Skip to main content

Advertisement

Log in

Surface fitting of 2D diffusion-edited 1H NMR spectroscopy data for the characterisation of human plasma lipoproteins

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

Determining the concentration and size of lipoprotein complexes is very important due to their role in cardiovascular diseases and metabolic disorders. However, standard methods for lipoprotein fractionation are manual and time consuming and cannot be used as standard diagnostic tools. Because different subclasses of lipoproteins have different radii and, hence, different diffusion velocities, we propose a fast and reliable method that uses 2D diffusion-edited 1H NMR spectroscopy to acquire a set of 2D spectra of plasma samples, followed by a surface fitting algorithm based on Lorentzian functions to estimate the sizes and the relative proportions of different lipoprotein subclasses. We were able to demonstrate that the derived sizes and positions related to the Lorentzian functions follow an exponential relationship for normolipidaemic and dislipaemic samples with coefficients of determination (r 2) of 0.85 and 0.81, respectively. Moreover, we found a linear relationship between the width and size of the Lorentzian functions for normolipidaemic samples (r 2 = 0.88) while for dislipaemic samples this relation was nonlinear (r 2 = 0.62). Dividing our samples set into four different lipoprotein profiles (normal lipid values, low HDL/LDL ratio, high triglycerides values and both risk factors) and using principal component analysis (PCA) followed by multivariate analysis of variance (MANOVA), our method was able to statistically discriminate between those groups, with p-values of 0.0016, 0.0006, <1e−4 and 0.0035, respectively. These parameters are characteristic and indicative of different lipoprotein profiles and can be used to distinguish between normolipidaemic, hypercholesterolaemic, hypertriglyceridaemic and chylomicronaemic profiles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • AlaKorpela, M. (1995) H-1 NMR spectroscopy of human blood plasma. Progress in Nuclear Magnetic Resonance Spectroscopy, 27, 475–554.

  • Ala-Korpela, M. (2008). Critical evaluation of H-1 NMR metabonomics of serum as a methodology for disease risk assessment and diagnostics. Clinical Chemistry and Laboratory Medicine, 46, 27–42.

    Article  PubMed  CAS  Google Scholar 

  • AlaKorpela, M., Hiltunen, Y., & Bell, J. D. (1995). Quantification of biomedical NMR data using artificial neural network analysis: Lipoprotein lipid profiles from H-1 NMR data of human plasma. NMR in Biomedicine, 8, 235–244.

    Article  CAS  Google Scholar 

  • Antalek, B. (2002). Using pulsed gradient spin echo NMR for chemical mixture analysis: How to obtain optimum results. Concepts in Magnetic Resonance, 14, 225–258.

    Article  CAS  Google Scholar 

  • Bachorik, P. S., & Ross, J. W. (1995). National-cholesterol-education-program recommendations for measurement of low-density-lipoprotein cholesterol—executive summary. Clinical Chemistry, 41, 1414–1420.

    PubMed  CAS  Google Scholar 

  • Bathen, T. F., Krane, J., Engan, T., Bjerve, K. S., & Axelson, D. (2000). Quantification of plasma lipids and apolipoproteins by use of proton NMR spectroscopy, multivariate and neural network analysis. NMR in Biomedicine, 13, 271–288.

    Article  PubMed  CAS  Google Scholar 

  • Beckwith-Hall, B. M., Thompson, N. A., Nicholson, J. K., Lindon, J. C., & Holmes, E. (2003). A metabonomic investigation of hepatotoxicity using diffusion-edited H-1 NMR spectroscopy of blood serum. Analyst, 128, 814–818.

    Article  PubMed  CAS  Google Scholar 

  • Cantor C. R., & Schimmel, P. R. (1980). Biophysical chemistry, part ii: Techniques for the study of biological structure and function. San Francisco: W.H. Freeman.

  • Chapman, M. J., Goldstein, S., Lagrange, D., & Laplaud, P. M. (1981). A density gradient ultra-centrifugal procedure for the isolation of the major lipoprotein classes from human-serum. Journal of Lipid Research, 22, 339–358.

    PubMed  CAS  Google Scholar 

  • Duell, P. B., Illingworth, D. R., & Connor, W. E. (2001). Endocrinology and metabolism (4th ed.). McGraw-Hill: New York.

    Google Scholar 

  • Dyrby, M., Petersen, M., Whittaker, A. K., Lambert, L., Norgaard, L., Bro, R., et al. (2005). Analysis of lipoproteins using 2D diffusion-edited NMR spectroscopy and multi-way chemometrics. Analytica Chimica Acta, 531, 209–216.

    Article  CAS  Google Scholar 

  • Festa, A., Williams, K., Hanley, A. J. G., Otvos, J. D., Goff, D. C., Wagenknecht, L. E., et al. (2005). Nuclear magnetic resonance lipoprotein abnormalities in prediabetic subjects in the insulin resistance atherosclerosis study. Circulation, 111, 3465–3472.

    Article  PubMed  Google Scholar 

  • Fossel, E. T., Carr, J. M., & McDonagh, J. (1986). Detection of malignant-tumors—water-suppressed proton nuclear-magnetic-resonance spectroscopy of plasma. New England Journal of Medicine, 315, 1369–1376.

