Complex effects of sequence variants on lipid levels and coronary artery disease.

Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.

Genetic Architecture and Clinical Outcomes of Combined Lipid Disturbances.

BACKGROUND: Dyslipoproteinemia often involves simultaneous derangements of multiple lipid traits. We aimed to evaluate the phenotypic and genetic characteristics of combined lipid disturbances in a general population-based cohort. METHODS: Among UK Biobank participants without prevalent coronary artery disease, we used blood lipid and apolipoprotein B concentrations to ascribe individuals into 1 of 6 reproducible and mutually exclusive dyslipoproteinemia subtypes. Incident coronary artery disease risk was estimated for each subtype using Cox proportional hazards models. Phenome-wide analyses and genome-wide association studies were performed for each subtype, followed by in silico causal gene prioritization and heritability analyses. Additionally, the prevalence of disruptive variants in causal genes for Mendelian lipid disorders was assessed using whole-exome sequence data. RESULTS: Among 450 636 UK Biobank participants: 63 (0.01%) had chylomicronemia; 40 005 (8.9%) had hypercholesterolemia; 94 785 (21.0%) had combined hyperlipidemia; 13 998 (3.1%) had remnant hypercholesterolemia; 110 389 (24.5%) had hypertriglyceridemia; and 49 (0.01%) had mixed hypertriglyceridemia and hypercholesterolemia. Over a median (interquartile range) follow-up of 11.1 (10.4-11.8) years, incident coronary artery disease risk varied across subtypes, with combined hyperlipidemia exhibiting the largest hazard (hazard ratio, 1.92 [95% CI, 1.84-2.01]; P=2×10-16), even when accounting for non-HDL-C (hazard ratio, 1.45 [95% CI, 1.30-1.60]; P=2.6×10-12). Genome-wide association studies revealed 250 loci significantly associated with dyslipoproteinemia subtypes, of which 72 (28.8%) were not detected in prior single lipid trait genome-wide association studies. Mendelian lipid variant carriers were rare (2.0%) among individuals with dyslipoproteinemia, but polygenic heritability was high, ranging from 23% for remnant hypercholesterolemia to 54% for combined hyperlipidemia. CONCLUSIONS: Simultaneous assessment of multiple lipid derangements revealed nuanced differences in coronary artery disease risk and genetic architectures across dyslipoproteinemia subtypes. These findings highlight the importance of looking beyond single lipid traits to better understand combined lipid and lipoprotein phenotypes and implications for disease risk.

Thrombin Generation Is Associated With Extracellular Vesicle and Leukocyte Lipid Membranes in Atherosclerotic Cardiovascular Disease.

BACKGROUND: Clotting, leading to thrombosis, requires interactions of coagulation factors with the membrane aminophospholipids (aPLs) phosphatidylserine and phosphatidylethanolamine. Atherosclerotic cardiovascular disease (ASCVD) is associated with elevated thrombotic risk, which is not fully preventable using current therapies. Currently, the contribution of aPL to thrombotic risk in ASCVD is not known. Here, the aPL composition of circulating membranes in ASCVD of varying severity will be characterized along with the contribution of external facing aPL to plasma thrombin generation in patient samples. METHODS: Thrombin generation was measured using a purified factor assay on platelet, leukocyte, and extracellular vesicles (EVs) from patients with acute coronary syndrome (n=24), stable coronary artery disease (n=18), and positive risk factor (n=23) and compared with healthy controls (n=24). aPL composition of resting/activated platelet and leukocytes and EV membranes was determined using lipidomics. RESULTS: External facing aPLs were detected on EVs, platelets, and leukocytes, elevating significantly following cell activation. Thrombin generation was higher on the surface of EVs from patients with acute coronary syndrome than healthy controls, along with increased circulating EV counts. Thrombin generation correlated significantly with externalized EV phosphatidylserine, plasma EV counts, and total EV membrane surface area. In contrast, aPL levels and thrombin generation from leukocytes and platelets were not impacted by disease, although circulating leukocyte counts were higher in patients. CONCLUSIONS: The aPL membrane of EV supports an elevated level of thrombin generation in patient plasma in ASCVD. Leukocytes may also play a role although the platelet membrane did not seem to contribute. Targeting EV formation/clearance and developing strategies to prevent the aPL surface of EV interacting with coagulation factors represents a novel antithrombotic target in ASCVD.

Integrative Metabolomics Differentiate Coronary Artery Disease, Peripheral Artery Disease, and Venous Thromboembolism Risks.

