Cardiovascular Diabetology最新文献

Background: Type 2 diabetes mellitus (T2DM) predisposes patients to adverse cardiac remodeling even before the development of cardiomyopathic symptoms. The mechanisms for such early perturbations remain elusive. Given that myosin is the most abundant and energy‑demanding cardiac protein, we tested whether its regulation is impaired even in non‑failing human diabetic hearts.

Methods: Left ventricular strips were individually isolated from organ donors with and without T2DM. These strips were then subjected to a combination of acetyl‑proteomics, X-ray diffraction, in-silico simulations and Mant-ATP chase experiments.

Results: Strikingly, we identified nine cardiac myosin (MYH7) lysine residues with significantly altered acetylation levels in T2DM ventricles, many of which were predicted to destabilize the protein coiled‑coil regions. Consistently, X‑ray diffraction revealed increased lattice spacing and a shift towards myosin ON‑state in T2DM tissue. However, and surprisingly, Mant‑ATP chase analyses indicated no bioenergetic consequences at the myosin level.

Conclusions: Human T2DM myocardium exhibits early, site‑specific myosin acetylations that destabilize myosin structural OFF‑state. This myosin 'preload' remodeling occurs at no energetic cost and may constitute a potential early marker of latent myocardial vulnerability in T2DM.

Background: Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot contributing to coronary atherosclerosis, yet the molecular mechanisms underlying EAT-related coronary artery disease (CAD) in type 2 diabetes mellitus (T2DM) remain unclear. Previously, we identified novel circulating miRNAs targeting fatty acid metabolism in T2DM-CAD. This study aimed to investigate whether EAT may explain the association between dysregulated hsa-miR-4505, hsa-miR-4743-5p, hsa-miR-4750-3p and CAD in T2DM patients and whether it can detect diabetic atherosclerosis alone or in a multi-modal combination.

Methods: Seventy-six patients with T2DM and/or CAD along with eighteen healthy controls were enrolled in the study. All participants underwent transthoracic echocardiography to assess EAT thickness on the free wall of the right ventricle at end-systole and bioelectrical impedance analysis for body composition determination. Spearman's rank correlation and multivariate linear regression accounting for relevant clinical confounders were used to explore the associations between EAT and miRNAs. To further investigate whether EAT acts as an intermediary between miRNA and CAD in T2DM, causal mediation analysis was employed. The receiver operating characteristics curves were generated to evaluate the diagnostic performance of the combined models built using multivariate logistic regression.

Results: The median EAT thickness was significantly higher in T2DM-CAD patients compared to T2DM subjects and controls (p < 0.0001). The bivariate analysis showed a positive correlation between triglyceride concentration and EAT thickness, and a negative one with hsa-miR-4750-3p expression. After multivariable adjustment, hsa-miR-4750-3p (β = - 0.445, p = 0.003) emerged as a standalone predictor of EAT thickness. Logistic regression analysis identified enlarged EAT, up-regulated hsa-miR-4505, hsa-miR-4743-5p and down-regulated hsa-miR-4750-3p to be independently associated with higher CAD risk in T2DM. Adding miRNAs to EAT improved CAD detection in T2DM (AUC = 0.988), outperforming both EAT (AUC = 0.869), clinical factors (AUC = 0.829), and their combination (AUC = 0.901). The mediation analysis revealed that EAT accounted for 48.79% of the total effect of hsa-miR-4750-3p on CAD in T2DM.

Conclusions: These findings suggest that the proposed miRNA-EAT regulatory axis may be involved in the pathogenesis of diabetic atherosclerosis, with EAT appearing to partially mediate the relationship between hsa-miR-4750-3p and CAD. The integrated approach linking EAT and miRNAs holds potential for CAD risk stratification in T2DM.

Background: Cardiovascular metabolic diseases (CMDs) are a major contributor to global mortality and disability, yet their pathogenesis remains incompletely understood, partly because existing in vitro models fail to capture disease complexity. Conventional engineered heart tissues (EHT), which typically contain only a limited set of cell types and lack neural components, cannot replicate the intricate neuro-cardiac interactions involved in CMDs.

Objective: This study aimed to develop a neuron-like-Integrated Engineered Heart Tissue for investigating neuro-cardiac interactions under both physiological and pathological conditions, offering a new tool for CMD research.

