Open science datasets from PREVENT-AD, a longitudinal cohort of pre-symptomatic Alzheimer’s disease
Jennifer Tremblay‐Mercier, Cécile Madjar, Samir Das, Alexa Pichet Binette, Stephanie O. M. Dyke, Pierre Étienne, Marie‐Élyse Lafaille‐Magnan, Jordana Remz, Pierre Bellec, D. Louis Collins, M. Natasha Rajah, Véronique D. Bohbot, Jeannie‐Marie Leoutsakos, Yasser Iturria‐Medina, Justin Kat, Richard D. Hoge, Serge Gauthier, Christine Tardif, M. Mallar Chakravarty, Jean‐Baptiste Poline, Pedro Rosa‐Neto, Alan C. Evans, Sylvia Villeneuve, Judes Poirier, John C.S. Breitner
Abstract
To move Alzheimer Disease (AD) research forward it is essential to collect data from large cohorts, but also make such data available to the global research community. We describe the creation of an open science dataset from the PREVENT-AD (PResymptomatic EValuation of Experimental or Novel Treatments for AD) cohort, composed of cognitively unimpaired older individuals with a parental or multiple-sibling history of AD. From 2011 to 2017, 386 participants were enrolled (mean age 63 years old ± 5) for sustained investigation among whom 349 have retrospectively agreed to share their data openly. Repositories are findable through the unified interface of the Canadian Open Neuroscience Platform and contain up to five years of longitudinal imaging data, cerebral fluid biochemistry, neurosensory capacities, cognitive, genetic, and medical information. Imaging data can be accessed openly at https://openpreventad.loris.ca while most of the other information, sensitive by nature, is accessible by qualified researchers at https://registeredpreventad.loris.ca. In addition to being a living resource for continued data acquisition, PREVENT-AD offers opportunities to facilitate understanding of AD pathogenesis.