Contemporary Management of Stable Coronary Artery Disease

Identification of plasma miR-4505, miR-4743-5p and miR-4750-3p as novel diagnostic biomarkers for coronary artery disease in patients with type 2 diabetes mellitus: a case-control study

BACKGROUND

Type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) are commonly coexisting clinical entities with still growing incidence worldwide. Recently, circulating microRNAs (miRNAs) have emerged as novel molecular players in cardiometabolic diseases. This study aimed to identify a specific miRNA signature as a candidate biomarker for CAD in T2DM and to delineate potential miRNA-dependent mechanisms contributing to diabetic atherosclerosis.

METHODS

A total of 38 plasma samples from T2DM patients with and without CAD, CAD patients and healthy controls were collected for expression profiling of 2,578 miRNAs using microarrays. To investigate the regulatory role of differentially expressed (DE)-miRNA target genes, functional annotation and pathway enrichment analyses were performed utilizing multiple bioinformatics tools. Then, protein-protein interaction networks were established leveraging the STRING database in Cytoscape software, followed by cluster analysis and hub gene identification. Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was carried out for microarray data validation in the larger replication cohort of 94 participants. Receiver operating characteristic analysis was applied to evaluate the diagnostic values of miRNAs. Multivariate logistic regression analysis was used to develop miRNA-based diagnostic models.

RESULTS

In the discovery stage, overexpression of hsa-miR-4505, hsa-miR-4743-5p, hsa-miR-6846-5p, and down-regulation of hsa-miR-3613-3p, hsa-miR-4668-5p, hsa-miR-4706, hsa-miR-6511b-5p, hsa-miR-6750-5p, hsa-miR-4750-3p, hsa-miR-320e, hsa-miR-4717-3p, hsa-miR-7850-5p were detected in T2DM-CAD patients. The DE-miRNA target genes were significantly enriched in calcium ion binding, regulation of actin cytoskeleton, and gene expression. hsa-miR-4505, hsa-miR-4743-5p, and hsa-miR-4750-3p were found to be involved in fatty acid metabolism, leukocyte transendothelial migration, and neurotrophin signaling pathway. Dysregulation of hsa-miR-4505, hsa-miR-4743-5p, and hsa-miR-4750-3p in T2DM-CAD patients compared with T2DM subjects and controls (all p < 0.001) was further confirmed by RT-qPCR. All validated miRNAs demonstrated good discriminatory values for T2DM-CAD (AUC = 0.833-0.876). The best performance in detecting CAD in T2DM was achieved for a combination of three miRNAs (AUC = 0.959, 100% sensitivity, 86.67% specificity).

CONCLUSIONS

Our study revealed a unique profile of plasma-derived miRNAs in T2DM patients with CAD. Potential miRNA-regulated pathways were also identified, exploring the underlying pathogenesis of CAD in T2DM. We developed a specific three-miRNA panel of hsa-miR-4505, hsa-miR-4743-5p and hsa-miR-4750-3p, that could serve as a novel non-invasive biomarker for CAD in patients with T2DM.

Identification and verification of circRNA biomarkers for coronary artery disease based on WGCNA and the LASSO algorithm

BACKGROUND

The role of circular RNAs (circRNAs) as biomarkers of coronary artery disease (CAD) remains poorly explored. This study aimed to identify and validate potential circulating circRNAs as biomarkers for the diagnosis of CAD.

METHODS

The expression profile of circRNAs associated with CAD was obtained from Gene Expression Omnibus (GEO) database. Differential expression analysis, weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operation (LASSO) were employed to identify CAD-related hub circRNAs. The expression levels of these hub circRNAs were validated using qRT-PCR in blood samples from 100 CAD patients and 100 controls. The diagnostic performance of these circRNAs was evaluated through logistic regression analysis, receiver operator characteristic (ROC) analysis, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Functional enrichment analyses were performed to predict the possible mechanisms of circRNAs in CAD.

