07 اردیبهشت 1403
اميرحسين احمدي

امیرحسین احمدی

مرتبه علمی: استادیار
نشانی: دانشکده علوم و فناوری نانو و زیستی - گروه علوم زیستی
تحصیلات: دکترای تخصصی / ژنتیک مولکولی
تلفن: 07733441497
دانشکده: دانشکده علوم و فناوری نانو و زیستی

مشخصات پژوهش

عنوان Predictive Inflammation-related microRNAs for Cardiovascular Events Following Early-Onset Coronary Artery Disease
نوع پژوهش مقالات در نشریات
کلیدواژه‌ها
Early-onset CAD, MACE, miRNAs, Inflammation
مجله ARCHIVES OF MEDICAL RESEARCH
شناسه DOI 10.1016/j.arcmed.2020.10.004
پژوهشگران شایان ضیایی (نفر اول) ، مریم حسین دخت (نفر دوم) ، سارا چراغی (نفر سوم) ، لیلا پورقلی (نفر چهارم) ، امیرحسین احمدی (نفر پنجم) ، سعید صادقیان (نفر ششم به بعد) ، سید حسام الدین عباسی (نفر ششم به بعد) ، طاهره داورپسند (نفر ششم به بعد) ، محمدعلی برومند (نفر ششم به بعد)

چکیده

Background Early-onset coronary artery disease (EOCAD) increases the risk of major cardiac adverse events (MACE) at the level of safety/effectiveness-related events. Since adverse events affect the quality of life of young patients with EOCAD, MACE prediction is of great importance for improving medical decision-making. Aims of the Study We sought to determine whether the most important inflammation-related microRNAs in atherogenesis could predict MACE among patients with EOCAD. Methods This nested case-control study recruited 143 young patients (males ≤45 and females ≤55 years old), selected from a cohort of patients with premature coronary atherosclerosis at a median follow-up period of 64.1 months. Total RNAs were extracted from their peripheral blood mononuclear cells. The expression levels of 18 miRNAs, which are involved in inflammation and atherogenesis, were analyzed via quantitative reverse transcription PCR. Results A scoring model based on the upregulation of miR-146a_1 and miR-342_1, along with a history of myocardial infarction and the chronic usage of antithrombotic drugs, was able to predict MI/death at the level of safety-related events (higher vs lower risk scores: sHR: 4.61, 95% CI: 1.57–13.57, and p = 0.005). Another prediction model based on the downregulation of miR-145_1, age, and a history of unstable angina was also able to predict revascularization at the level of effectiveness-related events (higher vs lower risk scores: sHR: 2.90, 95% CI: 1.49–5.66, and p = 0.002). Conclusions Our results highlighted the role of miRNAs in adverse cardiac events and suggest that miR-146a_1, miR-342_1, and miR-145_1 may be useful biomarkers in predictive and preventive cardiology.