Methods: We constructed a Sympathetic-like-Integrated Engineered Heart Tissue (SIEHT) by incorporating sympathetic-like neuronal cells into EHT. The structural and functional properties of SIEHT were systematically compared with conventional EHT using morphological analysis, immunofluorescence staining, contractility measurements, qPCR, and RNA sequencing. The model was then exposed to advanced glycation end products (AGEs) to assess pathological remodeling through multiple parameters, including cell viability, oxidative stress, structural and functional integrity, and transcriptomic profiles.

Results: SIEHT exhibited greater structural and functional maturation than EHT, as indicated by improved cardiomyocyte alignment, increased contraction amplitude, and upregulated expression of connexin 43. Transcriptomic analysis revealed enriched pathways associated with multi-system development. Under AGEs-induced pathological conditions, SIEHT demonstrated a more pronounced reduction in cell viability, elevated reactive oxygen species levels, more severe contractile dysfunction, a higher frequency of abnormal spontaneous beating, and greater neural injury relative to controls. Transcriptome profiling further identified significant enrichment of the AGE-RAGE signaling pathway in diabetic complications.

Conclusions: We successfully established a novel SIEHT model that recapitulates physiological neuro-cardiac interactions and AGEs-induced adverse remodeling across multiple dimensions, providing a powerful and innovative tool for elucidating the pathophysiological mechanisms of neuro-cardiac dysregulation in CMDs.

Background: The triglyceride-glucose (TyG) index, estimated glucose disposal rate (eGDR), and metabolic score for insulin resistance (METS-IR) are well-established surrogate indices of insulin resistance (IR). Although both IR and elevated basal metabolic rate (BMR) are recognized risk factors for cardiometabolic diseases, their joint effects on the risk of cardiometabolic multimorbidity (CMM) remain unclear. This study aimed to investigate the separate and combined associations of these IR surrogates and BMR with incident CMM.

Methods: We included 7204 eligible participants from the 2011-2020 survey waves of the China Health and Retirement Longitudinal Study (CHARLS). Participants were stratified by median values of IR surrogate indices and BMR. The associations with CMM were assessed using Kaplan-Meier curves, multivariable Cox regression, and restricted cubic splines (RCS). Predictive performance was evaluated using receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Mediation and interaction analyses were performed to explore potential underlying relationships.

Results: Over a median follow-up of 9 years, 1103 participants (15.31%) developed CMM. Compared to those with low IR and low BMR, participants with high levels of both exhibited the highest risk of CMM, with hazard ratios of 2.13 (95% CI 1.73-2.63) for TyG, 1.93 (95% CI 1.57-2.36) for eGDR, and 1.92 (95% CI 1.61-2.29) for METS-IR. These associations remained consistent in subgroup and sensitivity analyses. Adding IR indices and BMR to the baseline model significantly improved CMM prediction: TyG (AUC 0.759, NRI 0.371, IDI 0.017; all P < 0.001), eGDR (AUC 0.753, NRI 0.330, IDI 0.012; all P < 0.01), and METS-IR (AUC 0.747, NRI 0.170, IDI 0.004; all P < 0.01). Mediation analysis demonstrated that all IR indices significantly mediated the association between BMR and CMM, and a bidirectional mediation relationship was specifically observed between BMR and the TyG index. Notably, no significant additive or multiplicative interactions were detected.

Conclusion: IR surrogate indices and BMR independently and jointly predicted the risk of CMM, with IR pathways substantially mediating the effect of BMR. The combined assessment of these parameters may improve CMM risk stratification and guide primary prevention strategies.

Background: Cardiovascular-kidney-metabolic (CKM) syndrome integrates metabolic, renal, and cardiovascular disease risk. While increasing evidence suggests that triglyceride-glucose (TyG)-related indices are associated with the future risk of cardiometabolic multimorbidity (CMM), their link to CMM in CKM syndrome has not been established.

Methods: This study analyzed participants with CKM syndrome stage 0-3 from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. We used Cox regression analysis, restricted cubic spline (RCS) curves, and Kaplan-Meier (K-M) survival curves to evaluate the relationship between TyG-related indices and CMM risk in patients with CKM stage 0-3 syndrome. Receiver operating characteristic (ROC) curves, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) analyses were used to assess the predictive performance of the TyG-related indices for CMM.

