Recent Advancements in the LC- and GC-Based Analysis of Malondialdehyde (MDA): A Brief Overview

• Published in: Chromatographia Vol. 75; no. 9-10; pp. 433 - 440
• Main Authors: Giera, Martin, Lingeman, Henk, Niessen, Wilfried M. A.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01-05-2012; Springer
• Subjects: Analytical Chemistry; Biological and medical sciences; Cell metabolism, cell oxidation; Cell physiology; Chemistry; Chemistry and Materials Science; Chromatography; Fundamental and applied biological sciences. Psychology; Investigative techniques, diagnostic techniques (general aspects); Laboratory Medicine; Medical sciences; Miscellaneous. Technology; Molecular and cellular biology; Pathology. Cytology. Biochemistry. Spectrometry. Miscellaneous investigative techniques; Pharmacy; Proteomics; Review; Malondialdehyde (MDA); Biomarker; Derivatization; LC–MS(MS); Human; Biological fluid; Oxidative stress; Tandem mass spectrometry; Chemical analysis; Coupled method; HPLC chromatography; Dialdehyde; Biological marker; Lipids; Review; LC―MS(MS); Gas chromatography; Tissue; Animal; Clinical biology; Mass spectrometry; Peroxidation
• ISSN: 0009-5893; 1612-1112
• DOI: 10.1007/s10337-012-2237-1

Malondialdehyde (MDA) is an end-product of lipid peroxidation and a side product of thromboxane A
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synthesis. Moreover, it is not only a frequently measured biomarker of oxidative stress, but its high reactivity and toxicity underline the fact that this molecule is more than “just” a biomarker. Additionally, MDA was proven to be a mutagenic substance. Having said this, it is evident that there is a major interest in the highly selective and sensitive analysis of this molecule in various matrices. In this review, we will provide a brief overview of the most recent developments and techniques for the liquid chromatography (LC) and gas chromatography (GC)-based analysis of MDA in different matrices. While the 2-thiobarbituric acid assay still is the most prominent methodology for determining MDA, several advanced techniques have evolved, including GC–MS(MS), LC–MS(MS) as well as several derivatization-based strategies.