BACKGROUND: Arterial and venous cardiovascular conditions, such as coronary artery disease (CAD), peripheral artery disease (PAD), and venous thromboembolism (VTE), are genetically correlated. Interrogating underlying mechanisms may shed light on disease mechanisms. In this study, we aimed to identify (1) epidemiological and (2) causal, genetic relationships between metabolites and CAD, PAD, and VTE. METHODS: We used metabolomic data from 95 402 individuals in the UK Biobank, excluding individuals with prevalent cardiovascular disease. Cox proportional-hazards models estimated the associations of 249 metabolites with incident disease. Bidirectional 2-sample Mendelian randomization (MR) estimated the causal effects between metabolites and outcomes using genome-wide association summary statistics for metabolites (n=118 466 from the UK Biobank), CAD (n=184 305 from CARDIoGRAMplusC4D 2015), PAD (n=243 060 from the Million Veterans Project), and VTE (n=650 119 from the Million Veterans Project). Multivariable MR was performed in subsequent analyses. RESULTS: We found that 196, 115, and 74 metabolites were associated (P<0.001) with CAD, PAD, and VTE, respectively. Further interrogation of these metabolites with MR revealed 94, 34, and 9 metabolites with potentially causal effects on CAD, PAD, and VTE, respectively. There were 21 metabolites common to CAD and PAD and 4 common to PAD and VTE. Many putatively causal metabolites included lipoprotein traits with heterogeneity across different sizes and lipid subfractions. Small VLDL (very-low-density lipoprotein) particles increased the risk for CAD while large VLDL particles decreased the risk for VTE. We identified opposing directions of CAD and PAD effects for cholesterol and triglyceride concentrations within HDLs (high-density lipoproteins). Subsequent sensitivity analyses including multivariable MR revealed several metabolites with robust, potentially causal effects of VLDL particles on CAD. CONCLUSIONS: While common vascular conditions are associated with overlapping metabolomic profiles, MR prioritized the role of specific lipoprotein species for potential pharmacological targets to maximize benefits in both arterial and venous beds.

Influence of Polygenic Background on the Clinical Presentation of Familial Hypercholesterolemia.

BACKGROUND: Heterozygous familial hypercholesterolemia (FH) is among the most common genetic conditions worldwide that affects ≈ 1 in 300 individuals. FH is characterized by increased levels of low-density lipoprotein cholesterol (LDL-C) and increased risk of coronary artery disease (CAD), but there is a wide spectrum of severity within the FH population. This variability in expression is incompletely explained by known risk factors. We hypothesized that genome-wide genetic influences, as represented by polygenic risk scores (PRSs) for cardiometabolic traits, would influence the phenotypic severity of FH. METHODS: We studied individuals with clinically diagnosed FH (n=1123) from the FH Canada National Registry, as well as individuals with genetically identified FH from the UK Biobank (n=723). For all individuals, we used genome-wide gene array data to calculate PRSs for CAD, LDL-C, lipoprotein(a), and other cardiometabolic traits. We compared the distribution of PRSs in individuals with clinically diagnosed FH, genetically diagnosed FH, and non-FH controls and examined the association of the PRSs with the risk of atherosclerotic cardiovascular disease. RESULTS: Individuals with clinically diagnosed FH had higher levels of LDL-C, and the incidence of atherosclerotic cardiovascular disease was higher in individuals with clinically diagnosed compared with genetically identified FH. Individuals with clinically diagnosed FH displayed enrichment for higher PRSs for CAD, LDL-C, and lipoprotein(a) but not for other cardiometabolic risk factors. The CAD PRS was associated with a risk of atherosclerotic cardiovascular disease among individuals with an FH-causing genetic variant. CONCLUSIONS: Genetic background, as expressed by genome-wide PRSs for CAD, LDL-C, and lipoprotein(a), influences the phenotypic severity of FH, expanding our understanding of the determinants that contribute to the variable expressivity of FH. A PRS for CAD may aid in risk prediction among individuals with FH.

COVID-19 Is a Coronary Artery Disease Risk Equivalent and Exhibits a Genetic Interaction With ABO Blood Type.

