Ashton, NJ;
Nevado-Holgado, AJ;
Barber, IS;
Lynham, S;
Gupta, V;
Chatterjee, P;
Goozee, K;
... Hye, A; + view all
(2019)
A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease.
Science Advances
, 5
(2)
, Article eaau7220. 10.1126/sciadv.aau7220.
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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.
Type: | Article |
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Title: | A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease |
Location: | United States |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1126/sciadv.aau7220 |
Publisher version: | https://doi.org/10.1126/sciadv.aau7220 |
Language: | English |
Additional information: | The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S.Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10069022 |
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