Proitsi, P;
Kim, M;
Whiley, L;
Simmons, A;
Sattlecker, M;
Velayudhan, L;
Lupton, MK;
... Legido-Quigley, C; + view all
(2017)
Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis.
Alzheimer's & Dementia
, 13
(2)
pp. 140-151.
10.1016/j.jalz.2016.08.003.
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Abstract
INTRODUCTION The aim of this study was to (1) replicate previous associations between six blood lipids and Alzheimer's disease (AD) (Proitsi et al 2015) and (2) identify novel associations between lipids, clinical AD diagnosis, disease progression and brain atrophy (left/right hippocampus/entorhinal cortex). METHODS We performed untargeted lipidomic analysis on 148 AD and 152 elderly control plasma samples and used univariate and multivariate analysis methods. RESULTS We replicated our previous lipids associations and reported novel associations between lipids molecules and all phenotypes. A combination of 24 molecules classified AD patients with >70% accuracy in a test and a validation data set, and we identified lipid signatures that predicted disease progression (R2 = 0.10, test data set) and brain atrophy (R2 ≥ 0.14, all test data sets except left entorhinal cortex). We putatively identified a number of metabolic features including cholesteryl esters/triglycerides and phosphatidylcholines. DISCUSSION Blood lipids are promising AD biomarkers that may lead to new treatment strategies.
| Type: | Article |
|---|---|
| Title: | Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jalz.2016.08.003 |
| Publisher version: | http://dx.doi.org/10.1016/j.jalz.2016.08.003 |
| Language: | English |
| Additional information: | © 2016 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer’s Association. Thisis an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Keywords: | Alzheimer's disease, Dementia, Brain atrophy, sMRI, Rate of cognitive decline, Lipidomics, Metabolomics, Biomarkers, Machine learning, Multivariate, Classification, Random forest, CEREBROSPINAL-FLUID, ER MEMBRANES, PLASMA, RISK, BIOMARKERS, DISCOVERY, IDENTIFICATION, DYSLIPIDEMIA, EPIDEMIOLOGY, TECHNOLOGY |
| 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 Population Health Sciences > Institute of Health Informatics UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics > Clinical Epidemiology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1521591 |
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