BACKGROUND: COVID-19 is associated with acute risk of major adverse cardiac events (MACE), including myocardial infarction, stroke, and mortality (all-cause). However, the duration and underlying determinants of heightened risk of cardiovascular disease and MACE post-COVID-19 are not known. METHODS: Data from the UK Biobank was used to identify COVID-19 cases (n=10 005) who were positive for polymerase chain reaction (PCR+)-based tests for SARS-CoV-2 infection (n=8062) or received hospital-based International Classification of Diseases version-10 (ICD-10) codes for COVID-19 (n=1943) between February 1, 2020 and December 31, 2020. Population controls (n=217 730) and propensity score-matched controls (n=38 860) were also drawn from the UK Biobank during the same period. Proportional hazard models were used to evaluate COVID-19 for association with long-term (>1000 days) risk of MACE and as a coronary artery disease risk equivalent. Additional analyses examined whether COVID-19 interacted with genetic determinants to affect the risk of MACE and its components. RESULTS: The risk of MACE was elevated in COVID-19 cases at all levels of severity (HR, 2.09 [95% CI, 1.94-2.25]; P<0.0005) and to a greater extent in cases hospitalized for COVID-19 (HR, 3.85 [95% CI, 3.51-4.24]; P<0.0005). Hospitalization for COVID-19 represented a coronary artery disease risk equivalent since incident MACE risk among cases without history of cardiovascular disease was even higher than that observed in patients with cardiovascular disease without COVID-19 (HR, 1.21 [95% CI, 1.08-1.37]; P<0.005). A significant genetic interaction was observed between the ABO locus and hospitalization for COVID-19 (Pinteraction=0.01), with risk of thrombotic events being increased in subjects with non-O blood types (HR, 1.65 [95% CI, 1.29-2.09]; P=4.8×10-5) to a greater extent than subjects with blood type O (HR, 0.96 [95% CI, 0.66-1.39]; P=0.82). CONCLUSIONS: Hospitalization for COVID-19 represents a coronary artery disease risk equivalent, with post-acute myocardial infarction and stroke risk particularly heightened in non-O blood types. These results may have important clinical implications and represent, to our knowledge, one of the first examples of a gene-pathogen exposure interaction for thrombotic events.

Lipidomic-Based Algorithms Can Enhance Prediction of Obstructive Coronary Artery Disease.

Lipidomics emerges as a promising research field with the potential to help in personalized risk stratification and improve our understanding on the functional role of individual lipid species in the metabolic perturbations occurring in coronary artery disease (CAD). This study aimed to utilize a machine learning approach to provide a lipid panel able to identify patients with obstructive CAD. In this posthoc analysis of the prospective CorLipid trial, we investigated the lipid profiles of 146 patients with suspected CAD, divided into two categories based on the existence of obstructive CAD. In total, 517 lipid species were identified, from which 288 lipid species were finally quantified, including glycerophospholipids, glycerolipids, and sphingolipids. Univariate and multivariate statistical analyses have shown significant discrimination between the serum lipidomes of patients with obstructive CAD. Finally, the XGBoost algorithm identified a panel of 17 serum biomarkers (5 sphingolipids, 7 glycerophospholipids, a triacylglycerol, galectin-3, glucose, LDL, and LDH) as totally sensitive (100% sensitivity, 62.1% specificity, 100% negative predictive value) for the prediction of obstructive CAD. Our findings shed light on dysregulated lipid metabolism's role in CAD, validating existing evidence and suggesting promise for novel therapies and improved risk stratification.

Homocysteine concentration in coronary artery disease and severity of coronary lesions.

Our previous study reckons that the impact of the rs1801133 variant of 5,10-methylenetetrahydrofolate reductase (MTHFR) on coronary artery disease (CAD) is possibly mediated by cardiometabolic disorder. This study is performed to verify this hypothesis. Four hundred and thirty CAD patients and 216 CAD-free individuals were enrolled in this case-control study. The rs1801133 variant was genotyped by PCR-RFLP. Severity of coronary lesions was evaluated by number of stenotic coronary vessels and extent of coronary stenosis. The rs1801133 T allele significantly increased homocysteine levels in patients with CAD and CAD-free individuals. Individuals with the T allele of rs1801133 had an increased risk of developing CAD. In contrast, individuals with the TT genotype of rs1801133 were at high risk of multiple vessel lesions. The carriers of CT genotype had higher levels of systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), and high-sensitivity C-reactive protein (hs-CRP), and lower levels of apolipoprotein A1 (APOA1) than those with CC genotype in male patients with CAD. The receiver operating characteristic (ROC) curve and precision-recall (PR) curve indicated that hyperhomocysteinemia was sensitive to predict the severity of CAD. Multivariate logistic regression revealed that homocysteine, rs1801133, age, smoking, weight, body mass index (BMI), lipoprotein(a) [Lp(a)], and hs-CRP were independent risk factors for CAD. The increased risk of CAD and severity of coronary lesions associated with rs1801133 in the Chinese Han population were attributed, at least partly, to high homocysteine levels. Hyperhomocysteinemia had a high predictive value for severe CAD or multiple vessel lesions.

