Display options
Cite
Vignoli A, Tenori L, Giusti B, et al. Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death. J Proteome Res. 2020;19(2):949-961doi: 10.1021/acs.jproteome.9b00779.
Vignoli, A., Tenori, L., Giusti, B., Valente, S., Carrabba, N., Balzi, D., Barchielli, A., Marchionni, N., Gensini, G. F., Marcucci, R., Gori, A. M., Luchinat, C., & Saccenti, E. (2020). Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death. Journal of proteome research, 19(2), 949-961. https://doi.org/10.1021/acs.jproteome.9b00779
Vignoli, Alessia, et al. "Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death." Journal of proteome research vol. 19,2 (2020): 949-961. doi: https://doi.org/10.1021/acs.jproteome.9b00779
Vignoli A, Tenori L, Giusti B, Valente S, Carrabba N, Balzi D, Barchielli A, Marchionni N, Gensini GF, Marcucci R, Gori AM, Luchinat C, Saccenti E. Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death. J Proteome Res. 2020 Feb 07;19(2):949-961. doi: 10.1021/acs.jproteome.9b00779. Epub 2020 Jan 17. PMID: 31899863; PMCID: PMC7011173.
Copy Download .nbib Format: NLM
Share it on

J Proteome Res. 2020 Feb 07;19(2):949-961. doi: 10.1021/acs.jproteome.9b00779. Epub 2020 Jan 17.

Differential Network Analysis Reveals Metabolic Determinants Associated with Mortality in Acute Myocardial Infarction Patients and Suggests Potential Mechanisms Underlying Different Clinical Scores Used To Predict Death.

Journal of proteome research

Alessia Vignoli, Leonardo Tenori, Betti Giusti, Serafina Valente, Nazario Carrabba, Daniela Balzi, Alessandro Barchielli, Niccolò Marchionni, Gian Franco Gensini, Rossella Marcucci, Anna Maria Gori, Claudio Luchinat, Edoardo Saccenti

Affiliations

  1. Magnetic Resonance Center (CERM) , University of Florence , Sesto Fiorentino 50019 , Italy.
  2. Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.) , Sesto Fiorentino 50019 , Italy.
  3. Department of Experimental and Clinical Medicine , University of Florence , Florence 50134 Italy.
  4. Atherothrombotic Diseases Center , Careggi Hospital , Florence 50134 , Italy.
  5. Excellence Centre for Research, Transfer and High Education for the Development of DE NOVO Therapies (DENOTHE) , University of Florence , Florence 50134 , Italy.
  6. Department of Cardiovascular and Thoracic Surgery , Careggi Hospital , Florence 50134 , Italy.
  7. Unit of Epidemiology , ASL 10, Florence 50122 , Italy.
  8. Centro Studi Medicina Avanzata (CESMAV) , Florence 50121 Italy.
  9. Department of Chemistry , University of Florence , Sesto Fiorentino 50019 , Italy.
  10. Laboratory of Systems and Synthetic Biology , Wageningen University & Research , Wageningen 6708 WE , the Netherlands.

PMID: 31899863 PMCID: PMC7011173 DOI: 10.1021/acs.jproteome.9b00779

Abstract

We present here the differential analysis of metabolite-metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 patients of which 123 died within 2 years from acute myocardial infarction (AMI). We investigated differences in metabolite connectivity of patients who survived, at 2 years, the AMI event, and we characterized metabolite-metabolite association networks specific to high and low risks of death according to four different risk parameters, namely, acute coronary syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomics NOESY RF risk score. We show significant differences in the connectivity patterns of several low-molecular-weight molecules, implying variations in the regulation of several metabolic pathways regarding branched-chain amino acids, alanine, creatinine, mannose, ketone bodies, and energetic metabolism. Our results demonstrate that the characterization of metabolite-metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.

Keywords: acute myocardial infarction; metabolite−metabolite association networks; metabolomics; network inference; nuclear magnetic resonance

