Transcriptomic Biomarkers for Individual Risk Assessment in New-Onset Heart Failure

Background— Prediction of prognosis remains a major unmet need in new-onset heart failure (HF). Although several clinical tests are in use, none accurately distinguish between patients with poor versus excellent survival. We hypothesized that a transcriptomic signature, generated from a single endomyocardial biopsy, could serve as a novel prognostic biomarker in HF. Methods and Results— Endomyocardial biopsy samples and clinical data were collected from all patients presenting with new-onset HF from 1997 to 2006. Among a total of 350 endomyocardial biopsy samples, 180 were identified as idiopathic dilated cardiomyopathy. Patients with phenotypic extremes in survival were selected: good prognosis (event-free survival for at least 5 years; n=25) and poor prognosis (events [death, requirement for left ventricular assist device, or cardiac transplant] within the first 2 years of presentation with HF symptoms; n=18). We used human U133 Plus 2.0 microarrays (Affymetrix) and analyzed the data with significance analysis of microarrays and prediction analysis of microarrays. We identified 46 overexpressed genes in patients with good versus poor prognosis, of which 45 genes were selected by prediction analysis of microarrays for prediction of prognosis in a train set (n=29) with subsequent validation in test sets (n=14 each). The biomarker performed with 74% sensitivity (95% CI 69% to 79%) and 90% specificity (95% CI 87% to 93%) after 50 random partitions. Conclusions— These findings suggest the potential of transcriptomic biomarkers to predict prognosis in patients with new-onset HF from a single endomyocardial biopsy sample. In addition, our findings offer potential novel therapeutic targets for HF and cardiomyopathy.

[1]  M. Yacoub,et al.  Molecular signature of recovery following combination left ventricular assist device (LVAD) support and pharmacologic therapy. , 2006, European heart journal.

[2]  Andrey Morgun,et al.  Molecular Profiling Improves Diagnoses of Rejection and Infection in Transplanted Organs , 2006, Circulation research.

[3]  Aravinda Chakravarti,et al.  Nature, nurture and human disease , 2003, Nature.

[4]  Joshua M. Hare,et al.  Is stem cell therapy ready for patients? Stem Cell Therapy for Cardiac Repair. Ready for the Next Step . , 2006, Circulation.

[5]  R. Hajjar,et al.  Prospects for gene therapy for heart failure. , 2000, Circulation research.

[6]  S. Russell,et al.  Increased levels of uric acid predict haemodynamic compromise in patients with heart failure independently of B-type natriuretic peptide levels , 2007, Heart.

[7]  H. Ariga,et al.  Identification and cDNA cloning of single-stranded DNA binding proteins that interact with the region upstream of the human c-myc gene. , 1994, Oncogene.

[8]  Jun Ma,et al.  The peripheral blood transcriptome dynamically reflects system wide biology: a potential diagnostic tool. , 2006, The Journal of laboratory and clinical medicine.

[9]  T. Klingler,et al.  Noninvasive Discrimination of Rejection in Cardiac Allograft Recipients Using Gene Expression Profiling , 2006, American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons.

[10]  J. Shay,et al.  The involvement of the Mre11/Rad50/Nbs1 complex in the generation of G‐overhangs at human telomeres , 2006, EMBO reports.

[11]  Peter C Austin,et al.  Predicting mortality among patients hospitalized for heart failure: derivation and validation of a clinical model. , 2003, JAMA.

[12]  B. Gückel,et al.  Differential function of CD80- and CD86-transfected human melanoma cells in the presence of IL-12 and IFN-gamma. , 1997, International immunology.

[13]  A. Maisel,et al.  B-type natriuretic peptide levels: diagnostic and prognostic in congestive heart failure: what's next? , 2002, Circulation.

[14]  R H Hruban,et al.  Underlying causes and long-term survival in patients with initially unexplained cardiomyopathy. , 2000, The New England journal of medicine.

[15]  S. Dudoit,et al.  Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data , 2002 .

[16]  John D. Storey A direct approach to false discovery rates , 2002 .