The alpha 7 nicotinic acetylcholine receptor agonist PHA 568487 dampens inflammation in PBMCs from patients with newly discovered coronary artery disease.

The alpha 7 nicotinic acetylcholine receptor (α7nAChR) regulates inflammation in experimental models and is expressed in human peripheral blood mononuclear cells (PBMCs) and in human atherosclerotic plaques. However, its role in regulating inflammation in patients with cardiovascular disease is unknown. This study aims to investigate whether α7nAChR stimulation can reduce the inflammatory response in PBMCs from patients with newly diagnosed coronary artery disease (CAD). Human PBMCs, extracted from patients with verified CAD (n = 38) and control participants with healthy vessels (n = 38), were challenged in vitro with lipopolysaccharide (LPS) in combination with the α7nAChR agonist PHA 568487. Cytokine levels of the supernatants were analyzed using a multiplex immunoassay. Patients in the CAD group were reexamined after 6 mo. The immune response to LPS did not differ between PBMCs from control and CAD groups. α7nAChR stimulation decreased TNFα in both control and CAD groups. The most pronounced effect of α7nAChR stimulation was observed in patients with CAD at their first visit, where 15 of 17 cytokines were decreased [IL-1ß, IL-2, IL-4, IL-5, IL-6, IL-7, IL-10, IL-12 (p70), IL-17A, G-CSF, GM-CSF, IFN-γ, MCP-1, MIP-1ß, and TNFα]. In conclusion, stimulation with α7nAChR agonist PHA 568487 dampens the inflammatory response in human PBMCs. This finding suggests that the anti-inflammatory properties of the α7nAChR may have a role in treating CAD.NEW & NOTEWORTHY The α7nAChR is an important regulator of inflammation; however, its anti-inflammatory function in patients with newly diagnosed coronary artery disease (CAD) remains unclear. We demonstrate that stimulation of α7nAChR with PHA 568487 attenuates the inflammatory response in immune cells extracted from healthy controls and patients with newly diagnosed CAD, with a more pronounced effect observed in patients with CAD. This suggests that the anti-inflammatory properties of α7nAChR may have a role in treating chronic inflammatory diseases.

Plasma proteomics for prediction of subclinical coronary artery calcifications in primary prevention.

BACKGROUND AND AIMS: Recent developments in high-throughput proteomic technologies enable the discovery of novel biomarkers of coronary atherosclerosis. The aims of this study were to test if plasma protein subsets could detect coronary artery calcifications (CAC) in asymptomatic individuals and if they add predictive value beyond traditional risk factors. METHODS: Using proximity extension assays, 1,342 plasma proteins were measured in 1,827 individuals from the Impaired Glucose Tolerance and Microbiota (IGTM) study and 883 individuals from the Swedish Cardiopulmonary BioImage Study (SCAPIS) aged 50-64 years without history of ischaemic heart disease and with CAC assessed by computed tomography. After data-driven feature selection, extreme gradient boosting machine learning models were trained on the IGTM cohort to predict the presence of CAC using combinations of proteins and traditional risk factors. The trained models were validated in SCAPIS. RESULTS: The best plasma protein subset (44 proteins) predicted CAC with an area under the curve (AUC) of 0.691 in the validation cohort. However, this was not better than prediction by traditional risk factors alone (AUC = 0.710, P = .17). Adding proteins to traditional risk factors did not improve the predictions (AUC = 0.705, P = .6). Most of these 44 proteins were highly correlated with traditional risk factors. CONCLUSIONS: A plasma protein subset that could predict the presence of subclinical CAC was identified but it did not outperform nor improve a model based on traditional risk factors. Thus, support for this targeted proteomics platform to predict subclinical CAC beyond traditional risk factors was not found.

Impact of Direct Measurement of Small Dense Low-Density Lipoprotein Cholesterol for Long-Term Secondary Prevention in Patients with Stable Coronary Artery Disease.

