Transcriptomic biomarkers for individual risk assessment in new-onset heart failure

Abstract

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.

Figure 1. Analysis of extracted total RNA with Agilent 2100 Bioanalyzer

Every sample was tested for its integrity and purity before microarray hybridization. The graph depicts a gel of 12 samples with consistent bands of 18S and 28S RNA. The left lane contains the reference marker.

Figure 2. Scheme of training and test sets as used for the development of a classifier with prediction analysis of microarrays

All samples obtained from patients with poor prognosis (PP, n=18) were selected from a biorepository (n=180), and those with good prognosis (GP, n=25) were chosen in a case-control fashion (see text for definitions of PP and GP). The classifier, a nearest shrunken centroid, was developed in two thirds of the data (17 samples with GP, 12 samples with PP) with subsequent validation in the remaining one third of data (8 samples with GP, 6 samples with PP). The overall test accuracy of the TBB was calculated from 50 random partitions into training and test sets.

Figure 3. Heat map of samples from all patients with IDCM (n=43)

Each column corresponds to a patient sample, and each row represents a gene. Samples classified as having poor prognosis (PP) form a distinct cluster and are highlighted in a red square. Downregulated genes are depicted with red, whereas upregulated genes are labeled blue. Yellow arrows denote misclassified samples. GP indicates good prognosis.

Figure 4. Pie chart illustrating involved pathways within the prognostic biomarker

Major pathways overexpressed in patients with good prognosis included transcription (26%), protein binding (15%), ion transport (13%), and neuromuscular development (10%). Developm indicates development.

Figure 5. Functional improvement of ejection fraction (EF) from baseline to end point

Within all enrolled cases of idiopathic cardiomyopathy (n=43), we further analyzed those for whom echocardiographic measurements at baseline and end point were available (n=17). Samples were classified into good prognosis (right panel) or poor prognosis (left panel) based on TBB prediction. Patients classified as having a good prognosis (n=11, average follow-up 49.9±21 months) experienced improvement of EF (*P=0.0009), whereas those with a poor prognosis (n=6, average follow-up 6.2±2.9 months) did not. Red line depicts 1 misclassified sample. Error bars represent SEM.