Using Molecular Pathology to Predict Response in Heart Failure

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DESCRIPTION (provided by applicant): Congestive heart failure is an enormously prevalent disease in Western society and is associated with substantial morbidity and mortality as well as with staggering health care costs. It is difficult to predict which patients will and will not respond to therapy. The subset of patients who don't respond to pharmacotherapy truly benefit from device therapy and/or consideration of mechanical support and/or transplant but often receive these interventions too late, after their disease has progressed or they have developed a morbid complication. Ejection fraction, functional capacity and multivariate heart failure "scores" have been utilized to guide clinical decisions, but have poor predictive values for disease progression. Our preliminary data, derived from the on-going BORG trial, suggest the general hypothesis that molecular profiling coupled with proteomic and genomic analyses of tissue obtained from an endomyocardial biopsy can offer a robust predictive tool that will allow for the early identification of patients who will and will not respond to pharmacotherapy. Therefore the broad goals of this C-TRIP proposal are first (Phase 1) to validate our methodology using this patient cohort that has already been clinically characterized and from whom serial endomyocardial biopsy material has already been collected and then subsequently (Phase 2) to design and execute a multicenter clinical trial that will use this methodology to prospectively predict heart failure progression. Our goal is to translate a molecular understanding of heart failure into clinical tools which can guide the diagnosis, classification, and management of these patients. Aim1 will develop a predictive algorithm from the analysis of an existing cohort of 72 patients with dilated cardiomyopathy who have undergone serial endomyocardial biopsies before and after initiation of betablocker therapy. This will be based on: A) mRNA profiling B) miRNA array data and C) quantitative proteomic assays targeting protein changes. Aim 2 will establish the infrastructure necessary to conduct a multi-center trial of patients with DCM in order to validate the predictive algorithm, with the goal of minimizing the health costs incurred by these patients and optimizing their care. RELEVANCE (See instructions): Our goal is to develop a personalized targeted approach to patient care incorporating molecular biomarkers from endomyocardial biopsies into a predictive model for heart failure patients. We believe patients identified early as non-responders should receive intervention targeted against preventing sudden cardiac death or death due to pump failure.