Imaging neurodegeneration in multiple sclerosis

多发性硬化症的影像学神经退行性变

• 批准号: 10330016
• 负责人: PETER A CALABRESI
• 金额: $ 59.65万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10330016
• 关键词: Address; African American; Algorithms; Atrophic; Biological; Biology; Brain; Brain imaging; C3 gene; Caring; Cerebrum; Characteristics; Clinical; Clinical Management; Clinical assessments; Complement; Complex; Custom; Data Pooling; Data Set; Decision Making; Development; Disabled Persons; Disease; Disease Outcome; Disease Progression; Enhancing Lesion; Ethnic Origin; Female; Ganglionic Layer; Genes; Genetic; Genetic Load; Genetic Predisposition to Disease; Genetic Risk; Genetic Variation; Genotype; Grant; Health; Image; Individual; Inflammatory; Inner Plexiform Layer; Life; Magnetic Resonance Imaging; Measures; Methodology; Methods; Modeling; Monitor; Multiple Sclerosis; Nerve Degeneration; Neuraxis; Neurodegenerative Disorders; Neurons; Neuroprotective Agents; Optical Coherence Tomography; Outcome; Pathology; Pathway interactions; Patient Care; Patient Care Management; Patients; Persons; Population Characteristics; Predisposition; Quality of life; Race; Resolution; Retina; Retinal Degeneration; Retinal Diseases; Retinal Ganglion Cells; Risk; Severity of illness; Site; Structure; Thalamic structure; Therapeutic; Thick; Thinness; Time; Toxic effect; Variant; Visual; aggressive therapy; axonal degeneration; burden of illness; caucasian American; central nervous system demyelinating disorder; clinical predictors; cognitive function; cohort; disability; disability risk; disease prognosis; efficacy testing; follow-up; ganglion cell; genetic analysis; genetic variant; gray matter; high resolution imaging; high risk; imaging genetics; imaging study; improved; individual patient; insight; large datasets; male; multiple sclerosis patient; multiple sclerosis treatment; negative affect; neuronal survival; novel; precision medicine; prediction algorithm; predictive modeling; predictive tools; recruit; research clinical testing; retinal imaging; risk variant; sex; tool

Project Summary One of the significant challenges facing treatment of people with multiple sclerosis (MS) is determining their individual likelihood of progression, as this information would significantly influence the type of therapy selected. Thus, developing specific tools to monitor and predict progression is critical to better manage patient care and to understand mechanisms of disease. We have been developing a multi-faceted approach to more readily monitor (through imaging) and predict (through both imaging and genetic analysis) disease progression in a real-time fashion. In the past cycle of this grant we demonstrated the utility of high resolution spectral domain optical coherence tomography (SD-OCT) and magnetic resonance imaging (3T MRI) in estimating disease burden in different CNS compartments. We showed that retinal degeneration occurs throughout the disease course and mirrors grey matter compartment atrophy in the cerebrum. A critical finding validating the clinical utility of this approach was that in a multicenter analysis of pooled data, a single OCT at baseline predicted risk of disability progression at 5 years of follow up. As MS is thought to have a strong genetic component, we sought to investigate whether there was an underlying genetic predisposition towards progression, which was made possible by the ability to utilize OCT in a real-time fashion to monitor degeneration and correlate with clinical outcome. We thus expanded the imaging study to include a genetic component in which we conducted a gene array to evaluate genetic variation among people with heterogeneous courses of MS and have preliminarily found that several gene variants in network pathways appear to be associated with more rapid rates of retinal neurodegeneration. The large data set that will be generated from these studies will also allow a corollary analysis in which we can begin to develop a risk profile model in which other population characteristics known to be associated with disease such as sex and ethnicity can be incorporated. The central hypotheses of the proposed studies are; that retinal ganglion layer thickness, thalamic and GM volumes predict 10 year disability across MS subtypes, that patients with high genetic load for gene variants in specific network pathways undergo faster neurodegeneration, and that combinations of OCT, MRI and genetic load measures may be used to develop clinically meaningful individual predictive scores for precision medicine. Aim 1: To determine whether baseline retinal ganglion layer thickness and thalamic and GM volumes predict 10 year disease outcomes. Aim 2: To determine whether genetic variation, sex and ethnicity influence rates of GCIP, thalamic, GM atrophy, and disability accumulation. Aim 3: To develop an algorithm disease progression model to predict disease outcome.

项目摘要 多发性硬化症患者（MS）面临的重大挑战之一是确定 他们的个人进展可能性，因为这些信息将极大地影响治疗的类型 选定。因此，开发特定的工具来监视和预测进展对于更好地管理患者至关重要 护理和了解疾病的机制。我们一直在开发一种多方面的方法 容易（通过成像）监测（通过成像和遗传分析）疾病进展 实时时尚。在这笔赠款的过去周期中，我们证明了高分辨率光谱的实用性 估计域光学相干断层扫描（SD-OCT）和磁共振成像（3T MRI） 不同中枢神经系统室中的疾病负担。我们表明，视网膜变性发生在整个过程中 疾病课程和反映大脑中的灰质室萎缩。验证验证的关键发现 这种方法的临床实用性是在对汇总数据的多中心分析中，基线时单个OCT 预测在5年随访时残疾进展的风险。由于MS被认为具有强大的遗传 组件，我们试图研究是否存在潜在的遗传易感性 进步，这是通过实时方式使用OCT监视的能力而成为可能的 变性并与临床结果相关。因此，我们扩展了成像研究以包括遗传 我们进行了一个基因阵列以评估患有遗传变异的成分 MS的异构课程，并初步发现网络途径中的几种基因变体 似乎与视网膜神经变性的更快速率有关。将是大的数据集 这些研究产生的还将允许推论分析，我们可以开始开发风险概况 模型的其他人口特征与性别和种族等疾病有关 可以合并。拟议研究的中心假设是：视网膜神经节层的厚度， 丘脑和GM体积预测MS亚型的10年残疾，遗传负荷的患者 对于特定网络途径中的基因变异，会经历更快的神经变性，并结合 OCT，MRI和遗传负荷度量可用于发展临床上有意义的个人预测评分 用于精确医学。 目标1：确定基线视网膜神经节层的厚度以及丘脑和GM体积是否预测 10年的疾病结局。 目标2：确定遗传变异，性别和种族是否影响GCIP，丘脑，GM的率 萎缩和残疾积累。 目标3：开发算法疾病进展模型以预测疾病结果。