Skip to main content
SpringerLink
Log in

Integrated protein network and microarray analysis to identify potential biomarkers after myocardial infarction

  • Original Paper
  • Published:
Functional & Integrative Genomics Aims and scope Submit manuscript

Abstract

A significant proportion of patients develop left ventricular (LV) dysfunction and heart failure (HF) after acute myocardial infarction (MI). Existing biomarkers of HF provide limited information after MI. To identify new prognostic biomarkers in MI patients, we designed an approach combining protein interaction networks and microarray analysis of blood cells. Blood samples for RNA and protein analysis were taken from 127 acute MI patients. Echocardiography was performed at one month. Assuming that angiogenesis is related to cardiac repair after MI, a protein-protein interaction network of angiogenesis was constructed and analyzed. Among the 556 proteins and 686 interactions of this network, a cluster of 53 proteins highly specialized in regulation of cell growth was identified. Of these 53 proteins, 38 were found differentially expressed by microarrays between low (≤ 40%) and high (>40%) LV ejection fraction (EF) patients (n = 32). Among these 38 genes, prediction analysis identified a set of three genes able to predict significant LV dysfunction (EF ≤ 40%) with an area under the receiver operating characteristic curve (AUC) of 0.82. These three genes—vascular endothelial growth factor B, thrombospondin-1 and placental growth factor—had a stronger predictive value than brain natriuretic peptide and troponin T (AUC of 0.63). Independent validations on protein expression and quantitative PCR datasets confirmed the results. In conclusion, a new strategy is described that allows identifying new potential biomarkers. The three specific biomarkers described here remain to be validated in a larger patient population.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Al-Shahrour F, Minguez P, Tarraga J, Montaner D, Alloza E, Vaquerizas JM, Conde L, Blaschke C, Vera J, Dopazo J (2006) BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Res 34:W472–W476

    Article  CAS  PubMed  Google Scholar 

  • Bader GD, Hogue CW (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4:2

    Article  PubMed  Google Scholar 

  • Bellomo D, Headrick JP, Silins GU, Paterson CA, Thomas PS, Gartside M, Mould A, Cahill MM, Tonks ID, Grimmond SM, Townson S, Wells C, Little M, Cummings MC, Hayward NK, Kay GF (2000) Mice lacking the vascular endothelial growth factor-B gene (Vegfb) have smaller hearts, dysfunctional coronary vasculature, and impaired recovery from cardiac ischemia. Circ Res 86:E29–E35

    CAS  PubMed  Google Scholar 

  • Braunwald E (2008) Biomarkers in heart failure. N Engl J Med 358:2148–2159

    Article  CAS  PubMed  Google Scholar 

  • Brindle JT, Antti H, Holmes E, Tranter G, Nicholson JK, Bethell HW, Clarke S, Schofield PM, McKilligin E, Mosedale DE, Grainger DJ (2002) Rapid and noninvasive diagnosis of the presence and severity of coronary heart disease using 1H-NMR-based metabonomics. Nat Med 8:1439–1444

    Article  CAS  PubMed  Google Scholar 

  • Cappuzzello C, Napolitano M, Arcelli D, Melillo G, Melchionna R, Di Vito L, Carlini D, Silvestri L, Brugaletta S, Liuzzo G, Crea F, Capogrossi MC (2009) Gene expression profiles in peripheral blood mononuclear cells of chronic heart failure patients. Physiol Genomics 38:233–240

    Article  PubMed  Google Scholar 

  • Carmeliet P, Baes M (2008) Metabolism and therapeutic angiogenesis. N Engl J Med 358:2511–2512

    Article  CAS  PubMed  Google Scholar 

  • Chatila K, Ren G, Xia Y, Huebener P, Bujak M, Frangogiannis NG (2007) The role of the thrombospondins in healing myocardial infarcts. Cardiovasc Hematol Agents Med Chem 5:21–27

    CAS  PubMed  Google Scholar 

  • Chin BS, Blann AD, Gibbs CR, Chung NA, Conway DG, Lip GY (2003) Prognostic value of interleukin-6, plasma viscosity, fibrinogen, von Willebrand factor, tissue factor and vascular endothelial growth factor levels in congestive heart failure. Eur J Clin Invest 33:941–948

    Article  CAS  PubMed  Google Scholar 

  • Cleary JG, Trigg L (1995) K*: an instance-based learner using an entropic distance measure. Proc Machine Learning '95, Lake Tahoe, USA:108–114

  • Ferrara N, Gerber HP, LeCouter J (2003) The biology of VEGF and its receptors. Nat Med 9:669–676

    Article  CAS  PubMed  Google Scholar 

  • Frank E, Hall M, Trigg L, Holmes G, Witten IH (2004) Data mining in bioinformatics using Weka. Bioinformatics 20:2479–2481

