BACKGROUND: Lymphocytic myocarditis is a clinically important condition that is difficult to diagnose and distinguish. We hypothesized that the transcriptome obtained from an endomyocardial biopsy would yield clinically relevant and accurate molecular signatures. METHODS AND RESULTS: Microarray analysis was performed on samples from patients with histologically proven lymphocytic myocarditis (n=16) and idiopathic dilated cardiomyopathy (n=32) to develop accurate diagnostic transcriptome-based biomarkers using multiple classification algorithms. We identified 9878 differentially expressed genes in lymphocytic myocarditis versus idiopathic dilated cardiomyopathy (fold change >1.2; false discovery rate <5%) from which a transcriptome-based biomarker containing 62 genes was identified that distinguished myocarditis with 100% sensitivity (95% confidence interval, 46 to 100) and 100% specificity (95% confidence interval, 66 to 100) and was generalizable to a broad range of secondary cardiomyopathies associated with inflammation (n=27), ischemic cardiomyopathy (n=8), and the normal heart (n=11). Multiple classification algorithms and quantitative real-time reverse-transcription polymerase chain reaction analysis further reduced this subset to a highly robust molecular signature of 13 genes, which still performed with 100% accuracy. CONCLUSIONS: Together, these findings demonstrate that transcriptomic biomarkers from a single endomyocardial biopsy can improve the clinical detection of patients with inflammatory diseases of the heart. This approach advances the clinical management and treatment of cardiac disorders with highly variable outcome.
BACKGROUND:Lymphocytic myocarditis is a clinically important condition that is difficult to diagnose and distinguish. We hypothesized that the transcriptome obtained from an endomyocardial biopsy would yield clinically relevant and accurate molecular signatures. METHODS AND RESULTS: Microarray analysis was performed on samples from patients with histologically proven lymphocytic myocarditis (n=16) and idiopathic dilated cardiomyopathy (n=32) to develop accurate diagnostic transcriptome-based biomarkers using multiple classification algorithms. We identified 9878 differentially expressed genes in lymphocytic myocarditis versus idiopathic dilated cardiomyopathy (fold change >1.2; false discovery rate <5%) from which a transcriptome-based biomarker containing 62 genes was identified that distinguished myocarditis with 100% sensitivity (95% confidence interval, 46 to 100) and 100% specificity (95% confidence interval, 66 to 100) and was generalizable to a broad range of secondary cardiomyopathies associated with inflammation (n=27), ischemic cardiomyopathy (n=8), and the normal heart (n=11). Multiple classification algorithms and quantitative real-time reverse-transcription polymerase chain reaction analysis further reduced this subset to a highly robust molecular signature of 13 genes, which still performed with 100% accuracy. CONCLUSIONS: Together, these findings demonstrate that transcriptomic biomarkers from a single endomyocardial biopsy can improve the clinical detection of patients with inflammatory diseases of the heart. This approach advances the clinical management and treatment of cardiac disorders with highly variable outcome.
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