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Front. Neuroinform. | doi: 10.3389/fninf.2018.00085

National Neuroinformatics Framework for Canadian Consortium on Neurodegeneration in Aging (CCNA)

 Zia Mohaddes1, 2*,  Samir Das1, 2, Rida Abou-Haidar1, 2, Mouna Safiharab1, 2, David Blader1, 2, Jessica Callegaro1, 2,  Charlie Henri-Bellemare1, 2,  Jingla-Fri Tunteng1, 2,  Leigh Evans1, 2,  Tara Campbell1, 2, Derek Lo1, 2,  pierre-emmanuel Morin3,  Victor Whitehead4,  Howard Chertkow4, 5 and  Alan C. Evans1, 2
  • 1McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Canada
  • 2Montreal Neurological Institute, Mcgill University, Canada
  • 3Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM), Canada
  • 4Lady Davis Institute (LDI), Canada
  • 5Department of Neurology and Neurosurgery, McGill University, Canada

The Canadian Institutes for Health Research (CIHR) launched the “International Collaborative Research Strategy for Alzheimer’s Disease” as a signature initiative, focusing on Alzheimer’s Disease (AD) and related neurodegenerative disorders (NDDs). The Canadian Consortium for Neurodegeneration and Aging (CCNA) was subsequently established to coordinate and strengthen Canadian research on AD and NDDs. To facilitate this research, CCNA uses LORIS, a modular data management system that integrates acquisition, storage, curation, and dissemination across multiple modalities. Through an unprecedented national collaboration studying various groups of dementia-related diagnoses, CCNA aims to investigate and develop proactive treatment strategies to improve disease prognosis and quality of life of those affected. However, this constitutes a unique technical undertaking, as heterogeneous data collected from sites across Canada must be uniformly organized, stored, and processed in a consistent manner. Currently clinical, neuropsychological, imaging, genomic, and biospecimen data for 509 CCNA subjects have been uploaded to LORIS. In addition, data validation is handled through a number of quality control (QC) measures such as double data entry (DDE), conflict flagging and resolution, imaging protocol checks, and visual imaging quality validation. Site coordinators are also notified of incidental findings found in MRI reads or biosample analyses. Data is then disseminated to CCNA researchers via a web-based Data-Querying Tool (DQT). This paper will detail the wide array of capabilities handled by LORIS for CCNA, aiming to provide the necessary neuroinformatic infrastructure for this nation-wide investigation of healthy and diseased aging.

Keywords: database, Neuroimaging, infrastructure, Dementia, Alzeimer’s disease

Received: 21 Aug 2018; Accepted: 31 Oct 2018.

Edited by:

Sook-Lei Liew, University of Southern California, United States

Reviewed by:

Andrei Irimia, University of Southern California, United States
David N. Kennedy, University of Massachusetts Medical School, United States  

Copyright: © 2018 Mohaddes, Das, Abou-Haidar, Safiharab, Blader, Callegaro, Henri-Bellemare, Tunteng, Evans, Campbell, Lo, Morin, Whitehead, Chertkow and Evans. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Mr. Zia Mohaddes, McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, Montreal, Canada,