Health Improvements by Understanding the Determinants of Residual Risk in Coronary Artery Disease and New Targets for Prevention and Treatment

Overview

Current medical treatments, in patients with stable coronary artery disease (CAD), mainly target established risk factors and are able to reduce morbidity and mortality but still leave a substantial residual risk of coronary artery disease progression and events. The main hypothesis of this study is that metabolic derangement, including pre-diabetes, elevated levels of triglycerides, low levels and functionality of high-density lipoprotein cholesterol, often associated with a chronic inflammatory state, is a currently unrecognized and undertreated conditon which could be the most relevant determinant of residual risk. The goal of HURRICANE observational study is to discover specific individual genetic/molecular profiles subtending emerging cardiometabolic and vascular risk patterns and associating with a more severe and progressive coronary artery disease. We will thus develop and preliminary validate new predictive models for the recognition of high-risk patients and explore possible new targets for individualized preventive treatment. The severity, extent and progression of coronary plaques will be assessed by qualitative and quantitative analysis of cardiac computed tomography (CCT) performed in retrospective and prospective cohorts of patients with stable coronary disease.

HURRICANE is an observational clinical study, performed in retrospective and prospective cohorts of patients with stable CAD, to assess the role of emerging cardiometabolic and vascular risk determinants to predict severe and progressive coronary atherosclerosis documented by advanced CCT imaging. The population of the retrospective study consists of two parallel, independent groups of patients enrolled in previous clinical trials focused on blood and CCT biomarkers of CAD. All participants are assessed for eligibility to the current study which includes in particular availability of blood samples in bio-bank and of interpretable CCT exams. For each cohort and for the whole retrospective population (561 patients) clinical variables (demographic data, cardiovascular risk factors, history of previous CAD, symptoms and medications) and conventional circulating biomarkers (lipid and glucose metabolism, systemic inflammation, liver and kidney function) are recorded. The coronary imaging variables which will provide the disease presence and severity end-points will be derived from qualitative and semiquantitative analyses of CCT exams according to CAD-RADS 2.0 classification system. The population of the prospective longitudinal study will include 400 patients referred at IRCCS SYNLAB SDN in Naples and FTGM in Pisa, over a 12 months period, to a clinically indicated CCT for suspected CAD, signing a written informed consent and fulfilling Inclusion and exclusion criteria. At baseline, patients will be characterized as in the retrospective study (same clinical variables, conventional circulating biomarkers and CCT imaging variables) and blood samples will be collected and stored in the dedicated Bio-Bank for advanced genetic/molecular analyses. They will be submitted to monitoring visits and a last follow-up visit at 12 months when compliance to medical treatment and events will be registered. A second blood sample will be collected and stored in dedicated Bio-Bank for advanced molecular analyses. A second CCT scan will be performed at 12 months with the same scanner, at the same institution, by the use of a state-of-the art CCT technology with high spatial and temporal resolution to provide quantitative measurements of coronary plaque volumes and coronary plaque composition which will be used to define the disease progression end-points. Qualitative and semiquantitative analyses of CCT exams will be performed by radiologists according to CAD-RADS 2.0 classification systemin both the retrospective and prospective populations. In the prospective population, CCT images at enrollment and follow-up will also be quantitatively analyzed to define evolving CAD phenotypes. Quantitative analysis will be performed on visually identified plaques using a dedicated software package (QAngio CT Research Edition version 3.1.2.0, Medis Medical Imaging Systems, Leiden, the Netherlands) to generate detailed output on the lumen and plaque statistics, including the degree of stenosis, lesion length, vessel volume, plaque burden, plaque volume, and plaque components (according to the virtual histology classification: dense calcium, necrotic core, fibrous-fatty, fibrous, and media). Additional CT-derived parameters will also be assessed, in particular epicardial and perivascular adipose tissue, to be tested in the predictive models of CAD evolution and to be entered in a Machine Learning data analysis as potential variables of the pathophysiologic CAD network. Circulating biomarkers will be evaluated by standard methodologies of clinical chemistry laboratories at the two participant clinical centers and specific circulating biomarkers will be analyzed at the IFC-CNR Core-Lab in both the retrospective and the prospective populations. In particular, additional markers of lipid metabolism and adipose tissue function, endothelial function and atherosclerotic burden will be evaluated by dedicated immunoassays, while markers of myocardial damage/function will be evaluated by automatized immunoassays. The inflammatory profile will be assessed by multiplex cytokine screens."Omics" analyses, in both populations, will include lipidomic, with the assessment of circulating lipid species using mass spectrometry, and genetic profiling by GWAS (Genome-Wide Association Study) performed by an external provider (Genomix4Life) using new generation microarray technology to genotype single-nucleotide variants (SNVs). In representative extreme groups of patients from the prospective population, a specific panel of 88 candidate genes involved in lipid/glucose homeostasis, endothelial/vascular function and systemic inflammation, together with other relevant genes emerging from the GWAS analysis, will be sequenced for known and unknown variants at FTGM by NGS (Next Generation Sequencing) approach. The library preparation for NGS will be performed using the Illumina DNA Prep with Enrichment Kit. Base-Space Variant Interpreter software will be used to annotate, filter and interpret the variants. The degree of pathogenicity will be also assessed on VarSome (https://varsome.com) and GWAS Catalog (https://www.ebi.ac.uk/gwas/), search engines and impact analysis tools for human genetic variation. The variants identified as pathogenetically relevant, in the subjects with extreme phenotypes will then be assessed in the rest of the population. Moreover, miRNAs, putatively associated with relevant gene variants and screened by in silico bioinformatic analysis, will be assessed by qPCR.