[17]  N. Schork,et al.  Linkage disequilibrium analysis of biallelic DNA markers, human quantitative trait loci, and threshold-defined case and control subjects. , 2000, American journal of human genetics.

[18]  S. Ito,et al.  A novel WD40 repeat protein, WDC146, highly expressed during spermatogenesis in a stage-specific manner. , 2001, Biochemical and biophysical research communications.

[19]  Sayan Mukherjee,et al.  Estimating Dataset Size Requirements for Classifying DNA Microarray Data , 2003, J. Comput. Biol..

[20]  Catalin C. Barbacioru,et al.  Evaluation of DNA microarray results with quantitative gene expression platforms , 2006, Nature Biotechnology.

[21]  G. Shipley,et al.  Unloaded heart in vivo replicates fetal gene expression of cardiac hypertrophy , 1998, Nature Medicine.

[22]  J. Hare,et al.  Advances in cell-based therapy for structural heart disease. , 2007, Progress in cardiovascular diseases.

[23]  T. McBride,et al.  Enrollment in Medicare Part D for rural beneficiaries is encouraging. , 2007, Rural policy brief.

[24]  R. Quaife,et al.  Myocardial gene expression in dilated cardiomyopathy treated with beta-blocking agents. , 2002, The New England journal of medicine.

[25]  Francisco Azuaje,et al.  Computational biology for cardiovascular biomarker discovery , 2009, Briefings Bioinform..

[26]  H. V. van Houwelingen,et al.  A prognostic model for predicting waiting-list mortality for a total national cohort of adult heart-transplant candidates , 2003, Transplantation.

[27]  O. Jöhren,et al.  Hypoxia rapidly activates HIF‐3α mRNA expression , 2003 .

[28]  Jack Lucentini Gene association studies typically wrong , 2004 .

[29]  P. Wangemann,et al.  Microarray-based comparison of three amplification methods for nanogram amounts of total RNA. , 2005, American journal of physiology. Cell physiology.

[30]  J. Hare,et al.  The use of transcriptomic biomarkers for personalized medicine , 2007, Heart Failure Reviews.

[31]  Wei Pan,et al.  A comparative study of discriminating human heart failure etiology using gene expression profiles , 2005, BMC Bioinformatics.

[32]  K. Moore,et al.  Stem Cells and Their Niches , 2006, Science.

[33]  J. Schwartz,et al.  Development and prospective validation of a clinical index to predict survival in ambulatory patients referred for cardiac transplant evaluation. , 1996, Circulation.

[34]  J. Hare,et al.  The potential for the transcriptome to serve as a clinical biomarker for cardiovascular diseases. , 2006, Circulation research.

[35]  Yin Chen,et al.  Expression of ssDNA in mammalian cells. , 2003, BioTechniques.

[36]  Renee F Wilson,et al.  Systematic Review: Gene Expression Profiling Assays in Early-Stage Breast Cancer , 2008, Annals of Internal Medicine.

[37]  Rafael A Irizarry,et al.  Gene expression in giant cell myocarditis: Altered expression of immune response genes. , 2005, International journal of cardiology.

[38]  M. Moorhouse,et al.  DNA microarray analysis for human congenital heart disease , 2006, Cell Biochemistry and Biophysics.

[39]  B. McManus,et al.  Affymetrix oligonucleotide analysis of gene expression in the injured heart. , 2005, Methods in molecular medicine.

[40]  D. Richman,et al.  Isothermal, in vitro amplification of nucleic acids by a multienzyme reaction modeled after retroviral replication. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[41]  A. Bradley,et al.  Disruption of mRad50 causes embryonic stem cell lethality, abnormal embryonic development, and sensitivity to ionizing radiation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[42]  Chris T. A. Evelo,et al.  Biologically relevant effects of mRNA amplification on gene expression profiles , 2006, BMC Bioinformatics.

[43]  M. Le Cunff,et al.  Transcriptomal analysis of failing and nonfailing human hearts. , 2003, Physiological genomics.

[44]  Wim H van Harten,et al.  Use of 70-gene signature to predict prognosis of patients with node-negative breast cancer: a prospective community-based feasibility study (RASTER). , 2007, The Lancet. Oncology.

