Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease

P Proitsi; M Kim; L Whiley; M Pritchard; R Leung; H Soininen; I Kloszewska; P Mecocci; M Tsolaki; B Vellas; P Sham; S Lovestone; J F Powell; R J B Dobson; C Legido-Quigley

doi:10.1038/tp.2014.127

Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease

P Proitsi, M Kim, L Whiley, M Pritchard, R Leung, H Soininen, I Kloszewska, P Mecocci, M Tsolaki, B Vellas, P Sham, S Lovestone, J F Powell, R J B Dobson, C Legido-Quigley

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Abstract

There is an urgent need for the identification of Alzheimer’s disease (AD) biomarkers. Studies have now suggested the promising use of associations with blood metabolites as functional intermediate phenotypes in biomedical and pharmaceutical research. The aim of this study was to use lipidomics to identify a battery of plasma metabolite molecules that could predict AD patients from controls. We performed a comprehensive untargeted lipidomic analysis, using ultra-performance liquid chromatography/mass spectrometry on plasma samples from 35 AD patients, 40 elderly controls and 48 individuals with mild cognitive impairment (MCI) and used multivariate analysis methods to identify metabolites associated with AD status. A combination of 10 metabolites could discriminate AD patients from controls with 79.2% accuracy (81.8% sensitivity, 76.9% specificity and an area under curve of 0.792) in a novel test set. Six of the metabolites were identified as long chain cholesteryl esters (ChEs) and were reduced in AD (ChE 32:0, odds ratio (OR)=0.237, 95% confidence interval (CI)=0.10–0.48, P=4.19E−04; ChE 34:0, OR=0.152, 95% CI=0.05–0.37, P=2.90E−04; ChE 34:6, OR=0.126, 95% CI=0.03–0.35, P=5.40E−04; ChE 32:4, OR=0.056, 95% CI=0.01–0.24, P=6.56E−04 and ChE 33:6, OR=0.205, 95% CI=0.06–0.50, P=2.21E−03, per (log2) metabolite unit). The levels of these metabolites followed the trend control>MCI>AD. We, additionally, found no association between cholesterol, the precursor of ChE and AD. This study identified new ChE molecules, involved in cholesterol metabolism, implicated in AD, which may help identify new therapeutic targets; although, these findings need to be replicated in larger well-phenotyped cohorts.

Original language	English
Article number	e494
Number of pages	8
Journal	Translational psychiatry
Volume	5
Early online date	13 Jan 2015
DOIs	https://doi.org/10.1038/tp.2014.127
Publication status	Published - 13 Jan 2015

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Plasma lipidomics analysis finds_PROITSI_Published13January2015_GOLD VoR (CC BY)Final published version, 624 KBLicence: CC BY

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Proitsi, P., Kim, M., Whiley, L., Pritchard, M., Leung, R., Soininen, H., Kloszewska, I., Mecocci, P., Tsolaki, M., Vellas, B., Sham, P., Lovestone, S., Powell, J. F., Dobson, R. J. B., & Legido-Quigley, C. (2015). Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease. Translational psychiatry, 5, Article e494. https://doi.org/10.1038/tp.2014.127

@article{a99a57a0e9ed437db6b17a33c007f811,

title = "Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease",

abstract = "There is an urgent need for the identification of Alzheimer{\textquoteright}s disease (AD) biomarkers. Studies have now suggested the promising use of associations with blood metabolites as functional intermediate phenotypes in biomedical and pharmaceutical research. The aim of this study was to use lipidomics to identify a battery of plasma metabolite molecules that could predict AD patients from controls. We performed a comprehensive untargeted lipidomic analysis, using ultra-performance liquid chromatography/mass spectrometry on plasma samples from 35 AD patients, 40 elderly controls and 48 individuals with mild cognitive impairment (MCI) and used multivariate analysis methods to identify metabolites associated with AD status. A combination of 10 metabolites could discriminate AD patients from controls with 79.2% accuracy (81.8% sensitivity, 76.9% specificity and an area under curve of 0.792) in a novel test set. Six of the metabolites were identified as long chain cholesteryl esters (ChEs) and were reduced in AD (ChE 32:0, odds ratio (OR)=0.237, 95% confidence interval (CI)=0.10–0.48, P=4.19E−04; ChE 34:0, OR=0.152, 95% CI=0.05–0.37, P=2.90E−04; ChE 34:6, OR=0.126, 95% CI=0.03–0.35, P=5.40E−04; ChE 32:4, OR=0.056, 95% CI=0.01–0.24, P=6.56E−04 and ChE 33:6, OR=0.205, 95% CI=0.06–0.50, P=2.21E−03, per (log2) metabolite unit). The levels of these metabolites followed the trend control>MCI>AD. We, additionally, found no association between cholesterol, the precursor of ChE and AD. This study identified new ChE molecules, involved in cholesterol metabolism, implicated in AD, which may help identify new therapeutic targets; although, these findings need to be replicated in larger well-phenotyped cohorts.",

author = "P Proitsi and M Kim and L Whiley and M Pritchard and R Leung and H Soininen and I Kloszewska and P Mecocci and M Tsolaki and B Vellas and P Sham and S Lovestone and Powell, {J F} and Dobson, {R J B} and C Legido-Quigley",

