[2] Researchers at 63 sites in the US and Canada track the progression of AD in the human brain with neuroimaging, biochemical, and genetic biological markers.
ADNI has made a global impact,[4] firstly by developing a set of standardized protocols to allow the comparison of results from multiple centers,[4] and secondly by its data-sharing policy which makes available all at the data without embargo to qualified researchers worldwide.
[7] The idea of a collaboration between public institutions and private pharmaceutical companies to fund a large biomarker project to study AD and to speed up progress toward effective treatments for the disease was conceived at the beginning of the millennium by Neil S. Buckholz at the National Institute on Aging (NIA) and Dr. William Potter, at Eli Lilly and Company.
After obtaining informed consent, participants undergo a series of initial tests that are repeated at intervals over subsequent years (Table 2):[2] Table 2 One defining characteristic of ADNI is the commitment by all participating research groups to share ownership of the data prior to the completion of the research and by collaborators to forgo any patent opportunities.
[4] These include methods for the acquisition and quality control of both MRI and PET scans on scanners differing in the vendor, software platform, and field strength, and also for the analysis of CSF biomarkers.
An initial goal of ADNI was to understand the development of AD pathology by tracking imaging and CSF biomarkers throughout disease progression[1] according to the amyloid hypothesis.
[9] The most successful to date have used deep learning approaches that combine longitudinal data chronicling changes in biomarkers over time from more than one imaging, genetic, or biological modality.
[40] Because AD pathology develops many years before outward signs of the disease such as memory loss, preventive therapies are targeted to cognitively normal people.
Subject selection ADNI studies have shown that people who are β-amyloid positive or have a small hippocampal volume, or carry an APOE ε4 allele are at a higher risk for AD.
Moreover, use of the selection strategy can reduce the number of participants required to detect a treatment effect over feasible trial (for example 3 years).