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Proton NMR analysis of plasma is a weak predictor of coronary artery disease

Nature Medicine volume 12, pages 705–710 (2006)Cite this article

An Erratum to this article was published on 01 July 2006

Abstract

Multivariate analysis of 1H-NMR spectra of blood sera was reported previously to predict angiographically defined advanced coronary artery disease (CAD) with >90% accuracy and specificity. The analysis depended mainly on the major lipid regions of the spectra, but many variables, including gender and drug treatment, affect lipid composition and are potential confounders. We have determined the predictive power of the same methodology for angiographically defined CAD using plasma samples from groups of male patients, classified by statin treatment, who had normal coronary arteries (NCAs) or CAD. Predictions for NCA and CAD groups were only 80.3% correct for patients not treated with statins and 61.3% for treated patients, compared with random correct predictions of 50%. A confidence limit of >99% was achieved for 36.2% of predictions for untreated groups and 6.2% for treated groups. Detection of CAD by 1H-NMR with >99% confidence was therefore very weak compared with angiography.

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Figure 1: 1H-NMR spectra and multivariate analyses comparing groups of male and female patients.
Figure 2: Model scores for multivariate analyses comparing groups of male and female patients and groups untreated and treated with statins.
Figure 3: Model scores for multivariate analyses comparing groups of male NCA and TVD patients not treated with statins.

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Notes

  1. NOTE: In the version of this article initially published, the layout of the data in Tables 1 and 2 is incorrect. The error has been corrected in the HTML and PDF versions of the article.

References

  1. Brindle, J.T. et al. Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat. Med. 8, 1439–1444 (2002).

    Article  CAS  Google Scholar 

  2. Brindle, J.T., Nicholson, J.K., Schofield, P.M., Grainger, D.J. & Holmes, E. Application of chemometrics to 1H NMR spectroscopic data to investigate a relationship between human serum metabolic profiles and hypertension. Analyst 128, 32–36 (2003).

    Article  CAS  Google Scholar 

  3. Bittner, V. Lipoprotein abnormalities related to women's health. Am. J. Cardiol. 90, 77I–84i (2002).

    Article  CAS  Google Scholar 

  4. Scandinavian Simvastatin Survival Study Group. Randomised trial of cholesterol lowering in 4444 patients with coronary heart disease: the Scandinavian Simvastatin Survival Study (4S). Lancet 344, 1383–1389 (1994).

  5. Legato, M.J. Dyslipidemia, gender, and the role of high-density lipoprotein cholesterol: implications for therapy. Am. J. Cardiol. 86, 15L–18L (2000).

    Article  CAS  Google Scholar 

  6. Jousilahti, P., Vartiainen, E., Tuomilehto, J. & Puska, P. Sex, age, cardiovascular risk factors, and coronary heart disease: a prospective follow-up study of 14786 middle-aged men and women in Finland. Circulation 99, 1165–1172 (1999).

    Article  CAS  Google Scholar 

  7. Lounila, J., Ala-Korpela, M., Jokisaari, J., Savolainen, M.J. & Kesaniemi, Y.A. Effects of orientational order and particle size on the NMR line positions of lipoproteins. Phys. Rev. Lett. 72, 4049–4052 (1994).

    Article  CAS  Google Scholar 

  8. Freedman, D.S. et al. Sex and age differences in lipoprotein subclasses measured by nuclear magnetic resonance spectroscopy: the Framingham Study. Clin. Chem. 50, 1189–1200 (2004).

    Article  CAS  Google Scholar 

  9. Blake, G.J., Otvos, J.D., Rifai, N. & Ridker, P.M. Low-density lipoprotein particle concentration and size as determined by nuclear magnetic resonance spectroscopy as predictors of cardiovascular disease in women. Circulation 106, 1930–1937 (2002).

    Article  CAS  Google Scholar 

  10. Ransohoff, D.F. Rules of evidence for cancer molecular-marker discovery and validation. Nat. Rev. Cancer 4, 309–314 (2004).

    Article  CAS  Google Scholar 

  11. Ransohoff, D.F. Bias as a threat to the validity of cancer molecular-marker research. Nat. Rev. Cancer 5, 142–149 (2005).

    Article  CAS  Google Scholar 

  12. Craig, W.Y. et al. Effect of sample storage on the assay of lipoprotein(a) by commercially available radial immunodiffusion and enzyme-linked immunosorbent assay kits. Clin. Chem. 38, 550–553 (1992).

    CAS  PubMed  Google Scholar 

  13. Lim, H.M. et al. Some factors that influence the plasma lipoprotein 1H NMR spectra of normal and cancer patients: an oncolipid test? Yale J. Biol. Med. 64, 63–77 (1991).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Bell, J.D., Sadler, P.J., Macleod, A.F., Turner, P.R. & La Ville, A. 1H NMR studies of human blood plasma. Assignment of resonances for lipoproteins. FEBS Lett. 219, 239–243 (1987).

