RESUMEN
OBJECTIVES: Growing evidence suggests that systemic lupus erythematosus (SLE), an organ-damaging systemic autoimmune illness, may be influenced by long-noncoding RNAs (lncRNAs). This study aimed to assess the relative expression of lncRNAs (MIR31HG, NKILA, and PACER) in patients with SLE to evaluate their role in the disease. DESIGN AND METHODS: This study involved 70 patients with SLE and 70 apparently healthy control subjects. The expression levels of lnc-MIR31HG, NKILA, and PACER were quantified using real-time PCR. RESULTS: Lnc-MIR31HG, NKILA, and PACER were significantly upregulated in SLE cases compared to controls (P < 0.001). ROC curve analysis revealed a 91.43 % sensitivity of PACER for the diagnosis of SLE at a cutoff point of > 1.46, followed by NKILA with 90 % sensitivity at a cutoff point of > 1.16, and MIR31HG with 85.71 % sensitivity at a cutoff point of > 1.43. MIR31HG had the highest sensitivity for the diagnosis of lupus nephritis (86.67 %) at a cutoff point of > 7.19, then NKILA with 80 % sensitivity at a cutoff point of > 8.12, and finally PACER expression with 73.33 % sensitivity at a cutoff point of > 18.19. Moreover, MIR31HG and NKILA revealed a significant correlation with albumin/creatinine ratio, estimated glomerular filtration rate, and the SLEDAI score. Regression analysis revealed the potential roles of MIR31HG, NKILA, and PACER expression as predictors for SLE. CONCLUSION: An upregulated lncRNA panel (MIR31HG, NKILA, and PACER) could play a role in the pathogenesis and, hence, the predispositiontoSLE. MIR31HG and NKILA can serve as prognostic markers significantly linked with disease activity.
Asunto(s)
Lupus Eritematoso Sistémico , Nefritis Lúpica , ARN Largo no Codificante , Humanos , ARN Largo no Codificante/genética , Lupus Eritematoso Sistémico/genética , Lupus Eritematoso Sistémico/diagnóstico , Nefritis Lúpica/diagnóstico , Nefritis Lúpica/genética , Curva ROC , Tasa de Filtración Glomerular , BiomarcadoresRESUMEN
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.