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.

Quantitative assessment of cell adhesion molecule gene expression in endomyocardial biopsy specimens from cardiac transplant recipients using competitive polymerase chain reaction.

BACKGROUND: Adhesion of leukocytes to vascular endothelium is an early step in cardiac allograft rejection leading to migration of lymphocytes into parenchymal tissues. Cell adhesion molecule (CAM) protein expression appears to increase as a result of rejection. The relationship of CAM gene expression to rejection is less well defined. The goal of this study was to define cell adhesion molecule gene expression in relation to the presence of acute cellular rejection in endomyocardial biopsies from cardiac transplant recipients. METHODS: To quantitatively assess intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1) and E-selectin gene expression, we developed a competitive PCR system using nonhomologous DNA fragments (MIMICs) with complementary sequences to CAM gene-specific primers as internal standards. MIMIC fragments with known concentrations were mixed in serial dilutions with constant amounts of cDNA from the biopsy specimens and amplified with common primers under the same polymerase chain reaction conditions. The relative CAM cDNA concentrations were determined by comparing the density of MIMIC to target cDNA bands on agarose gel. ICAM-1, VCAM-1, and E-selectin mRNA concentrations were analyzed from 38 cardiac transplant biopsies divided into 3 groups according to ISHLT rejection grade: group 1-grade 0 (n=13); group 2-grade 1A or 1B (n=13); group 3-grade 3A (n=12). Glyceraldehyde-3-phosphate dehydrogenase (a constitutive gene) was quantified in the same way as CAMs to normalize the relative levels of CAMs. RESULTS: The results expressed as mean (1x10(-3) pM) (+/-SEM) in groups 1, 2, and 3, respectively, were: ICAM-1; 5+/-1; 57+/-4*; 64+/-13*, VCAM-1; 0.8+/-0.1; 6+/-1**; 9+/-1*, E-selectin; 0.4+/-0.2; 0.8+/-0.2; 0.4+/-0.1 (*P<0.001 versus group 1; **P<0.01 versus group 1). CONCLUSIONS: ICAM-1 and VCAM-1 gene expression was increased during rejection in endomyocardial biopsy specimens. Competitive polymerase chain reaction can be used to quantitatively assess gene expression in biopsy specimens from patients.