An open science collection of data from persons at risk of developing Alzheimer’s Disease (AD) will help researchers study the pre-symptomatic phase of the disease and accelerate the develop of new therapies that could slow down the disease process.
The project, called PREVENT-AD, stands for Pre-symptomatic Evaluation of Experimental or Novel Treatments for AD, and was performed at The Centre for Studies on Prevention of Alzheimer’s Disease at the Douglas Mental Health University Institute in Montreal. Between 2011 and 2017 the centre followed 425 people at high risk of AD, collecting a wealth of medical information, including 1,704 MRI scanning sessions, 532 cerebrospinal fluid samples and 1,882 cognitive follow ups.
Using this data, researchers were able to develop mathematical models that track and predict AD pathology. One of these models has been used in the main to test the ability of drugs to slow the progression of AD .
PREVENT-AD is part of the Canadian Open Neuroscience Platform (CONP), a partnership of universities across Canada that will store, analyze, and disseminate research data among its members. As part of CONP’s open science mandate, PREVENT-AD data from consenting participants has been released to the entire scientific community to accelerate the pace of breakthroughs in knowledge of AD pathogenesis and possible target for treatment. The data released meets the principles of data management known as FAIR: findable, accessible, interoperable, and reusable.
“Preparing a dataset this large in a way that made open data sharing possible was a very challenging undertaking,” says Alan Evans, CONP’s scientific director. “Every step required a lot of care and attention, from assuring data quality to considering the ethical aspects of open science. Now researchers around the world can push their knowledge of pre-symptomatic AD to the next level using the PREVENT-AD dataset.”
PREVENT-AD research group was created under the leadership of Dr. John Breitner and is now directed by Judes Poirier and co-directed by Sylvia Villeneuve, with collaborators from 㽶Ƶ and from Université de Montréal and other leading institutions in the US and Europe.
“Proper mining of this dataset is bound to lead to exciting new discoveries and, more importantly, reassessment of old dogmas that failed to deliver therapeutic insights for the prevention of Alzheimer’s disease” says Poirier.