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Original research article
Improvement of myocardial infarction risk prediction via inflammation-associated metabolite biomarkers
  1. Cavin K Ward-Caviness1,
  2. Tao Xu1,2,
  3. Thor Aspelund3,4,
  4. Barbara Thorand1,
  5. Corinna Montrone5,
  6. Christa Meisinger1,
  7. Irmtraud Dunger-Kaltenbach5,
  8. Astrid Zierer1,
  9. Zhonghao Yu1,2,
  10. Inga R Helgadottir3,
  11. Tamara B Harris6,
  12. Lenore J Launer6,
  13. Andrea Ganna7,
  14. Lars Lind8,
  15. Gudny Eiriksdottir3,
  16. Melanie Waldenberger1,2,
  17. Cornelia Prehn9,
  18. Karsten Suhre5,
  19. Thomas Illig10,
  20. Jerzy Adamski9,11,
  21. Andreas Ruepp5,12,
  22. Wolfgang Koenig13,14,15,
  23. Vilmundur Gudnason3,16,
  24. Valur Emilsson3,17,
  25. Rui Wang-Sattler1,2,
  26. Annette Peters1,15,18
  1. 1 Institute of Epidemiology II, Helmholtz Zentrum München, Neuherberg, Germany
  2. 2 Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
  3. 3 Icelandic Heart Association, Kopavogur, Iceland
  4. 4 Centre for Public Health, University of Iceland, Reykjavik, Iceland
  5. 5 Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany
  6. 6 National Institute on Aging, Bethesda, Maryland, USA
  7. 7 Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
  8. 8 Department of Medical Sciences and Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden
  9. 9 Institute of Experimental Genetics, Genome Analysis Center, Helmholtz Zentrum München, Neuherberg, Germany
  10. 10 Hannover Unified Biobank, Hannover Medical School, Hannover, Germany
  11. 11 Chair of Experimental Genetics, Technische Universität München, München, Germany
  12. 12 Chair of Experimental Genetics, Technische Universität München, München, Germany
  13. 13 Department of Internal Medicine II, University of Ulm Medical Center, Ulm, Germany
  14. 14 Deutsches Herzzentrum, Technische Universität München, München, Germany
  15. 15 DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munchen, Germany
  16. 16 Faculty of Medicine, University of Iceland, Reykjavik, Iceland
  17. 17 Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavik, Iceland
  18. 18 Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA
  1. Correspondence to Dr Rui Wang-Sattler, Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München, Ingolstädter Landstr. 1, Neuherberg 85764, Germany; rui.wang-sattler{at}helmholtz-muenchen.de

Abstract

Objective The comprehensive assaying of low-molecular-weight compounds, for example, metabolomics, provides a unique tool to uncover novel biomarkers and understand pathways underlying myocardial infarction (MI). We used a targeted metabolomics approach to identify biomarkers for MI and evaluate their involvement in the pathogenesis of MI.

Methods and results Using three independent, prospective cohorts (KORA S4, KORA S2 and AGES-REFINE), totalling 2257 participants without a history of MI at baseline, we identified metabolites associated with incident MI (266 cases). We also investigated the association between the metabolites and high-sensitivity C reactive protein (hsCRP) to understand the relation between these metabolites and systemic inflammation. Out of 140 metabolites, 16 were nominally associated (p<0.05) with incident MI in KORA S4. Three metabolites, arginine and two lysophosphatidylcholines (LPC 17:0 and LPC 18:2), were selected as biomarkers via a backward stepwise selection procedure in the KORA S4 and were significant (p<0.0003) in a meta-analysis comprising all three studies including KORA S2 and AGES-REFINE. Furthermore, these three metabolites increased the predictive value of the Framingham risk score, increasing the area under the receiver operating characteristic score in KORA S4 (from 0.70 to 0.78, p=0.001) and AGES-REFINE study (from 0.70 to 0.76, p=0.02), but was not observed in KORA S2. The metabolite biomarkers attenuated the association between hsCRP and MI, indicating a potential link to systemic inflammatory processes.

Conclusions We identified three metabolite biomarkers, which in combination increase the predictive value of the Framingham risk score. The attenuation of the hsCRP–MI association by these three metabolites indicates a potential link to systemic inflammation.

  • Myocardial infarction
  • biomarkers
  • metabolomics
  • inflammation

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Footnotes

  • Contributors Conception: CKW-C, TX, RW-S; study design: CKW-C, TX, RW-S, AP; data acquisition: TX, TA, BT, CM, ID-K, AZ, ZY, IRH, TBH, LJL, AG, LL, GE, MW, CP, KS, TI, JA, AR, WK, VG, VE; data analysis: TX, TA, AG, RW-S; data interpretation: CKW-C, TX, RW-S, VG, VE, AP, ID-K, CM, AR, WK; manuscript drafting: CKW-C, TX, RW-S; critical revision: CKW-C, TX, VG, WK, VE, RW-S, AP.

  • Funding The KORA study was initiated and financed by the Helmholtz Zentrum München – German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research (BMBF) and by the State of in part by the German Federal Ministry of Education and Research (BMBF) within the framework of the e:Med research and funding concept (grant 01ZX1313A-2014). Part of this project was supported by EU FP7 grants HEALTH-2009-2.2.1-3/242114 (Project OPTiMiSE) and HEALTH-2013-2.4.2-1/602936 (Project CarTarDis). Part of the work was funded by the German Ministry of Education and Research (Agreement No 01ZX1313C; DZHK MH5.1; MH5.2). KS is supported by ‘Biomedical Research Program’ funds at Weill Cornell Medical College in Qatar, a programme funded by the Qatar Foundation; The Age, Gene/Environment Susceptibility Reykjavik Study is funded by NIH contract N01-AG-12100, the NIA Intramural Research Program, Hjartavernd (the Icelandic Heart Association) and the Althingi (the Icelandic Parliament). IRH was supported by the PhD research fund at the University of Iceland. VG, TA and VE were supported by Icelandic Research Foundation grant (141101-051) at RANNIS.

  • Competing interests None declared.

  • Ethics approval This study involved data collected from human subjects. The collection and analysis of data from KORA was approved by the ethics committee of the Bavarian Medical Association,Germany. The usage of data for Age,Gene/Environment Susceptibility (AGES)-Reykjavik and the Risk Evaluation For Infarct Estimates (REFINE)-Reykjavik studies are approved by the Icelandic National Bioethics Committee (VSN: 00-063, VSN:05-112 respectively) and the Data Protection Authority.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Correction notice This paper has been amended since it was published Online First. Owing to a scripting error, some of the publisher names in the references were replaced with 'BMJ Publishing Group'. This only affected the full text version, not the PDF. We have since corrected these errors and the correct publishers have been inserted into the references.