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Transcriptome Analysis in Patients with Progressive Coronary Artery Disease: Identification of Differential Gene Expression in Peripheral Blood

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Abstract

Inflammation as a systemic process plays a central role in atherosclerotic plaque progression (PP). Here we investigated other systemic correlates of PP by global gene expression profiling (GEP) in peripheral blood. From a database of 45,727 coronary angiograms, we identified two patient groups with good risk factor control, but different clinical evolution: First, 16 patients had significant PP leading to repeated coronary interventions, and second, 16 patients had angiographically documented stable courses. GEP revealed 93 differentially expressed genes, of which 23 have unknown function. Among the remaining 70 genes, 10 were associated with progenitor and pluripotent cells, but only three genes with atherosclerosis. We developed a risk prediction gene signature by a multivariable statistical model integrating comprehensive laboratory and clinical patient data. This signature identified PP with high sensitivity and specificity for new patients, as estimated by resampling techniques. GEP results were validated by qPCR for ANK2 and GSTT1.

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References

  1. Lusis, A. J. (2000). Atherosclerosis. Nature, 407, 233–241.

    Article  PubMed  CAS  Google Scholar 

  2. Hansson, G. K. (2005). Inflammation, atherosclerosis, and coronary artery disease. The New England Journal of Medicine, 352, 1685–1695.

    Article  PubMed  CAS  Google Scholar 

  3. Libby, P. (2002). Inflammation in atherosclerosis. Nature, 420, 868–874.

    Article  PubMed  CAS  Google Scholar 

  4. Libby, P., & Theroux, P. (2005). Pathophysiology of coronary artery disease. Circulation, 111, 3481–3488.

    Article  PubMed  Google Scholar 

  5. Baigent, C., Blackwell, L., Emberson, J., Holland, L. E., Reith, C., Bhala, N., et al. (2010). Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet, 376, 1670–1681.

    Article  PubMed  CAS  Google Scholar 

  6. Kwak, B., Mulhaupt, F., Myit, S., & Mach, F. (2000). Statins as a newly recognized type of immunomodulator. Nature Medicine, 6, 1399–1402.

    Article  PubMed  CAS  Google Scholar 

  7. Austen, W. G., Edwards, J. E., Frye, R. L., Gensini, G. G., Gott, V. L., Griffith, L. S., et al. (1975). A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc Committee for Grading of Coronary Artery Disease, Council on Cardiovascular Surgery, American Heart Association. Circulation, 51, 5–40.

    Article  PubMed  CAS  Google Scholar 

  8. Bestehorn, H. P., Neumann, F. J., Buttner, H. J., Betz, P., Sturzenhofecker, P., von Hodenberg, E., et al. (2004). Evaluation of the effect of oral verapamil on clinical outcome and angiographic restenosis after percutaneous coronary intervention: the randomized, double-blind, placebo-controlled, multicenter Verapamil Slow-Release for Prevention of Cardiovascular Events After Angioplasty (VESPA) Trial. Journal of the American College of Cardiology, 43, 2160–2165.

    Article  PubMed  CAS  Google Scholar 

  9. Ringqvist, I., Fisher, L. D., Mock, M., Davis, K. B., Wedel, H., Chaitman, B. R., et al. (1983). Prognostic value of angiographic indices of coronary artery disease from the Coronary Artery Surgery Study (CASS). The Journal of Clinical Investigation, 71, 1854–1866.

    Article  PubMed  CAS  Google Scholar 

  10. Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B: Methodological, 57, 289–300.

    Google Scholar 

  11. Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998). Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America, 95, 14863–14868.

    Article  PubMed  CAS  Google Scholar 

  12. Dennis, G., Jr., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., et al. (2003). DAVID: Database for Annotation, Visualization, and Integrated Discovery. Genome Biology, 4, P3.

    Article  PubMed  Google Scholar 

  13. Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009). GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics, 10, 48.

