Background and aim: Genetic factors play a significant role in the onset and progression of coronary artery disease (CAD). PIK3C2A may contribute to the development of acute coronary syndrome (ACS) by affecting blood glucose levels and oxidative stress. The expression levels of TXNIP were significantly higher in patients with unstable angina pectoris. However, the situation is different in ACS. In the current study, we aim to investigate the role of PIK3C2A and TXNIP as independent risk factors for chronic stable angina (CSA) and ACS.
Subjects and methods: This study involved 215 subjects (60 patients with CSA, 55 patients with ACS, and 100 controls). All subjects were exposed for assaying gene expressions of PIK3C2A and TXNIP by quantitative real-time polymerase chain reaction.
Results: It was found that TXNIP was upregulated, whereas PIK3C2A was downregulated in patients with CAD compared to the control group. PIK3C2A was significantly downregulated in patients with ACS compared to that in patients with CSA (p < 0.001), but TXNIP was not (p = 0.7). TXNIP was significantly upregulated in STEMI-ACS patients compared to CSA (p = 0.045) and NSTEMI ACS (p = 0.046), among non-diabetic (p = 0.023) smokers (p = 0.036) with hypertension (p = 0.005) and hypercholesterolemia (p = 0.001). ROC (receiver operating characteristic) curve analysis revealed that PIK3C2A (0.981; p < 0.001; 98.18) was the most sensitive mRNA for discriminating ACS from control, followed by TXNIP (0.775; p < 0.001; 70.91). However, for discriminating ACS from CSA combined mRNAs, (PIK3C2A + TXNIP) (0.893; p < 0.001; 98.18) and PIK3C2A (0.892; p < 0.001; 81.82) are promising biomarkers. On the other hand, the most sensitive mRNA for differentiating CSA from control is mRNAs (PIK3C2A + TXNIP) (0.963; p < 0.001; 95), then TXINP (81.3; p < 0.001; 93.33), and finally, PIK3C2A (0.782; p < 0.001; 81.67). In the multivariate regression model, PIK3C2A ((p = 0.002), 0.118 (0.031-0.445)) and smoking status ((p = 0.034); 0.151 (0.026-0.866)) were independent variables for ACS. Moreover, PIK3C2A ((p < 0.013); 0.706 (0.614-0.812)), Hb ((p = 0.013); 0.525 (0.317-0.871)), and total cholesterol ((p = 0.04); 0.865 (0.784-0.955)) were significantly (p < 0.05) and independently related to the prognosis of CSA. Furthermore, PIK3C2A ((p = 0.002), 0.923 (0.877-0.971)), TXNIP ((p = 0.001); 2.809 (1.558-5.064)) the body weight ((p = 0.033); 1.254 (1.018-1.544)) were independently associated with CSA.
Conclusions: Our study concluded that the dysregulated mRNA PIK3C2A and TXNIP gene expressions may be useful in diagnosis of CAD and prediction of ACS development.
Keywords: ACS; CSA; PIK3C2A; TXNIP; real-time PCR.