[Limitations and potential of combined epigenetic and transcriptional analysis on a large scale to identify therapeutic targets in cardiovascular diseases]
Abstract
Cardiovascular diseases are the major cause of morbidity and mortality worldwide. Given the complex pathophysiology of cardiovascular diseases, an experimental approach capable of identifying multiple signaling networks activated in the heart upon pathological conditions could be particularly effective to identify new diagnostic, prognostic or therapeutic targets. Latest generation techniques now allow high-resolution investigations of the entire genome, the proteome and the cellular metabolome, as well as epigenetic modifications and associated gene expression profiles.
In particular, the integration of epigenomic and transcriptomic data in the normal or pathological heart is a promising approach to identify novel molecular targets. These methods, although promising and innovative, can present several technical and analytical pitfalls. Here we will briefly describe these aspects and possible strategies to optimize the search for new diagnostic or therapeutic targets for cardiovascular diseases in the post-genomic era.
References
- 1) Lander ES, Linton LM, Birren B, et al. International Human Genome Sequencing Consortium. Initial sequencing and analysis of the human genome. Nature 2001; 409(6822): 860-921. DOI: https://doi.org/10.1038/35057062
- 2) Varga ZV, Giricz Z, Bencsik P, et al. Functional genomics of cardioprotection by ischemic conditioning and the influence of comorbid conditions: implications in target identification. Curr Drug Targets Cardiovasc Res 2015; 16(8): 904-11. DOI: https://doi.org/10.2174/1389450116666150427154203
- 3) Perrino C, Barabàsi AL, Condorelli G, et al. Epigenomic and transcriptomic approaches in the post-genomic era: path to novel targets for diagnosis and therapy of the ischaemic heart? Position Paper of the European Society of Cardiology Working Group on Cellular Biology of the Heart. Cardiovasc Res 2017; 113(7): 725-36. 4) Raghow R. An 'Omics' perspective on cardiomyopathies and heart failure. Trends Mol Med 2016; 22(9): 813-27. DOI: https://doi.org/10.1093/cvr/cvx070
- 5) Simkhovich BZ, Abdishoo S, Poizat C, et al. Gene activity changes in ischemically preconditioned rabbit heart gene: discovery array study. Heart Dis 2002; 4(2): 63-9. DOI: https://doi.org/10.1097/00132580-200203000-00002
- 6) Madonna R, Van Laake LW, Davidson SM, et al. Position Paper of the European Society of Cardiology Working Group Cellular Biology of the Heart: cell-based therapies for myocardial repair and regeneration in ischemic heart disease and heart failure. Eur Heart J 2016; 37(23): 1789-98. DOI: https://doi.org/10.1093/eurheartj/ehw113
- 7) Papait R, Cattaneo P, Kunderfranco P, et al. Genome-wide analysis of histone marks identifying an epigenetic signature of promoters and enhancers underlying cardiac hypertrophy. Proc Natl Acad Sci USA 2013; 110(50): 20164-9 8) Angrisano T, Schiattarella GG, Keller S, et al. Epigenetic switch at atp2a2 and myh7 gene promoters in pressure overload-induced heart failure. PLoS One 2014; 9(9): e106024. DOI: https://doi.org/10.1073/pnas.1315155110
- 9) Gilsbach R, Preissl S, Grüning BA, et al. Dynamic DNA methylation orchestrates cardiomyocyte development, maturation and disease. Nature Communications 2014; 5:5288. DOI: https://doi.org/10.1038/ncomms6288
- 10) Greco CM, Kunderfranco P, Rubino M, et al. DNA hydroxymethylation controls cardiomyocyte gene expression in development and hypertrophy. Nature Communications 2016; 7: 12418. DOI: https://doi.org/10.1038/ncomms12418
