Clinical Research in ALS and related disorders for Therapeutic Development (CReATe)

项目总结/摘要 ALS的生物学很难研究，部分原因是缺乏合适的工具，部分原因是 在疾病的过程中相对较晚的阶段，当诊断。在这份给父母的补充中， U 54奖，支持ALS和相关疾病治疗开发的临床研究， （CReATe）联盟，我们提出了一个分析计划，将有助于解决这两个问题。这里我们 介绍全脑质子磁共振波谱成像（1H MRSI）作为一种创新工具， 揭示了在与ALS相关的背景下，大脑中的生物化学（神经代谢物）变化， 症状前家族性ALS（Pre-fALS），一项纵向自然史和生物标志物研究， ALS的遗传风险前fALS已经持续了约15年，约20个个体表型转化为临床 明显的肌萎缩侧索硬化症在这些人的一个子集中，我们已经能够收集多模态脑MRI数据， 在表型转化前后。这一宝贵的资源提供了一个独特的机会，探索早期 ALS患者大脑中的生化变化，与未来的发展有潜在的相关性， 诊断生物标志物。我们的母公司U 54奖的项目-3建议描述解剖分布， 症状前C9 ORF 72和SOD 1突变携带者结构和功能变化的时间进程 使用结构、弥散、灌注和静息态功能MRI，但不包括全脑质子 磁共振波谱数据。本补充申请旨在填补这一空白，并提供独家 重点分析全脑MRS数据。利用已经从Pre-fALS研究中收集的MRSI数据， 这一补充将使我们能够表征大脑中神经代谢物变化的解剖分布 症状前SOD 1和C9 ORF 72突变携带者（Aim 1a）。此外，通过计划中的伪 纵向分析，我们的目标是通过研究神经退行性变的变化来确定神经退行性变的时间模式， 随着年龄的增长，症状前携带者的代谢物中的变化（目标1b）。最后，探索性纵向 对表型转化者的研究将允许绘制大脑代谢物的变化， 导致ALS的神经退行性模式（Aim 2）。作为Pre-fALS部分采集的MRSI数据的评价 将首次在症状前个体中生成详细的神经变性全脑地图 具有识别早期MRSI生物标志物的潜力，这些生物标志物可能具有未来的诊断实用性。这一补充， 由于时间相对较短（12个月），不需要任何新的MRI数据收集， Michael Benatar，MD，PhD（神经学家）和Mohammed Goryawala，PhD （放射科医生），谁是新的ALS领域。通过这种补充获得的知识将使改善 在早期症状前疾病中进行神经代谢物绘图，并可能产生早期疾病的生物标志物 进展这里提出的分析将为未来的R 01产生关键的试验数据， 1H MRSI用于告知ALS中神经解剖学疾病进展的空间和时间模式。

PROJECT SUMMARY / ABSTRACT The biology of ALS is difficult to study, in part because of a paucity of suitable tools, and in part because of the relatively late stage in the course of the disease when the diagnosis is made. In this supplement to the parent U54 award that supports the Clinical Research in ALS and Related Disorders for Therapeutic Development, (CReATe) Consortium, we propose an analytic plan that will help to address both of these issues. Here we introduce whole-brain proton magnetic resonance spectroscopic imaging (1H MRSI) as an innovative tool to shed light on the biochemical (neurometabolite) changes in the brain associated with ALS within the context of Pre-Symptomatic Familial ALS (Pre-fALS), a longitudinal natural history, and biomarker study of individuals at genetic risk for ALS. Pre-fALS has been ongoing for ~15 years, with ~20 individuals phenoconverting to clinically manifest ALS. In a subset of these individuals, we have been able to collect multi-modal brain MRI data both before and following phenoconversion. This valuable resource offers a unique opportunity to explore the early biochemical changes in the brains of patients with ALS, with potential relevance to the future development of diagnostic biomarkers. Project-3 of our parent U54 award proposed to characterize the anatomic distribution and temporal course of structural and functional changes in pre-symptomatic C9ORF72 and SOD1 mutation carriers using structural, diffusion, perfusion, and resting-state functional MRI but did not include whole-brain proton magnetic resonance spectroscopy data. This supplemental application aims to fill this gap, with an exclusive focus on the analysis of whole-brain MRS data. Utilizing already collected MRSI data from the Pre-fALS study, this supplement will allow us to characterize the anatomic distribution of neurometabolite changes in the brains of pre-symptomatic SOD1 and C9ORF72 mutation carriers (Aim 1a). Additionally, through the planned pseudo- longitudinal analysis we aim to identify temporal patterns of changes in neurodegeneration by studying changes in metabolites in pre-symptomatic carriers across advancing age (Aim 1b). Finally, an exploratory longitudinal study in phenoconvertors will allow mapping changes in brain metabolites that could provide insights into neurodegenerative patterns that lead to ALS (Aim 2). The evaluation of MRSI data acquired as part Pre-fALS will generate for the first time detailed whole-brain maps of neurodegeneration in pre-symptomatic individuals with the potential to identify early MRSI biomarkers that might have future diagnostic utility. This supplement, which does not entail any new MRI data collection given its relatively short timeframe (12 months), will strengthen the nascent collaboration between Michael Benatar, MD, PhD (neurologist), and Mohammed Goryawala, PhD (radiologist), who is new to the field of ALS. The knowledge gained through this supplement will enable improved neurometabolite mapping in early pre-symptomatic disease and may yield biomarkers of early disease progression. The analyses proposed here will generate critical pilot data for a future R01 focused on the use of 1H MRSI to inform the spatial and temporal patterns of neuroanatomic disease progression in ALS.