Cardiovascular Diabetology最新文献

Background: Current approaches to estimating the probability of coronary artery disease (CAD) in patients with type 2 diabetes mellitus (T2DM) often fail to reflect the clinical complexity of the condition, as they tend to oversimplify it by neglecting its progressive nature, variability in glycemic control, and the influence of disease duration. The SCORE2-Diabetes (SCORE2-D) model was developed to offer a more nuanced cardiovascular risk estimate by incorporating continuous variables and individualized risk factor weighting. However, its correlation with the actual presence and severity of CAD in diabetic patients remains under-investigated.

Objective: This study aims to evaluate the association between SCORE2-D scores and CAD characteristics, as assessed by computed tomography coronary angiography (CCTA), in patients with T2DM and no prior coronary revascularization. Specifically, it investigates the relationship between SCORE2-D risk categories and the presence, morphology, and severity of coronary plaques.

Methods: A retrospective analysis was conducted on patients aged 40-69 with T2DM, no history of atherosclerotic cardiovascular disease, and no severe target organ damage, who underwent CCTA at a tertiary care center. Clinical data, SCORE2-D values, and imaging results were collected. Patients were stratified into SCORE2-D risk categories, and coronary findings were compared across groups.

Results: The study included 104 patients (mean age 60.9 years; mean SCORE2-D 12.2 ± 4.9). Higher SCORE2-D scores were significantly associated with the presence of coronary plaques. In the low-moderate risk group, calcified and non-calcified plaques were similarly distributed, while in the high-very high risk group, non-calcified (lipid-rich and mixed) plaques predominated, indicating potentially more vulnerable lesions. Proximal coronary segments, especially the left anterior descending artery, were most frequently involved. A progressive increase in plaque burden and stenosis severity was observed with rising SCORE2-D risk category. Patients at higher risk were more often referred for invasive coronary angiography.

Conclusions: Higher SCORE2-D scores correlate with greater CAD burden, more severe stenosis, and a predominance of high-risk plaque features in patients with T2DM. These findings suggest that SCORE2-D may be a valuable tool in refining cardiovascular risk stratification and guiding clinical decision-making in diabetic populations.

Background: Sodium-glucose cotransporter-2 (SGLT2) inhibitors, primarily used to treat type 2 diabetes, exhibit cardioprotective effects by improving myocardial energy metabolism, reducing oxidative stress, and modulating inflammation and fibrosis, which are critical in the context of acute myocardial infarction (AMI). Our research aims to explore the molecular mechanisms of SGLT2 inhibitors, with a focus on their influence on non-coding RNAs through sirtuins pathways, to identify novel biomarkers and therapeutic strategies for preventing heart failure following AMI.

Methods: We identified microRNAs (miRNAs) that play a role in sirtuin pathways in AMI. We validated the expressions of precisely selected miRNAs along with sirtuin gene expressions (SIRT1-7) in a total of 227 patients with samples from baseline and after 26-week of either placebo or empagliflozin treatment by qRT-PCR. We also performed SHAP analysis of clinical data and miRNAs target predictions and advanced enrichment analyses.

Results: Empagliflozin treatment significantly modulated sirtuin and miRNA expression, with higher SIRT6 (p < 0.001) and lower SIRT4 (p = 0.018) expression compared to placebo after 26 weeks.(p (p In contrast, patients in the placebo group showed a reduction in SIRT6 expression (p = 0.006). Patients were divided according to the change in LVEF (ΔLVEF) between baseline and 26-weeks, using a cut-off of 11%. This threshold was derived from the third quartile distribution in the empagliflozin group. Baseline SIRT2 and SIRT4 levels independently predicted a ΔLVEF < 11% improvement (AUC: 0.806 and 0.765, respectively; both p < 0.01), as did miR-182-5p and miR-302a-3p (AUC: 0.716 and 0.757; both p < 0.01). A combined biomarker panel including SIRT2, SIRT4, miR-182-5p, and miR-302a-3p demonstrated superior predictive accuracy for ΔLVEF < 11% after 26-weeks of empagliflozin treatment (cross-validated AUC: 0.890; 81% sensitivity; 90% specificity). This association remained significant after multivariate adjustment for age, sex, hypertension, BMI, and ezetimibe treatment (OR: 18.70; 95% CI: 5.78-60.49). Importantly, baseline NT-proBNP levels did not significantly predict an unfavorable outcome after 26-weeks of empagliflozin treatment.

