Translating MEG-based biomarkers to EEG-based outcome measures for Autism Spectrum Disorders

将基于 MEG 的生物标志物转化为基于 EEG 的自闭症谱系障碍结果测量

• 批准号: 9762202
• 负责人: Tal Kenet
• 金额: $ 21.06万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-13 至 2020-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9762202
• 关键词: Address; Aftercare; Age; Area; Auditory; Base of the Brain; Biological Markers; Brain; Clinic; Clinical; Clinical Trials; Complex; Complex Analysis; Coupling; Data; Data Analyses; Data Collection; Development; Diagnosis; Double-blind trial; Drug Targeting; Electroencephalography; Ensure; Equipment; Future; Goals; Heterogeneity; Human; Individual; Intervention; Intervention Trial; Location; Magnetoencephalography; Maps; Measures; Methods; Nature; Noise; Outcome; Outcome Measure; Participant; Pharmacology; Phase; Placebo Effect; Population; Process; Public Health; Publishing; Radial; Research; Rest; Risk; Sensory; Severities; Signal Transduction; Site; Source; Standardization; System; Tactile; Testing; Translating; Translations; Validation; Work; age group; autism spectrum disorder; autistic children; base; behavior measurement; density; design; drug testing; laboratory equipment; neuromechanism; neurophysiology; novel; novel strategies; portability; response; sensor; source localization; success; theories; therapy development; tool; treatment trial; user-friendly; vibrotactile stimulation

ABSTRACT / SUMMARY There is currently a clear need for objective brain based outcome measures for autism spectrum disorders (ASD). Outcome measures are measures that are used before a clinical or intervention trial begins, to get a baseline measure, and are then repeated at the end of the trial, to determine whether changes have occurred as a result of the intervention. Currently, the vast majority of outcome measures used in ASD treatment trials are based on behavioral measures, usually parental, and are therefore subjective by nature. Even in double blind trials, there is still risk of contamination of the measures from a placebo effect. Therefore, there is a clear need for objective outcome measures in the field. One such class of potential outcome measures is brain-based. Since the most oft-found clinical lab equipment is a simple 10-20 EEG system, the ideal brain-based outcome measures for ASD would use such a system. However, the vast majority of known biomarkers for ASD, that would in theory have outcome measure potential, are derived using equipment that is far too complex and expensive to replicate in clinical settings, and using paradigms that require a setup and analyses methods that are too complex to carry out clinically on a large number of subjects with high inter-subject variability. Here, we propose a novel approach to this problem. We propose to translate three biomarkers for ASD identified in our lab or by other groups using magnetoencephalography (MEG), to clinical EEG. The study will focus on MEG-based biomarkers already known to be associated with ASD diagnosis and severity, one in the auditory domain, one in the tactile domain, and one using a relatively novel analysis of resting state data. The translation to clinical EEG would be judiciously carried out, by combining MEG and EEG data collection, and then using a data driven approach to validate the results. We will also develop a user-friendly toolbox as part of the process, to standardize data analysis and make the process easily portable and uniform across multiple sites. The initial development will be carried out using 10 typically developing participants, and 10 ASD participants, using high density simultaneous EEG/MEG data collection. The results will then be validated using 15 new participants per group, and simultaneous “clinical EEG” (i.e. minimal sensor locations) and high-density MEG data collection. This proof of concept proposal will take place entirely onsite, and will form the basis for future offsite studies across multiple clinical settings, ideally in conjunction with ongoing clinical trials.

摘要/摘要 目前显然需要对自闭症患者进行客观的基于大脑的结果测量。 谱系障碍(ASD)。结果测量是在临床或治疗前使用的测量 干预试验开始，以获得基线测量，然后在试验结束时重复， 以确定是否由于干预而发生了变化。目前，广大的 ASD治疗试验中使用的大多数结果测量是基于行为测量的， 通常是父母的，因此本质上是主观的。即使在双盲试验中，仍有 安慰剂效应导致措施受到污染的风险。因此，显然有必要 在现场进行客观结果测量。其中一类潜在的结果衡量标准是 以大脑为基础的。由于最常见的临床实验室设备是简单的10-20脑电系统， ASD理想的基于大脑的结果测量将使用这样的系统。然而，广大的 大多数已知的ASD生物标记物，从理论上讲都有结果测量潜力， 使用的设备过于复杂和昂贵，无法在临床上复制 设置，使用需要设置的范例，以及分析过于复杂的方法 对大量具有较高研究对象间变异性的受试者进行临床研究。 在这里，我们提出了一个新的方法来解决这个问题。我们建议翻译三个 我们实验室或其他小组使用脑磁图鉴定ASD的生物标记物 (MEG)，到临床脑电。这项研究将集中在已知的基于脑磁图的生物标记物 与ASD的诊断和严重程度相关，一个在听觉领域，一个在触觉领域 一种是使用相对新颖的静息状态数据分析。向临床的转化 脑电将明智地进行，通过结合脑磁图和脑电数据收集，然后 使用数据驱动的方法来验证结果。我们还将开发一个用户友好的工具箱 作为该过程的一部分，以标准化数据分析并使该过程易于移植和 跨多个站点统一。 初步开发将使用10个典型的开发参与者进行，以及 10名ASD参与者，使用高密度同步脑电/脑磁图数据采集。结果将会是 然后使用每组15名新参与者以及同时进行的“临床脑电”(即 传感器位置最少)和高密度脑磁图数据收集。此概念验证提案 将完全在现场进行，并将形成未来跨多个地点的非现场研究的基础 临床环境，最好与正在进行的临床试验相结合。