Received on February 20, 2006
Accepted on May 2, 2006

Automation and Analytical Techniques

Diagnosing Inborn Errors of Lipid Metabolism with Proton Nuclear Magnetic Resonance Spectroscopy

¹ Laboratory of Pediatrics and Neurology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
² Department of Pediatric Neurology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands

^* To whom correspondence should be addressed. E-mail: r.wevers{at}cukz.umcn.nl.

Background: Many severe diseases are caused by defects in lipid metabolism. As a result, patients often accumulate unusual lipids in their blood and tissues, and proper identification of these lipids is essential for correct diagnosis. In this study, we investigated the potential use of proton nuclear magnetic resonance (¹H-NMR) spectroscopy to simultaneously identify and quantify unusual lipids present in the blood of patients with different inborn errors of lipid metabolism.

Methods: We extracted blood plasma or serum lipids in chloroform-methanol (2:1 by volume). After addition of the nonvolatile chemical shift and concentration reference compound octamethylcyclotetrasiloxane, we performed ¹H-NMR measurements on a 500-MHz spectrometer. Assignments were based on the literature, computer simulations, and reference spectra of relevant authentic standards.

Results: Spectra of normal plasma samples allowed the identification of 9 lipid species. We found good correlation between conventional methods and ¹H-NMR for cholesterol and triglyceride concentrations. We also investigated 4 inborn errors of lipid metabolism (3 in sterol metabolism and 1 in fatty acid metabolism). NMR analysis led to a correct diagnosis for all 4 diseases, whereas the concentration of the diagnostic metabolite could be determined for 3.

Conclusions: ¹H-NMR spectroscopy of blood plasma or serum lipid extracts can be used to accurately identify and quantify lipids. The method can also identify unusual lipids in the blood of patients with inborn errors of lipid metabolism. This technique may therefore be applicable in clinical diagnosis and follow-up.