A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer’s disease

Nicholas J. Ashton, Alejo J. Nevado-Holgado, Imelda S. Barber, Steven Lynham, Veer Gupta, Pratishtha Chatterjee, Kathryn Goozee, Eugene Hone, Steve Pedrini, Kaj Blennow, Michael Schöll, Henrik Zetterberg, Kathryn A. Ellis, Ashley I. Bush, Christopher C. Rowe, Victor L. Villemagne, David Ames, Colin L. Masters, Dag Aarsland, John Powell & 3 others Simon Lovestone, Ralph Martins, Abdul Hye*

*Corresponding author for this work

Research output: Contribution to journalArticle

11 Citations (Scopus)
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Abstract

A blood-based assessment of preclinical disease would have huge potential in the enrichment of participants for Alzheimer’s disease (AD) therapeutic trials. In this study, cognitively unimpaired individuals from the AIBL and KARVIAH cohorts were defined as Aβ negative or Aβ positive by positron emission tomography. Nontargeted proteomic analysis that incorporated peptide fractionation and high-resolution mass spectrometry quantified relative protein abundances in plasma samples from all participants. A protein classifier model was trained to predict Aβ-positive participants using feature selection and machine learning in AIBL and independently assessed in KARVIAH. A 12-feature model for predicting Aβ-positive participants was established and demonstrated high accuracy (testing area under the receiver operator characteristic curve = 0.891, sensitivity = 0.78, and specificity = 0.77). This extensive plasma proteomic study has unbiasedly highlighted putative and novel candidates for AD pathology that should be further validated with automated methodologies.

Original languageEnglish
Article numbereaau7220
Pages (from-to)1-12
Number of pages12
JournalScience Advances
Volume5
Issue number2
DOIs
Publication statusPublished - 6 Feb 2019

Bibliographical note

Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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    Ashton, N. J., Nevado-Holgado, A. J., Barber, I. S., Lynham, S., Gupta, V., Chatterjee, P., ... Hye, A. (2019). A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer’s disease. Science Advances, 5(2), 1-12. [eaau7220]. https://doi.org/10.1126/sciadv.aau7220