- 11) Movassagh M, Choy MK, Goddard M, et al. Differential DNA methylation correlates with differential expression of angiogenic factors in human heart failure. PLos One 2010; 5(5): e8564. DOI: https://doi.org/10.1371/journal.pone.0008564
- 12) Movassagh M, Choy MK, Knowles DA, et al. Distinct epigenomic features in end-stage failing human hearts. Circulation 2011; 124(22): 2411-22. DOI: https://doi.org/10.1161/CIRCULATIONAHA.111.040071
- 13) Meder B, Haas J, Sedaghat-Hamedani F, et al. Epigenome-Wide Association Study Identifies Cardiac Gene Patterning and a Novel Class of Biomarkers for Heart Failure. Circulation 2017; 136(16): 1528-44. DOI: https://doi.org/10.1161/CIRCULATIONAHA.117.027355
- 14) Haas J, Frese KS, Park YJ, et al. Alterations in cardiac DNA methylation in human dilated cardiomyopathy. EMBO Mol Med 2013; 5(3): 413-29. DOI: https://doi.org/10.1002/emmm.201201553
- 15) Haider S, Cordeddu L, Robinson E, et al. The landscape of DNA repeat elements in human heart failure. Genome Biol 2012; 13(10): R90. DOI: https://doi.org/10.1186/gb-2012-13-10-r90
- 16) Puskas LG, Nagy ZB, Giricz Z, et al. Cholesterol diet-induced hyperlipidemia influences gene expression pattern of rat hearts: a DNA microarray study. FEBS Lett 2004; 562(1-3): 99-104. DOI: https://doi.org/10.1016/S0014-5793(04)00189-9
- 17) Georgiadi A, Boekschoten MV, Muller M, et al. Detailed transcriptomics analysis of the effect of dietary fatty acids on gene expression in the heart. Physiol Genomics 2012; 44(6): 352-61. DOI: https://doi.org/10.1152/physiolgenomics.00115.2011
- 18) Philip-Couderc P, Smih F, Hall JE, et al. Kinetic analysis of cardiac transcriptome regulation during chronic high-fat diet in dogs. Physiol Genomics 2004; 19(1): 32-40. DOI: https://doi.org/10.1152/physiolgenomics.00001.2004
- 19) Philip-Couderc P, Pathak A, Smih F, et al. Uncomplicated human obesity is associated with a specific cardiac transcriptome: involvement of the Wnt pathway. FASEB J 2004; 18(13): 1539-40. 20) Ferdinandy P, Hausenloy DJ, Heusch G, et al. Interaction of risk factors, comorbidities, and comedications with ischemia/reperfusion injury and cardioprotection by preconditioning, postconditioning, and remote conditioning. Pharmacol Rev 2014; 66(4): 1142-74. 21) Rivera CM, Ren B. Mapping human epigenomes. Cell 2013; 155(1): 39-55. DOI: https://doi.org/10.1124/pr.113.008300
- 22) Esposito G, Perrino C, Schiattarella GG, et al. Induction of mitogenactivated protein kinases is proportional to the amount of pressure overload. Hypertension 2010 Jan; 55(1): 137-43. DOI: https://doi.org/10.1161/HYPERTENSIONAHA.109.135467
- 23) McCarroll SA, Murphy CT, Zou S, et al. Comparing genomic expression patterns across species identifies shared transcriptional profile in aging. Nat Genet 2004; 36(2): 197-204. DOI: https://doi.org/10.1038/ng1291
- 24) Kooij V, Venkatraman V, Tra J, et al. Sizing up models of heart failure: proteomics from flies to humans. Proteomics Clin Appl 2014; 8(9-10): 653-64. DOI: https://doi.org/10.1002/prca.201300123
- 25) DeLaughter DM, Bick AG, Wakimoto H, et al. Single-cell resolution of temporal gene expression during heart development. Dev Cell 2016; 39(4): 480-90. DOI: https://doi.org/10.1016/j.devcel.2016.10.001
- 26) Ferrazzi F, Bellazzi R, Engel FB. Gene network analysis: from heart development to cardiac therapy. Thromb Haemost 2015; 113(3): 522-31. DOI: https://doi.org/10.1160/TH14-06-0483
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