Molecular predictors of resistance and vulnerability to cardiovascular events in stable ischemic heart disease

项目摘要

PROJECT ABSTRACT More reliable and personalized ways to predict adverse cardiovascular (CV) events could improve outcomes and quality of life for over 18 million Americans with stable ischemic heart disease (SIHD). Contemporary risk stratification in SIHD assesses clinical risk factors and tests for inducible myocardial ischemia and obstructive coronary artery disease (CAD). As we recently showed in the NHLBI ISCHEMIA trial, inducible ischemia can be chronic and well-tolerated, and CAD stenoses often do not progress to CV events. After ISCHEMIA, clinicians need better tools to supplement clinical testing of ischemia and CAD to identify SIHD patients at high risk for CV events and ultimately target the pathways conferring risk. If we could use biomarkers and molecular assays to better identify these high-risk patients, we could better target resource-intensive therapies to the right patient, at the right time. Molecular markers of thrombosis, inflammation, and myocardial injury – processes at the root of SIHD and CV events – are strong candidates to predict events in SIHD. However, these markers have not been evaluated against state-of-the-art clinical measures of inducible ischemia and CAD severity linked to centrally adjudicated CV events. As a result, it remains difficult to determine if these and other assays can improve on clinical risk factors and testing for SIHD risk stratification. To overcome this limitation, we will leverage a population of stable outpatients representing the risk spectrum of SIHD, with core-lab confirmed inducible ischemia, CAD severity, and centrally adjudicated CV events drawn from two large, NHLBI-funded strategy trials with robust biorepositories: the ISCHEMIA trial and the PROMISE trial. We will validate our findings in the multi “omics” cohorts of the NHLBI’s TOPMed (Trans-Omics for Precision Medicine) program. Our central hypothesis is that augmenting clinical testing with biomarker analysis will predict CV events in SIHD more accurately and with greater efficiency than clinical testing alone. In Aim 1, we will determine whether biomarkers reported to predict CV events improve prediction of death or myocardial infarction when added to unique clinical testing of patients with SIHD available for our use. In Aim 2, we will discover novel molecular features that improve prediction of death or myocardial infarction when added to detailed clinical testing in SIHD. With these aims, we will develop a multi-dimensional model of biomarkers, novel molecular features and clinical testing to improve the prognosis and management of patients with SIHD.