diseases (L.B., A.T., D.M., M.S.), Hertie-Institute for Clinical Brain Research and Center for Neurology, and German Center for Neurodegenerative Diseases (DZNE) (L.B., A.T., D.M., K.D.-J., M.S., R.S.), University of Tübingen; Section Computational Sensomotorics (J.S., W.I.), Hertie Institute for Clinical Brain Research; Centre for Integrative Neuroscience (CIN) (J.S., W.I.); Department of Neurodegenerative Diseases (C.K.), Hertie-Institute for Clinical Brain Research and Center for Neurology, University of Tübingen; Center for Neurology and Hertie Institute for Clinical Brain Research (K.D.-J., R.S.), University Hospital Tübingen, Germany; Molecular Medicine (I.R., S.S.), IRCCS Fondazione Stella Maris, Pisa, Italy; Koç University (N.A.B.), Translational Medicine Research Center, KUTTAM-NDAL, Istanbul, Turkey; Sorbonne Université (G.C.), Paris Brain Institute, INSERM, CNRS, APHP, France; Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (D.T.), University Hospital Essen, University of Duisburg-Essen, Germany; Groupe de recherche interdisciplinaire sur les maladies neuromusculaires (GRIMN) (C.G.), Centre intégré universitaire de santé et de services sociaux du Saguenay-Lac-St-Jean; Centre de recherche du Centre intégré universitaire de santé et de services sociaux du Saguenay-Lac-St-Jean (C.G.); Faculté de médecine et des sciences de la santé (C.G.), Université de Sherbrooke, Québec, Canada; Department of Neurology (B.P.C.v.d.W.), Radboud University Medical Center, Nijmegen, the Netherlands; and Division of Neurodegenerative Diseases (R.S.), Department of Neurology, Heidelberg University Hospital, Germany.
Neurology. 2024 Dec 24;103(12):e209887. doi: 10.1212/WNL.0000000000209887. Epub 2024 Dec 2.
With targeted treatment trials on the horizon, identification of sensitive and valid outcome measures becomes a priority for >100 spastic ataxias. While digital-motor measures, assessed using wearable sensors, are considered prime outcome candidates for spastic ataxias, genotype-specific validation studies are lacking. We here aimed to identify candidate digital-motor outcomes for spastic paraplegia type 7 (SPG7)-one of the most common spastic ataxias-that (1) reflect patient-relevant health aspects, even in mild, trial-relevant disease stages; (2) are suitable for a multicenter setting; and (3) assess mobility also during uninstructed walking simulating real life.
This cross-sectional multicenter study (7 centers, 6 countries) analyzed defined laboratory-based walking and uninstructed "supervised free walking" in patients with SPG7 and healthy controls using 3 wearable sensors (Opal APDM). For the extracted digital gait measures, we assessed effect sizes for the discrimination of patients and controls (Cliff δ) and Spearman correlations with measures of functional mobility and overall disease severity (Spastic Paraplegia Rating Scale [SPRS], including mobility subscore SPRS; Scale for the Assessment and Rating of Ataxia [SARA]) and the activities of daily living subscore of the Friedreich Ataxia Rating Scale (FARS-ADL).
Gait was analyzed in 65 patients with SPG7 and 50 healthy controls. Among 30 hypothesis-based gait measures, 18 demonstrated at least moderate effect size (δ > 0.5) in discriminating patients from controls and 17 even in mild disease stages (SPRS ≤ 9, n = 41). Spatiotemporal variability measures such as spatial variability measure SPcmp (ρ = 0.67, < 0.0001) and stride time CV (ρ = 0.67, < 0.0001) showed the largest correlations with functional mobility (SPRS)-as with overall disease severity (SPRS, SARA) and activities of daily living (FARS-ADL). The correlations of variability measures with SPRS could be confirmed in mild disease stages (e.g., SPcmp: ρ = 0.50, < 0.0001) and in "supervised free walking" (e.g., stride time CV: ρ = -0.57, < 0.0001).
We here identified trial-ready digital-motor candidate outcomes for the spastic ataxia SPG7 with proven multicenter applicability, ability to discriminate patients from controls, and correlation with measures of patient-relevant health aspects-even in mild disease stages. If validated longitudinally, these sensor outcomes might inform future natural history and treatment trials in SPG7 and other spastic ataxias.
随着靶向治疗试验即将开展，对于100多种痉挛性共济失调而言，确定敏感且有效的结局指标成为当务之急。虽然使用可穿戴传感器评估的数字运动指标被视为痉挛性共济失调的主要结局候选指标，但缺乏针对特定基因型的验证研究。我们的目的是确定7型痉挛性截瘫（SPG7，最常见的痉挛性共济失调之一）的数字运动候选结局指标，这些指标要满足：（1）即使在与试验相关的轻度疾病阶段，也能反映与患者相关的健康状况；（2）适用于多中心研究；（3）在模拟现实生活的无指导行走过程中也能评估运动能力。
这项横断面多中心研究（涉及7个中心，6个国家）使用3个可穿戴传感器（Opal APDM），分析了SPG7患者和健康对照者基于实验室定义的行走以及无指导的“监督下自由行走”。对于提取的数字步态指标，我们评估了区分患者和对照的效应量（Cliff δ），以及与功能运动能力和整体疾病严重程度指标（痉挛性截瘫评定量表[SPRS]，包括运动亚评分SPRS；共济失调评估与评分量表[SARA]）和弗里德赖希共济失调评定量表日常生活活动亚评分（FARS-ADL）的斯皮尔曼相关性。
对65例SPG7患者和50名健康对照者的步态进行了分析。在30项基于假设的步态指标中，18项在区分患者和对照方面显示出至少中等程度的效应量（δ>0.5），17项在轻度疾病阶段（SPRS≤9，n = 41）也是如此。时空变异性指标，如空间变异性指标SPcmp（ρ = 0.67，<0.0001）和步幅时间CV（ρ = 0.67，<0.0001）与功能运动能力（SPRS）的相关性最强，与整体疾病严重程度（SPRS、SARA）和日常生活活动（FARS-ADL）也是如此。变异性指标与SPRS的相关性在轻度疾病阶段（如SPcmp：ρ = 0.50，<0.0001）和“监督下自由行走”（如步幅时间CV：ρ = -0.57，<0.0001）中也得到了证实。
我们确定了适用于试验的痉挛性共济失调SPG7数字运动候选结局指标，这些指标已证明具有多中心适用性、区分患者和对照的能力，以及与患者相关健康状况指标的相关性，即使在轻度疾病阶段也是如此。如果经过纵向验证，这些传感器指标可能为未来SPG7和其他痉挛性共济失调的自然史和治疗试验提供信息。
