Metabolomic distinction of microvascular effects of lipoprotein apheresis--a pilot study.
OBJECTIVE
The study of small-molecule metabolites may assist in cardiovascular risk monitoring during therapy. We assessed whether acute changes in the metabolome by lipoprotein apheresis are able to predict changes in microvascular function.


METHODS
We performed mass-spectrometry-based profiling of 186 metabolites in peripheral plasma of 21 hyperlipidemic patients before and after a single session of lipoprotein apheresis. To evaluate the capability of metabolites to predict microvascular outcome after apheresis, patients were stratified according to improvement and deterioration of retinal endothelial function. Endothelial function was assessed as the relative change in retinal vessel diameter in response to flicker light stimulation.


RESULTS
We observed pronounced but not uniform changes in the metabolome after a single session of lipoprotein apheresis. Improvements in microvascular function were associated with a decline in lysophosphatidylcholines C14:0, C16:0, C16:1, C18:0, C18:1, C18:2, C20:4, C28:0, C28:1; in the amino acid serine and the dicarboxyacylcarnitine C12-DC. A positive relationship was found for methionine and ornithine. Applying decision tree and receiver-operator characteristic curve analysis, a change in serine of smaller than 11% by lipoprotein apheresis predicted an improvement of microvascular function with high sensitivity.


CONCLUSIONS
Lipoprotein apheresis elicits changes in the metabolome favoring an anti-atherosclerotic environment. Monitoring the serine profile may assist in risk management of patients undergoing regular lipoprotein apheresis.
Autonomic and Neuroendocrinological Laboratory, Department of Neurology, University Hospital Carl Gustav Carus, Dresden, Fetscherstr 74, 01307 Dresden, Germany. manja.reimann@uniklinikum-dresden.de
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M
Reimann
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Peitzsch
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Ziemssen
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U
Julius
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Eisenhofer
D000328:Adult; D000368:Aged; D015415:Biomarkers / Q000097:blood; D001781:Blood Component Removal; D002331:Carnitine / Q000031:analogs & derivatives / Q000097:blood; D016009:Chi-Square Distribution; D003663:Decision Trees; D005260:Female; D006801:Humans; D006949:Hyperlipidemias / Q000097:blood / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy*; D008074:Lipoproteins / Q000097:blood*; D008244:Lysophosphatidylcholines / Q000097:blood; D008297:Male; D055432:Metabolomics / Q000379:methods; D008715:Methionine / Q000097:blood; D055806:Microvessels / Q000503:physiopathology*; D008875:Middle Aged; D009952:Ornithine / Q000097:blood; D010775:Photic Stimulation; D010865:Pilot Projects; D012372:ROC Curve; D012171:Retinal Vessels / Q000503:physiopathology*; D018570:Risk Assessment; D012307:Risk Factors; D012694:Serine / Q000097:blood; D021241:Spectrometry, Mass, Electrospray Ionization; D053719:Tandem Mass Spectrometry; D016896:Treatment Outcome
D015415:Biomarkers; D008074:Lipoproteins; D008244:Lysophosphatidylcholines; C116917:acylcarnitine; D012694:Serine; D008715:Methionine; D009952:Ornithine; D002331:Carnitine