Differential Expression of Long Noncoding RNAs in Patients with Coronary Artery Disease

2021 ◽  
pp. 1-7
Author(s):  
Hamide Saygili ◽  
Ibrahim Bozgeyik ◽  
Onder Yumrutas ◽  
Erdal Akturk ◽  
Haydar Bagis
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Operating Characteristic ◽  
Obstructive Coronary Artery Disease ◽  
Noncoding Rnas ◽  
Diagnostic Value ◽  
Long Noncoding Rnas ◽  
Receiver Operating Characteristic Curves ◽  
Cardiovascular Pathologies ◽  
Artery Disease

Long noncoding RNAs (lncRNAs) constitute the largest class of noncoding RNAs and play significant roles in the development of cardiovascular pathologies. In the present study, we aimed to evaluate whether 4 candidate lncRNAs – MIAT, MEG3, MALAT1, and MCM3AP-AS1 – have distinct expression levels in patients with obstructive coronary artery disease (CAD) and reveal the diagnostic and therapeutic potentials of these lncRNAs for CAD. A total of 90 patients who subjected to coronary angiography were enrolled. Relative expression of lncRNAs were assayed using qRT-PCR methodology. As a result, <i>MIAT</i> was downregulated, while <i>MEG3</i> was upregulated in CAD patients. Receiver operating characteristic curves demonstrated that these lncRNAs have a high potential to provide sensitive and specific diagnosis of CAD. The calculated area under curve levels indicated that MIAT and MEG3 have high diagnostic value for detecting the presence of significant CAD. However, <i>MALAT1</i> and <i>MCM3AP-AS1</i> levels were not sufficiently reliable for CAD development in our cases. Here, we demonstrate that <i>MIAT</i> and <i>MEG3</i> were differentially expressed in our patients and might be promising biomarkers and therapeutic targets for CAD. These results indicate that <i>MIAT</i> and <i>MEG3</i> could play chief roles in CAD development.

scholarly journals Serum neutrophil gelatinase-associated lipocalin and cystatin C are diagnostic markers of renal dysfunction in older patients with coronary artery disease

2018 ◽  
Vol 46 (6) ◽  
pp. 2177-2185 ◽  
Author(s):  
Hong Zhu ◽  
Yuying Qian
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Renal Dysfunction ◽  
Cystatin C ◽  
Older Patients ◽  
Diagnostic Value ◽  
Receiver Operating Characteristic Curves ◽  
Neutrophil Gelatinase Associated Lipocalin ◽  
Artery Disease ◽  
Neutrophil Gelatinase

Objective This study aimed to assess the diagnostic value of serum neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C for renal dysfunction in older patients with coronary disease. Methods A total of 84 older patients with coronary artery disease were included in this study. Serum NGAL and cystatin C levels were analysed using commercially available kits. Medical data of all patients were recorded and analysed. Results NGAL and cystatin C levels were significantly positively correlated with N-terminal prohormone of brain natriuretic peptide levels and negatively correlated with the estimated glomerular filtration rate. The areas under the receiver operating characteristic curves of serum NGAL and cystatin C levels for diagnosing early renal dysfunction were 0.884 and 0.744, respectively. Conclusion Serum NGAL and cystatin C are potential early and sensitive markers of renal dysfunction in older patients with coronary artery disease.

Evaluation of the diagnostic value of joint PET myocardial perfusion and metabolic imaging for vascular stenosis in patients with obstructive coronary artery disease (Preprint)

2020 ◽  
Author(s):  
Shuxia Wang
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Myocardial Perfusion ◽  
Diagnostic Performance ◽  
Obstructive Coronary Artery Disease ◽  
Diagnostic Value ◽  
Metabolic Imaging ◽  
Pet Ct ◽  
Vascular Stenosis ◽  
Artery Disease

BACKGROUND To investigate the diagnostic value of joint PET myocardial perfusion and metabolic imaging for vascular stenosis in patients with suspected obstructive coronary artery disease (CAD). OBJECTIVE To investigate the diagnostic value of joint PET myocardial perfusion and metabolic imaging for vascular stenosis in patients with suspected obstructive coronary artery disease (CAD). METHODS . Eighty-eight patients (53 and 35 applied for training and validation, respectively) with suspected obstructive CAD were referred to 13N-NH3 PET/CT myocardial perfusion imaging (MPI) and 18F-FDG PET/CT myocardial metabolic imaging (MMI) with available coronary angiography for analysis. One semi-quantitative indicator summed rest score (SRS) and five quantitative indicators, namely, perfusion defect extent (EXT), total perfusion deficit (TPD), myocardial blood flow (MBF), scar degree (SCR), and metabolism-perfusion mismatch (MIS), were extracted from the PET rest MPI and MMI scans. Different combinations of indicators and seven machine learning methods were used to construct diagnostic models. Diagnostic performance was evaluated using the sum of four metrics (noted as sumScore), namely, area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS In univariate analysis, MIS outperformed other individual indicators in terms of sumScore (2.816–3.042 vs. 2.138–2.908). In multivariate analysis, support vector machine (SVM) consisting of three indicators (MBF, SCR, and MIS) achieved the best performance (AUC 0.856, accuracy 0.810, sensitivity 0.838, specificity 0.757, and sumScore 3.261). This model consistently achieved significantly higher AUC compared with the SRS method for four specific subgroups (0.897, 0.833, 0.875, and 0.949 vs. 0.775, 0.606, 0.713, and 0.744; p=0.041, 0.005, 0.034 0.003, respectively). CONCLUSIONS The joint evaluation of PET rest MPI and MMI could improve the diagnostic performance for obstructive CAD. The multivariate model (MBF, SCR, and MIS) combined with SVM outperformed other methods.

scholarly journals MicroRNAs or Long Noncoding RNAs in Diagnosis and Prognosis of Coronary Artery Disease

2019 ◽  
Vol 10 (2) ◽  
pp. 353 ◽  
Author(s):  
Yuan Zhang ◽  
Lei Zhang ◽  
Yu Wang ◽  
Han Ding ◽  
Sheng Xue ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Noncoding Rnas ◽  
Long Noncoding Rnas ◽  
Diagnosis And Prognosis ◽  
Artery Disease
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