    Article  PubMed  Google Scholar 

  14. Tutz, G., & Binder, H. (2007). Boosting ridge regression. Computational Statistics & Data Analysis, 51, 6044–6059.

    Article  Google Scholar 

  15. Binder, H., & Schumacher, M. (2008). Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples. Statistical Applications in Genetics and Molecular Biology, 7, 12.

    Article  Google Scholar 

  16. Schmittgen, T. D., & Livak, K. J. (2008). Analyzing real-time PCR data by the comparative C(T) method. Nature Protocols, 3, 1101–1108.

    Article  PubMed  CAS  Google Scholar 

  17. Mohr, S., & Liew, C. C. (2007). The peripheral-blood transcriptome: new insights into disease and risk assessment. Trends in Molecular Medicine, 13, 422–432.

    Article  PubMed  CAS  Google Scholar 

  18. Ma, J., & Liew, C. C. (2003). Gene profiling identifies secreted protein transcripts from peripheral blood cells in coronary artery disease. Journal of Molecular and Cellular Cardiology, 35, 993–998.

    Article  PubMed  CAS  Google Scholar 

  19. Sinnaeve, P. R., Donahue, M. P., Grass, P., Seo, D., Vonderscher, J., Chibout, S. D., et al. (2009). Gene expression patterns in peripheral blood correlate with the extent of coronary artery disease. PloS One, 4, e7037.

    Article  PubMed  Google Scholar 

  20. Patino, W. D., Mian, O. Y., Kang, J. G., Matoba, S., Bartlett, L. D., Holbrook, B., et al. (2005). Circulating transcriptome reveals markers of atherosclerosis. Proceedings of the National Academy of Sciences of the United States of America, 102, 3423–3428.

    Article  PubMed  CAS  Google Scholar 

  21. Wingrove, J. A., Daniels, S. E., Sehnert, A. J., Tingley, W., Elashoff, M. R., Rosenberg, S., et al. (2008). Correlation of peripheral-blood gene expression with the extent of coronary artery stenosis. Circulation. Cardiovascular Genetics, 1, 31–38.

    Article  PubMed  CAS  Google Scholar 

  22. Ma, J., Dempsey, A. A., Stamatiou, D., Marshall, K. W., & Liew, C. C. (2007). Identifying leukocyte gene expression patterns associated with plasma lipid levels in human subjects. Atherosclerosis, 191, 63–72.

    Article  PubMed  CAS  Google Scholar 

  23. Timofeeva, A. V., Goryunova, L. E., Khaspekov, G. L., Kovalevskii, D. A., Scamrov, A. V., Bulkina, O. S., et al. (2006). Altered gene expression pattern in peripheral blood leukocytes from patients with arterial hypertension. Annals of the New York Academy of Sciences, 1091, 319–335.

    Article  PubMed  CAS  Google Scholar 

  24. Hitoshi, S., Ishino, Y., Kumar, A., Jasmine, S., Tanaka, K. F., Kondo, T., et al. (2011). Mammalian Gcm genes induce Hes5 expression by active DNA demethylation and induce neural stem cells. Nature Neuroscience, 14, 957–964.

    Article  PubMed  CAS  Google Scholar 

  25. van der Flier, L. G., van Gijn, M. E., Hatzis, P., Kujala, P., Haegebarth, A., Stange, D. E., et al. (2009). Transcription factor achaete scute-like 2 controls intestinal stem cell fate. Cell, 136, 903–912.

    Article  PubMed  Google Scholar 

  26. Schmidt-Lucke, C., Rossig, L., Fichtlscherer, S., Vasa, M., Britten, M., Kamper, U., et al. (2005). Reduced number of circulating endothelial progenitor cells predicts future cardiovascular events: proof of concept for the clinical importance of endogenous vascular repair. Circulation, 111, 2981–2987.

    Article  PubMed  Google Scholar 

  27. Werner, N., Kosiol, S., Schiegl, T., Ahlers, P., Walenta, K., Link, A., et al. (2005). Circulating endothelial progenitor cells and cardiovascular outcomes. The New England Journal of Medicine, 353, 999–1007.

