Koscik Timothy R, Sloat Lauren, van der Plas Ellen, Joers James M, Deelchand Dinesh K, Lenglet Christophe, Öz Gülin, Nopoulos Peggy C
Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA 52242-1000, USA.
Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN 55455, USA.
Brain Commun. 2020 Dec 15;2(2):fcaa184. doi: 10.1093/braincomms/fcaa184. eCollection 2020.
Spinocerebellar ataxia type 1 is a progressive neurodegenerative, movement disorder. With potential therapies on the horizon, it is critical to identify biomarkers that (i) differentiate between unaffected and spinocerebellar ataxia Type 1-affected individuals; (ii) track disease progression; and (iii) are directly related to clinical changes of the patient. Magnetic resonance imaging of volumetric changes in the brain may be a suitable source of biomarkers for spinocerebellar ataxia Type 1. In a previous report on a longitudinal study of patients with spinocerebellar ataxia Type 1, we evaluated the volume and magnetic resonance spectroscopy measures of the cerebellum and pons, showing pontine volume and pontine -acetylaspartate-to--inositol ratio were sensitive to change over time. As a follow-up, the current study conducts a whole brain exploration of volumetric MRI measures with the aim to identify biomarkers for spinocerebellar ataxia Type 1 progression. We adapted a joint label fusion approach using multiple, automatically generated, morphologically matched atlases to label brain regions including cerebellar sub-regions. We adjusted regional volumes by total intracranial volume allowing for linear and power-law relationships. We then utilized Bonferroni corrected linear mixed effects models to (i) determine group differences in regional brain volume and (ii) identify change within affected patients only. We then evaluated the rate of change within each brain region to identify areas that changed most rapidly. Lastly, we used a penalized, linear mixed effects model to determine the strongest brain predictors of motor outcomes. Decrease in pontine volume and accelerating decrease in putamen volume: (i) reliably differentiated spinocerebellar ataxia Type 1-affected and -unaffected individuals; (ii) were observable in affected individuals without referencing an unaffected comparison group; (iii) were detectable within ∼6-9 months; and (iv) were associated with increased disease burden. In conclusion, volumetric change in the pons and putamen may provide powerful biomarkers to track disease progression in spinocerebellar ataxia Type 1. The methods employed here are readily translatable to current clinical settings, providing a framework for study and usage of volumetric neuroimaging biomarkers for clinical trials.
1型脊髓小脑共济失调是一种进行性神经退行性运动障碍。随着潜在疗法的出现,识别生物标志物至关重要,这些生物标志物要能够:(i)区分未受影响和受1型脊髓小脑共济失调影响的个体;(ii)追踪疾病进展;(iii)与患者的临床变化直接相关。大脑体积变化的磁共振成像可能是1型脊髓小脑共济失调生物标志物的合适来源。在之前一项关于1型脊髓小脑共济失调患者的纵向研究报告中,我们评估了小脑和脑桥的体积及磁共振波谱测量结果,结果显示脑桥体积以及脑桥乙酰天冬氨酸与肌醇的比值随时间变化较为敏感。作为后续研究,本研究对全脑体积MRI测量进行了探索,旨在识别1型脊髓小脑共济失调进展的生物标志物。我们采用了一种联合标签融合方法,使用多个自动生成的、形态匹配的图谱来标记包括小脑亚区域在内的脑区。我们通过总颅内体积对区域体积进行调整,以考虑线性和幂律关系。然后,我们利用Bonferroni校正的线性混合效应模型:(i)确定区域脑体积的组间差异;(ii)仅识别受影响患者体内的变化。接着,我们评估每个脑区内的变化率,以识别变化最迅速的区域。最后,我们使用惩罚线性混合效应模型来确定运动结果最强的脑预测指标。脑桥体积减小和壳核体积加速减小:(i)可靠地区分了受1型脊髓小脑共济失调影响和未受影响的个体;(ii)在受影响个体中可观察到,无需参考未受影响的对照组;(iii)在约6 - 9个月内可检测到;(iv)与疾病负担增加相关。总之,脑桥和壳核的体积变化可能为追踪1型脊髓小脑共济失调的疾病进展提供有力的生物标志物。这里采用的方法很容易转化到当前的临床环境中,为临床试验中体积神经影像学生物标志物的研究和使用提供了一个框架。