Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter February 4, 2021

Long term pronostic value of suPAR in chronic heart failure: reclassification of patients with low MAGGIC score

  • Anne Marie Dupuy , Nils Kuster , Anne Sophie Bargnoux , Sylvain Aguilhon , Fabien Huet , Florence Leclercq , Jean-Luc Pasquié , François Roubille and Jean Paul Cristol EMAIL logo

Abstract

Objectives

Inflammation is a hallmark of heart failure (HF) and among inflammatory biomarkers, the most studied remains the C-reactive protein (CRP). In recent years several biomarkers have emerged, such as sST2 and soluble urokinase–type plasminogen activator receptor (suPAR). This study set out to examine the relative importance of long-time prognostic strength of suPAR and the potential additive information on patient risk with chronic HF in comparison with pronostic value of CRP and sST2.

Methods

Demographics, clinical and biological variables were assessed in a total of 182 patients with chronic HF over median follow-up period of 80 months. Inflammatory biomarkers (i.e., CRP, sST2, and suPAR) were performed.

Results

In univariate Cox regression analysis age, NYHA class, MAGGIC score and the five biomarkers (N-terminal pro brain natriuretic peptide [NT-proBNP], high-sensitive cardiac troponin T [hs-cTnT], CRP, sST2, and suPAR) were associated with both all-cause and cardiovascular mortality. In the multivariate model, only NT-proBNP, suPAR, and MAGGIC score remained independent predictors of all-cause mortality as well as of cardiovascular mortality. Risk classification analysis was significantly improved with the addition of suPAR particularly for all-cause short- and long-term mortality. Using a classification tree approach, the same three variables could be considered as significant classifier variables to predict all-cause or cardiovascular mortality and an algorithm were reported. We demonstrated the favorable outcome associated with patients with a low MAGGIC score and a low suPAR level by comparison to patients with low MAGGIC score but high suPAR values.

Conclusions

The main findings of our study are (1) that among the three inflammatory biomarkers, only suPAR levels were independently associated with 96-month mortality for patients with chronic HF and (2) that an algorithm based on clinical score, a cardiomyocyte stress biomarker and an inflammatory biomarker could help to a more reliable long term risk stratification in heart failure.


Corresponding author: Jean Paul Cristol, Department of Biochemistry, Centre Ressources Biologiques de Montpellier, University Hospital of Montpellier, Montpellier cédex 534295, France; and PhyMedExp, University of Montpellier, INSERM U1046, CNRS UMR 9214, Montpellier, France, Fax: +33 4 67 33 83 93, E-mail:

Acknowledgments

The suPAR Assay was provided by Virogates, Birkerød, Danemark.

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: The local Institutional Review Board deemed the study exempt from review.

References

1. Levine, B1, Kalman, J, Mayer, L, Fillit, HM, Packer, M. Elevated circulating levels of tumor necrosis factor in severe chronic heart failure. N Engl J Med 1990;323:236–41.10.1056/NEJM199007263230405Search in Google Scholar PubMed

2. Yousuf, O, Mohanty, BD, Martin, SS, Joshi, PH, Blaha, MJ, Nasir, K, et al.. High-sensitivity C-reactive protein and cardiovascular disease: a resolute belief or an elusive link? J Am Coll Cardiol 2013;62:397–408.10.1016/j.jacc.2013.05.016Search in Google Scholar PubMed

3. Li, Y, Zhong, X, Cheng, G, Zhao, C, Zhang, L, Hong, Y, et al.. Hs-CRP and all-cause, cardiovascular, and cancer mortality risk: a meta-analysis. Atherosclerosis 2017;259:75–82.10.1016/j.atherosclerosis.2017.02.003Search in Google Scholar PubMed

4. Aimo, A, Vergaro, G, Passino, C, Ripoli, A, Ky, B, Miller, WL, et al.. Prognostic value of soluble suppression of tumorigenicity-2 in chronic heart failure: a meta-analysis. JACC Heart Fail 2017;5:280–6.10.1016/j.jchf.2016.09.010Search in Google Scholar PubMed

