Cardiovascular Diabetology最新文献

Background: Most existing risk equations for predicting/stratifying individual diabetic kidney disease (DKD) risks were developed using relatively dated data from selective and homogeneous trial populations comprising predominately Caucasian type 2 diabetes (T2D) patients. We seek to adapt risk equations for prediction of DKD progression (microalbuminuria, macroalbuminuria, and renal failure) using empiric data from a real-world population with T2D in Taiwan.

Methods: Risk equations from three well-known simulation models: UKPDS-OM2, RECODe, and CHIME models, were adapted. Discrimination and calibration were determined using the area under the receiver operating characteristic curve (AUROC), a calibration plot (slope and intercept), and the Greenwood-Nam-D'Agostino (GND) test. Recalibration was performed for unsatisfactory calibration (p-value of GND test < 0.05) by adjusting the baseline hazards of risk equations to address risk variations among patients.

Results: The RECODe equations for microalbuminuria and macroalbuminuria showed moderate discrimination (AUROC: 0.62 and 0.76) but underestimated the event risks (calibration slope > 1). The CHIME equation had the best discrimination for renal failure (AUROCs from CHIME, UKPDS-OM2 and RECODe: 0.77, 0.60 and 0.64, respectively). All three equations overestimated renal failure risk (calibration slope < 1). After rigorous updating, the calibration slope/intercept of the recalibrated RECODe for predicting microalbuminuria (0.87/0.0459) and macroalbuminuria (1.10/0.0004) risks as well as the recalibrated CHIME equation for predicting renal failure risk (0.95/-0.0014) were improved.

Conclusions: Risk equations for prediction of DKD progression in real-world Taiwanese T2D patients were established, which can be incorporated into a multi-state simulation model to project and differentiate individual DKD risks for supporting timely interventions and health economic research.

Background: The impact of dynamic changes in the degree of atherosclerosis on the development of prediabetes remains unclear. This study aims to investigate the association between cumulative atherogenic index of plasma (CumAIP) exposure during follow-up and the development of prediabetes in middle-aged and elderly individuals.

Methods: A total of 2,939 prediabetic participants from the first wave of the China Health and Retirement Longitudinal Study (CHARLS) were included. The outcomes for these patients, including progression to diabetes and regression to normal fasting glucose (NFG), were determined using data from the third wave. CumAIP was calculated as the ratio of the average AIP values measured during the first and third waves to the total exposure duration. The association between CumAIP and the development of prediabetes was analyzed using multivariable Cox regression and restricted cubic spline (RCS) regression.

Results: During a median follow-up period of 3 years, 15.21% of prediabetic patients progressed to diabetes, and 22.12% regressed to NFG. Among the groups categorized by CumAIP quartiles, the proportion of prediabetes progressing to diabetes gradually increased (Q1: 10.61%, Q2: 13.62%, Q3: 15.65%, Q4: 20.95%), while the proportion regressing to NFG gradually decreased (Q1: 23.54%, Q2: 23.71%, Q3: 22.18%, Q4: 19.05%). Multivariable-adjusted Cox regression showed a significant positive linear correlation between high CumAIP exposure and prediabetes progression, and a significant negative linear correlation with prediabetes regression. Furthermore, in a stratified analysis, it was found that compared to married individuals, those who were unmarried (including separated, divorced, widowed, or never married) had a relatively higher risk of CumAIP-related diabetes.

Conclusion: CumAIP is closely associated with the development of prediabetes. High CumAIP exposure not only increases the risk of prediabetes progression but also hinders its regression within a certain range. These findings suggest that monitoring and maintaining appropriate AIP levels may help prevent the deterioration of blood glucose levels.

Background: N⁶-methyladenosine (m⁶A) modification of messenger RNA (mRNA) is crucial for liquid-liquid phase separation in mammals. Increasing evidence indicates that liquid-liquid phase separation in proteins and RNAs affects diabetic cardiomyopathy. However, the molecular mechanism by which m⁶A-mediated phase separation regulates diabetic cardiac fibrosis remains elusive.

Methods: Leptin receptor-deficient mice (db/db), cardiac fibroblast-specific Notch1 conditional knockout (POSTN-Cre × Notch1^flox/flox) mice, and Cre mice were used to induce diabetic cardiac fibrosis. Adeno-associated virus 9 carrying cardiac fibroblast-specific periostin (Postn) promoter-driven small hairpin RNA targeting Alkbh5, Ythdf2, or Notch1, and the phase separation inhibitor 1,6-hexanediol were administered to investigate their roles in diabetic cardiac fibrosis. Histological and biochemical analyses were performed to determine how Alkbh5 and Ythdf2 regulate Notch1 expression in diabetic cardiac fibrosis. NOTCH1 was reconstituted in ALKBH5- and YTHDF2-deficient cardiac fibroblasts and mouse hearts to study its effects on mitochondrial fission and diabetic cardiac fibrosis. Heart tissue samples from patients with diabetic cardiomyopathy were used to validate our findings.