BACKGROUND: This study investigated whether directly measured small dense low-density lipoprotein cholesterol (D-sdLDL-C) can predict long-term coronary artery disease (CAD) events compared with low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), apolipoprotein B (apoB), and estimated small dense low-density lipoprotein cholesterol (E-sdLDL-C) determined by the Sampson equation in patients with stable CAD. METHODS: D-sdLDL-C measured at Showa University between 2010 and 2022, and E-sdLDL-C were evaluated in 790 male and 244 female patients with stable CAD. CAD events, defined as sudden cardiac death, onset of acute coronary syndrome, and/or need for coronary revascularization, were monitored for 12 years. Cutoff lipid levels were determined by receiver operating characteristic curves. RESULTS: CAD events were observed in 238 male and 67 female patients. The Kaplan-Meier event-free survival curves showed that patients with D-sdLDL-C ≥32.1 mg/dL (0.83 mmol/L) had an increased risk for CAD events (P = 0.007), whereas risk in patients with E-sdLDL-C ≥36.2 mg/dL (0.94 mmol/L) was not increased. In the group with high D-sdLDL-C, the multivariable-adjusted hazard ratio (HR) was 1.47 (95% CI, 1.15-1.89), and it remained significant after adjustment for LDL-C, non-HDL-C, or apoB and in patients treated with statins. HRs for high LDL-C, non-HDL-C, or apoB were not statistically significant after adjustment for high D-sdLDL-C. Higher D-sdLDL-C was associated with enhanced risk of high LDL-C, non-HDL-C, and apoB (HR 1.73; 95% CI, 1.27-2.37). CONCLUSIONS: Higher D-sdLDL-C can predict long-term recurrence of CAD in stable CAD patients independently of apoB and non-HDL-C. D-sdLDL-C is an independent risk enhancer for secondary CAD prevention, whereas E-sdLDL-C is not.UMIN-CTR Clinical Trial Number: UMIN000027504.

The association of atherogenic index of plasma with cardiovascular outcomes in patients with coronary artery disease: A systematic review and meta-analysis.

BACKGROUND: Atherogenic index of plasma (AIP) represents a novel marker in the current era of cardiovascular diseases. In this meta-analysis, we aimed to evaluate the association of AIP with cardiovascular prognosis in patients with coronary artery disease (CAD). METHODS: PubMed, Scopus, and Web of Science databases were searched from inception through 2024. The primary outcome was major cardiovascular events (MACE). The secondary outcomes included all-causes death, cardiovascular death, myocardial infarction (MI), stroke, revascularization, and no-reflow phenomenon. AIP was determined by taking the logarithm of the ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C). The data analysis was represented using the risk ratio (RR) along with a 95% confidence interval (CI). RESULTS: Sixteen studies with a total number of 20,833 patients met the eligible criteria. The pooled-analysis showed a significant increased risk of MACE in the highest AIP group compared with the lowest AIP group (RR = 1.63; 95% CI, 1.44-1.85; P < 0.001). A similar result was observed when AIP was regarded as a continuous variable (RR = 1.54; 95% CI, 1.30-1.83; P < 0.001). Besides, elevated AIP was associated with increased risk of cardiovascular death (RR = 1.79; 95% CI, 1.09-2.78; P = 0.02), MI (RR = 2.21; 95% CI, 1.55-3.13; P < 0.001), revascularization (RR = 1.62; 95% CI, 1.34-1.97; P < 0.001), no-reflow phenomenon (RR = 3.12 95% CI, 1.09-8.96; P = 0.034), and stent thrombosis (RR = 13.46; 95%CI, 1.39-129.02; P = 0.025). However, AIP was not significantly associated with the risk of all-causes death and stroke among patients with CAD. CONCLUSIONS: The results of this study demonstrated that increased AIP is an independent prognostic factors in patients with CAD. Further research is warranted to elucidate the potential development of targeted interventions to modify AIP levels and improve patient outcomes.

Which surrogate insulin resistance indices best predict coronary artery disease? A machine learning approach.

BACKGROUND: Various surrogate markers of insulin resistance have been developed, capable of predicting coronary artery disease (CAD) without the need to detect serum insulin. For accurate prediction, they depend only on glucose and lipid profiles, as well as anthropometric features. However, there is still no agreement on the most suitable one for predicting CAD. METHODS: We followed a cohort of 2,000 individuals, ranging in age from 20 to 74, for a duration of 9.9 years. We utilized multivariate Cox proportional hazard models to investigate the association between TyG-index, TyG-BMI, TyG-WC, TG/HDL, plus METS-IR and the occurrence of CAD. The receiver operating curve (ROC) was employed to compare the predictive efficacy of these indices and their corresponding cutoff values for predicting CAD. We also used three distinct embedded feature selection methods: LASSO, Random Forest feature selection, and the Boruta algorithm, to evaluate and compare surrogate markers of insulin resistance in predicting CAD. In addition, we utilized the ceteris paribus profile on the Random Forest model to illustrate how the model's predictive performance is affected by variations in individual surrogate markers, while keeping all other factors consistent in a diagram. RESULTS: The TyG-index was the only surrogate marker of insulin resistance that demonstrated an association with CAD in fully adjusted model (HR: 2.54, CI: 1.34-4.81). The association was more prominent in females. Moreover, it demonstrated the highest area under the ROC curve (0.67 [0.63-0.7]) in comparison to other surrogate indices for insulin resistance. All feature selection approaches concur that the TyG-index is the most reliable surrogate insulin resistance marker for predicting CAD. Based on the Ceteris paribus profile of Random Forest the predictive ability of the TyG-index increased steadily after 9 with a positive slope, without any decline or leveling off. CONCLUSION: Due to the simplicity of assessing the TyG-index with routine biochemical assays and given that the TyG-index was the most effective surrogate insulin resistance index for predicting CAD based on our results, it seems suitable for inclusion in future CAD prevention strategies.

