Abstract
INTRODUCTION: One of the clinical dilemmas in cardiology is to accurately diagnose the etiology of patients with new onset heart failure such as to differentiate between potentially reversible myocarditis from idiopathic dilated cardiomyopathy (IDCM). Furthermore, it is difficult to predict the clinical trajectory of patients with IDCM. We hypothesized that the transcriptomic signatures generated from endomyocardial biopsies, obtained from patients at first presentation of heart failure, could serve as novel biomarkers to distinguish between myocarditis and IDCM as well as to predict the prognosis of patients classified as having IDCM.
METHODS AND RESULTS: Endomyocardial biopsy samples were collected from 68 patients with new onset heart failure due to IDCM (n=49) and myocarditis (n=19). The average follow-up was 5 years and included information on mortality, need for left ventricular assist device (LVAD), or heart transplant. We used the U133 Plus 2.0 microarray (Affymetrix) and data analysis was performed with Significance Analysis of Microarrays (SAM) and Prediction Analysis of Microarrays (PAM). First, we identified a molecular signature of 39 genes in our training cohort (n=25 IDCM and n=8 myocarditis). When tested in independent patients (myocarditis: n=11; IDCM: n=11), this signature performed with 97% accuracy. Next, we identified a transcriptomic signature of 45 genes in a group of patients with IDCM that delineated between patients classified as having a good prognosis (event free survival > 5 years; n=18) vs a bad prognosis (death or requirement for insertion of LVAD or tx within 2 years of presentation; n=12). We tested this biomarker in independent samples and were able to predict prognosis with 87% accuracy. The transcriptomic biomarker was substantially more accurate in assigning prognosis than the Seattle Heart Failure Score (p=0.011).
CONCLUSION: Together these findings illustrate the potential utility of using transcriptomic biomarkers generated from a single endomyocardial biopsy to improve the accuracy of diagnosis and prognosis in patients with new onset heart failure. This creates novel modalities to enhance management and identification of patients at highest risk for complications of heart failure in the short term.