Results: In mice with diabetic cardiac fibrosis, decreased Notch1 expression was accompanied by high m⁶A mRNA levels and mitochondrial fission. Fibroblast-specific deletion of Notch1 enhanced mitochondrial fission and cardiac fibroblast proliferation and induced diabetic cardiac fibrosis in mice. Notch1 downregulation was associated with Alkbh5-mediated m⁶A demethylation in the 3'UTR of Notch1 mRNA and elevated m⁶A mRNA levels. These elevated m⁶A levels in Notch1 mRNA markedly enhanced YTHDF2 phase separation, increased the recognition of m⁶A residues in Notch1 mRNA by YTHDF2, and induced Notch1 degradation. Conversely, epitranscriptomic downregulation rescues Notch1 expression, resulting in the opposite effects. Human heart tissues from patients with diabetic cardiomyopathy were used to validate the findings in mice with diabetic cardiac fibrosis.

Conclusions: We identified a novel epitranscriptomic mechanism by which m⁶A-mediated phase separation suppresses Notch1 expression, thereby promoting mitochondrial fission in diabetic cardiac fibrosis. Our findings provide new insights for the development of novel treatment approaches for patients with diabetic cardiac fibrosis.

Metabolic dysfunction-associated steatotic liver disease (MASLD), previously termed nonalcoholic fatty liver disease (NAFLD), poses a significant global health challenge due to its increasing prevalence and strong association with cardiovascular disease (CVD). This comprehensive review summarizes the current knowledge on the MASLD-CVD relationship, compares analysis of how different terminologies for fatty liver disease affect cardiovascular (CV) risk assessment using different diagnostic criteria, explores the pathophysiological mechanisms connecting MASLD to CVD, the influence of MASLD on traditional CV risk factors, the role of noninvasive imaging techniques and biomarkers in the assessment of CV risk in patients with MASLD, and the implications for clinical management and prevention strategies. By incorporating current research and clinical guidelines, this review provides a comprehensive overview of the complex interplay between MASLD and cardiovascular health.

Aims: To estimate the incidence of major adverse cardiovascular events (MACE), expanded MACE, and MACE or Death across Fibrosis- 4 score (FIB-4) categories in people with type 2 diabetes and to determine whether efpeglenatide's effect varies with increasing FIB-4 severity.

Materials and methods: AMPLITUDE-O trial data were used to estimate the relationship of FIB-4 score categories to the hazard of MACE, expanded MACE, and MACE or death. Interactions on these outcomes between baseline FIB-4 score, and between FIB-4 score and efpeglenatide were also assessed.

Results: Baseline FIB-4 score was available for 4059 participants (99.6%) allowing subdivision of the population in tertiles. During a median follow-up of 1.8 years, numerical increases in the incidence of all 3 outcomes did not change significantly across tertiles of FIB-4 score (P for trend ≥ 0.25) with negligible relationship of the score to incident outcomes (MACE HR, per 1 SD higher score, 95% CI: 1.00, 0.89-1.13). Efpeglenatide's effect on all MACE outcomes did not vary across FIB-4 tertiles (all interaction p values ≥ 0.64).

Conclusions: In high-risk people with type 2 diabetes, the degree of liver fibrosis, as estimated by FIB-4 score, was not related to incident cardiovascular outcomes. The beneficial effect of efpeglenatide on these outcomes is independent of FIB-4 category.

Background: Hyperglycemia-induced oxidative stress is a well-established pathological mediator of vascular complications in diabetes. We assessed plasma oxidant and antioxidant levels in response to acute and chronic hyperglycemia in relation to vascular stiffness and varying degrees of kidney disease in type 1 diabetes individuals.

Methods: The acute hyperglycemia study included 22 type 1 diabetic individuals with normal albumin excretion rate (AER) and 13 non-diabetic controls. These individuals received an acute glucose challenge during a 120-minute hyperglycemic clamp. The chronic hyperglycemia study included 118 type 1 diabetic individuals with chronically low (n = 60) or high (n = 58) HbA1c concentrations and varying degrees of diabetic kidney disease (DKD) classified as normal, moderate, or severe albuminuria (AER). Levels of malondialdehyde (MDA), reactive oxygen metabolites (ROMs), total antioxidant capacity (TAC), biological antioxidant potential (BAP) and superoxide dismutase (SOD) were measured from plasma or serum samples in the FinnDiane study.