[45]  N. Nomura,et al.  Complete sequencing and characterization of 21,243 full-length human cDNAs , 2004, Nature Genetics.

[46]  K. Margulies,et al.  Mixed Messages: Transcription Patterns in Failing and Recovering Human Myocardium , 2005, Circulation research.

[47]  G. Parmigiani,et al.  Identification of a Gene Expression Profile That Differentiates Between Ischemic and Nonischemic Cardiomyopathy , 2004, Circulation.

[48]  R. Irizarry,et al.  Gene expression analysis of ischemic and nonischemic cardiomyopathy: shared and distinct genes in the development of heart failure. , 2005, Physiological genomics.

[49]  Stephen Archacki,et al.  Expression profiling of cardiovascular disease , 2004, Human Genomics.

[50]  M. Herrler,et al.  Linear mRNA amplification from as little as 5 ng total RNA for global gene expression analysis. , 2004, BioTechniques.

[51]  B. McManus,et al.  Genetic Determinants of Coxsackievirus B3 Pathogenesis , 2002, Annals of the New York Academy of Sciences.

[52]  C. Oakley,et al.  Prediction of outcome in dilated cardiomyopathy. , 1987, British heart journal.

[53]  Hanlee P. Ji,et al.  The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. , 2006, Nature biotechnology.

[54]  Guoying Liu,et al.  NetAffx: Affymetrix probesets and annotations , 2003, Nucleic Acids Res..

[55]  M. Bristow,et al.  Serial gene expression profiling in the intact human heart. , 2006, The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation.

[56]  G. Lanfranchi,et al.  Differential gene expression profiling in genetic and multifactorial cardiovascular diseases. , 2006, Journal of molecular and cellular cardiology.

[57]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[58]  M. Russell,et al.  Obscurin-like 1, OBSL1, is a novel cytoskeletal protein related to obscurin. , 2007, Genomics.

[59]  C. O'connor,et al.  The problem of decompensated heart failure: nomenclature, classification, and risk stratification. , 2003, American heart journal.

[60]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[61]  Maqc Consortium The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements , 2006, Nature Biotechnology.

[62]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[63]  O. Jöhren,et al.  Hypoxia rapidly activates HIF-3alpha mRNA expression. , 2003, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[64]  A. Remppis,et al.  Serum troponin T: diagnostic marker for acute myocarditis. , 1996, Clinical chemistry.

[65]  Renu Virmani,et al.  A Scientific Statement from the American Heart Association, the American College of Cardiology, and the European Society of Cardiology , 2022 .

[66]  Rafael A. Irizarry,et al.  Transcriptomics: Translation of Global Expression Analysis to Genomic Medicine , 2009 .

[67]  R. Tibshirani,et al.  Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[68]  K. Coombes,et al.  Comparison of the predictive accuracy of DNA array-based multigene classifiers across cDNA arrays and Affymetrix GeneChips. , 2005, The Journal of molecular diagnostics : JMD.

[69]  E. Topol,et al.  Identification of new genes differentially expressed in coronary artery disease by expression profiling. , 2003, Physiological genomics.

[70]  Hans Lehrach,et al.  Expression profiling of human idiopathic dilated cardiomyopathy. , 2003, Cardiovascular research.

[71]  D. Mozaffarian,et al.  The Seattle Heart Failure Model: Prediction of Survival in Heart Failure , 2006, Circulation.

[72]  G. Semenza Pulmonary vascular responses to chronic hypoxia mediated by hypoxia-inducible factor 1. , 2005, Proceedings of the American Thoracic Society.

[73]  P. Thomas,et al.  Hybridization of denatured RNA and small DNA fragments transferred to nitrocellulose. , 1980, Proceedings of the National Academy of Sciences of the United States of America.

[74]  T. Gingeras,et al.  Transcription-based amplification system and detection of amplified human immunodeficiency virus type 1 with a bead-based sandwich hybridization format. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[75]  M. Russell,et al.  Obscurin is required for the lateral alignment of striated myofibrils in zebrafish , 2006, Developmental dynamics : an official publication of the American Association of Anatomists.