Development and evaluation of a liquid chromatography-mass spectrometry method for rapid, accurate quantitation of malondialdehyde in human plasma.

J Chromatogr B Analyt Technol Biomed Life Sci

University of Victoria-Genome BC Proteomics Centre, Vancouver Island Technology Park, 3101-4464 Markham Street, Victoria, BC V8Z 7X8, Canada; Department of Biochemistry and Microbiology, University of Victoria, Petch Building Room 207, 3800 Finnerty Road, Victoria, BC V8P 5C2, Canada; Segal Cancer Centre, Jewish General Hospital, McGill University, 3755 Cote Ste-Catherine Road, Montreal, QC H3T 1E2, Canada. Electronic address:

Published: September 2016

Malondialdhyde (MDA) is a commonly used marker of lipid peroxidation in oxidative stress. To provide a sensitive analytical method that is compatible with high throughput, we developed a multiple reaction monitoring-mass spectrometry (MRM-MS) approach using 3-nitrophenylhydrazine chemical derivatization, isotope-labeling, and liquid chromatography (LC) with electrospray ionization (ESI)-tandem mass spectrometry assay to accurately quantify MDA in human plasma. A stable isotope-labeled internal standard was used to compensate for ESI matrix effects. The assay is linear (R(2)=0.9999) over a 20,000-fold concentration range with a lower limit of quantitation of 30fmol (on-column). Intra- and inter-run coefficients of variation (CVs) were <2% and ∼10% respectively. The derivative was stable for >36h at 5°C. Standards spiked into plasma had recoveries of 92-98%. When compared to a common LC-UV method, the LC-MS method found near-identical MDA concentrations. A pilot project to quantify MDA in patient plasma samples (n=26) in a study of major depressive disorder with winter-type seasonal pattern (MDD-s) confirmed known associations between MDA concentrations and obesity (p<0.02). The LC-MS method provides high sensitivity and high reproducibility for quantifying MDA in human plasma. The simple sample preparation and rapid analysis time (5x faster than LC-UV) offers high throughput for large-scale clinical applications.

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http://dx.doi.org/10.1016/j.jchromb.2016.07.013DOI Listing

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