Article ID Journal Published Year Pages File Type
1211824 Journal of Chromatography B 2016 8 Pages PDF
Abstract

•A new high throughput LC–MS method was developed to quantify MDA in human plasma.•The new method uses 3-nitrophenylhydrazine for chemical derivatization followed by LC/MRM–MS detection.•The method offers a short analysis time of <2.5 min per sample.•The LC–MS method affords very high specificity and high sensitivity.•The LC–MS method has a wider linear range of concentrations than existing methods.

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 (R2 = 0.9999) over a 20,000-fold concentration range with a lower limit of quantitation of 30 fmol (on-column). Intra- and inter-run coefficients of variation (CVs) were <2% and ∼10% respectively. The derivative was stable for >36 h 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.

Related Topics
Physical Sciences and Engineering Chemistry Analytical Chemistry
Authors
, , , , , ,