RESULTS

A total of ten CAD-related hub circRNAs were identified through WGCNA and LASSO analysis. Among them, hsa_circ_0069972 and hsa_circ_0021509 were highly expressed in blood samples of CAD patients, and they were identified as independent predictors after adjustment for relevant confounders. The area under the ROC curve for hsa_circ_0069972 and hsa_circ_0021509 was 0.760 and 0.717, respectively. The classification of patients was improved with the incorporation of circRNAs into the clinical model composed of conventional cardiovascular risk factors, showing an IDI of 0.131 and NRI of 0.170 for hsa_circ_0069972, and an IDI of 0.111 and NRI of 0.150 for hsa_circ_0021509. Functional enrichment analyses revealed that the hsa_circ_0069972-miRNA-mRNA network was enriched in TGF-β、FoxO and Hippo signaling pathways, while the hsa_circ_0021509-miRNA-mRNA network was enriched in PI3K/Akt and MAPK signaling pathways.

CONCLUSION

Hsa_circ_0069972 and hsa_circ_0021509 were identified by integrated analysis, and they are highly expressed in CAD patients. They may serve as novel biomarkers for CAD.

Predictors of percutaneous coronary intervention derived from CCTA in patients with chronic coronary syndrome

BACKGROUND

To identify anatomical and morphological plaque features predictors of PCI and create a multiparametric score to increase the predictive yield. Moreover, we assessed the incremental predictive value of FFRCT (Fractional Flow Reserve derived from CCTA) trans-lesion gradient (ΔFFRCT) when integrated into the score.

METHODS

Observational cohort study including patients undergoing CCTA for suspected coronary artery disease, with FFRCT available, referred to invasive coronary angiogram and assessment of fractional flow reserve. Plaque analysis was performed using validated semi-automated software. Logistic regression was performed to identify anatomical and morphological plaque features predictive of PCI. Optimal thresholds were defined by area under the receiver-operating characteristics curve (AUC) analysis. A scoring system was developed in a derivation cohort (70 ​% of the study population) and tested in a validation cohort (30 ​% of patients).

RESULTS

The overall study population included 340 patients (455 vessels), among which 238 patients (320 vessels) were included in the derivation cohort. At multivariate logistic regression analysis, absence of left main disease, diameter stenosis (DS), non-calcified plaque (NCP) volume, and percent atheroma volume (PAV) were independent predictors of PCI. Optimal thresholds were: DS ​≥ ​50 ​%, volume of NCP>113 ​mm3 and PAV>17 ​%. A weighted score (CT-PCI Score) ranging from 0 to 11 was obtained. The AUC of the score was 0.80 (95%CI 0.74-0.86). The integration of ΔFFRCT in the CT-PCI score led to a mild albeit not significant increase in the AUC (0.82, 95%CI 0.77-0.87, p ​= ​0.328).

CONCLUSIONS

Plaque anatomy and morphology derived from CCTA could aid in identifying patients amenable to PCI.

Intrastent Restenosis: A Comprehensive Review

The primary objective of this paper is to delineate and elucidate the contemporary advancements, developments, and prevailing trajectories concerning intrastent restenosis (ISR). We aim to provide a thorough overview of the most recent developments in this area, covering various aspects such as pathophysiological insights, therapeutic approaches, and new strategies for tackling the complex challenges of ISR in modern clinical settings. The authors have undertaken a study to address a relatively new medical challenge, recognizing its significant impact on the morbidity and mortality of individuals with cardiovascular diseases. This effort is driven by the need to fully understand, analyze, and possibly improve the outcomes of this emerging medical issue within the cardiovascular disease field. We acknowledge its considerable clinical implications and the necessity for innovative methods to mitigate its effects on patient outcomes. Therefore, our emphasis was directed towards elucidating the principal facets of the condition's prevalence, expounding upon the foundational mechanisms underscoring conspicuous restenosis, and delineating the risk factors relevant in shaping the contemporary landscape of diagnostic and therapeutic modalities. This thorough examination aims to provide a comprehensive understanding of the various dimensions of the condition, including epidemiological data, pathophysiological complexities, and clinical considerations critical for evaluating and enhancing current diagnostic and treatment approaches.