Results: During a median follow-up of 9 years, 652 participants (9.5%) developed CMM. The fully adjusted model revealed an elevated CMM risk across the highest quartiles of all indices, with hazard increases ranging from 72 to over 200%. A linear dose-response relationship was observed for most indices, except for triglyceride glucose-a body shape index (TyG-ABSI) and C-reactive protein-triglyceride-glucose index (CTI). The triglyceride glucose-Chinese visceral adiposity index (TyG-CVAI) achieved the highest area under the curve (AUC) for CMM prediction (0.679), and compared with the fully adjusted model (Model 4), all indices provided significant incremental predictive values.

Conclusion: Nine TyG-related indices, particularly TyG-CVAI, are strong independent predictors of future CMM in patients with CKM syndrome stage 0-3. These findings underscore the utility of TyG-related indices, particularly TyG-CVAI, in identifying high-risk individuals, thereby informing strategies for the early detection and prevention of CKM syndrome.

Background: The ketogenic diet (KD) is widely recognized for its potential benefits in individuals with type 2 diabetes, but findings from both human and animal studies remain inconsistent. Type 2 diabetes is often comorbid with liver steatosis and atherosclerosis which are characterized by inflammation and dysregulated lipid metabolism. Moreover, whereas KD has shown mixed, sometimes detrimental, effects on circulating cholesterol levels in humans, it is currently unclear the whole-body balance of risk and benefit across hepatic, atherosclerotic, and pancreatic effects.

Methods: We used lean, diet-induced obese, and diet-induced obese, atherosclerotic (PCSK9 overexpression (OE)) mouse models to assess the impact of an extreme KD on cardiometabolic outcomes. Obese and PCSK9 OE mice received 10 weeks of cholesterol-supplemented HFD before 12 weeks of KD intervention whereas lean mice received KD, chow, or HFD for 12 weeks.

Results: KD intervention induced weight loss in obese female and PCSK9 OE male mice, but not male, wildtype mice. Across models, KD did not improve glucose tolerance or ex vivo insulin secretion, despite elevated levels of insulinotropic GLP-1 after glucose gavage. Pancreas lipids were similar between diet groups in obese mice, but liver steatosis or inflammation were generally improved in all models on KD. All KD groups had increased hepatic expression of genes for fatty acid oxidation, ketone body production, and ketone utilization. KD-intervened PCSK9 OE mice had lower circulating TNFα and chemokines (CCL2, CCL4, CXCL1, CXCL2) as well as smaller atherosclerotic lesion area relative to mice that continued on the HFD. The PCSK9 OE male mice on KD intervention also had reduced circulating LDL cholesterol but this effect was lost in mice with intact LDL receptor signaling, which also had fasting hypertriglyceridemia in line with HFD continuers.

Conclusions: This study demonstrates that, in mice, a high cholesterol KD can improve hepatic steatosis particularly when weight loss is achieved, compared to maintaining the western-style HFD. However, no improvements to insulin secretion and glucose tolerance were observed despite elevated post-glucose GLP-1 levels and long-term diminished requirements for insulin.

Objective: The atherogenic index of plasma (AIP) is a marker of atherosclerosis, while frailty reflects cumulative physiological decline. However, the combined impact of AIP-frailty index (AIP-FI) has not been adequately explored. This study aimed to investigate the association between AIP-FI and the risk of cardiovascular disease (CVD), stroke, and heart disease.

Methods: This prospective cohort study included 6896 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS) without CVD, stroke, or heart disease at baseline. The Cox proportional hazard models and restricted cubic spline (RCS) analysis were applied to explore the association between AIP-FI with the risk of CVD, stroke, and heart disease.

Results: During a median follow-up period of 9 years, 1648 (23.9%) of CVD events, 548 (7.9%) of stroke events, and 1280 (18.6%) of heart disease events were recorded. Cox regression analysis revealed that each 1-unit increment in the AIP-FI was significantly associated with higher risk of CVD (HR: 2.95, 95% CI 2.15, 4.05), stroke (HR: 3.14, 95% CI 1.88, 5.26), and heart disease (HR: 2.72, 95% CI 1.06, 1.89, 3.92). The RCS revealed a significant positive nonlinear relationship between AIP-FI with the risk of CVD, stroke, and heart disease (all P-overall < 0.05, and all P for non-linear < 0.05).