    Article  PubMed  CAS  Google Scholar 

  • Freedman, D. S., Otvos, J. D., Jeyarajah, E. J., Barboriak, J. J., Anderson, A. J., & Walker, J. A. (1998). Relation of lipoprotein subclasses as measured by proton nuclear magnetic resonance spectroscopy to coronary artery disease. Arteriosclerosis, Thrombosis, and Vascular Biology, 18, 1046–1053.

    Article  PubMed  CAS  Google Scholar 

  • Friedewa, W. T, Fredrick, D. S., & Levy, R. I. (1972). Estimation of concentration of low-density lipoprotein cholesterol in plasma, without use of preparative ultracentrifuge. Clinical Chemistry, 18, 499–502.

    Google Scholar 

  • Gidez, L. I., Miller, G. J., Burstein, M., Slagle, S., & Eder, H. A. (1982). Separation and quantitation of subclasses of human-plasma high-density lipoproteins by a simple precipitation procedure. Journal of Lipid Research, 23, 1206–1223.

    PubMed  CAS  Google Scholar 

  • Gofman, J. W., Lindgren, F. T., & Elliott, H. (1949). Ultracentrifugal studies of lipoproteins of human serum. Journal of Biological Chemistry, 179, 973–979.

    PubMed  CAS  Google Scholar 

  • Jerschow, A., & Muller, N. (1997). Suppression of convection artifacts in stimulated-echo diffusion experiments. Double-stimulated-echo experiments. Journal of Magnetic Resonance, 125, 372–375.

    Article  CAS  Google Scholar 

  • Jeyarajah, E. J., Cromwell, W. C., & Otvos, J. D. (2006). Lipoprotein particle analysis by nuclear magnetic resonance spectroscopy. Clinics in Laboratory Medicine, 26, 847–870.

    Google Scholar 

  • Jialal, I., Hirany, S. V., Devaraj, S., & Sherwood, T. A. (1995). Comparison of an immunoprecipitation method for direct measurement of LDL-cholesterol with beta-quantification (ultracentrifugation). American Journal of Clinical Pathology, 104, 76–81.

    PubMed  CAS  Google Scholar 

  • Johnson, C. S. (1999). Diffusion ordered nuclear magnetic resonance spectroscopy: Principles and applications. Progress in Nuclear Magnetic Resonance Spectroscopy, 34, 203–256.

    Article  CAS  Google Scholar 

  • Kesmarky, G., Kenyeres, P., Rabai, M., & Toth, K. (2008). Plasma viscosity: A forgotten variable. Clin. Hemorheol. Microcirc., 39, 243–246.

    PubMed  Google Scholar 

  • Kremer, W., Kalbitzer, H. R., & Huber, F. (2008). US Patent Application 2008/0038829 A1.

  • Kumpula, L. S., Makela, S. M., Makinen, V. P., Karjalainen, A., Liinamaa, J. M., Kaski, K., et al. (2010). Characterization of metabolic interrelationships and in silico phenotyping of lipoprotein particles using self-organizing maps. Journal of Lipid Research, 51, 431–439.

    Article  PubMed  CAS  Google Scholar 

  • Lamarche, B., & Lewis, G. F. (1998). Atherosclerosis prevention for the next decade: Risk assessment beyond low density lipoprotein cholesterol. Canadian Journal of Cardiology, 14, 841–851.

    PubMed  CAS  Google Scholar 

  • Lamarche, B., Moorjani, S., Cantin, B., Dagenais, G. R., Lupien, P. J., & Despres, J. P. (1997). Associations of HDL2 and HDL3 subfractions with ischemic heart disease in men—prospective results from the Quebec cardiovascular study. Arteriosclerosis, Thrombosis, and Vascular Biology, 17, 1098–1105.

    Article  PubMed  CAS  Google Scholar 

  • Liu, M. L., Tang, H. R., Nicholson, J. K., & Lindon, J. C. (2002). Use of H-1 NMR-determined diffusion coefficients to characterize lipoprotein fractions in human blood plasma. Magnetic Resonance in Chemistry, 40, S83–S88.

    Article  CAS  Google Scholar 

  • Lounila, J., Alakorpela, M., Jokisaari, J., Savolainen, M. J., & Kesaniemi, Y. A. (1994). Effects of orientational order and particle-size on the NMR line positions of lipoproteins. Physical Review Letters, 72, 4049–4052.

    Article  PubMed  CAS  Google Scholar 

  • Nicholson, J. K., Foxall, P. J. D., Spraul, M., Farrant, R. D., & Lindon, J. C. (1995). 750-Mhz H-1 and H-1-C-13 NMR-spectroscopy of human blood-plasma. Analytical Chemistry, 67, 793–811.

    Article  PubMed  CAS  Google Scholar 

  • Noble, R. P. (1968). Electrophoretic separation of plasma lipoproteins in agarose gel. Journal of Lipid Research, 9, 693–700.

