4.1 Article

Evaluation of Plasma Proteomic Data for Alzheimer Disease State Classification and for the Prediction of Progression From Mild Cognitive Impairment to Alzheimer Disease

Journal

ALZHEIMER DISEASE & ASSOCIATED DISORDERS
Volume 27, Issue 3, Pages 233-243

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/WAD.0b013e31826d597a

Keywords

Alzheimer; mild cognitive impairment; ADNI; Rules-Based Medicine; machine learning; biomarker; random forest; proteomic

Funding

  1. Abbott
  2. National Institutes of Health
  3. AstraZeneca AB
  4. Bayer Schering Pharma AG
  5. Bristol-Myers Squibb
  6. Eisai Global Clinical Development
  7. Elan Corporation
  8. Genentech
  9. GE Healthcare
  10. GlaxoSmithKline
  11. Innogenetics
  12. Johnson Johnson
  13. Eli Lilly and Co.
  14. Merck and Co. Inc.
  15. Novartis AG
  16. Pfizer Inc.
  17. F. Hoffmann-La Roche
  18. Schering-Plough
  19. Synarc Inc.
  20. Wyeth
  21. Abbott Laboratories

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Previous studies that have examined the potential for plasma markers to serve as biomarkers for Alzheimer disease (AD) have studied single analytes and focused on the amyloid- and isoforms and have failed to yield conclusive results. In this study, we performed a multivariate analysis of 146 plasma analytes (the Human DiscoveryMAP v 1.0 from Rules-Based Medicine) in 527 subjects with AD, mild cognitive impairment (MCI), or cognitively normal elderly subjects from the Alzheimer's Disease Neuroimaging Initiative database. We identified 4 different proteomic signatures, each using 5 to 14 analytes, that differentiate AD from control patients with sensitivity and specificity ranging from 74% to 85%. Five analytes were common to all 4 signatures: apolipoprotein A-II, apolipoprotein E, serum glutamic oxaloacetic transaminase, -1-microglobulin, and brain natriuretic peptide. None of the signatures adequately predicted progression from MCI to AD over a 12- and 24-month period. A new panel of analytes, optimized to predict MCI to AD conversion, was able to provide 55% to 60% predictive accuracy. These data suggest that a simple panel of plasma analytes may provide an adjunctive tool to differentiate AD from controls, may provide mechanistic insights to the etiology of AD, but cannot adequately predict MCI to AD conversion.

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