Conclusion: Baseline levels of SIRT2, SIRT4, miR-182-5p, and miR-302a-3p were identified as predictors of ΔLVEF < 11% changes after 26-weeks of treatment, which suggests their potential for stratifying responders and non-responders to empagliflozin. The combined panel of these markers demonstrated the highest predictive accuracy, suggesting the epigenetic influence of SGLT2 inhibitors and the potential for genomic characterization in personalized treatment approaches.

Background: Epicardial adipose tissue (EAT) is linked to both Atrial fibrillation (AF) and metabolic syndrome (MetS). Whether EAT inflammation relates to AF type, recurrence after ablation, or MetS, is incompletely known, likewise if it can be measured by CT angiography.

Aim: To establish the link between (1) atrial EAT inflammatory composition and AF type, AF recurrence, and metabolic comorbidities. (2) EAT inflammation and EAT-volume or density.

Methods: Patients undergoing thoracoscopic ablation for advanced AF (that is, usually persistent, with enlarged left atria and previous failed ablations) with a cardiac CT-scan before and 6 months after surgery were enrolled. CT-EAT atrial volume and attenuation (density), were used for analyses. Patients' left atrial appendages (LAA + EAT) were excised during ablation and stained for adipocytes and different inflammatory cells.

Results: Among the 134 included patients, 113 had a LAA available for (immuno)histo-chemistry. Patients with persistent versus paroxysmal AF had more EAT neutrophils: 155[257] versus 63[106] cells/mm², (p = 0.003), and less anti-inflammatory CD163 + macrophages: 126[134] versus 224[179], (p = 0.03). The AUC curve for differentiating persistent from paroxysmal AF through neutrophil-count was 0.75 (p value < 0.001, CI 0.63-0.87). EAT neutrophil-count related to CT-EAT-attenuation, multivariable analysis: expB 1.01, CI 1.00-1.02, (p = 0.04). CT-EAT-attenuation distinguished persistent from paroxysmal AF: - 73.0 ± 4.6 versus - 75.3 ± 5.3HU, (p = 0.03). Patients with versus without recurrence had similar inflammatory cell counts, but larger adipocytes, multivariable analysis: ExpB 1.002, CI 1.00-1.003, (p = 0.02). Hypertensive and diabetic patients also had an increased adipocyte size.

Conclusion: Patients with persistent versus paroxysmal AF exhibited increased EAT neutrophils, which is reflected by CT-EAT-attenuation. Those with AF recurrence, hypertension and diabetes had adipocyte hypertrophy which may imply a common mechanism underlying these conditions.

Background: Type 2 diabetes mellitus (T2DM) increases the risk of cardiovascular disease (CVD), largely by alterations in the blood lipids and the metabolism of circulating lipoproteins (LPs). We studied whether the presence of additional risk factors, such as hypertension, or CVD itself, is associated with further alterations in the LP profiles in individuals with T2DM.

Methods: We performed LP profiling using ¹H NMR spectroscopy and quantified 65 parameters in 393 healthy controls (HC) and in 390 T2DM patients with and without cardiovascular comorbidities. Univariate and multivariate analyses were used to assess alterations in LPs in diabetic patients.

Results: Triglycerides in all major LP classes, as well as particle numbers of very low-density lipoproteins (VLDL) and intermediate-density lipoproteins (IDL) were increased in T2DM compared to HC. In contrast, particle numbers of low-density lipoproteins (LDL) and high-density lipoproteins (HDL) were reduced, suggesting slower lipolytic conversion of IDL to LDL and impaired clearance of triglyceride-enriched HDL. Univariate and multivariate analyses converged in identifying distinct LP profiles associated with T2DM, while differences between patients with and without hypertension or CVD were minor, indicating that T2DM is the primary factor driving LP dysregulation. T2DM, with or without cardiovascular comorbidities, also causes differential disruption of the correlation structure among LPs.