Triglyceride-glucose index is associated with myocardial ischemia and poor prognosis in patients with ischemia and no obstructive coronary artery disease.

BACKGROUND: Ischemia and no obstructive coronary artery disease (INOCA) is increasingly recognized and associated with poor outcomes. The triglyceride-glucose (TyG) index is a reliable alternative measure of insulin resistance significantly linked to cardiovascular disease and adverse prognosis. We investigated the association between the TyG index and myocardial ischemia and the prognosis in INOCA patients. METHODS: INOCA patients who underwent both coronary angiography and myocardial perfusion imaging (MPI) were included consecutively. All participants were divided into three groups according to TyG tertiles (T1, T2, and T3). Abnormal MPI for myocardial ischemia in individual coronary territories was defined as summed stress score (SSS) ≥ 4 and summed difference score (SDS) ≥ 2. SSS refers to the sum of all defects in the stress images, and SDS is the difference of the sum of all defects between the rest images and stress images. All patients were followed up for major adverse cardiac events (MACE). RESULTS: Among 332 INOCA patients, 113 (34.0%) had abnormal MPI. Patients with higher TyG index had a higher rate of abnormal MPI (25.5% vs. 32.4% vs. 44.1%; p = 0.012). Multivariate logistic analysis showed that a high TyG index was significantly correlated with abnormal MPI in INOCA patients (OR, 1.901; 95% CI, 1.045-3.458; P = 0.035). During the median 35 months of follow-up, 83 (25%) MACE were recorded, and a higher incidence of MACE was observed in the T3 group (T3 vs. T2 vs. T1: 36.9% vs. 21.6% vs. 16.4%, respectively; p = 0.001). In multivariate Cox regression analysis, the T3 group was significantly associated with the risk of MACE compared to the T1 group (HR, 2.338; 95% CI 1.253-4.364, P = 0.008). CONCLUSION: This study indicates for the first time that the TyG index is significantly associated with myocardial ischemia and poor prognosis among INOCA patients.

Endothelial microRNAs in INOCA patients with diabetes mellitus.

Ischemia with non-obstructive coronary artery (INOCA) is a common cause of hospital admissions, leading to negative outcomes and reduced quality of life. Central to its pathophysiology is endothelial dysfunction, which contributes to myocardial ischemia despite the absence of significant coronary artery blockage. Addressing endothelial dysfunction is essential in managing INOCA to alleviate symptoms and prevent cardiovascular events. Recent studies have identified diabetes mellitus (DM) as a significant factor exacerbating INOCA complications by promoting endothelial impairment and coronary microvascular dysfunction. MicroRNAs (miRNAs) have emerged as potential biomarkers and therapeutic targets in various biological processes, including endothelial dysfunction and cardiovascular diseases. However, research on miRNA biomarkers in INOCA patients is sparse. In this study, we examined a panel of circulating miRNAs involved in the regulation of endothelial function in INOCA patients with and without DM. We analyzed miRNA expression using RT-qPCR in a cohort of consecutive INOCA patients undergoing percutaneous coronary intervention. We detected a significant dysregulation of miR-363-5p and miR-92a-3p in INOCA patients with DM compared to those without DM, indicating their role as biomarkers for predicting and monitoring endothelial dysfunction in INOCA patients with DM.

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.

The triglyceride glucose: high-density lipoprotein cholesterol ratio is associated with coronary artery calcification evaluated via non-gated chest CT.