    Article  CAS  PubMed  Google Scholar 

  • Good DJ, Polverini PJ, Rastinejad F, Le Beau MM, Lemons RS, Frazier WA, Bouck NP (1990) A tumor suppressor-dependent inhibitor of angiogenesis is immunologically and functionally indistinguishable from a fragment of thrombospondin. Proc Natl Acad Sci U S A 87:6624–6628

    Article  CAS  PubMed  Google Scholar 

  • Hoeben A, Landuyt B, Highley MS, Wildiers H, Van Oosterom AT, De Bruijn EA (2004) Vascular endothelial growth factor and angiogenesis. Pharmacol Rev 56:549–580

    Article  CAS  PubMed  Google Scholar 

  • Horwitz PA, Tsai EJ, Putt ME, Gilmore JM, Lepore JJ, Parmacek MS, Kao AC, Desai SS, Goldberg LR, Brozena SC, Jessup ML, Epstein JA, Cappola TP (2004) Detection of cardiac allograft rejection and response to immunosuppressive therapy with peripheral blood gene expression. Circulation 110:3815–3821

    Article  CAS  PubMed  Google Scholar 

  • King JY, Ferrara R, Tabibiazar R, Spin JM, Chen MM, Kuchinsky A, Vailaya A, Kincaid R, Tsalenko A, Deng DX-F, Connolly A, Zhang P, Yang E, Watt C, Yakhini Z, Ben-Dor A, Adler A, Bruhn L, Tsao P, Quertermous T, Ashley EA (2005) Pathway analysis of coronary atherosclerosis. Physiol Genomics 23:103–118

    Article  CAS  PubMed  Google Scholar 

  • Kolakowski S, Berry MF, Atluri P, Grand T, Fisher O, Moise MA, Cohen J, Hsu V, Woo YJ (2006) Placental growth factor provides a novel local angiogenic therapy for ischemic cardiomyopathy. J Card Surg 21:559–564

    Article  PubMed  Google Scholar 

  • Le Brigand K, Barbry P (2007) Mediante: a web-based microarray data manager. Bioinformatics 23:1304–1306

    Article  PubMed  Google Scholar 

  • Le Brigand K, Russell R, Moreilhon C, Rouillard JM, Jost B, Amiot F, Magnone V, Bole-Feysot C, Rostagno P, Virolle V, Defamie V, Dessen P, Williams G, Lyons P, Rios G, Mari B, Gulari E, Kastner P, Gidrol X, Freeman TC, Barbry P (2006) An open-access long oligonucleotide microarray resource for analysis of the human and mouse transcriptomes. Nucleic Acids Res 34:e87

    Article  PubMed  Google Scholar 

  • Lee SH, Wolf PL, Escudero R, Deutsch R, Jamieson SW, Thistlethwaite PA (2000) Early expression of angiogenesis factors in acute myocardial ischemia and infarction. N Engl J Med 342:626–633

    Article  CAS  PubMed  Google Scholar 

  • Michowitz Y, Goldstein E, Wexler D, Sheps D, Keren G, George J (2007) Circulating endothelial progenitor cells and clinical outcome in patients with congestive heart failure. Heart 93:1046–1050

    Article  PubMed  Google Scholar 

  • Montaner D, Tarraga J, Huerta-Cepas J, Burguet J, Vaquerizas JM, Conde L, Minguez P, Vera J, Mukherjee S, Valls J, Pujana MA, Alloza E, Herrero J, Al-Shahrour F, Dopazo J (2006) Next station in microarray data analysis: GEPAS. Nucleic Acids Res 34:W486–W491

    Article  CAS  PubMed  Google Scholar 

  • Nonaka-Sarukawa M, Yamamoto K, Aoki H, Nishimura Y, Tomizawa H, Ichida M, Eizawa T, Muroi K, Ikeda U, Shimada K (2007) Circulating endothelial progenitor cells in congestive heart failure. Int J Cardiol 119:344–348

    Article  PubMed  Google Scholar 

  • Novikov E, Barillot E (2007) Software package for automatic microarray image analysis (MAIA). Bioinformatics 23:639–640