Conclusions: T2DM is associated with major alterations in LP metabolism independent of hypertension or CVD. Thus, early lipid management in T2DM is important to mitigate CVD risk. Further research is needed to elucidate how T2DM progresses to CVD in relation to atherogenic LPs.

Background: To evaluate whether integrating proteomics, metabolomics, and a cardiovascular disease specific polygenic risk score (CVD-PRS) in the SCORE2-Diabetes model improves sex-specific 10-year prediction of major adverse cardiovascular events (MACE) in individuals with type 2 diabetes (T2D).

Methods: Genome-wide association study (GWAS), plasma proteomics (with the Olink Explore 3072 platform), and metabolomics (with nuclear magnetic resonance spectroscopy by Nightingale Health) data were measured in the UK Biobank. A novel sex-specific protein algorithm was developed using bootstrap-LASSO (Least absolute shrinkage and selection operator) regression. The CVD-PRS and sex-specific metabolite algorithms were used from previous UK Biobank projects. In a subset of 990 participants with T2D, age 40-69 years, with no prior MACE, and complete multi-omics data, we evaluated, which omics data improved the SCORE2-Diabetes model performance using Harrell's C-index.

Results: Overall 9 proteins were selected for males and 7 for females and adding them to the SCORE2-Diabetes model significantly improved discrimination in the total population (C-index increase from 0.766 to 0.835 (P < 0.001)). Further adding of metabolites significantly improved model performance (C-index, 0.846, P = 0.035), which was mostly attributable to model improvement among males (∆C-index, 0.012, P = 0.078) but not among females (∆C-index, 0.004, P = 0.723). Further adding the CVD-PRS did not statistically significantly improve the SCORE2-Diabetes + proteomics + metabolomics model further in the total population (C-index, 0.848 (P = 0.070)).

Conclusions: Sex-specific proteomic signatures markedly improved 10-year MACE risk prediction in individuals with T2D. In men but not in women, further integration of metabolomics may enhance model performance whereas adding the CVD-PRS is not needed. External validation is warranted.

Background: Statins are a cornerstone of cardiovascular disease prevention, but growing evidence suggests they may increase the risk of new-onset type 2 diabetes. The cardiovascular implications of diabetes that develops during statin therapy, however, remain unclear. This study aimed to evaluate whether incident diabetes during statin use is associated with increased risk of major adverse cardiovascular events (MACE) or all-cause mortality, compared with individuals with preexisting diabetes and statin users who remained free of diabetes.

Methods: We conducted two retrospective cohort studies using data from the Korean National Health Insurance Service (KNHIS) database between 2009 and 2020, which includes nationwide, population-based data from both primary and secondary care settings. From a source population of 1,500,959 adults, Study 1 identified 4371 individuals who had used statins continuously for ≥ 730 days before receiving a new diagnosis of type 2 diabetes mellitus (T2DM). These individuals were propensity score-matched 1:1 to individuals who initiated statin therapy after a prior diagnosis of T2DM, matched by age, sex, and low-density lipoprotein cholesterol levels. In Study 2, 4191 statin users who developed T2DM during follow-up were matched 1:1 with statin users who remained diabetes-free during the same period. The primary outcome was MACE, defined as a composite of myocardial infarction and stroke. All-cause mortality was assessed as a secondary outcome.

Results: In Study 1, individuals who developed diabetes during statin therapy had a significantly lower risk of MACE compared with those who initiated statins after diabetes diagnosis (adjusted hazard ratio [aHR] 0.607; 95% confidence interval [CI], 0.458-0.805; p = 0.0005), primarily driven by a reduced stroke risk (aHR 0.504; 95% CI, 0.357-0.711; p < 0.001). In Study 2, incident diabetes during statin use was not associated with increased risk of MACE (aHR 1.122; 95% CI, 0.784-1.605; p = 0.53) or all-cause mortality (aHR 0.555; 95% CI, 0.290-1.063; p = 0.0758), compared with remaining diabetes-free.

Conclusions: Diabetes that develops during statin therapy was associated with a lower risk of MACE compared with initiating statins after diabetes diagnosis and was not linked to increased risk of MACE or all-cause mortality compared with remaining diabetes-free.