BACKGROUND: Coronary artery calcification (CAC) is a common risk factor of cardiovascular disease. Although triglyceride glucose (TYG) index and high-density lipoprotein cholesterol (HDL-c) are both associated with CAC, no study has evaluated the correlation between the TYG/HDL-c ratio and CAC. In the present study, we investigated the relationships between CAC and the TYG index and the TYG/HDL-c ratio. METHODS: A total of 9585 participants who underwent computed tomography (CT) screening for lung cancer from 2018 to 2020 were included in this cross-sectional study. Demographic data, laboratory test data and medical history data were collected from medical records. TYG = Ln[fasting glucose (mg/dL)×fasting TG (mg/dL/2]. The triglyceride glucose-HDL-c ratio was calculated as TYG/HDL-c. CAC was evaluated on chest CT images. Multivariate logistic regression analysis and restricted cubic splines were used to determine the relationships among the TYG index, TYG/HDL-c ratio and risk of CAC. The receiver operating characteristic (ROC) curve was used to evaluate the performance of the TYG index and TYG/HDL-c ratio in identifying CACs in individuals aged 60 years and above. RESULTS: CAC was detected in 2515 of 9585 participants (mean age 51.8 ± 15.5 years, 61.2% men). The prevalence of CAC was significantly greater in participants with a high TYG/HDL-c ratio (32.6% in the fourth quartile vs. 19.1% in the first quartile, p < 0.001). Multivariate logistic regression revealed that both the TYG index (odds ratio (OR) = 1.06, 95% confidence interval (CI): 1.02-1.10) and the TYG/HDL-c ratio were associated with coronary artery calcification (OR = 1.32, 95% CI: 1.14-1.51). No such association was observed between the TYG index and CAC when further adjusted for the serum lipid level (OR = 1.23, 95% CI: 0.99-1.54). The TYG/HDL-c ratio was still associated with CAC after further adjustment for low-density lipoprotein cholesterol and total cholesterol (OR = 1.21, 95% CI: 1.09-1.35). TYG/HDL-c ratio was associated both with single vessel and multivessel calcification (OR = 1.14, 95%CI:1.05-1.23; OR = 1.15, 95%CI: 1.05-1.21). Similar trends were observed when we categorized individuals by TYG index and TYG/HDL-c quartiles and in subjects older than 60 years. Restricted cubic splines revealed that the TYG/HDL ratio had a better dose‒responsive relationship than did the TYG index. Subgroup analysis revealed that the association between the TYG/HDL-c ratio and coronary artery calcification was mainly observed in nondiabetic or nonhypertensive participants, regardless of low-density lipoprotein cholesterol levels. The ROC curve also revealed that the TYG/HDL-c ratio was better able to identify CAC than the TYG index was (area under the curve = 0.54 vs. 0.52, p < 0.01) in subjects older than 60 years. CONCLUSION: An increase in the TYG/HDL-c ratio is significantly positively associated with the risk of CAC, and the TYG/HDL-c ratio has a more stable association with CAC than TYG.

Insulin resistance, coronary artery lesion complexity and adverse cardiovascular outcomes in patients with acute coronary syndrome.

BACKGROUND: Insulin resistance (IR) is linked to both the complexity of coronary artery lesions and the prognosis of acute coronary syndrome (ACS). However, the precise extent of this correlation and its impact on adverse cardiovascular outcomes in ACS patients remain unclear. Therefore, this study aims to investigate the intricate relationship between IR, coronary artery lesion complexity, and the prognosis of ACS through a cohort design analysis. METHOD: A total of 986 patients with ACS who underwent percutaneous coronary intervention (PCI) were included in this analysis. IR was assessed using the triglyceride-glucose (TyG) index, while coronary artery lesion complexity was evaluated using the SYNTAX score. Pearson's correlation coefficients were utilized to analyze the correlations between variables. The association of the TyG index and SYNTAX score with major adverse cardiovascular events (MACEs) in ACS was investigated using the Kaplan-Meier method, restricted cubic splines (RCS), and adjusted Cox regression. Additionally, a novel 2-stage regression method for survival data was employed in mediation analysis to explore the mediating impact of the SYNTAX score on the association between the TyG index and adverse cardiovascular outcomes, including MACEs and unplanned revascularization. RESULTS: During a median follow-up of 30.72 months, 167 cases of MACEs were documented, including 66 all-cause deaths (6.69%), 26 nonfatal myocardial infarctions (MIs) (2.64%), and 99 unplanned revascularizations (10.04%). The incidence of MACEs, all-cause death, and unplanned revascularization increased with elevated TyG index and SYNTAX score. Both the TyG index (non-linear, P = 0.119) and SYNTAX score (non-linear, P = 0.004) displayed a positive dose-response relationship with MACEs, as illustrated by the RCS curve. Following adjustment for multiple factors, both the TyG index and SYNTAX score emerged as significant predictors of MACEs across the total population and various subgroups. Mediation analysis indicated that the SYNTAX score mediated 25.03%, 18.00%, 14.93%, and 11.53% of the correlation between the TyG index and MACEs in different adjusted models, respectively. Similar mediating effects were observed when endpoint was defined as unplanned revascularization. CONCLUSION: Elevated baseline TyG index and SYNTAX score were associated with a higher risk of MACEs in ACS. Furthermore, the SYNTAX score partially mediated the relationship between the TyG index and adverse cardiovascular outcomes.