Diagnostic accuracy of coronary artery stenosis and thrombosis assessment using unenhanced multiplanar 3D post-mortem cardiac magnetic resonance imaging

BACKGROUND

A 3D sequence was introduced to unenhanced post-mortem cardiac magnetic resonance imaging (PMCMR) to enable multiplanar coronary artery image analysis and to investigate its diagnostic accuracy for the diagnosis of coronary artery stenosis and thrombosis.

MATERIALS AND METHODS

N = 200 forensic cases with suspected coronary artery pathology underwent 3 Tesla PMCMR (sequence used: T2 weighted transversal 3D turbo spin echo) before autopsy. Main coronary artery stenosis and thrombosis were assessed in PMCMR by multiplanar image analysis by two observers. Coronary artery histology was determined as the gold standard and compared to PMCMR. Sensitivity, specificity, negative (NPV) and positive predictive values (PPV) with 95% confidence intervals were calculated.

RESULTS

For all coronary arteries combined, sensitivity was 75% (PPV 73%) for the diagnosis of stenosis and 72% (PPV 71%) for the diagnosis of thrombosis. Specificity was 92% (NPV 90%) for correct diagnosis of non-existing stenosis and 97% (NPV 97%) for non-existing thrombosis. Sensitivity for correct diagnosis of different degrees of stenosis ranged between 67% and 80% (PPVs 67-82%); specificity ranged between 96% and 99% (NPVs 96-99%).

CONCLUSION

Multiplanar PMCMR coronary artery stenosis and thrombosis assessment based on an unenhanced T2 weighted 3D sequence provide moderate sensitivity and high specificity for the diagnosis of coronary artery stenosis and/or thrombosis. Hence, 3D T2w PMCMR cannot reliably detect existing coronary artery stenosis and thrombosis but may be particularly useful for the exclusion of stenosis or thrombosis of the main coronary arteries.

The Triglyceride-Glucose Index Might Be a Better Indicator for Predicting Poor Cardiovascular Outcomes in Chronic Coronary Syndrome

This study aimed to explore the potential association between the triglyceride-glucose index (TyG) and the atherogenic index of plasma (AIP)-both considered surrogate markers for atherosclerosis-and major adverse cardiovascular events (MACEs) in patients diagnosed with chronic coronary syndrome (CCS). We conducted a retrospective analysis, encompassing 715 consecutive patients with intermediate CCS risk, who presented at the outpatient clinic between June 2020 and August 2022. MACEs included non-fatal myocardial infarction, hospitalization for heart failure, cerebrovascular events, non-cardiac mortality, and cardiac mortality. The primary outcome was the composite occurrence of MACEs during the follow-up period. For time-to-event analysis of the primary outcome, we employed Kaplan-Meier plots and Cox proportional hazard models. The median age of the overall study population was 55 years, with a median follow-up duration of 17 months. Multivariate Cox regression analysis identified age, hypertension, Coronary Artery Disease-Reporting and Data System score, and TyG index as independent predictors of the primary outcome. Notably, individuals with high TyG levels exhibited a significantly higher primary outcome rate compared to those with low TyG levels (18.7% vs. 3.8%, p < 0.001). Similarly, patients with elevated TyG values demonstrated statistically higher rates of cerebrovascular events, hospitalizations for heart failure, non-fatal myocardial infarctions, non-cardiac mortality, and cardiac mortality. These findings suggest that TyG may serve as a predictive marker for adverse cardiovascular outcomes in patients with CCS.

The Application of Deep Learning for the Segmentation and Classification of Coronary Arteries

In recent years, the prevalence of coronary artery disease (CAD) has become one of the leading causes of death around the world. Accurate stenosis detection of coronary arteries is crucial for timely treatment. Cardiologists use visual estimations when reading coronary angiography images to diagnose stenosis. As a result, they face various challenges which include high workloads, long processing times and human error. Computer-aided segmentation and classification of coronary arteries, as to whether stenosis is present or not, significantly reduces the workload of cardiologists and human errors caused by manual processes. Moreover, deep learning techniques have been shown to aid medical experts in diagnosing diseases using biomedical imaging. Thus, this study proposes the use of automatic segmentation of coronary arteries using U-Net, ResUNet-a, UNet++, models and classification using DenseNet201, EfficientNet-B0, Mobilenet-v2, ResNet101 and Xception models. In the case of segmentation, the comparative analysis of the three models has shown that U-Net achieved the highest score with a 0.8467 Dice score and 0.7454 Jaccard Index in comparison with UNet++ and ResUnet-a. Evaluation of the classification model's performances has shown that DenseNet201 performed better than other pretrained models with 0.9000 accuracy, 0.9833 specificity, 0.9556 PPV, 0.7746 Cohen's Kappa and 0.9694 Area Under the Curve (AUC).

