Deep and Frequent Phenotyping; combinatorial biomarkers for dementia experimental medicine

在多年的失败之后，阿尔茨海默病(AD)疾病改良方面取得进展的第一批令人振奋的迹象正在出现。阿尔茨海默病(AD)可以说是一种相对于发达国家的患病率和成本而言需求最大的未得到满足的疾病。不过，很明显，这对药物开发是有借鉴意义的。首先，生物标记物是必不可少的--只有随着它们的使用，20-30%的试验参与者才变得明显没有靶向病理。其次，这种疗效最有可能出现在疾病的早期阶段，包括前驱症状阶段。第三，也是最重要的一点是，使用目前可用的方法，疾病修改的概念验证阶段明显不足。在前驱疾病中进行短期、中等规模的概念验证是困难的，如果不是不可能的，而结果测量仍然是长期的和临床的。深度和频繁的表型研究旨在通过为先兆AD的概念验证生成一个生物标记物集来纠正这一点。目标是在以往研究的基础上，在年度评估中主要集中于已建立的生物标志物，并使用一年多来频繁应用的已建立的、正在开发的和新的生物标志物模式进行非常深入的表型鉴定。一项初步研究表明，可以在多个地点有效地建立这种复杂的方案，试验参与者充分致力于这种毁灭性疾病的研究，尽管研究要求繁重，但他们仍然参与其中。具体地说，我们的目标是实现淀粉样蛋白和tau蛋白的PET成像和脑脊液生物化学，功能和结构磁共振，突触功能的电生理学，包括EEG和MEG，步态测量和用于一系列表型的生态有效性评估的远程监测，视网膜病理测量和在分子生物标记物潜在用途方面无与伦比的生物样本收集，并建立用于体外研究的干细胞。有些措施，如PET将在基线和随访时进行，另一些措施最长每2个月进行一次，有些措施，如外周设备，将持续进行。这项研究建立在Dementias平台英国的基础上；我们将使用信息工作流从组成队列中招募人才，将利用成像工作流，并将通过CELS工作流将材料存入银行。此外，该方案将嵌套在IMI-欧洲预防阿尔茨海默病联合登记、队列和适应性试验方案(www.ep-ad.org)内，这是迅速发展的全球阿尔茨海默病平台预防阿尔茨海默病倡议中规模最大、也是最主要的倡议。这些国际公私合作伙伴关系已承诺超过1亿GB用于相关的概念验证阶段试验倡议；该倡议依赖于识别生物标记物来加快试验进程。这项建议旨在为此类标记提供数据。通过ADNI及其合作伙伴的研究，我们将向科学界提供非常广泛的汇总数据，并努力使人们能够访问海量的基础原始数据。在小组内部，我们将使用建模和机器学习方法来分析这些数据，以寻找前驱AD变化的标记物，结合跟踪或改进高级认知测量和病理PET测量的标记物的不同形式。在疾病的这个阶段，生物标记物的结果将是决定性的；如果这样的标记物是可以实现的，那么这项研究将确定它们。可交付成果既是科学界进行广泛进一步分析的数据，也是用于第二阶段概念验证试验的组合生物标记物。这样的标记将加快决策速度，减少临床试验的费用，增加在这个阶段测试的化合物的数量。缺乏这样的标记物是在寻找AD的疾病改良或二级预防治疗方面取得进展的最严重的单一障碍之一。

After years of failure the first promising signs of progress in disease modification of Alzheimer's disease (AD), arguably the disorder with the greatest unmet need relative to prevalence and cost in the developed world, are emerging. Already though it is clear that there are lessons for drug development. First, that biomarkers are essential - it is only with their use that it became apparent that 20-30% of trial participants do not have the targeted pathology. Second, that efficacy is most likely in early phases of disease including prodromal stage. Third, and most important, that the proof of concept phase for disease modification is significantly deficient using currently available approaches. It is hard, if not impossible, to conduct short term, modest-size proof of concept in prodromal disease whilst outcome measures remain long term and clinical. The Deep and Frequent Phenotyping study is designed to rectify this by generating a biomarker set for proof of concept in prodromal AD. The objective is to build on previous studies, focussing largely on established biomarkers in annual assessment, with very deep phenotyping using established, developing and novel biomarker modalities applied frequently over a year. A pilot study demonstrated that such complex protocols can be effectively established across multiple sites and that trials participants are sufficiently committed to research for this devastating disease that they remain engaged despite taxing study demands. Specifically, we aim to implement PET imaging and CSF biochemistry for amyloid and tau, functional and structural MRI, electrophysiology for synaptic function including EEG and MEG, measures of gait and use of remote monitoring for ecologically valid assessment of a range of phenotypes, measures of retinal pathology and a collection of bio-samples unparalleled in potential utility for molecular biomarkers and to establish stem cells for in vitro studies. Some measures such as PET will be applied at baseline and follow up, others up to every 2 months and some, such as the peripheral devices, continuously. The study builds upon the Dementias Platform UK; we will recruit from constituent cohorts using the information workstream, will utilise the imaging workstream and will bank materials through the cells workstream. Furthermore, the programme will be nested within the IMI-European Prevention of AD combined registry, cohort and adaptive trial programme (www.ep-ad.org), the largest and the leading initiative within the rapidly growing Global Alzheimer's Platform Prevention of Alzheimer's Disease (GAP-PAD) initiative. These international public-private partnerships have committed over £100m to a linked proof of concept phase trials initiative; an initiative dependent on identifying biomarkers to speed the trials process. This proposal is designed to provide the data for such markers. Taking the lead from ADNI and its partner studies, we will make summary data very widely available to the scientific community and work to enable access to the immense volumes of underlying primary data. Within group we will use modelling and machine learning approaches to analyse these data for markers of change in prodromal AD, combining different modalities for markers that track or improve upon advanced measures of cognition and PET measures of pathology. The outcome will be definitive for biomarkers in this phase of disease; if such markers are achievable then this study will identify them. The deliverable will be both the data to the scientific community for wide further analysis as well as a combinatorial biomarker for use in phase II, proof of concept trials. Such a marker would speed decision making, reduce expense of clinical trials, increase the number of compounds tested at this phase. The absence of such a marker is one of the most grievous single obstacles to progress in the search for a disease modification or secondary prevention therapy for AD.