    Article  CAS  PubMed  Google Scholar 

  • Peri S, Navarro JD, Amanchy R, Kristiansen TZ, Jonnalagadda CK, Surendranath V, Niranjan V, Muthusamy B, Gandhi TK, Gronborg M, Ibarrola N, Deshpande N, Shanker K, Shivashankar HN, Rashmi BP, Ramya MA, Zhao Z, Chandrika KN, Padma N, Harsha HC, Yatish AJ, Kavitha MP, Menezes M, Choudhury DR, Suresh S, Ghosh N, Saravana R, Chandran S, Krishna S, Joy M, Anand SK, Madavan V, Joseph A, Wong GW, Schiemann WP, Constantinescu SN, Huang L, Khosravi-Far R, Steen H, Tewari M, Ghaffari S, Blobe GC, Dang CV, Garcia JG, Pevsner J, Jensen ON, Roepstorff P, Deshpande KS, Chinnaiyan AM, Hamosh A, Chakravarti A, Pandey A (2003) Development of human protein reference database as an initial platform for approaching systems biology in humans. Genome Res 13:2363–2371

    Article  CAS  PubMed  Google Scholar 

  • Platt J (1998) Sequential minimal optimization: a fast algorithm for training support vector machines. Microsoft Research Technical Report MSR-TR-98-14. http://research.microsoft.com/en-us/um/people/jplatt/smotr.pdf. Accessed 16 April 2010

  • Richards AM, Nicholls MG, Espiner EA, Lainchbury JG, Troughton RW, Elliott J, Frampton C, Turner J, Crozier IG, Yandle TG (2003) B-type natriuretic peptides and ejection fraction for prognosis after myocardial infarction. Circulation 107:2786–2792

    Article  CAS  PubMed  Google Scholar 

  • Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504

    Article  CAS  PubMed  Google Scholar 

  • Talwar S, Squire IB, Downie PF, McCullough AM, Campton MC, Davies JE, Barnett DB, Ng LL (2000) Profile of plasma N-terminal proBNP following acute myocardial infarction; correlation with left ventricular systolic dysfunction. Eur Heart J 21:1514–1521

    Article  CAS  PubMed  Google Scholar 

  • Torabi A, Cleland JG, Khan NK, Loh PH, Clark AL, Alamgir F, Caplin JL, Rigby AS, Goode K (2008) The timing of development and subsequent clinical course of heart failure after a myocardial infarction. Eur Heart J 29:859–870

    Article  PubMed  Google Scholar 

  • Tusher VG, Tibshirani R, Chu G (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc Natl Acad Sci U S A 98:5116–5121

    Article  CAS  PubMed  Google Scholar 

  • Ware JH (2006) The limitations of risk factors as prognostic tools. N Engl J Med 355:2615–2617

    Article  CAS  PubMed  Google Scholar 

  • Wingrove JA, Daniels SE, Sehnert AJ, Tingley W, Elashoff M, Rosenberger S, Buellesfeld L, Grube E, Newby LK, Ginsburg GS, Kraus WE (2008) Correlation of peripheral-blood gene expression with the extent of coronary artery stenosis. Circ Cardiovasc Genet 1:31–38

    Article  CAS  PubMed  Google Scholar 

  • Zentilin L, Puligadda U, Lionetti V, Zacchigna S, Collesi C, Pattarini L, Ruozi G, Camporesi S, Sinagra G, Pepe M, Recchia FA, Giacca M (2009) Cardiomyocyte VEGFR-1 activation by VEGF-B induces compensatory hypertrophy and preserves cardiac function after myocardial infarction. FASEB J DOI. doi:10.1096/fj.09-143180

    Google Scholar 

  • Zethelius B, Berglund L, Sundstrom J, Ingelsson E, Basu S, Larsson A, Venge P, Arnlov J (2008) Use of multiple biomarkers to improve the prediction of death from cardiovascular causes. N Engl J Med 358:2107–2116

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors thank Céline Jeanty, Malou Gloesener and Loredana Jacobs for expert technical assistance. We also thank Dr. Georges Gilson, Laboratory of Biochemistry, Centre Hospitalier, Luxembourg, for NT-pro-BNP assessment. This work was supported by grants from the Society for Research on Cardiovascular Diseases, the National Funds for Research, and the Ministry of Culture, Higher Education and Research of Luxembourg.

Author information

Authors and Affiliations

  1. Laboratory of Cardiovascular Research, Centre de Recherche Public-Santé, 120 route d’Arlon, 1150, Luxembourg, Luxembourg

    Yvan Devaux, Francisco Azuaje, Mélanie Vausort & Céline Yvorra

  2. Division of Cardiology, Centre Hospitalier, 4 rue Barblé, 1210, Luxembourg, Luxembourg

    Daniel R. Wagner

Authors
  1. Yvan Devaux
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Francisco Azuaje
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mélanie Vausort
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Céline Yvorra
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Daniel R. Wagner
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yvan Devaux.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Devaux, Y., Azuaje, F., Vausort, M. et al. Integrated protein network and microarray analysis to identify potential biomarkers after myocardial infarction. Funct Integr Genomics 10, 329–337 (2010). https://doi.org/10.1007/s10142-010-0169-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10142-010-0169-0

Keywords

Search

Navigation