Expression data for patients with myocardial infarction (MI) vs healthy patients

Myocardial infarction (MI) is one of the most severe manifestations of coronary artery disease (CAD) and the leading cause of death from non-infectious diseases worldwide. It is known, that the central component of CAD pathogenesis is a chronic vascular inflammation. However, the mechanisms underlying the changes that occur in T, B and NK-lymphocytes, monocytes and other immune cells during CAD and MI are still poorly understood. One of those pathogenic mechanisms might be the dysregulation of intracellular signaling pathways in the immune cells. In the present study we performed a transcriptome profiling in peripheral blood mononuclear cells of MI patients and healthy individuals. The machine learning algorithm was then used to search for MI-associated signatures, that could reflect the dysregulation of intracellular signaling pathways and be assisted in MI diagnosis and/or prognosis. ADAP2, KLRC1, MIR21, PDGFD and CD14 genes were identified as the most important signatures for the classification model with L1-norm penalty function. The classifier output quality was equal to 0.911 by Receiver Operating Characteristic metric on test data. These results were validated on two independent open GEO datasets. 6 patients with myocardial infarction (MI) were analyzed vs 6 healty patients