5. Kuster, N, Huet, F, Dupuy, AM, Akodad, M, Battistella, P, Agollo, A, et al.. Multimarker approach including CRP, sST2, and GDF-15 for prognostic stratification in stable heart failure. ESC Heart Fail J 2020;7:2230–39.10.1002/ehf2.12680Search in Google Scholar PubMed PubMed Central

6. Eugen-Olsen, J, Andersen, O, Linneberg, A, Ladelund, S, Hansen, TW, Langkilde, A, et al.. Circulating soluble urokinase plasminogen activator receptor predicts cancer, cardiovascular disease, diabetes and mortality in the general population. J Intern Med 2010;268:296–308.10.1111/j.1365-2796.2010.02252.xSearch in Google Scholar PubMed

7. Thunø, M, Macho, B, Eugen-Olsen, J. suPAR: the molecular crystal ball. Dis Markers 2009;27:157–72.10.1155/2009/504294Search in Google Scholar

8. Eapen, DJ, Manocha, P, Ghasemzadeh, N, Patel, RS, Al Kassem, H, Hammadah, M, et al.. Soluble urokinase plasminogen activator receptor level is an independent predictor of the presence and severity of coronary artery disease and of future adverse events. J Am Heart Assoc 2014;3:e001118.10.1161/JAHA.114.001118Search in Google Scholar PubMed PubMed Central

9. Dupuy, AM, Curinier, C, Kuster, N, Huet, F, Leclercq, F, Davy, JM, et al.. Multi-marker strategy in heart failure: combination of ST2 and CRP predicts poor outcome. PLoS One 2016;11:e0157159.10.1371/journal.pone.0157159Search in Google Scholar PubMed PubMed Central

10. Dupuy, AM, Kuster, N, Curinier, C, Huet, F, Plawecki, M, Solecki, K, et al.. Exploring collagen remodeling and regulation as prognosis biomarkers in stable heart failure. Clin Chim Acta 2019;490:167–71.10.1016/j.cca.2018.08.042Search in Google Scholar PubMed

11. Sartipy, U, Dahlström, U, Edner, M, Lund, LH. Predicting survival in heart failure: validation of the MAGGIC heart failure risk score in 51,043 patients from the Swedish heart failure registry. Eur J Heart Fail 2014;16:173–79.10.1111/ejhf.32Search in Google Scholar

12. Heagerty, PJ, Lumley, T, Pepe, MS. Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics 2000;56:337–44.10.1111/j.0006-341X.2000.00337.xSearch in Google Scholar

13. Pencina, MJ, D’Agostino, RBS, Steyerberg, EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 2011;15:11–21.10.1002/sim.4085Search in Google Scholar

14. Strasser, H, Weber, C. On the asymptotic theory of permutation statistics. Math Methods Stat 1999;8:220–50.Search in Google Scholar

15. Koller, L, Stojkovic, S, Richter, B, Sulzgruber, P, Potolidis, C, Liebhart, F, et al.. Soluble urokinase-type plasminogen activator receptor improves risk prediction in patients with chronic heart failure. JACC Heart Fail 2017;5:268–77.10.1016/j.jchf.2016.12.008Search in Google Scholar

16. Emerging Risk Factors Collaboration, Kaptoge, S, Di Angelantonio, E, Lowe, G, Pepys, MB, Thompson, SG, et al.. C-reactive protein concentration and risk of coronary heart disease, stroke, and mortality: an individual participant meta-analysis. Lancet 2010;375:132–40.10.1016/S0140-6736(09)61717-7Search in Google Scholar

17. Yamada, S, Gotoh, T, Nakashima, Y, Kayaba, K, Ishikawa, S, Nago, N, et al.. Distribution of serum C-reactive protein and its association with atherosclerotic risk factors in a Japanese population: Jichi Medical School Cohort Study. Am J Epidemiol 2001;153:1183–90.10.1093/aje/153.12.1183Search in Google Scholar PubMed

