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Alzheimers Dement. 2017 Feb;13(2):140-151. doi: 10.1016/j.jalz.2016.08.003. Epub 2016 Sep 28.

Association of blood lipids with Alzheimer's disease: A comprehensive lipidomics analysis.

Author information

1
King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK. Electronic address: petroula.proitsi@kcl.ac.uk.
2
King's College London, Institute of Pharmaceutical Science, London, UK.
3
King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK; NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation Trust, London UK.
4
King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK.
5
QIMR Berghofer Medical Research Institute, Brisbane, Australia.
6
Department of Neurology, Kuopio University Hospital and University of Eastern Finland, Kuopio, Finland.
7
Department of Old Age Psychiatry & Psychotic Disorders, Medical University of Lodz, Lodz, Poland.
8
Section of Gerontology and Geriatrics, Department of Medicine, University of Perugia, Perugia, Italy.
9
Memory and Dementia Centre, Aristotle University of Thessaloniki, Thessaloniki, Greece.
10
Department of Internal and Geriatrics Medicine, INSERM U 1027, Gerontopole, Hôpitaux de Toulouse, Toulouse, France.
11
Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK.
12
King's College London, Institute of Psychiatry, Psychology & Neuroscience, London, UK; NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation Trust, London UK; The Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, UCL, UK.

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.

KEYWORDS:

Alzheimer's disease; Biomarkers; Brain atrophy; Classification; Dementia; Lipidomics; Machine learning; Metabolomics; Multivariate; Random forest; Rate of cognitive decline; sMRI

PMID:
27693183
DOI:
10.1016/j.jalz.2016.08.003
[Indexed for MEDLINE]
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