miRNA clusters efficiently differentiate SA and UA patients from Controls.

<p>Hierarchical clustering demonstrated that different miRNA “signatures” efficiently classify between matched controls (CTRLS) and CAD patients. The cluster composed by miR-1 and miR-126 and miR-485-3p can be used to correctly classify SA patients from controls with 90.2% (yellow bar) efficiency. Similarly the miR-1, miR-126 and miR-133a cluster can be used to correctly classify UA patients from controls with 87.2% (red bar) efficiency. No signatures of miRNAs could be found to efficiently discriminate SA from UA patients with an accuracy > 66% (miR-126 and miR-337-5p cluster, blue bar). </p

ROC curve analysis of CAD-miRNAs in Unstable Angina patients and control subjects.

<p>The figure depicts calculated ROC curve and respective AUC values for miR-1, miR-126, and miR-133a, which exhibited good accuracy (AUC>0.85) in differentiating Unstable Angina (UA) patients from matched controls (C).</p

ROC curve analysis of CAD-miRNAs in Stable and Unstable Angina patients.

<p>None of the investigated miRNAs exhibited adequate accuracy in differentiating Stable (SA) from Unstable Angina (UA) patients: AUC values ranged between 0.404 (miR-145) and 0.678 (miR-337-5p).</p

ROC curve analysis of CAD-miRNAs in Stable Angina patients and control subjects.

<p>The figure depicts calculated ROC curve and respective AUC values for miR-1, miR-126, and miR-485-3p, which exhibited good accuracy (AUC>0.85) in differentiating Stable Angina (SA) patients from matched controls (C).</p