Clinical Management of Patients With Stable Ischemic Heart Disease

Ischemic heart disease is considered stable, if patients are asymptomatic or have well controlled symptoms. Based on the pretest probability, noninvasive imaging tests are performed to rule out the disease, and coronary computed tomography angiography being the first line. Invasive coronary angiography remains the gold standard method for diagnosing coronary artery disease. In patients with stable coronary artery disease, comorbidities such as hyperlipidemia, hypertension, and diabetes should be optimized. For patients with persistent anginal symptoms even with optimized medical therapy, coronary revascularization with percutaneous coronary intervention can be considered. Coronary artery bypass grafting may be more beneficial for patients who has stable coronary artery disease with left main disease and/or left ventricular dysfunction and/or multivessel disease; however, treatment should be individualized to the overall clinical picture.

Association of Metabolic Syndrome with Adverse Outcomes in Patients with Stable Coronary Artery Disease: A Meta-Analysis

A consensus has not been reached on the association of metabolic syndrome (MetS) with adverse outcomes in patients with stable coronary artery disease (CAD). The purpose of this systematic review and meta-analysis was to summarize the prognostic implication of MetS in patients with stable CAD. We comprehensively searched articles indexing in PubMed and Embase databases until August 14, 2022. Original studies investigating the association of MetS with adverse outcomes in patients with stable CAD were included. Seven studies including 32 736 patients with stable CAD were identified. Depending on the definition of MetS, the reported prevalence of MetS ranged from 23.4% to 63%. Meta-analysis showed that patients with MetS conferred an increased risk of all-cause mortality [risk ratio (RR) 1.22; 95% confidence intervals (CI) 1.15-1.19], cardiovascular mortality (RR 1.49; 95% CI 1.16-1.92), and MACEs defined by death, myocardial infarction, revascularization, cardiac arrest, or angina admission (RR 1.47; 95% CI 1.20-1.79), respectively. Leave-one-out sensitivity analysis indicated the robustness of the value of MetS in prediction of all-cause mortality. MetS may be an independently predictor of adverse outcomes in patients with stable CAD. However, future studies are required to consolidate the current evidence due to the small number of studies included.

MicroRNAs as Biomarkers for Coronary Artery Disease Related to Type 2 Diabetes Mellitus-From Pathogenesis to Potential Clinical Application

Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease with still growing incidence among adults and young people worldwide. Patients with T2DM are more susceptible to developing coronary artery disease (CAD) than non-diabetic individuals. The currently used diagnostic methods do not ensure the detection of CAD at an early stage. Thus, extensive research on non-invasive, blood-based biomarkers is necessary to avoid life-threatening events. MicroRNAs (miRNAs) are small, endogenous, non-coding RNAs that are stable in human body fluids and easily detectable. A number of reports have highlighted that the aberrant expression of miRNAs may impair the diversity of signaling pathways underlying the pathophysiology of atherosclerosis, which is a key player linking T2DM with CAD. The preclinical evidence suggests the atheroprotective and atherogenic influence of miRNAs on every step of T2DM-induced atherogenesis, including endothelial dysfunction, endothelial to mesenchymal transition, macrophage activation, vascular smooth muscle cells proliferation/migration, platelet hyperactivity, and calcification. Among the 122 analyzed miRNAs, 14 top miRNAs appear to be the most consistently dysregulated in T2DM and CAD, whereas 10 miRNAs are altered in T2DM, CAD, and T2DM-CAD patients. This up-to-date overview aims to discuss the role of miRNAs in the development of diabetic CAD, emphasizing their potential clinical usefulness as novel, non-invasive biomarkers and therapeutic targets for T2DM individuals with a predisposition to undergo CAD.