    Article  CAS  Google Scholar 

  15. Le Moyec, L., Valensi, P., Charniot, J.C., Hantz, E. & Albertini, J.P. Serum 1H-nuclear magnetic spectroscopy followed by principal component analysis and hierarchical cluster analysis to demonstrate effects of statins on hyperlipidemic patients. NMR Biomed. 18, 421–429 (2005).

    Article  CAS  Google Scholar 

  16. Mierisova, S. & Ala-Korpela, M. MR spectroscopy quantitation: a review of frequency domain methods. NMR Biomed. 14, 247–259 (2001).

    Article  CAS  Google Scholar 

  17. van der Veen, J.W., de Beer, R., Luyten, P.R. & van Ormondt, D. Accurate quantification of in vivo31P NMR signals using the variable projection method and prior knowledge. Magn. Reson. Med. 6, 92–98 (1988).

    Article  CAS  Google Scholar 

  18. Vanhamme, L., van den Boogaart, A. & Van Huffel, S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J. Magn. Reson. 129, 35–43 (1997).

    Article  CAS  Google Scholar 

  19. Clarke, S.C., Schofield, P.M., Grace, A.A., Metcalfe, J.C. & Kirschenlohr, H.L. Tamoxifen effects on endothelial function and cardiovascular risk factors in men with advanced atherosclerosis. Circulation 103, 1497–1502 (2001).

    Article  CAS  Google Scholar 

  20. Clarke, S.C., Kelleher, J., Lloyd-Jones, H., Slack, M. & Schofiel, P.M. A study of hormone replacement therapy in postmenopausal women with ischaemic heart disease: the Papworth HRT atherosclerosis study. BJOG 109, 1056–1062 (2002).

    Article  CAS  Google Scholar 

  21. Anthony, M.L., Sweatman, B.C., Beddell, C.R., Lindon, J.C. & Nicholson, J.K. Pattern recognition classification of the site of nephrotoxicity based on metabolic data derived from proton nuclear magnetic resonance spectra of urine. Mol. Pharmacol. 46, 199–211 (1994).

    CAS  PubMed  Google Scholar 

  22. Eriksson, L., Johansson, E., Kettaneh-Wold, N. & Wold, S. in Multi- and Megavariate Data Analysis. Principles and Applications. 43–69, 71–112, 229–234 (Umetrics Academy, Umea, Sweden, 2001).

    Google Scholar 

  23. Gavaghan, C.L., Holmes, E., Lenz, E., Wilson, I.D. & Nicholson, J.K. An NMR-based metabonomic approach to investigate the biochemical consequences of genetic strain differences: application to the C57BL10J and Alpk:ApfCD mouse. FEBS Lett. 484, 169–174 (2000).

    Article  CAS  Google Scholar 

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Acknowledgements

This study was funded by a Co-operative Group grant from the Medical Research Council (to J.C.M.) and a grant from the Biotechnology and Biological Sciences Research Council (to K.M.B.). Sample collections were funded by grants from the Dr Scholl Foundation, Chicago (to P.M.S.) and from NeoRx Corporation, Seattle (to A.A.G.). J.L.G. is a Royal Society University Research Fellow.

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Authors and Affiliations

  1. Department of Biochemistry, University of Cambridge, Building O, Downing Site, Tennis Court Road, Cambridge, CB2 1QW, UK

    Heide L Kirschenlohr, Julian L Griffin, Andrew A Grace, Kevin M Brindle & James C Metcalfe

  2. Department of Cardiology, Papworth Hospital NHS Trust, Papworth Everard, CB3 8RE, UK

    Sarah C Clarke, Ranyl Rhydwen, Andrew A Grace & Peter M Schofield

Authors
  1. Heide L Kirschenlohr
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  2. Julian L Griffin
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  3. Sarah C Clarke
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  4. Ranyl Rhydwen
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  5. Andrew A Grace
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  6. Peter M Schofield
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  7. Kevin M Brindle
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  8. James C Metcalfe
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Contributions

H.L.K. performed experimental design, data collection and analysis. J.L.G. and K.M.B. performed experimental design and data analysis. A.A.G. and P.M.S. led clinical trials for plasma sample collections. J.C.M. performed experimental design and data analysis, and wrote the manuscript.

Corresponding author

Correspondence to James C Metcalfe.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Baseline data for patient groups. (PDF 45 kb)

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Kirschenlohr, H., Griffin, J., Clarke, S. et al. Proton NMR analysis of plasma is a weak predictor of coronary artery disease. Nat Med 12, 705–710 (2006). https://doi.org/10.1038/nm1432

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