Literature DB >> 16730730

The inherent accuracy of 1H NMR spectroscopy to quantify plasma lipoproteins is subclass dependent.

Mika Ala-Korpela1, Niko Lankinen, Aino Salminen, Teemu Suna, Pasi Soininen, Reino Laatikainen, Petri Ingman, Matti Jauhiainen, Marja-Riitta Taskinen, Károly Héberger, Kimmo Kaski.   

Abstract

Proton NMR spectroscopy as a means to quantify lipoprotein subclasses has received wide clinical interest. The experimental part is a fast routine procedure that contrasts favourably to other lipoprotein measurement protocols. The difficulties in using (1)H NMR, however, are in uncovering the subclass specific information from the overlapping data. The NMR-based quantification has been evaluated only in relation to biochemical measures, thereby leaving the inherent capability of NMR rather vague due to biological variation and diversity among the biochemical experiments. Here we will assess the use of (1)H NMR spectroscopy of plasma per se. This necessitates data for which the inherent parameters, namely the shapes and areas of the (1)H NMR signals of the subclasses are available. This was achieved through isolation and (1)H NMR experiments of 11 subclasses--VLDL1, VLDL2, IDL, LDL1, LDL2, LDL3, HDL(2b), HDL(2a), HDL(3a), HDL(3b) and HDL(3c)--and the subsequent modelling of the spectra. The subclass models were used to simulate biochemically representative sets of spectra with known subclass concentrations. The spectral analyses revealed 10-fold differences in the quantification accuracy of different subclasses by (1)H NMR. This finding has critical significance since the usage of (1)H NMR methodology in the clinical arena is rapidly increasing.

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Year:  2006        PMID: 16730730     DOI: 10.1016/j.atherosclerosis.2006.04.020

Source DB:  PubMed          Journal:  Atherosclerosis        ISSN: 0021-9150            Impact factor:   5.162


  13 in total

1.  Diagnosing diabetic nephropathy by 1H NMR metabonomics of serum.

Authors:  Ville-Petteri Mäkinen; Pasi Soininen; Carol Forsblom; Maija Parkkonen; Petri Ingman; Kimmo Kaski; Per-Henrik Groop; Mika Ala-Korpela
Journal:  MAGMA       Date:  2006-12-15       Impact factor: 2.310

2.  Characterization of metabolic interrelationships and in silico phenotyping of lipoprotein particles using self-organizing maps.

Authors:  Linda S Kumpula; Sanna M Mäkelä; Ville-Petteri Mäkinen; Anna Karjalainen; Johanna M Liinamaa; Kimmo Kaski; Markku J Savolainen; Minna L Hannuksela; Mika Ala-Korpela
Journal:  J Lipid Res       Date:  2009-09-05       Impact factor: 5.922

3.  Liposcale: a novel advanced lipoprotein test based on 2D diffusion-ordered 1H NMR spectroscopy.

Authors:  Roger Mallol; Núria Amigó; Miguel A Rodríguez; Mercedes Heras; Maria Vinaixa; Núria Plana; Edmond Rock; Josep Ribalta; Oscar Yanes; Lluís Masana; Xavier Correig
Journal:  J Lipid Res       Date:  2015-01-07       Impact factor: 5.922

Review 4.  Quantitative 1H NMR. Development and potential of an analytical method: an update.

Authors:  Guido F Pauli; Tanja Gödecke; Birgit U Jaki; David C Lankin
Journal:  J Nat Prod       Date:  2012-04-06       Impact factor: 4.050

5.  Squeezing lipids: NMR characterization of lipoprotein particles under pressure.

Authors:  Mary R Starich; Jingrong Tang; Alan T Remaley; Nico Tjandra
Journal:  Chem Phys Lipids       Date:  2020-01-21       Impact factor: 3.329

6.  Developing high performance lipoprotein density profiling for use in clinical studies relating to cardiovascular disease.

Authors:  Craig D Larner; Ronald R Henriquez; Jeffrey D Johnson; Ronald D Macfarlane
Journal:  Anal Chem       Date:  2011-10-18       Impact factor: 6.986

7.  Metabonomic Response to Milk Proteins after a Single Bout of Heavy Resistance Exercise Elucidated by 1H Nuclear Magnetic Resonance Spectroscopy.

Authors:  Christian Clement Yde; Ditte Bruun Ditlev; Søren Reitelseder; Hanne Christine Bertram
Journal:  Metabolites       Date:  2013-01-30

8.  An integrated functional genomic study of acute phenobarbital exposure in the rat.

Authors:  Claire L Waterman; Richard A Currie; Lisa A Cottrell; Jacky Dow; Jayne Wright; Catherine J Waterfield; Julian L Griffin
Journal:  BMC Genomics       Date:  2010-01-06       Impact factor: 3.969

9.  A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data.

Authors:  Aki Vehtari; Ville-Petteri Mäkinen; Pasi Soininen; Petri Ingman; Sanna M Mäkelä; Markku J Savolainen; Minna L Hannuksela; Kimmo Kaski; Mika Ala-Korpela
Journal:  BMC Bioinformatics       Date:  2007-05-03       Impact factor: 3.169

Review 10.  High density lipoproteins: Measurement techniques and potential biomarkers of cardiovascular risk.

Authors:  Anouar Hafiane; Jacques Genest
Journal:  BBA Clin       Date:  2015-01-31
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