Results: Levels of MDA (p < 0.01) and ROMs (p < 0.01) were elevated in type 1 diabetes individuals compared to non-diabetic controls at baseline. Acute hyperglycemia further increased MDA levels (p < 0.05) and sustained the elevation of ROMs in type 1 diabetes individuals. Acute hyperglycemic challenge impaired TAC in both non-diabetic (p < 0.05) and type 1 diabetes (p < 0.01) individuals compared to baseline whereas BAP was increased (p < 0.05) with no difference observed in non-diabetic controls. There was a positive association between high circulating MDA and AIx (r2 = 0.611, p = 0.05), and between delta ROMs and delta AIx (r2 = 0.955, p = 0.014) in combined analysis of individuals with type 1 diabetes and non-diabetic controls. Type 1 diabetes individuals with varying status of DKD, showed elevated levels of ROMs in those with high HbA1c compared to their counterpart with low HbA1c (p < 0.05). Individuals with severe albuminuria showed elevated ROM levels (p < 0.01) and depressed antioxidant capacity (p < 0.01) compared to those with normal AER of comparable HbA1c concentrations.

Conclusions: Biomarkers of oxidative stress are associated with vascular stiffness and DKD following acute and chronic hyperglycemic exposure and may provide added value to HbA1c in understanding disease pathology, predicting risk and assessing the status of secondary complications of type 1 diabetes.

Background: Type 2 diabetes mellitus (T2DM) is associated with decreased heart rate variability (HRV) with an unclear intermediate mechanism. This study aimed to conduct mediation analysis to explore the impact of various adipose tissues on the relationship between T2DM and HRV.

Methods: A total of 380 participants were enrolled for analysis, including 249 patients with T2DM and 131 non-diabetic controls. The thicknesses of four adipose tissues (subcutaneous, extraperitoneal, intraperitoneal, and epicardial) were measured by abdominal ultrasound or echocardiography respectively. HRV was assessed by 24-hour Holter for monitoring both frequency domain indices (LF, HF, and LF/HF) and time domain indices (SDNN, SDANN, SDNN index, rMSSD and pNN50). Mediation analysis was used toexamine whether adipose tissues mediated the relationship between T2DM and each index of HRV. Then, a latent variable - HRV burden - was constructed by structural equation model with selected HRV indices to comprehensively assess the whole HRV.

Results: Compared to non-diabetic controls, patients with T2DM exhibited a significant reduction in indices of HRV, and a remarkable increase in the thicknesses of extraperitoneal, intraperitoneal, and epicardial adipose tissues. Mediation analysis found significant indirect effects of T2DM on six indices of HRV, including HF, SDNN, SDANN, SDNN index, rMSSD, and pNN50, which was mediated by epicardial adipose tissue rather than other adipose tissues, with the mediation proportions of 64.21%, 16.38%, 68.33%, 24.34%, 24.10% and 30.51%, respectively. Additionally, epicardial adipose tissue partially mediated the relationship between T2DM and reduced HRV burden (24.26%), which composed by SDNN, SDNN index, rMSSD, and pNN50.

Conclusion: Epicardial adipose tissue partially mediated the relationship between T2DM and reduced HRV, which reinforces the value of targeting heart-specific visceral fat to prevent cardiac autonomic neuropathy in diabetes.

Background: The pericoronary fat attenuation index (FAI) has emerged as a novel and sensitive biomarker reflecting the degree of coronary artery inflammation. Semaglutide has been demonstrated to exert a cardiovascular protective effect independent of hypoglycemia; however, its impact on coronary artery inflammation remains elusive. This study aimed to investigate the association between semaglutide treatment and coronary artery inflammation based on FAI in patients with type 2 diabetes mellitus (T2DM).

Methods: This study enrolled 497 T2DM patients who underwent coronary computed tomography angiography (CCTA) at Hebei General Hospital, of whom 93 treated with semaglutide (Sema+) and 404 did not (Sema-). Clinical data, laboratory indicators, and CCTA parameters were collected and compared between the two groups at baseline. Propensity score matching (PSM) was used to adjust for confounders, and pericoronary FAI was compared. Multivariate linear regression models were used to analyze the association between semaglutide treatment and pericoronary FAI.

