Genetic Variants and Heart Rate Variability in Patients with History of Acute Coronary Syndrome

Abstract

Introduction - Cardiovascular diseases (CVDs) comprise the leading cause of morbidity and mortality worldwide, highlighting the coronary artery disease (CAD), which is characterized by the presence of atheromas or atherosclerotic plaques in blood vessels of the heart circulation. Risk factors including diabetes mellitus, hypertension, dyslipidemia and obesity, as well as genetic and biochemical changes may influence atherogenesis and destabilization of atherosclerotic plaques, leading to acute coronary syndrome (ACS). Epidemiological and family studies have shown that genetic predisposition contributes 40 % to 60 % risk of CAD. In this case, it stands out association studies of the complete genome (GWAS - genome- wide association study), as a method to evaluate, simultaneously, many single nucleotide polymorphisms (SNPs), and detection of inheritable risk factors. In this context, the understanding of their genetic factors may contribute to the prevention and treatment of SCA. Objectives - To characterize the genetic profile and correlate with biochemical and anthropometric profile, as well as heart rate variability (HRV), and quality and lifestyle habits in patients with dyslipidemia with or without ACS. Patients and Methods - They will study 30 patients ( LDLc e70 mg / dL ) , already clinically stable and with atherosclerotic coronary artery disease in treatment with potent statin at maximum tolerated doses for at least 30 consecutive days , regardless of sex , age > 45 years , and 40 with early ACS history for at least 12 months of the event and 40 with dyslipidemia in primary prevention for cardiovascular outcomes. All patients will be submitted to collection of peripheral blood sample for DNA analysis microarray (up to 5 million SNPs), held in high performance equipment (iSCAN - BeadChip large-scale), and anthropometric APPRAISAL (body mass index and waist circumference) and heart rate variability. In this case, a heart rate monitor to record the fluctuations in intervals between consecutive heart beats (RR intervals) will be used. The biochemical profile (total cholesterol and fractions, triglycerides, blood glucose and glycated hemoglobin) will be obtained from electronic medical records. Statistical analysis will be performed using the t test, linear regression model and Pearson correlation. We will be admitted significance level for P value <0.05. The analysis of the complete genome will be performed by bioinformatics tools with specific software. (AU)