Cardiovascular Diabetology最新文献

Background: The atherogenic index of plasma (AIP) serves as a crucial indicator for assessing atherosclerotic risk. It reflects the degree of dyslipidaemia and cardiovascular disease (CVD) risk. The cardiometabolic index (CMI) provides a comprehensive evaluation of obesity-related metabolic risk, acting as a key biomarker for predicting multiple cardiometabolic diseases. The relationship between AIP and CMI in patients with non-alcoholic fatty liver disease (NAFLD) and mortality or CVD risk remains unclear.

Methods: This study included 5792 adult (≥ 18 years) NAFLD patients from the US National Health and Nutrition Examination Survey (NHANES, 1999-2018). Weighted logistic regression and Cox proportional hazards models were employed to investigate the association between AIP, CMI and all-cause mortality, CVD mortality and CVD risk. Restricted cubic spline (RCS) curves assessed non-linear associations. Subgroup analyses and mediation analyses examined the effect modifiers and mediators. The incremental predictive value of AIP and CMI was evaluated. Sensitivity analyses were conducted to validate the robustness.

Results: During follow-up, 721 all-cause deaths (including 241 CVD deaths) and 726 total CVD events were recorded. After adjusting for confounding factors, patients in the highest quartiles of AIP and CMI had a significantly higher risk of specific CVD events. The strongest association was observed for CHF (AIP: OR = 3.157, 95% CI 1.684, 5.922, p < 0.001; CMI: OR = 3.604, 95% CI 1.843, 7.047, p < 0.001), followed by heart attack and CHD. CMI consistently demonstrated a stronger effect than AIP. RCS analysis indicates a non-linear relationship between CMI and CHD, angina pectoris. Subgroup analysis revealed that both AIP and CMI demonstrated high predictive value for all-cause mortality in the 40-60 age cohort. Mediation analysis revealed that Mets, NLR, hypertension and HOMA-IR partially mediated the aforementioned associations. The inclusion of AIP and CMI partially improved the predictive capability of the basic model. Sensitivity analyses validated the robustness of these findings.

Conclusions: In patients with NAFLD, CMI is a stronger predictor of non-fatal CVD than AIP. While both indices show limited value for predicting mortality, CMI holds promise as a practical supplementary tool for clinical risk assessment.

Background: Mitochondrial dysfunction is a hallmark of diabetic kidney disease (DKD), yet its regulatory mechanisms remain poorly defined. Mitochondrial transcription factor A (TFAM), a central regulator of mitochondrial homeostasis, undergoes lysine 76 (K76) acetylation, but the functional significance of this modification in DKD has not been established.

Methods: We collected kidney tissues from DKD patients and DKD mice, and assessed TFAM acetylation in HK-2 cells and primary renal tubular cells under high-glucose conditions. In addition, to investigate the potential mechanism of TFAM acetylation in mitochondrial damage within the kidney, we explored relevant pathways using proteomics and utilized streptozotocin (STZ)-induced DKD mouse models with tubular-specific expression of TFAM wild-type and mutant forms to examine kidney injury. Moreover, we identified TFAM K76 acetylation-specific inhibitors through high-throughput virtual screening and thoroughly validated them in HK-2 cells, primary cells, and DKD mice, confirming the critical role of TFAM acetylation in DKD-related kidney injury.

Results: Here, we identify TFAM K76 acetylation as a critical mediator of mitochondrial injury in DKD. TFAM K76 acetylation was markedly elevated in kidney tissues from DKD patients and diabetic mouse models, correlating with mitochondrial damage, inflammation, and fibrosis under hyperglycemic conditions. In vivo, overexpression of acetylation-mimetic TFAM K76Q in renal tubular epithelial cells aggravated renal injury and ultrastructural damage, whereas its deacetylation attenuated these effects. Mechanistically, TFAM K76 acetylation impaired oxidative phosphorylation and excessively activated autophagy, further exacerbating mitochondrial damage. We identified sirtuin 3 (SIRT3) as an upstream deacetylase that regulates this modification. Importantly, through high-throughput virtual screening, we discovered a novel small-molecule inhibitor (C14) that selectively reduces TFAM K76 acetylation and effectively alleviates hyperglycemia-induced mitochondrial dysfunction, inflammation, and fibrosis in both in vitro and in vivo models.