Conclusions: Our study demonstrated that higher AIP-FI was significantly associated with increased risk of CVD, stroke, and heart disease. By integrating metabolic and frailty information, AIP-FI offers an effective and accessible tool for cardiovascular risk assessment, supporting earlier prevention and intervention strategies in the middle-aged and elderly Chinese populations.

Background: Patients with type 2 diabetes have an increased risk of tachyarrhythmias and more frequently require implantable cardioverter defibrillators (ICD) than those without diabetes (No-DM). This study aims to investigate whether there is a difference in the indication, prognosis and complication rates for ICD-implantation between patients with and without type 2 diabetes in different ICD prevention groups.

Research design and methods: This Swedish retrospective cohort study included patients with de novo ICDs implanted between 2010 and 2021. Data from six national registries were analyzed to compare type 2 diabetes and No-DM patients regarding indications, complications, and outcomes (major adverse cardiovascular events [MACE], all-cause mortality). Subgroup analyses compared type 2 diabetes and No-DM by primary (PP) or secondary prevention (SP) ICD indication, and within the type 2 diabetes and No-DM groups (PP vs. SP).

Results: The study cohort consisted of 12,885 patients, including 2,843 with type 2 diabetes. Patients with diabetes had a mean age of 67.9 years and 85.4% were male, compared with 62.1 years and 78.1% among No-DM patients (both p < 0.0001). PP was more frequent in patients with type 2 diabetes (62.7%) than No-DM (54.4%, p < 0.0001). Ischemic heart disease was the most common etiology in both patients with/without type 2 diabetes (47.7% vs. 32.6%, p < 0.0001). Non-ischemic etiologies were more common in No-DM patients, e.g. dilated cardiomyopathy (15.3% vs. 17.5%, p = 0.007). Type 2 diabetes patients had a higher adjusted risk of all-cause mortality (Hazard ratio 1.95 [95% CI: 1.81-2.11]) and MACE (1.87 [1.71-2.05]), with a more pronounced risk in SP than PP. Infection rates were comparable between patients with type 2 diabetes and No-DM (1.1% vs. 1.3%).

Conclusions: Patients with type 2 diabetes more often received ICDs for PP and ischemic indications than No-DM patients and had a worse prognosis despite similar one-year infection risk. This likely reflects greater comorbidity burden and diabetes-specific factors, indicating the need for tailored risk management strategies beyond device implantation in patients with type 2 diabetes.

Background: Dapagliflozin (DAPA) has shown major nephroprotective effects, improving kidney metabolism and oxigenation. Lipidomics and metabolomics are powerful tools for understanding such effects, providing a comprehensive look at how SGLT2 inhibitors might change the metabolic landscape beyond their primary glucose-lowering action. We investigated changes in plasma metabolomic/lipidomic profile and urinary excretion of metabolites that could occur independent of increased diuresis.

Methods: A two-armed, parallel-design, randomized clinical trial was conducted in subjects with type 2 diabetes and hypertension who received treatment with DAPA 10 mg/day or hydrochlorothiazide 12.5 mg/day for four weeks. Lipidomics and metabolomics were performed by high resolution mass spectrometry in fasting plasma and 24-hour urine samples collected before and after treatment.

Results: Compared to hydrochlorothiazide, DAPA significantly increased plasma isoleucine, methionine, citrate, β-hydroxybutyrate and decreased lactate. DAPA induced plasma lipid remodeling towards a significant raise in free fatty acids (FFAs) and some sphingomyelins and lysophosphatidylcholines containing these fatty acids. A significant change was observed in plasma medium- and short-chain acylcarnitines, positively correlated with changes in plasma FFAs and β-hydroxybutyrate. In addition, DAPA, but not hydrochlorothiazide, significantly increased 24-h urinary excretion of several amino-acids, lactate, TCA cycle metabolites, β-hydroxybutyrate and electrolytes, except for a decrease in malate excretion.

Conclusions: DAPA treatment has major effects on the plasma lipidomic and the urine metabolomic profiles, with significant increased renal excretion of several metabolites, especially amino-acids, independently of increased diuresis. These data offer insights into the complex metabolic pathways leading to kidney protection by SGLT2 inhibitors.

Clinical trial information: European Union Drug Regulating Authorities Clinical Trials No. 2015-004164-11.