Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimer's disease. The Alzheimer's disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state-of-The-art in predicting cognitive outcomes in Alzheimer's disease based on high dimensional, publicly available genetic and structural imaging data. This meta-analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.
|Number of pages||9|
|Journal||Alzheimer's and Dementia|
|State||Published - Jun 1 2016|
Bibliographical noteFunding Information:
This study was supported by the following individuals and organizations: Alan Evans (McGill University), Gaurav Pandey (MSSM), Gil Rabinovici (UCSF), Kaj Blennow (Göteborg University), Kristine Yaffe (UCSF), Maria Isaac (EMA), Nolan Nichols (University of Washington), Paul Thompson (UCLA), Reisa Sperling (Harvard), Scott Small (Columbia), Guy Eakin (BrightFocus Foundation), Maria Carillo (Alzheimer's Association), Neil Buckholz (NIA), Alzheimer's Research UK, European Medicines Agency, Global CEO Initiative on Alzheimer's Disease, Pfizer, Inc, Ray and Dagmar Dolby Family Fund, Rosenberg Alzheimer's Project, Sanofi S.A, and Takeda Pharmaceutical Company Ltd, USAgainstAlzheimer's.
© 2016 The Authors.
- Azheimer's disease
- Big data
- Cognitive decline
ASJC Scopus subject areas
- Clinical Neurology
- Geriatrics and Gerontology
- Psychiatry and Mental health
- Cellular and Molecular Neuroscience
- Health Policy
- Developmental Neuroscience