Conclusions: Collectively, our findings define TFAM K76 acetylation as a pathogenic driver of DKD and propose C14 as a promising therapeutic candidate targeting mitochondrial metabolism.

Background/aims: Current clinical risk tools in type 1 diabetes do not include left ventricular dysfunction or inflammation, potentially limiting early risk detection. We aimed to evaluate the associations and predictive value of combining echocardiography with inflammatory biomarkers for mortality and major adverse cardiovascular events (MACE).

Methods: In a prospective cohort of individuals with type 1 diabetes without known cardiovascular disease, we evaluated whether subclinical left ventricular dysfunction, defined by an elevated ratio of early mitral inflow velocity to early diastolic mitral annular velocity (E/e') or impaired global longitudinal strain (GLS), combined with elevated levels of an inflammatory biomarker (interleukin-6 [IL-6], soluble urokinase-plasminogen-activator-receptor [suPAR], or high-sensitivity C-reactive-protein [hsCRP]), was associated with all-cause mortality and MACE. Cox models were adjusted for all 10 variables included in the Steno T1 Risk Engine variables: age, sex, systolic blood pressure, duration of diabetes, HbA1c, low-density lipoprotein, estimated glomerular filtration rate, albuminuria status, smoking, and physical activity. C-statistics and net reclassification improvement were assessed.

Results: Among 876 participants (51% male, median age 50 years), 114 deaths occurred over 14.5 years of follow-up. Elevated E/e' combined with IL-6 or suPAR, but not hsCRP, was independently associated with mortality. Compared with individuals with E/e' <8 and non-elevated IL-6, the hazard ratio (HR) for E/e' 8-13 with elevated IL-6 was 2.5 (95% CI 1.4 to 4.6, P < 0.01), and for E/e' ≥13 with elevated IL-6 was 3.4 (1.5-7.6; P < 0.01). Corresponding HRs for suPAR were 2.4 (1.2 to 4.7, P < 0.01) and 3.9 (1.8 to 8.5, P < 0.01). Adding E/e' and an inflammatory biomarker increased the C-statistic from 0.839 (Steno T1 Risk Engine alone) to 0.887 (E/e' and IL6) and 0.868 (E/e' and suPAR). Findings were similar for GLS and with MACE as the outcome.

Conclusions: Echocardiography combined with inflammatory biomarkers synergistically identifies individuals with type 1 diabetes, without known cardiovascular disease, who are at high risk of mortality and MACE.

Background: Myocardial infarction (MI) remains a leading cause of global mortality, with risk varying substantially across demographic and clinical subgroups. Although SCORE2 is widely implemented for cardiovascular risk stratification, the extent to which clinical subgroup specific plasma proteomics can further refine personalized MI risk prediction remains uncertain.

Methods: SCORE2-Pro, a clinical subgroup-stratified plasma proteome prediction model was built stratified by sex, age, smoking status, non-high-density lipoprotein (non-HDL) cholesterol, and systolic blood pressure. In 51,010 UK Biobank participants (aged 40-69 years; 54.9% female) without MI at baseline, 70% were used for model development, and the remaining 30% for an internal hold-out validation. We used light gradient boosting machine classifiers and Cox proportional hazards models to identify top-predictive protein combinations and stratification strategies for MI.

Results: The SCORE2-Pro model revealed distinct and highly effective protein panels for each subgroup. Compared with the clinical model, SCORE2-Pro remarkably enhanced predictive performance across demographic and clinical subgroups. A 9-protein model in females improved AUC by + 0.061 (P = 1.51 × 10^-3), with a net reclassification index (NRI) of + 0.125 (P = 2.69 × 10^-6). Similarly, a 7-protein model for middle-aged subpopulation demonstrated an AUC improvement of + 0.036 (P = 0.033) with an NRI of + 0.127 (P = 8.09 × 10^-11). Notably, in high-risk populations, SCORE2-Pro model significantly improved reclassification performance compared with the clinical model (NRI: + 0.121, P = 0.020).