18. Kelley-Hedgepeth, A, Lloyd-Jones, DM, Colvin, A, Matthews, KA, Johnston, J, Sowers, MR, et al.. Ethnic differences in C-reactive protein concentrations. Clin Chem 2008;54:1027–37.10.1373/clinchem.2007.098996Search in Google Scholar PubMed

19. Dieplinger, B, Mueller, T. Soluble ST2 in heart failure. Clin Chim Acta 2015;443:57–70.10.1016/j.cca.2014.09.021Search in Google Scholar PubMed

20. Kakkar, R, Lee, RT. The IL-33/ST2 pathway: therapeutic target and novel biomarker. Nat Rev 2008;7:827–40.10.1038/nrd2660Search in Google Scholar PubMed PubMed Central

21. Tajima, S, Bando, M, Ohno, S, Sugiyama, Y, Oshikawa, K, Tominaga, S, et al.. ST2 gene induced by type 2 helper T cell (Th2) and proinflammatory cytokine stimuli may modulate lung injury and fibrosis. Exp Lung Res 2007;33:81–97.10.1080/01902140701198583Search in Google Scholar PubMed

22. Oshikawa, K, Kuroiwa, K, Tago, K, Iwahana, H, Yanagisawa, K, Ohno, S, et al.. Elevated soluble ST2 protein levels in sera of patients with asthma with an acute exacerbation. Am J Respir Crit Care Med 2001;164:277–81.10.1164/ajrccm.164.2.2008120Search in Google Scholar PubMed

23. Oshikawa, K, Yanagisawa, K, Ohno, S, Tominaga, S, Sugiyama, Y. Expression of ST2 in helper T lymphocytes of malignant pleural effusions. Am J Respir Crit Care Med 2002;165:1005–9.10.1164/ajrccm.165.7.2105109Search in Google Scholar PubMed

24. Lyngbæ, S, Marott, JL, Sehestedt, T, Hansen, TW, Olsen, MH, Andersen, O, et al.. Cardiovascular risk prediction in the general population with use of suPAR, CRP, and Framingham Risk Score. Int J Cardiol 2013;167:2904–11.10.1016/j.ijcard.2012.07.018Search in Google Scholar PubMed

25. Hamie, L, Daoud, G, Nemer, G, Nammour, T, El Chediak, A, Uthman, IW, et al.. SuPAR, an emerging biomarker in kidney and inflammatory diseases. Postgrad Med 2018;94:517–24.10.1136/postgradmedj-2018-135839Search in Google Scholar PubMed

26. Hodges, GW, Bang, CN, Wachtell, K, Eugen-Olsen, J, Jeppesen, JL. suPAR: a new biomarker for cardiovascular disease? Can J Cardiol 2015;31:1293–302.10.1016/j.cjca.2015.03.023Search in Google Scholar PubMed

27. Lyngbæk, S, Sehestedt, T, Marott, JL, Hansen, TW, Olsen, MH, Andersen, O, et al.. CRP and suPAR are differently related to anthropometry and subclinical organ damage. Int J Cardiol 2013;167:781–5.10.1016/j.ijcard.2012.03.040Search in Google Scholar PubMed

28. Blasi, F, Carmeliet, P. uPAR: a versatile signalling orchestrator. Nat Rev Mol Cell Biol 2002;3:932–43.10.1038/nrm977Search in Google Scholar PubMed

29. Madsen, CD, Ferraris, GM, Andolfo, A, Cunningham, O, Sidenius, N. uPAR-induced cell adhesion and migration: vitronectin provides the key. J Cell Biol 2007;177:927–39.10.1083/jcb.200612058Search in Google Scholar PubMed PubMed Central


Supplementary Material

The online version of this article offers supplementary material https://doi.org/10.1515/cclm-2020-0903.


Received: 2020-06-12
Accepted: 2021-01-22
Published Online: 2021-02-04
Published in Print: 2021-06-25

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 26.4.2024 from https://www.degruyter.com/document/doi/10.1515/cclm-2020-0903/html
Scroll to top button