As revealed from the results, the mentioned eight candidate features may have optimal diagnostic value with respect to distinguishing CAD patients from healthy people: CCNDBP1 (AUC = 0.854), CDC42SE1 (AUC = 0.886), ERCC5 (AUC = 0.893), HES6 (AUC = 0.984), PCSK1N (AUC = 0.918), PTGDS (AUC = 0.978), RAB2A (AUC = 0.838) and RORA (AUC = 0.936) (Fig. 5). Here, RAB2A is linked to coronary artery disorder.