    Google Scholar 

  • Otvos, J. D., Jeyarajah, E. J., Bennett, D. W., & Krauss, R. M. (1992). Development of a proton nuclear-magnetic-resonance spectroscopic method for determining plasma-lipoprotein concentrations and subspecies distributions from a single, rapid measurement. Clinical Chemistry, 38, 1632–1638.

    PubMed  CAS  Google Scholar 

  • Otvos, J. D., Jeyarajah, E. J., Hayes, L. W., Freedman, D. S., Janjan, N. A., & Anderson, T. (1991). Relationships between the proton nuclear-magnetic-resonance properties of plasma-lipoproteins and cancer. Clinical Chemistry, 37, 369–376.

    PubMed  CAS  Google Scholar 

  • Petersen, M., Dyrby, M., Toubro, S., Engelsen, S. B., Norgaard, L., Pedersen, H. T., et al. (2005). Quantification of lipoprotein subclasses by proton nuclear magnetic resonance-based partial least-squares regression models. Clinical Chemistry, 51, 1457–1461.

    Article  PubMed  CAS  Google Scholar 

  • Roheim, P. S., & Asztalos, B. F. (1995). Clinical-significance of lipoprotein size and risk for coronary atherosclerosis. Clinical Chemistry, 41, 147–152.

    PubMed  CAS  Google Scholar 

  • Rosenson, R. S., Shott, S., & Tangney, C. C. (2002). Hypertriglyceridemia is associated with an elevated blood viscosity Rosenson: Triglycerides and blood viscosity. Atherosclerosis, 161, 433–439.

    Article  PubMed  CAS  Google Scholar 

  • Savorani, F., Kristensen, M., Larsen, F. H., Astrup, A., & Engelsen, S. B. (2010). High throughput prediction of chylomicron triglycerides in human plasma by nuclear magnetic resonance and chemometrics. Nutrition & Metabolism, 7, 8.

    Article  Google Scholar 

  • Schaefer, E. J., Anderson, D. W., Brewer, H. B., Levy, R. I., Danner, R. N., & Blackwelder, W. C. (1978). Plasma-triglycerides in regulation of HDL-cholesterol levels. Lancet, 2, 391–393.

    Article  PubMed  CAS  Google Scholar 

  • Schectman, G., Patsches, M., & Sasse, E. A. (1996). Variability in cholesterol measurements: Comparison of calculated and direct LDL cholesterol determinations. Clinical Chemistry, 42, 732–737.

    PubMed  CAS  Google Scholar 

  • Schumaker, V. N., & Puppione, D. L. (1986). Sequential flotation ultracentrifugation. Methods in Enzymology, 128, 155–170.

    Article  PubMed  CAS  Google Scholar 

  • Seplowitz, A. H., Chien, S., & Smith, F. R. (1981). Effects of lipoproteins on plasma viscosity. Atherosclerosis, 38, 89–95.

    Article  PubMed  CAS  Google Scholar 

  • Stein, E. A., & Myers, G. L. (1995). National-cholesterol-education-program recommendations for triglyceride measurement—executive summary. Clinical Chemistry, 41, 1421–1426.

    PubMed  CAS  Google Scholar 

  • Suna, T., Salminen, A., Soininen, P., Laatikainen, R., Ingman, P., Makela, S., et al. (2007). H-1 NMR metabonomics of plasma lipoprotein subclasses: Elucidation of metabolic clustering by self-organising maps. NMR in Biomedicine, 20, 658–672.

    Article  PubMed  CAS  Google Scholar 

  • Thompson, G. R. (1998). Angiographic evidence for the role of triglyceride-rich lipoproteins in progression of coronary artery disease. European Heart Journal, 19, H31–H36.

    PubMed  CAS  Google Scholar 

  • Tyrrell, H. J. V., & Harris, K. R. (1984). Diffusion in liquids: A theoretical and experimental study. London: Butterworths.

    Google Scholar 

  • Vehtari, A., Makinen, V. P., Soininen, P., Ingman, P., Makela, S. M., Savolainen, M. J., et al. (2007). A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in H-1 NMR metabonomic data. Bmc Bioinformatics, 8(suppl 2).

  • Warnick, G. R., & Wood, P. D. (1995). National-cholesterol-education-program recommendations for measurement of high-density-lipoprotein cholesterol—executive summary. Clinical Chemistry, 41, 1427–1433.

    PubMed  CAS  Google Scholar 

  • Wu, P. S. C., & Otting, G. (2005). Rapid pulse length determination in high-resolution NMR. Journal of Magnetic Resonance, 176, 115–119.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

We acknowledge CIBER de Diabetes y Enfermedades Metabólicas, an initiative of ISCIII (Ministerio de Ciencia e Innovación) for partially funding this work, as well as FIS (project PI 081409). We acknowledge Dr. Gareth Morris for fruitful discussions about the diffusion experiments.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Roger Mallol.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOC 84 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Mallol, R., Rodríguez, M.A., Heras, M. et al. Surface fitting of 2D diffusion-edited 1H NMR spectroscopy data for the characterisation of human plasma lipoproteins. Metabolomics 7, 572–582 (2011). https://doi.org/10.1007/s11306-011-0273-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11306-011-0273-8

Keywords

Navigation