Conclusions: By adopting a clinical subgroup stratification approach using factors derived from SCORE2, we identified subgroup-specific proteomic signatures for MI that considerably improve predictive accuracy and reclassification beyond traditional clinical models.

Background: Estrogen therapy and androgen‑deprivation were once combined to treat prostate cancer (PrCa). Clinical studies later showed that prolonged estrogen exposure in androgen‑deprived men raises cardiovascular disease (CVD) risk, yet the metabolic pathways responsible remain unclear.

Methods: We generated an androgen‑deprived, 17β‑estradiol (E2)-treated mouse model by gonadectomizing male C57BL/6 J mice and implanting sub‑cutaneous delayed‑release E2 or vehicle pellets. Mice received a Western‑style diet and were housed at thermoneutrality to accelerate CVD‑risk phenotypes. Metabolic profiling included hyperinsulinemic‑euglycemic clamps, oral lipid and pyruvate tolerance tests, flow cytometry of immune cells, and single‑nucleus RNA sequencing of liver tissue.

Results: In hypogonadal males, E2 treatment induced several metabolic disturbances. During clamps, E2‑treated mice showed markedly elevated gluconeogenesis, corroborated by higher glucose peaks and AUC during pyruvate tolerance testing and by up‑regulation of hepatic Pck1 mRNA. Triglyceride (TG) clearance, which improves with E2 in females, was impaired in E2‑treated males: oral lipid‑tolerance testing revealed prolonged TG excursions, reduced maximal lipase activity, lower non‑lipase clearance at 6 h post-OLTT, and decreased free‑fatty‑acid peak levels. Hepatic lipase, VLDL clearance receptors Ldlr and Lrp1, and microsomal triglyceride transfer protein (MTP) transcripts were down‑regulated. SnRNA‑seq showed suppression of lipid‑clearance genes with E2 treatment in males. Subcutaneous adipocytes were hypertrophic, and flow cytometry identified increased TNFα‑positive macrophages, an inflammatory milieu that could promote insulin resistance. Cardiac morphology was modestly altered; E2‑treated males exhibited a larger left‑ventricular end‑diastolic diameter, while ejection fraction and arterial pressure remained unchanged.

Conclusion: Estradiol administration in androgen‑deprived male mice produces a constellation of metabolic derangements-including enhanced hepatic gluconeogenesis, impaired TG clearance, and inflammatory adipocyte hypertrophy-that likely underlie the increased CVD risk observed clinically. The identified molecular nodes (PEPCK, hepatic lipase, LRP1, LDLR, MTP, and adipose‑macrophage TNFα) provide potential targets for mitigating estrogen‑induced CVD risk while preserving its therapeutic benefit for PrCa.

Cardiac organoids have emerged as pivotal models for cardiovascular disease research and drug development due to their ability to recapitulate the in vivo cardiac microenvironment, structure, and function. Imaging technologies are core tools for deciphering their three-dimensional (3D) complexity. This review outlines the key framework of cardiac organoid imaging research, focusing on pre-imaging sample processing, mainstream imaging technologies, image analysis workflows and applications in disease mechanisms and drug screening. We also provide guidelines for technique selection based on research objectives. Currently, long-term 4D imaging of cardiac organoids is still in its infancy. Future efforts should optimize imaging strategies and advance high-resolution dynamic techniques to deepen understanding of the temporal dynamics of cardiac pathology, providing technical support for cardiovascular research.

Background: Patients with type 2 diabetes (T2D) are at an increased risk of developing acute myocardial infarction (AMI), yet the role of 5-hydroxymethylcytosines (5hmC) changes in T2D-associated cardiovascular events remains poorly understood. Despite therapeutic advances, patients with T2D who suffer an AMI continue to exhibit markedly elevated cardiovascular risk and poor prognosis, underscoring the need for improved detection and risk assessment.