Effects of the stress hyperglycemia ratio on long-term mortality in patients with triple-vessel disease and acute coronary syndrome.

AIMS: Risk assessment for triple-vessel disease (TVD) remain challenging. Stress hyperglycemia represents the regulation of glucose metabolism in response to stress, and stress hyperglycemia ratio (SHR) is recently found to reflect true acute hyperglycemic status. This study aimed to evaluate the prognostic value of SHR and its role in risk stratification in TVD patients with acute coronary syndrome (ACS). METHODS: A total of 3812 TVD patients with ACS with available baseline SHR measurement were enrolled from two independent centers. The endpoint was cardiovascular mortality. Cox regression was used to evaluate the association between SHR and cardiovascular mortality. The SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) II (SSII) was used as the reference model in the model improvement analysis. RESULTS: During a median follow-up of 5.1 years, 219 (5.8%) TVD patients with ACS suffered cardiovascular mortality. TVD patients with ACS with high SHR had an increased risk of cardiovascular mortality after robust adjustment for confounding (high vs. median SHR: adjusted hazard ratio 1.809, 95% confidence interval 1.160-2.822, P = 0.009), which was fitted as a J-shaped pattern. The prognostic value of the SHR was found exclusively among patients with diabetes instead of those without diabetes. Moreover, addition of SHR improved the reclassification abilities of the SSII model for predicting cardiovascular mortality in TVD patients with ACS. CONCLUSIONS: The high level of SHR is associated with the long-term risk of cardiovascular mortality in TVD patients with ACS, and is confirmed to have incremental prediction value beyond standard SSII. Assessment of SHR may help to improve the risk stratification strategy in TVD patients who are under acute stress.

Comprehensive analysis of the association between triglyceride-glucose index and coronary artery disease severity across different glucose metabolism states: a large-scale cross-sectional study from an Asian cohort.

BACKGROUND: The triglyceride-glucose (TyG) index is associated with the development and prognosis of coronary artery disease (CAD). However, the impact of the TyG index on CAD severity across different glucose metabolism states exhibits significant disparities in previous research. METHODS: This cross-sectional study comprised 10,433 participants from a prospective cohort. Participants were categorized into four groups based on glucose metabolism state: normal glucose regulation (NGR), prediabetes (pre-DM), diabetes mellitus (DM) without insulin prescribed (Rx), and DM with insulin Rx. The TyG index was determined by the following formula: Ln [TG (mg/dL) × FPG (mg/dL) / 2], where TG is triglycerides and FPG is fasting plasm glucose. Statistical methods such as binary logistic regression, interaction analysis, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were employed to analyze the relationship between the TyG index and CAD severity across the entire population and glucose metabolism subgroups. Mediation analysis was conducted to examine the mediating effects of glycated hemoglobin (HbA1c) on these relationships. Sensitivity analysis was performed to ensure the robustness of the findings. RESULTS: Multivariable logistic regression analysis revealed a significant positive association between the TyG index and multi-vessel CAD in the entire population (OR: 1.34; 95% CI: 1.22-1.47 per 1-unit increment). Subgroup analysis demonstrated consistent positive associations in the NGR, pre-DM, and DM non-insulin Rx groups, with the highest OR observed in the NGR group (OR: 1.67; 95% CI: 1.3-2.14 per 1-unit increment). No correlation was found in the DM with insulin Rx subgroup. RCS analyses indicated the distinct dose-response relationships across different glucose metabolism subgroups. Including the TyG index in the established model slightly improved the predictive accuracy, particularly in the NGR group. Mediation analyses showed varying mediating effects of HbA1c among different glucose metabolism subgroups. Sensitivity analysis confirmed the robustness of the aforementioned relationships in the new-onset CAD population and in individuals not using antilipidemic medications. CONCLUSIONS: The TyG index positively associated with CAD severity across all glucose metabolism states, except for individuals receiving insulin treatment. Moreover, it might serve as a supplementary noninvasive predictor of CAD severity in addition to established factors, especially in NGR patients.