Results: Before PSM, pericoronary FAI of the LAD and LCX was lower in patients treated with semaglutide than those without semaglutide treatment. The results of the PSM analysis revealed a lower FAI in all three major coronary arteries in the Sema + group compared to the Sema- group. Multivariate linear regression analyses revealed an independent association between semaglutide treatment and reduced FAI in all three major coronary arteries. This association varied across T2DM patients of differing profiles.

Conclusion: Semaglutide treatment may be associated with lower coronary artery inflammation in patients with T2DM, which might partially explain its cardiovascular protective mechanism.

Background: To investigate the relationship between estimated glucose disposal rate (eGDR), a surrogate indicator of insulin resistance, and atherosclerotic cardiovascular diseases (ASCVD) incidence risk.

Methods: This prospective cohort study utilized data from the 6026 participants from the Multi-Ethnic Study of Atherosclerosis. The eGDR (mg/kg/min) was computed as 21.158 - (0.09 × waist circumference [cm]) - (3.407 × hypertension [yes/no]) - (0.551 × HbA1c [%]). The population was categorized into four subgroups according to the quartiles (Q) of eGDR. Cox proportional hazard models were applied to assess the associations between eGDR and ASCVD incidence, and restricted cubic spine (RCS) was employed to examine the dose-response relationship.

Results: The mean age of participants was 63.6 ± 10.1 years, comprising 3163 (52.5%) women. Over a median follow-up duration of 14.1 years, 565 (9.4%) developed ASCVD, including 256 (4.2%) myocardial infarctions, 234 (3.9%) strokes, and 358 (5.9%) fatal coronary heart disease. Compared to the lowest quartile, the adjusted hazard ratios (95% confidence intervals) for incident ASCVD for Q2-Q4 were 0.87 (0.68-1.10), 0.63 (0.47-0.84), and 0.43 (0.30-0.64), respectively. Per 1 standard deviation increase in eGDR was associated with a 30% (HR: 0.70, 95% CI 0.60-0.80) risk reduction of ASCVD, with the subgroup analyses indicating that age and hypertension modified the association (P for interaction < 0.05). RCS analysis indicated a significant and linear relationship between eGDR and ASCVD incidence risk.

Conclusion: eGDR level was negatively associated with incident ASCVD risk in a linear fashion among the general population. Our findings may contribute to preventive measures by improving ASCVD risk assessment.

Background: Cardiovascular disease, also known as circulation system disease, remains the leading cause of morbidity and mortality worldwide. Traditional methods for diagnosing cardiovascular disease are often expensive and time-consuming. So the purpose of this study is to construct machine learning models for the diagnosis of cardiovascular diseases using easily accessible blood routine and biochemical detection data and explore the unique hematologic features of cardiovascular diseases, including some metabolic indicators.

Methods: After the data preprocessing, 25,794 healthy people and 32,822 circulation system disease patients with the blood routine and biochemical detection data were utilized for our study. We selected logistic regression, random forest, support vector machine, eXtreme Gradient Boosting (XGBoost), and deep neural network to construct models. Finally, the SHAP algorithm was used to interpret models.

Results: The circulation system disease prediction model constructed by XGBoost possessed the best performance (AUC: 0.9921 (0.9911-0.9930); Acc: 0.9618 (0.9588-0.9645); Sn: 0.9690 (0.9655-0.9723); Sp: 0.9526 (0.9477-0.9572); PPV: 0.9631 (0.9592-0.9668); NPV: 0.9600 (0.9556-0.9644); MCC: 0.9224 (0.9165-0.9279); F1 score: 0.9661 (0.9634-0.9686)). Most models of distinguishing various circulation system diseases also had good performance, the model performance of distinguishing dilated cardiomyopathy from other circulation system diseases was the best (AUC: 0.9267 (0.8663-0.9752)). The model interpretation by the SHAP algorithm indicated features from biochemical detection made major contributions to predicting circulation system disease, such as potassium (K), total protein (TP), albumin (ALB), and indirect bilirubin (NBIL). But for models of distinguishing various circulation system diseases, we found that red blood cell count (RBC), K, direct bilirubin (DBIL), and glucose (GLU) were the top 4 features subdividing various circulation system diseases.

Conclusions: The present study constructed multiple models using 50 features from the blood routine and biochemical detection data for the diagnosis of various circulation system diseases. At the same time, the unique hematologic features of various circulation system diseases, including some metabolic-related indicators, were also explored. This cost-effective work will benefit more people and help diagnose and prevent circulation system diseases.