Supplementary funding for U01NS104326 Clinical Trial Readiness for SCA1 and SCA3 (“READISCA”)

项目摘要/摘要 为了加强正在进行的READISCA项目的临床试验准备情况，本行政补编 申请要求批准和资助两项纵向生物标记物研究：1)确定 血浆神经丝轻链(NFL)水平，以及2)容量和弥散磁共振成像的附加分析 从携带SCA1或SCA3突变的受试者那里获得的数据。 1)在基线就诊时获得的血浆样本显示，NFL水平可以区分共济失调前期 来自对照和早期共济失调样本的样本。后续样本中的NFL水平预计将 提供NFL水平从共济失调前范围到早期共济失调范围的演变， 血浆NFL水平与标准化反应平均数(SRM)、 以及血浆NFL水平在预测共济失调前期受试者发病年龄中的作用。所有样本都要 作为Aim1的一部分，目前储存在BioSEND储存库。SiMoA分析 血浆样本将决定NFL水平。血浆NFL水平将与临床相关 结果评估(COA)数据。 2)增加基于标准感兴趣区域(ROI)的结构体积分析的价值 磁共振数据和简单扩散张量成像(DTI)分析在READISCA的目标2中，我们将执行 为结构磁共振数据添加基于体素的分析，并使用高阶模型和基于固定像素的分析。 我们的假设是，对于血浆NFL水平和MR参数的演变存在临界阈值 哪些表型转换(即，共济失调疾病发病)发生在携带SCA1或SCA1的共济失调前期受试者 SCA3突变。我们进一步假设，血浆和成像生物标记物共同提供了 转化率和发病年龄强于单个生物标志物。我们将使用SARA总分≥3 作为表观转化指示剂。对于统计学，我们计划使用生存模型来确定 转换。结合生存模型和线性混合模型的联合模型将被用来寻找 时变协变量的影响。最佳模型将使用C静力学标准进行选择。

Project Summary/Abstract To enhance the clinical trial readiness of the ongoing READISCA project, this Administrative Supplement application requests approval and funding for two longitudinal biomarker studies: 1) determination of the plasma level of neurofilament light chain (NfL), and 2) additional analyses of the volumetric and diffusion MRI data obtained from subjects who carry a mutation of SCA1 or SCA3. 1) Plasma samples obtained at baseline visits showed that the NfL level can distinguish pre-ataxia samples from control and early-ataxia samples. NfL levels in the follow-up samples are expected to provide the evolution of the NfL level from the pre-ataxia range to the early ataxia range, the resoponsiveness of the plasma NfL level with indices such as the standardized response mean (SRM), and the utility of plasma NfL level in predicting the age at onset in pre-ataxia subjects. All samples to be analyzed are currently stored at the BioSEND repository as a part of Aim1. The SIMOA analysis of the plasma samples will determine the NfL level. The plasma NfL level will be correlated with clinical outcome assessment (COA) data. 2) To augment the value of standard region-of-interest (ROI) based volumetric analyses of the structural MR data and the simple diffusion tensor imaging (DTI) analyses in Aim 2 of READISCA, we will perform add voxel-based analyses for structural MR data and use higher-order models and fixel-based analysis. Our hypothesis is that there are critical thresholds for the evolving plasma NfL level and MR parameters at which the phenoconversion (i.e., ataxia disease onset) occurs in pre-ataxia subjects who carry the SCA1 or SCA3 mutation. We further postulate that plasma and imaging biomarkers together provide the prediction of the conversion and the age at onset stronger than individual biomarkers. We will use the SARA total score ≥3 as the phenoconversion indicator. For statistics, we plan to use survival models to identify predictors of conversion. Joint models that combine survival models and linear mixed models will be used to look for the influence of time varying covariates. The best model will be selected using C statics criteria.