Journal
ALZHEIMERS & DEMENTIA
Volume 12, Issue 7, Pages 815-822Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jalz.2015.12.008
Keywords
Preclinical Alzheimer's disease; Biomarker; Metabolomics; Phospholipids; Machine learning
Categories
Funding
- Intramural Research Program, National Institute on Aging, National Institutes of Health
- National Institutes of Health [N01-AG-12100]
- National Institute on Aging Intramural Research Program, Hjartavernd (the Icelandic Heart Association)
- Althingi (the Icelandic Parliament)
Ask authors/readers for more resources
Introduction: Recently, quantitative metabolomics identified a panel of 10 plasma lipids that were highly predictive of conversion to Alzheimer's disease (AD) in cognitively normal older individuals (n = 28, area under the curve [AUC] = 0.92, sensitivity/specificity of 90%/90%). Methods: Quantitative targeted metabolomics in serum using an identical method as in the index study. Results: We failed to replicate these findings in a substantially larger study from two independent cohorts-the Baltimore Longitudinal Study of Aging ([BLSA], n = 93, AUC = 0.642, sensitivity/specificity of 51.6%/65.7%) and the Age, Gene/Environment Susceptibility-Reykjavik Study ([AGES-RS], n = 100, AUC = 0.395, sensitivity/specificity of 47.0%/36.0%). In analyses applying machine learning methods to all 187 metabolite concentrations assayed, we find a modest signal in the BLSA with distinct metabolites associated with the preclinical and symptomatic stages of AD, whereas the same methods gave poor classification accuracies in the AGES-RS samples. Discussion: We believe that ours is the largest blood biomarker study of preclinical AD to date. These findings underscore the importance of large-scale independent validation of index findings from biomarker studies with relatively small sample sizes. Published by Elsevier Inc. on behalf of the Alzheimer's Association.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available