    Article  PubMed  CAS  Google Scholar 

  28. Briguori, C., Testa, U., Riccioni, R., Colombo, A., Petrucci, E., Condorelli, G., et al. (2010). Correlations between progression of coronary artery disease and circulating endothelial progenitor cells. The FASEB Journal, 24, 1981–1988.

    Article  CAS  Google Scholar 

  29. Doney, A. S., Lee, S., Leese, G. P., Morris, A. D., & Palmer, C. N. (2005). Increased cardiovascular morbidity and mortality in type 2 diabetes is associated with the glutathione S transferase theta-null genotype: a Go-DARTS study. Circulation, 111, 2927–2934.

    Article  PubMed  CAS  Google Scholar 

  30. Ellis, K. L., Newton-Cheh, C., Wang, T. J., Frampton, C. M., Doughty, R. N., Whalley, G. A., et al. (2011). Association of genetic variation in the natriuretic peptide system with cardiovascular outcomes. Journal of Molecular and Cellular Cardiology, 50, 695–701.

    Article  PubMed  CAS  Google Scholar 

  31. Norskov, M. S., Frikke-Schmidt, R., Loft, S., Sillesen, H., Grande, P., Nordestgaard, B. G., et al. (2011). Copy number variation in glutathione S-transferases M1 and T1 and ischemic vascular disease: four studies and meta-analyses. Circulation. Cardiovascular Genetics, 4, 418–428.

    Article  PubMed  CAS  Google Scholar 

  32. Zacho, J., Tybjaerg-Hansen, A., Jensen, J. S., Grande, P., Sillesen, H., & Nordestgaard, B. G. (2008). Genetically elevated C-reactive protein and ischemic vascular disease. The New England Journal of Medicine, 359, 1897–1908.

    Article  PubMed  CAS  Google Scholar 

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Acknowledgments

We gratefully acknowledge the contribution made to this study through technical assistance of Petra Enderle.

Funding

Funding of the study was provided by the Herz-Zentrum Bad Krozingen.

Conflict of Interest

None.

Author information

Authors and Affiliations

  1. Klinik für Kardiologie und Angiologie II, Universitäts-Herzzentrum Freiburg • Bad Krozingen, Südring 15, 79189, Bad Krozingen, Germany

    Thomas G. Nührenberg, Christian Stratz, Rolf-Peter Kienzle, Dietmar Trenk & Franz-Josef Neumann

  2. Medizinische Klinik mit Schwerpunkt Kardiologie, Campus Virchow Klinikum, Charité, Berlin, Germany

    Nicole Langwieser & Dietlind Zohlnhöfer-Momm

  3. Berlin-Brandenburg Center for Regenerative Therapies, Berlin, Germany

    Nicole Langwieser & Dietlind Zohlnhöfer-Momm

  4. Institut für Medizinische Biometrie, Epidemiologie und Informatik, Universitätsmedizin der Johannes-Gutenberg-Universität Mainz, Mainz, Germany

    Harald Binder

  5. Institut für Medizinische Biometrie und Medizinische Informatik, Universitätsklinikum Freiburg, Freiburg, Germany

    Harald Binder

  6. Zentrum für Biosystemanalyse der Universität Freiburg, Freiburg, Germany

    Thorsten Kurz

Authors
  1. Thomas G. Nührenberg
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  2. Nicole Langwieser
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Correspondence to Thomas G. Nührenberg.

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Nührenberg, T.G., Langwieser, N., Binder, H. et al. Transcriptome Analysis in Patients with Progressive Coronary Artery Disease: Identification of Differential Gene Expression in Peripheral Blood. J. of Cardiovasc. Trans. Res. 6, 81–93 (2013). https://doi.org/10.1007/s12265-012-9420-5

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  • DOI: https://doi.org/10.1007/s12265-012-9420-5

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