Methods: We evaluated genome-wide 5hmC modifications in circulating cell-free DNA (cfDNA) for their value as noninvasive biomarkers for AMI in T2D. Genome-wide mapping of 5hmC in plasma cfDNA were obtained using the 5hmC-Seal technique from 225 participants, including 57 T2D patients with AMI (T2D + AMI), and 168 T2D patients without AMI (T2D + non-AMI). A weighted 5hmC-based model was developed to compute an epigenetic score for each individual, which was first derived from baseline cross-sectional data to discriminate between the patients from the two groups. Subsequently, the utility of the epigenetic score for predicting composite cardiovascular outcomes (CCO) was assessed prospectively within the same cohort using 5-year longitudinal follow-up data.

Results: 255 differential 5hmC-gene bodies (P < 0.05) associated with T2D + AMI, involving pathways related to cardiac functions, such as heart process and heart contraction. A seven-feature weighted model based on 5hmC signatures was developed for distinguishing T2D + AMI from T2D + non-AMI, which achieved an area under the curve (AUC) of 99.2% (95% CI 98.1-100.0%) in training set and 95.6% (95% CI 89.8-100.0%) in testing set. Furthermore, we established and tested a 5hmC-derived weighted epigenetic score for predicting cardiovascular events in diabetic population (eSCORE-CARD) over a median follow-up of 5.3 years. Multivariate Cox regression analysis showed that the eSCORE-CARD values were significantly associated with an increased risk of CCO (HR = 4.25; 95% CI 1.41-12.80; P < 0.05). When combined with other established risk tools (SCORE2-Diabetes and SCORE2-OP), eSCORE-CARD demonstrated improved performance achieving an AUC of 76.4% (95% CI 65.9-86.8%), which holds promise for detection and prognosis of cardiovascular events in T2D.

Conclusions: Our work indicated specific 5hmC signatures implicated in AMI with T2D background, and provided the foundation for a comprehensive cardiovascular risk management tool for diabetic population.

Backgrounds: Despite numerous studies investigating the effects of antidiabetic medications on cardiovascular outcomes, the optimal second-line oral antidiabetic medication for atrial fibrillation (AF) prevention remains unclear. This study aims to compare the effects of second-line oral antidiabetic medications including sodium-glucose cotransporter 2 (SGLT2) inhibitors, thiazolidinediones, dipeptidyl peptidase-4 (DPP-4) inhibitors, or sulfonylureas, on the risk of incident AF in patients with type 2 diabetes.

Methods: This retrospective study analyzed data from the National Health Insurance Service data on adults with type 2 diabetes who simultaneously initiated metformin and second-line oral antidiabetic medication (SGLT2 inhibitors, thiazolidinediones, DPP-4 inhibitors, or sulfonylureas) between September 2014 and December 2017. Exact matching by sex and age categories was conducted in a 1:1:5:5 ratio corresponding to SGLT2 inhibitor, thiazolidinedione, DPP-4 inhibitor, and sulfonylurea users, with inverse probability of treatment weighting used to balance the baseline characteristics. The primary outcome was incident AF, which was analyzed using a Fine-Gray model treating all-cause mortality as a competing risk.

Results: During a mean follow-up of 6.2 years, 774 cases of AF occurred among the 36,744 participants (mean age 55.3 years; 33.6% female). Compared with SGLT2 inhibitors, the risk of AF was significantly higher in patients using thiazolidinediones (subdistribution hazard ratio [SHR], 1.22; 95% confidence interval [CI], 1.09-1.36), DPP-4 inhibitor (SHR, 1.14; 95% CI, 1.02-1.28), and sulfonylureas (SHR, 1.20; 95% CI, 1.07-1.34). However, pairwise comparisons among thiazolidinediones, DPP-4 inhibitors, and sulfonylureas revealed no significant differences in AF risk. Subgroup analyses revealed significant effect modifications according to age, hypertension status, and renal function.

Conclusions: This study showed that SGLT2 inhibitor use was associated with a significantly lower risk of AF than use of thiazolidinediones, DPP-4 inhibitors, and sulfonylureas.

Background: Endothelial to mesenchymal transition (EndMT), the transformation of endothelial cells into a mesenchymal-like state, is regulated by various factors, including transcription factors such as activator protein 1 (AP-1). While recent studies have confirmed the role of EndMT in atherosclerosis, the involvement of AP-1 in EndMT, particularly in the context of human diabetes, remains unclear.

