<p>Coronary artery disease (CAD) and myocardial infarction (MI) remain the leading cause of death worldwide and in the US. In recent years, clinical studies that considered intermediate phenotypes (phenotypic or genomic data isolated between DNA and the main disease phenotype) have greatly enhanced our understanding of complex traits like CAD by enabling inference of biological networks from the combination of genetic and genomic datasets isolated from disease-relevant tissue(s). The NGS-PREDICT study used whole transcriptome sequence data generated from primary macrophages derived in vitro from venous blood that was obtained from CAD cases and non-CAD controls. This study provided a valuable resource for the validation of biomarkers identified in <a href="https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001203">STARNET</a> NGS data from macrophages obtained from patients with and without CAD. It also can be used as a reference dataset for the study of metabolic syndrome as well as other systemic inflammatory diseases.</p>

Next Generation Sequencing to Predict Risk of Events from Coronary Artery Disease

Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases

A mechanistic framework for cardiometabolic and coronary artery diseases