Using Molecular Pathology to Predict Response in Heart Failure

描述(由申请人提供)： 充血性心力衰竭在西方社会是一种非常普遍的疾病，与相当大的发病率和死亡率以及惊人的医疗费用有关。很难预测哪些患者会对治疗有反应，哪些患者不会。对药物治疗没有反应的患者子组真正受益于设备治疗和/或机械支持和/或移植的考虑，但在他们的疾病进展或出现病态并发症后，往往接受这些干预的时间太晚了。射血分数、功能容量和多变量心力衰竭“评分”已被用于指导临床决策，但对疾病进展的预测价值较差。我们从正在进行的Borg试验中获得的初步数据表明，一般的假设是，分子图谱结合从心内膜心肌活检获得的组织的蛋白质组和基因组分析可以提供一个强大的预测工具，允许及早识别哪些患者对药物治疗有反应，哪些患者没有反应。因此，这个C-Trip方案的主要目标是首先(第一阶段)使用已经进行临床特征并且已经从他们那里收集了连续心内膜心肌活检材料的患者队列来验证我们的方法，然后(第二阶段)设计和执行一项多中心临床试验，该试验将使用这种方法来前瞻性地预测心力衰竭的进展。我们的目标是将对心力衰竭的分子理解转化为临床工具，指导这些患者的诊断、分类和治疗。AIM1将根据对72名扩张型心肌病患者的现有队列的分析，开发一种预测算法，这些患者在开始倍他布洛克治疗前后接受了一系列心内膜心肌活组织检查。这将基于：A)信使核糖核酸图谱，B)miRNA阵列数据和C)针对蛋白质变化的定量蛋白质组分析。目标2将建立对扩张型心肌病患者进行多中心试验所需的基础设施，以验证预测算法，目标是将这些患者产生的医疗成本降至最低，并优化他们的护理。相关性(参见说明书)：我们的目标是开发一种个性化的、有针对性的患者护理方法，将心内膜心肌活检的分子生物标记物纳入心力衰竭患者的预测模型。我们认为，早期被确定为无反应的患者应该接受有针对性的干预，以防止心脏性猝死或因泵故障而导致的死亡。

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.