Background: Initiation of Glucagon-Like Peptide-1 receptor agonists (GLP-1RA) in patients with type 2 diabetes (T2D) treated with levothyroxine may decrease the required levothyroxine dose due to weight loss or enhance levothyroxine absorption through delayed gastric emptying. These changes may cause thyroid hormone over-replacement and increased risk of atrial fibrillation/flutter (AF/Aflutter) and stroke. Our study aims to investigate the impact of GLP-1RA initiation on risks of AF/Aflutter and stroke in patients with T2D treated with levothyroxine, compared to sodium-glucose cotransporter 2 (SGLT2) inhibitors.

Methods: Leveraging the target trial emulation framework, we conducted a retrospective study using observational data to emulate a new user, active comparator trial examining the effects of initiating GLP-1RA (exposure group) versus SGLT2 inhibitors (control group), with random treatment assignment emulated by propensity score matching with 1:1 ratio. We used a 15% nationally representative sample of U.S. Medicare beneficiaries to identify participants > 65 years, continuously on stable dose of levothyroxine for ≥ 6 months before the index date (i.e., GLP-1RA or SGLT2 inhibitor initiation), with continuous Medicare enrollment, without malignant cancer or palliative care during 1 year before the index date. The primary outcome was AF/Aflutter, and secondary outcome was stroke, including ischemic stroke or transient ischemic attack. We assessed the per-protocol effects of GLP-1RA vs. SGLT2 inhibitors using inverse-probability-censoring weighted Cox proportional hazards models.

Results: After matching, the study cohort included 2,384 participants in both GLP-1RA and SGLT2 groups with mean age (SD): 73.3 (5.9) vs. 73.2 (5.8), and 71.5% and 71.8% of female. The median follow-up time was 1.05 years. Compared to SGLT2 inhibitors, initiation of GLP-1RA was associated with higher risk of AF/Aflutter (HR: 1.46; 95% CI: 1.28-1.67), while no statistically significant difference was observed between the two groups for stroke (HR: 1.17; 95% CI: 0.98-1.39). Sensitivity analyses showed consistent results, including restricting outcomes to inpatient visits, conducting an intention-to-treat analysis, applying a prevalent new user design, and substituting SGLT2 inhibitors with dipeptidyl peptidase-4 (DPP4) inhibitors as the active comparator.

Conclusions: In patients with T2D historically treated with stable doses of levothyroxine, GLP-1RA initiation was associated with a higher risk of AF/Aflutter. Further research is warranted to investigate the potential roles of weight loss, TSH fluctuations, and levothyroxine dose adjustment after GLP-1RA in mediating the cardiovascular risk.

Background/objective: Chronic vascular complications are the primary threat in long-standing type 1 diabetes (T1D) patients. We examined the associations between oral-gut microbiome dysbiosis and these complications, offering novel insights into therapeutic strategies and underlying mechanisms.

Methods: This cross-sectional study enrolled 75 T1D participants (disease duration ≥ 10 years) and 43 healthy controls who underwent comprehensive clinical assessment, including blood glucose, lipid profile, and complication-related examinations. Fecal and oral rinse samples were collected for shotgun metagenomic sequencing. T1D participants were stratified by the presence of microvascular (retinopathy, nephropathy, or neuropathy) or macrovascular complications separately. Microbial differences across groups were assessed.

Results: Significant differences in oral and gut microbiota compositions were observed between T1D participants with and without complications (both microvascular and macrovascular). A core set of 26 gut and 8 oral microbial species was specifically associated with vascular complications. Butyrate-producing gut bacteria (Blautia wexlerae, Anaerobutyricum hallii, Roseburia inulinivorans, A. soehngenii) and specific oral Neisseria species were enriched in T1D without complications individuals, suggesting protective effects against complications. Mediation analysis indicated associations consistent with partial mediation between certain microbial species and the relationships of glycemic control or insulin resistance (HbA1c, glucose risk index, estimated glucose disposal rate) with complication risk. Moreover, potential oral-gut microbiome interconnections were implicated in complication development. Finally, classification models integrating both oral and gut microbial features significantly outperformed models based on either site alone in distinguishing T1D patients with complications.

Conclusions: Distinct oral and gut microbiome features are associated with chronic vascular complications in T1D. These findings highlight the potential of microbiome-targeted strategies for understanding and preventing T1D-related complications.