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doi = "10.1038/tp.2014.127",

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Proitsi, P , Kim, M , Whiley, L , Pritchard, M , Leung, R, Soininen, H, Kloszewska, I, Mecocci, P, Tsolaki, M, Vellas, B, Sham, P, Lovestone, S, Powell, JF, Dobson, RJB & Legido-Quigley, C 2015, 'Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease', Translational psychiatry, vol. 5, e494. https://doi.org/10.1038/tp.2014.127

TY - JOUR

T1 - Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease

AU - Proitsi, P

AU - Kim, M

AU - Whiley, L

AU - Pritchard, M

AU - Leung, R

AU - Soininen, H

AU - Kloszewska, I

AU - Mecocci, P

AU - Tsolaki, M

AU - Vellas, B

AU - Sham, P

AU - Lovestone, S

AU - Powell, J F

AU - Dobson, R J B

AU - Legido-Quigley, C

PY - 2015/1/13

Y1 - 2015/1/13

N2 - There is an urgent need for the identification of Alzheimer’s disease (AD) biomarkers. Studies have now suggested the promising use of associations with blood metabolites as functional intermediate phenotypes in biomedical and pharmaceutical research. The aim of this study was to use lipidomics to identify a battery of plasma metabolite molecules that could predict AD patients from controls. We performed a comprehensive untargeted lipidomic analysis, using ultra-performance liquid chromatography/mass spectrometry on plasma samples from 35 AD patients, 40 elderly controls and 48 individuals with mild cognitive impairment (MCI) and used multivariate analysis methods to identify metabolites associated with AD status. A combination of 10 metabolites could discriminate AD patients from controls with 79.2% accuracy (81.8% sensitivity, 76.9% specificity and an area under curve of 0.792) in a novel test set. Six of the metabolites were identified as long chain cholesteryl esters (ChEs) and were reduced in AD (ChE 32:0, odds ratio (OR)=0.237, 95% confidence interval (CI)=0.10–0.48, P=4.19E−04; ChE 34:0, OR=0.152, 95% CI=0.05–0.37, P=2.90E−04; ChE 34:6, OR=0.126, 95% CI=0.03–0.35, P=5.40E−04; ChE 32:4, OR=0.056, 95% CI=0.01–0.24, P=6.56E−04 and ChE 33:6, OR=0.205, 95% CI=0.06–0.50, P=2.21E−03, per (log2) metabolite unit). The levels of these metabolites followed the trend control>MCI>AD. We, additionally, found no association between cholesterol, the precursor of ChE and AD. This study identified new ChE molecules, involved in cholesterol metabolism, implicated in AD, which may help identify new therapeutic targets; although, these findings need to be replicated in larger well-phenotyped cohorts.

AB - There is an urgent need for the identification of Alzheimer’s disease (AD) biomarkers. Studies have now suggested the promising use of associations with blood metabolites as functional intermediate phenotypes in biomedical and pharmaceutical research. The aim of this study was to use lipidomics to identify a battery of plasma metabolite molecules that could predict AD patients from controls. We performed a comprehensive untargeted lipidomic analysis, using ultra-performance liquid chromatography/mass spectrometry on plasma samples from 35 AD patients, 40 elderly controls and 48 individuals with mild cognitive impairment (MCI) and used multivariate analysis methods to identify metabolites associated with AD status. A combination of 10 metabolites could discriminate AD patients from controls with 79.2% accuracy (81.8% sensitivity, 76.9% specificity and an area under curve of 0.792) in a novel test set. Six of the metabolites were identified as long chain cholesteryl esters (ChEs) and were reduced in AD (ChE 32:0, odds ratio (OR)=0.237, 95% confidence interval (CI)=0.10–0.48, P=4.19E−04; ChE 34:0, OR=0.152, 95% CI=0.05–0.37, P=2.90E−04; ChE 34:6, OR=0.126, 95% CI=0.03–0.35, P=5.40E−04; ChE 32:4, OR=0.056, 95% CI=0.01–0.24, P=6.56E−04 and ChE 33:6, OR=0.205, 95% CI=0.06–0.50, P=2.21E−03, per (log2) metabolite unit). The levels of these metabolites followed the trend control>MCI>AD. We, additionally, found no association between cholesterol, the precursor of ChE and AD. This study identified new ChE molecules, involved in cholesterol metabolism, implicated in AD, which may help identify new therapeutic targets; although, these findings need to be replicated in larger well-phenotyped cohorts.

U2 - 10.1038/tp.2014.127

DO - 10.1038/tp.2014.127

M3 - Article

SN - 2158-3188

VL - 5

JO - Translational psychiatry

JF - Translational psychiatry

M1 - e494

ER -

Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease

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