On the Market | Published:

Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics

Nature Medicine volume 8, pages 14391445 (2002) | Download Citation

Subjects

  • A Corrigendum to this article was published on 01 April 2003

Abstract

Although a wide range of risk factors for coronary heart disease have been identified from population studies, these measures, singly or in combination, are insufficiently powerful to provide a reliable, noninvasive diagnosis of the presence of coronary heart disease. Here we show that pattern-recognition techniques applied to proton nuclear magnetic resonance (1H-NMR) spectra of human serum can correctly diagnose not only the presence, but also the severity, of coronary heart disease. Application of supervised partial least squares-discriminant analysis to orthogonal signal-corrected data sets allows >90% of subjects with stenosis of all three major coronary vessels to be distinguished from subjects with angiographically normal coronary arteries, with a specificity of >90%. Our studies show for the first time a technique capable of providing an accurate, noninvasive and rapid diagnosis of coronary heart disease that can be used clinically, either in population screening or to allow effective targeting of treatments such as statins.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    National Statistics Series DH1 no. 31, Mortality Statistics (1998). The Stationery Office (UK Government), London, England.

  2. 2.

    , & Brief description of the Multiple Risk Factor Intervention Trial. Am. J. Clin. Nutr. 65 (Suppl. 1), 191S–195S (1997).

  3. 3.

    et al. Cigarette smoking and mortality. MRFIT Research Group. Prev. Med. 20, 638–654 (1991).

  4. 4.

    Multiple Risk Factor Intervention Trial Research Group. Relationship between baseline risk factors and coronary heart disease and total mortality in the Multiple Risk Factor Intervention Trial. Prev. Med. 15, 254–273 (1986).

  5. 5.

    , , & Application of the MRFIT smoking cessation program to a healthy, mixed-sex sample. Am. J. Prev. Med. 8, 165–170 (1992).

  6. 6.

    Atherosclerosis—an inflammatory disease. N. Engl. J. Med. 340, 115–126 (1999).

  7. 7.

    , , & Lipoproteins and cardiovascular risk—from genetics to CHD prevention. Eur. Heart J. 19 (Suppl. C), C5–C11 (1998).

  8. 8.

    & Identifying patients at risk for coronary heart disease: Implications from trials of lipid-lowering drug therapy. Q.J. Med. 93, 567–574 (2000).

  9. 9.

    , & 'Metabonomics': Understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29, 1181–1189 (1999).

  10. 10.

    & High resolution proton magnetic resonance spectroscopy of biological fluids Prog. Nucl. Magn. Reson. Spectrosc. 21, 449–501 (1989).

  11. 11.

    , & Pattern recognition methods and applications in biomedical magnetic resonance. Prog. Nucl. Magn. Reson. Spectrosc. 39, 1–40 (2001).

  12. 12.

    , , & Metabonomics: metabolic processes studied by NMR spectroscopy of biofluids. Concepts Magn. Reson. 12, 289–320 (2000).

  13. 13.

    et al. Chemometric models for toxicity classification based on NMR spectra of biofluids. Chem. Res. Toxicol. 13, 471–478 (1999).

  14. 14.

    , , , & Transcriptomics in predictive toxicology. Curr. Opin. Drug Discov. Devel. 5, 90–97 (2002).

  15. 15.

    , , , & 750 MHz 1H and 1H-13C NMR spectroscopy of human blood plasma. Anal. Chem. 67, 793–811 (1995).

  16. 16.

    1H-NMR spectroscopy of human blood plasma. Prog. Nucl. Magn. Reson. Spectrosc. 27, 475–554 (1995).

  17. 17.

    , , & Introduction to Multi and Megavariate Data Analysis Using Projection Methods (PCA and PLS-DA) (Umetrics AB, Malmo, Sweden, 1999).

  18. 18.

    , , & Orthogonal signal correction of near-infrared spectra. Chemometrics Intelligent Lab. Systems 44, 175–185 (1998).

  19. 19.

    , & Quantification of biomedical NMR data using artificial neural network analysis: Lipoprotein lipid profiles from 1H NMR data of human plasma. NMR Biomed. 8, 235–244 (1995).

  20. 20.

    In Handbook of Lipoprotein Testing (eds. Rifai, N., Warnick, R. & Dominiczak, M.) 497–508 (AACC Press, Washington DC, 1997).

Download references

Author information

Affiliations

  1. Biological Chemistry, Biomedical Sciences Division, Faculty of Medicine, Imperial College of Science, Technology and Medicine, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, UK

    • Joanne T. Brindle
    • , Henrik Antti
    • , Elaine Holmes
    • , George Tranter
    •  & Jeremy K. Nicholson
  2. Department of Cardiology, Papworth Hospital NHS Trust, Cambridge, UK

    • Hugh W.L. Bethell
    • , Sarah Clarke
    •  & Peter M. Schofield
  3. GlaxoSmithKline, Medicines Research Centre, Gunnels Wood Road, Stevenage, UK

    • Elaine McKilligin
  4. Department of Medicine, Box 157, Addenbrooke's Hospital, Cambridge, UK

    • David E. Mosedale
    •  & David J. Grainger

Authors

  1. Search for Joanne T. Brindle in:

  2. Search for Henrik Antti in:

  3. Search for Elaine Holmes in:

  4. Search for George Tranter in:

  5. Search for Jeremy K. Nicholson in:

  6. Search for Hugh W.L. Bethell in:

  7. Search for Sarah Clarke in:

  8. Search for Peter M. Schofield in:

  9. Search for Elaine McKilligin in:

  10. Search for David E. Mosedale in:

  11. Search for David J. Grainger in:

Competing interests

E.H., J.K.N and D.J.G. declare financial interest in this publication. These authors are named inventors on one or more patents filed partly as a result of the work described in this report, and these patents are assigned to Metabometrix Limited, a company in which E.H. and J.K.N. hold more than 5% equity stakes.

Corresponding author

Correspondence to David J. Grainger.

Supplementary information

About this article

Publication history

Published

DOI

https://doi.org/10.1038/nm1202-802

Further reading