Relationship between long non-coding RNA and prognosis of patients with coronary heart disease after percutaneous coronary intervention: A protocol for systematic review and meta-analysis

Clinical Significance of MicroRNAs, Long Non-Coding RNAs, and CircRNAs in Cardiovascular Diseases

Based on recent research, the non-coding genome is essential for controlling genes and genetic programming during development, as well as for health and cardiovascular diseases (CVDs). The microRNAs (miRNAs), lncRNAs (long ncRNAs), and circRNAs (circular RNAs) with significant regulatory and structural roles make up approximately 99% of the human genome, which does not contain proteins. Non-coding RNAs (ncRNA) have been discovered to be essential novel regulators of cardiovascular risk factors and cellular processes, making them significant prospects for advanced diagnostics and prognosis evaluation. Cases of CVDs are rising due to limitations in the current therapeutic approach; most of the treatment options are based on the coding transcripts that encode proteins. Recently, various investigations have shown the role of nc-RNA in the early diagnosis and treatment of CVDs. Furthermore, the development of novel diagnoses and treatments based on miRNAs, lncRNAs, and circRNAs could be more helpful in the clinical management of patients with CVDs. CVDs are classified into various types of heart diseases, including cardiac hypertrophy (CH), heart failure (HF), rheumatic heart disease (RHD), acute coronary syndrome (ACS), myocardial infarction (MI), atherosclerosis (AS), myocardial fibrosis (MF), arrhythmia (ARR), and pulmonary arterial hypertension (PAH). Here, we discuss the biological and clinical importance of miRNAs, lncRNAs, and circRNAs and their expression profiles and manipulation of non-coding transcripts in CVDs, which will deliver an in-depth knowledge of the role of ncRNAs in CVDs for progressing new clinical diagnosis and treatment.

Functional Evaluation of Percutaneous Coronary Intervention Based on CT Images of Three-Dimensional Reconstructed Coronary Artery Model

In order to explore the computerized tomography (CT) based on three-dimensional reconstruction of coronary artery model, the functional evaluation was made after percutaneous coronary intervention (PCI). In this study, 90 patients with coronary heart disease who received elective PCI were selected. The blood flow reserve fraction (FFR) and SYNTAX score were calculated by three-dimensional reconstruction of CT images, followed up for 2-4 years. According to the SYNTAX score, 0-22 points were defined as the low group (28 cases), 23-32 points as the medium group (33 cases), and 33 points as the high group (29 cases). In this paper, the accuracy, sensitivity, and specificity of CT images of three-dimensional reconstructed coronary artery model are 91%, 73%, and 62%, respectively. The follow-up results showed that the incidence of major adverse cerebrovascular events in the high group was significantly higher than that in the low group and the middle group, and the difference was statistically significant (P < 0.05). Pearson correlation analysis showed that SYNTAX score was related to serum total cholesterol (r = 0.234, P=0.003), triglyceride (r = 0.237, P=0.014), low-density lipoprotein cholesterol (r = 0.285, P=0.004), and ApoB/ApoA1 (R = 0.004). In this study, FFR is calculated by CT images based on three-dimensional reconstruction of coronary artery model, which can provide support for the diagnosis and treatment of coronary heart disease. SYNTAX score can be used as a risk predictor for PCI patients with coronary heart disease.

Comprehensive Landscape of Modules-Dysregulated Functions Reveals a Profound Role of ceRNAs in Coronary Heart Disease

Coronary heart disease (CHD) is one of the most common severe cardiovascular diseases. Competitive endogenous RNAs (ceRNA) play critical roles in complex diseases. However, our understanding of the dysregulated functions of ceRNAs in CHD remains limited. Here, we systematically analyzed the alterations of ceRNAs and identified the specific functions based on dysregulated modules from the ceRNA network. A total of 2457 significantly differential expressed genes and 212 differential expressed lncRNAs were identified. We got 76679 regulator relationship between different expression genes and miRNAs and 336 regulator relationship between differential expressed lncRNAs and miRNAs. We constructed the ceRNA network and selected five dysregulated modules. Furthermore, CHD specific functions based on dysregulated modules from the ceRNA network were identified, including histone acetylation, platelet degranulation, cAMP-dependent protein kinase complex, xenobiotic transport and so on. Our results will provide novel insight for a better understanding of the mechanism of ceRNAs and facilitate the identification of novel diagnostic and therapeutic biomarkers in CHD.