Deep and Frequent Phenotyping; combinatorial biomarkers for dementia experimental medicine

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.