Over the last decades, beta-blockers have been a key component of heart failure therapy. However, currently there is no method to identify patients who will benefit from beta-blocking therapy versus those who will be unresponsive or worsen. Furthermore, there is an unmet need to better understand molecular mechanisms through which heart failure therapies, such as beta-blockers, improve cardiac function, in order to design novel targeted therapies. Solving these issues is an important step towards personalized medicine. Here, we present a comprehensive transcriptomic analysis of molecular pathways that are affected by beta-blocking agents and a transcriptomic biomarker to predict therapy response.
Keywords: AR, adrenergic receptor; EF, ejection fraction; EMB, endomyocardial biopsy; GO, gene ontology; HF, heart failure; MYH, myosin heavy chain; MiPP, Misclassified Penalized Posteriors; SAM, significance analysis of microarrays; SERCA, sarcoplasmic reticulum calcium-dependent ATPase; TBB, transcriptomic-based biomarker; beta-blocking agents; biomarker; gene expression; heart failure; transcriptomics.