Objectives: This study aimed to elucidate the role of the AP-1 transcription factor complex in EndMT associated with atherosclerosis in diabetes, utilising both an in vivo preclinical model and an ex vivo model using patient-derived serum for translational relevance. Additionally, it sought to profile gene expression changes following AP-1 inhibition in an EndMT model under high glucose conditions.

Methods: Serum from patients with and without type 2 diabetes mellitus (T2DM) was used to assess EndMT in primary human aortic endothelial cells (HAECs) in the presence and absence of the AP-1 inhibitor T-5224. EndMT was evaluated through immunofluorescent staining of these cells and of aortic sections from a murine model of diabetes-associated atherosclerosis in a preclinical early intervention study. Furthermore, HAECs were used to explore the effects of AP-1 inhibition on the transcriptional signature of EndMT.

Results: Patient-derived serum induced EndMT in HAECs, which T-5224 effectively prevented, as confirmed by immunofluorescent staining. Immunofluorescent analysis of the aortic sinus also revealed that T-5224 treatment inhibited EndMT, leading to reduced atherosclerosis in Apoe^-/- mice. In parallel, in the HAECs-based in vitro EndMT model, T-5224 mitigated TNF-α and high glucose-induced EndMT. RNA sequencing identified 242 differentially expressed genes (DEGs) associated with EndMT under high glucose conditions, with T-5224 treatment restoring the expression of 77 DEGs.

Conclusion: This study identifies AP-1 inhibition with T-5224 as a potential therapeutic approach for EndMT resulting in reduced atherosclerosis in diabetes. The use of human serum underscores the translational relevance of these findings.

Background: Obesity is prevalent in patients with heart failure with reduced ejection fraction (HFrEF). With the advent of glucagon-like peptide 1 analogues, understanding the relationship between body mass index (BMI) and clinical outcomes in HFrEF is crucial.

Objective: This study investigated whether a BMI > 27 kg/m² is associated with higher rates of all-cause mortality, cardiovascular mortality, and heart failure (HF) hospitalization in patients with HFrEF.

Methods: A total of 1017 clinically stable and medically optimized HFrEF patients from the NorthStar study (enrolled 2005-2009) were analyzed. Patients were followed until 2023 using Danish nationwide registries. The primary outcome was all-cause mortality, while secondary outcomes included cardiovascular mortality, HF hospitalization, and a composite of all-cause mortality or HF hospitalization. Cox proportional-hazards models adjusted for prognostic factors were used to assess associations. Interaction analyses for the primary outcome were conducted for BMI categories (< 24, 24-27, > 27 kg/m²) and prognostic variables.

Results: Compared to patients with a BMI of 24-27 kg/m², those with a BMI > 27 had a higher prevalence of diabetes (27.8% vs. 17.7%), similar HF etiology (ischemic: 57.5% vs. 58.7%), and lower NT-proBNP levels (median 776 vs. 1163 pg/mL). Over a median follow-up of 8.8 years, the primary outcome occurred in 235 patients (71.9%) with BMI 24-27, and 338 patients (71.8%) with BMI > 27 (ref. BMI 24-27: Hazard ratios (HR) 1.11 [0.94 - 1.32]). 124 patients (37.9%) and 186 patients (39.5%) died from cardiovascular causes, respectively (HR 1.21 [0.96 - 1.53]). A first worsening HF event occurred in 214 patients (65.4%) and 317 patients (67.3%) (HR 1.12 [0.93 - 1.33]). A combined outcome of all-cause death and first worsening HF events occurred in 277 patients (84.7%) and 398 patients (84.5%) (HR 1.09 [0.93 - 1.27]). The subgroup analyses revealed a significantly higher mortality rate for BMI > 27 vs 24-27 in patients with ischemic cardiomyopathy (HR 1.31 [1.05-1.64]), but not in patients with non-ischemic cardiomyopathy (HR 0.86 [0.66-1.12]).

Conclusion: In HFrEF patients, a BMI > 27 was not associated with increased mortality, contradicting the "obesity-survival paradox." In fact, patients with ischemic cardiomyopathy and a BMI > 27 may be associated with a higher mortality rate.