References

  1. J Proteome Res. 2018 Jan 5;17(1):97-107 - PubMed
  2. J Proteomics. 2017 May 8;160:38-46 - PubMed
  3. Am J Physiol Heart Circ Physiol. 2016 Nov 1;311(5):H1160-H1169 - PubMed
  4. Nat Rev Cardiol. 2019 Mar;16(3):133 - PubMed
  5. Lancet. 2010 Jan 9;375(9709):132-40 - PubMed
  6. Angew Chem Int Ed Engl. 2019 Jan 21;58(4):968-994 - PubMed
  7. Cell Metab. 2017 Aug 1;26(2):281-283 - PubMed
  8. J Am Heart Assoc. 2017 Oct 20;6(10): - PubMed
  9. J Proteome Res. 2019 Mar 1;18(3):1228-1236 - PubMed
  10. Interv Cardiol. 2018 Sep;13(3):112-120 - PubMed
  11. Metabolomics. 2018;14(4):37 - PubMed
  12. Arterioscler Thromb Vasc Biol. 2012 Aug;32(8):e51-9 - PubMed
  13. Cardiovasc Res. 1997 Feb;33(2):243-57 - PubMed
  14. Clin Cancer Res. 2017 Mar 15;23(6):1422-1431 - PubMed
  15. Circulation. 2016 May 24;133(21):2038-49 - PubMed
  16. PLoS Biol. 2005 Jul;3(7):e228 - PubMed
  17. J Am Coll Cardiol. 2011 May 10;57(19):e215-367 - PubMed
  18. J Diabetes Res. 2016;2016:3898502 - PubMed
  19. World J Cardiol. 2014 Aug 26;6(8):865-73 - PubMed
  20. PLoS One. 2019 Sep 18;14(9):e0222353 - PubMed
  21. Med Hypotheses. 2009 Aug;73(2):263-4 - PubMed
  22. ScientificWorldJournal. 2012;2012:186495 - PubMed
  23. Int J Cardiol. 2016 Feb 1;204:112-3 - PubMed
  24. J Biomed Inform. 2018 May;81:53-60 - PubMed
  25. J Biol Chem. 1977 Jul 25;252(14):5010-8 - PubMed
  26. J Invasive Cardiol. 2009 Oct;21(10):493-8 - PubMed
  27. Sci Rep. 2016 Nov 08;6:36359 - PubMed
  28. J Biol Chem. 2011 Mar 25;286(12):10193-200 - PubMed
  29. Eur Heart J Acute Cardiovasc Care. 2018 Dec;7(8):739-742 - PubMed
  30. Front Pharmacol. 2018 Apr 17;9:258 - PubMed
  31. Anal Bioanal Chem. 2017 Feb;409(5):1405-1413 - PubMed
  32. Annu Rev Nutr. 1984;4:409-54 - PubMed
  33. Metabolomics. 2015;11(6):1815-1833 - PubMed
  34. Cancer Treat Rev. 2018 Jun;67:88-96 - PubMed
  35. N Engl J Med. 2001 Apr 12;344(15):1140-4 - PubMed
  36. Sci Rep. 2019 Aug 13;9(1):11742 - PubMed
  37. Diabetes Care. 2011 Apr;34(4):982-7 - PubMed
  38. BMC Med. 2019 Jan 7;17(1):3 - PubMed
  39. Exp Biol Med (Maywood). 2012 Dec;237(12):1369-78 - PubMed
  40. Thromb Haemost. 2013 May;109(5):846-53 - PubMed
  41. Circulation. 2015 Jan 27;131(4):e29-322 - PubMed
  42. Am J Cardiol. 1967 Oct;20(4):457-64 - PubMed
  43. J Biomol NMR. 2011 Apr;49(3-4):231-43 - PubMed
  44. J Am Heart Assoc. 2015 Dec 31;5(1): - PubMed
  45. Atherosclerosis. 2007 Oct;194(2):397-402 - PubMed
  46. Atherosclerosis. 2015 Oct;242(2):589-94 - PubMed
  47. Am Heart J. 2007 Jan;153(1):29-35 - PubMed
  48. Front Physiol. 2018 Aug 29;9:1017 - PubMed
  49. Zhongguo Yao Li Xue Bao. 1998 Sep;19(5):493-6 - PubMed
  50. J Proteome Res. 2015 Feb 6;14(2):1101-11 - PubMed
  51. Sci Rep. 2018 Oct 25;8(1):15809 - PubMed
  52. Br J Pharmacol. 2014 Apr;171(8):2080-90 - PubMed
  53. Circulation. 2001 Sep 18;104(12):1413-8 - PubMed
  54. Eur Heart J. 2019 Sep 7;40(34):2883-2896 - PubMed
  55. Eur Heart J. 2013 Jul;34(26):1982-9 - PubMed
  56. Nucleic Acids Res. 2013 Jan;41(Database issue):D801-7 - PubMed
  57. J Proteome Res. 2016 Sep 2;15(9):3298-307 - PubMed
  58. Clin Transl Sci. 2012 Jun;5(3):285-8 - PubMed
  59. BMC Syst Biol. 2011 Jan 31;5:21 - PubMed
  60. J Proteome Res. 2017 Jul 7;16(7):2547-2559 - PubMed
  61. Int J Clin Exp Med. 2014 Dec 15;7(12):5588-92 - PubMed
  62. Ann Med. 2009;41(8):591-8 - PubMed
  63. PLoS One. 2017 Apr 17;12(4):e0175591 - PubMed
  64. Rambam Maimonides Med J. 2018 Jul 30;9(3): - PubMed

MeSH terms

Publication Types