Literature DB >> 18430805

Genomic analysis reveals poor separation of human cardiomyopathies of ischemic and nonischemic etiologies.

Ruprecht Kuner1, Andreas S Barth, Markus Ruschhaupt, Andreas Buness, Ludwig Zwermann, Eckart Kreuzer, Gerhard Steinbeck, Annemarie Poustka, Holger Sültmann, Michael Nabauer.   

Abstract

Clinically, the differentiation between ischemic (ICM) and nonischemic (NICM) human cardiomyopathies is highly relevant, because ICM and NICM differ with respect to prognosis and certain aspects of pharmacological therapy, despite a common final phenotype characterized by ventricular dilatation and reduced contractility. So far, it is unclear whether microarray-based signatures can be used to infer the etiology of heart failure. Using three different classification algorithms, we independently analyzed one cDNA and two publicly available high-density oligonucleotide microarray studies comprising a total of 279 end-stage human heart failure samples. When classifiers identified in a single study were applied to the remaining studies, misclassification rates >25% for ICM and NICM specimens were noted, indicating poor separation of both etiologies. However, data mining of 458 classifier genes that were concordantly identified in at least two of the three data sets points to different biological processes in ICM vs. NICM. Consistent with the underlying ischemia, cytokine signaling pathways and immediate-early response genes were overrepresented in ICM samples, whereas NICM samples displayed a deregulation of cytoskeletal transcripts, genes encoding for the major histocompatibility complex, and antigen processing and presentation pathways, potentially pointing to immunologic processes in NICM. Overall, our results suggest that ICM and NICM exhibit substantial heterogeneity at the transcriptomic level. Prospective studies are required to test whether etiology-specific gene expression patterns are present at earlier disease stages or in subsets of both etiologies.

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Year:  2008        PMID: 18430805     DOI: 10.1152/physiolgenomics.00299.2007

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  11 in total

1.  Gene expression profiling in peripheral blood nuclear cells in patients with refractory ischaemic end-stage heart failure.

Authors:  S Szmit; M Jank; H Maciejewski; M Grabowski; R Glowczynska; A Majewska; K J Filipiak; T Motyl; G Opolski
Journal:  J Appl Genet       Date:  2010       Impact factor: 3.240

2.  Right ventricular protein expression profile in end-stage heart failure.

Authors:  Yan Ru Su; Manuel Chiusa; Evan Brittain; Anna R Hemnes; Tarek S Absi; Chee Chew Lim; Thomas G Di Salvo
Journal:  Pulm Circ       Date:  2015-09       Impact factor: 3.017

3.  A kinase interacting protein (AKIP1) is a key regulator of cardiac stress.

Authors:  Mira Sastri; Kristofer J Haushalter; Mathivadhani Panneerselvam; Philip Chang; Heidi Fridolfsson; J Cameron Finley; Daniel Ng; Jan M Schilling; Atsushi Miyanohara; Michele E Day; Hiro Hakozaki; Susanna Petrosyan; Antonius Koller; Charles C King; Manjula Darshi; Donald K Blumenthal; Sameh Saad Ali; David M Roth; Hemal H Patel; Susan S Taylor
Journal:  Proc Natl Acad Sci U S A       Date:  2013-01-14       Impact factor: 11.205

4.  Reciprocal transcriptional regulation of metabolic and signaling pathways correlates with disease severity in heart failure.

Authors:  Andreas S Barth; Ami Kumordzie; Constantine Frangakis; Kenneth B Margulies; Thomas P Cappola; Gordon F Tomaselli
Journal:  Circ Cardiovasc Genet       Date:  2011-08-09

5.  Transcriptome signature of ventricular arrhythmia in dilated cardiomyopathy reveals increased fibrosis and activated TP53.

Authors:  Mary E Haywood; Andrea Cocciolo; Kadijah F Porter; Evgenia Dobrinskikh; Dobromir Slavov; Sharon L Graw; T Brett Reece; Amrut V Ambardekar; Michael R Bristow; Luisa Mestroni; Matthew R G Taylor
Journal:  J Mol Cell Cardiol       Date:  2020-01-18       Impact factor: 5.000

6.  Will global transcriptome analysis allow the detection of novel prognostic markers in coronary artery disease and heart failure?

Authors:  Monika Gora; Marek Kiliszek; Beata Burzynska
Journal:  Curr Genomics       Date:  2013-09       Impact factor: 2.236

7.  The transcriptomic profile of peripheral blood nuclear cells in dogs with heart failure.

Authors:  Magdalena Hulanicka; Magdalena Garncarz; Marta Parzeniecka-Jaworska; Michał Jank
Journal:  BMC Genomics       Date:  2014-06-21       Impact factor: 3.969

Review 8.  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.

Authors:  Cinzia Perrino; Albert-Laszló Barabási; Gianluigi Condorelli; Sean Michael Davidson; Leon De Windt; Stefanie Dimmeler; Felix Benedikt Engel; Derek John Hausenloy; Joseph Addison Hill; Linda Wilhelmina Van Laake; Sandrine Lecour; Jonathan Leor; Rosalinda Madonna; Manuel Mayr; Fabrice Prunier; Joost Petrus Geradus Sluijter; Rainer Schulz; Thomas Thum; Kirsti Ytrehus; Péter Ferdinandy
Journal:  Cardiovasc Res       Date:  2017-06-01       Impact factor: 10.787

9.  Transcriptome analysis of human heart failure reveals dysregulated cell adhesion in dilated cardiomyopathy and activated immune pathways in ischemic heart failure.

Authors:  Mary E Sweet; Andrea Cocciolo; Dobromir Slavov; Kenneth L Jones; Joseph R Sweet; Sharon L Graw; T Brett Reece; Amrut V Ambardekar; Michael R Bristow; Luisa Mestroni; Matthew R G Taylor
Journal:  BMC Genomics       Date:  2018-11-12       Impact factor: 3.969

10.  Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases.

Authors:  Lucas B Edelman; Giuseppe Toia; Donald Geman; Wei Zhang; Nathan D Price
Journal:  BMC Genomics       Date:  2009-12-05       Impact factor: 3.969

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