Oxidative Stress and Changes of Important Metabolic Gene Expressions as a Potential Biomarker in the Diagnosis of Atherosclerosis in Leukocytes

ABSTRACT Introduction: Presenilin 1 (PSEN1), catalase (CAT), glutathione-S-transferase (GST) and paraoxonase 1 (PON1) play a vital role in prediction, diagnosis and therapy of metabolic disorders. Methods: Metabolic enzyme activities and lipid peroxidation in serum of cerebrovascular diseases (CVD) and coronary artery diseases were measured by spectrophotometric methods. mRNA was isolated from leukocytes of the patient group and healthy adult patients. Quantitative gene expression of PSEN1, CAT and GST mRNA was identified by quantitative real-time polymerase chain reaction (qPCR). Results: The PSEN1, CAT and GST expression in patients showed significant differences compared to the control group. PSEN1 expression in leukocytes was significantly about twice as high as that of the control group in patients with CVD. The GST, CAT and PON1 activity showed significant differences in patient groups compared to the control group. Conclusion: The mRNA expression levels can be used as a potential biomarker in the diagnosis of atherosclerosis that occurs as a result of the metabolic disorder. In atherosclerotic patients, antioxidant status is independently related to an increased risk of cardiovascular events. Antioxidant activities and mRNA expressions may have predictive value, as well as available risk factors.

摘要
引言：早老素1（Presenilin 1, PSEN1）、过氧化氢酶（catalase, CAT）、谷胱甘肽S-转移酶（glutathione-S-transferase, GST）及对氧磷酶1（paraoxonase 1, PON1）在代谢性疾病的预测、诊断及治疗中发挥关键作用。
方法：采用分光光度法检测脑血管疾病（cerebrovascular diseases, CVD）患者与冠状动脉疾病患者血清中的代谢酶活性及脂质过氧化水平。从患者组及健康成人受试者的白细胞中分离总mRNA，通过实时定量聚合酶链式反应（quantitative real-time polymerase chain reaction, qPCR）对PSEN1、CAT及GST的mRNA表达水平进行定量分析。
结果：与健康对照组相比，患者组的PSEN1、CAT及GST mRNA表达水平存在显著统计学差异。其中脑血管疾病患者的白细胞PSEN1表达量约为对照组的两倍，差异具有统计学意义。此外，患者组的GST、CAT及PON1酶活性与对照组相比同样存在显著统计学差异。
结论：mRNA表达水平可作为代谢紊乱引发的动脉粥样硬化诊断的潜在生物标志物。在动脉粥样硬化患者中，机体抗氧化状态与心血管事件风险升高呈独立相关关系。抗氧化活性与mRNA表达水平或可与现有临床风险因子一样，具备疾病预测价值。