Cardiovasc Diabetol [JOURNAL]
Sun
200 papers
Joint longitudinal trajectories of the triglyceride-glucose index combined with BMI and waist-to-height ratio and incident cardiovascular disease: a prospective cohort study from the English longitudinal study of ageing.
Liu Z, Li Q, Wang B … +5 more , Zhou Y, Dong Y, Tang B, Yang H, Yu S
Cardiovasc Diabetol · 2026 Jul · PMID 42402573 · Full text
BACKGROUND: The triglyceride-glucose (TyG) index and its composite obesity indices have been linked to cardiovascular disease (CVD) risk. However, most prior studies relied on single baseline measurements, and few have e...
BACKGROUND: The triglyceride-glucose (TyG) index and its composite obesity indices have been linked to cardiovascular disease (CVD) risk. However, most prior studies relied on single baseline measurements, and few have employed group-based multi-trajectory modeling to capture concurrent longitudinal changes in metabolic and anthropometric indicators. This study aimed to identify joint longitudinal trajectory groups of TyG combined with body mass index (BMI) and waist-to-height ratio (WHtR) using parallel approaches and evaluate their associations with incident CVD in middle-aged and older adults. METHODS: This prospective cohort study included 1808 CVD-free participants aged ≥ 50 years from the English Longitudinal Study of Ageing. Group-based multi-trajectory modeling was applied to jointly identify latent trajectory classes using repeated measurements of TyG with BMI and TyG with WHtR across three waves over approximately 8 years. Cox proportional hazards models with four sequential adjustment models estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for incident composite CVD, heart disease, and stroke. Subgroup analyses were stratified by age, gender, smoking, diabetes, and hypertension status. Nine sensitivity analyses were conducted to assess robustness. RESULTS: During follow-up, 263 participants (14.5%) developed incident CVD. Four trajectory groups were identified for each approach. In fully adjusted BMI + TyG models, compared with the normal weight-low TyG reference group, composite CVD risk increased progressively across the overweight-moderate TyG (HR 2.31, 95% CI 1.40-3.83), obese-high TyG (HR 2.72, 95% CI 1.63-4.52), and severely obese-high TyG groups (HR 5.06, 95% CI 3.01-8.51). The WHtR + TyG approach demonstrated a consistent dose-response pattern, with HRs of 2.22, 2.75, and 5.12 for ascending risk groups. For stroke, only the highest-risk groups reached statistical significance (HR 6.74 and 5.00, respectively). Formal discriminative comparison showed no significant difference between the two approaches (C-statistic difference 0.003, P = 0.723). All nine sensitivity analyses consistently corroborated the primary findings. CONCLUSIONS: Both approaches yield robust and comparable dose-response gradients, supporting further validation of serial TyG-related composite index monitoring for cardiovascular risk stratification in aging populations.
Synergistic SGLT2 and GLP-1R targeting alleviates systemic inflammation-induced and M1 monocyte-driven endothelial dysfunction in coronary artery disease.
Mroueh A, Fakih W, Kerth S … +16 more , Kikuchi S, Aboueddahab C, Gong DS, Choi M, Nicolas A, Fass S, Trimaille A, Granier A, Carmona A, Amissi S, Pompach P, Oak MH, Jesel L, Görlach A, Morel O, Schini-Kerth V
Cardiovasc Diabetol · 2026 Jul · PMID 42401896 · Full text
BACKGROUND AND OBJECTIVE: Systemic residual inflammation plays a pivotal role in the pathophysiology of coronary artery disease (CAD). Cardiovascular protection by SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (G...
BACKGROUND AND OBJECTIVE: Systemic residual inflammation plays a pivotal role in the pathophysiology of coronary artery disease (CAD). Cardiovascular protection by SGLT2 inhibitors (SGLT2i) and GLP-1 receptor agonists (GLP-1Ra) is associated with reduced inflammatory burden but underlying cellular mechanisms remain incompletely defined. We investigated whether SGLT2i and GLP-1Ra synergistically suppress monocyte activation and prevent both systemic inflammatory mediator-induced and monocyte-driven endothelial dysfunction in CAD. METHODS AND RESULTS: Plasma and circulating monocytes were analyzed in healthy individuals (n = 20), patients with cardiovascular disease without CAD (n = 20), and patients with stable CAD (n = 55), and their effects on endothelial cell responses were assessed. CAD plasma showed increased IL-1β, IL-6, TNF-α, MCP-1, soluble ICAM-1, and VCAM-1, and a proteomic profile enriched in complement, innate immune, and extracellular matrix remodeling pathways. CAD plasma induced oxidative stress in endothelial cells, reduced nitric oxide, increased leukocyte and platelet adhesion, and enhanced procoagulant activity, correlating with circulating TNF-α and sICAM-1. CAD monocytes exhibited a metabolically activated phenotype with increased oxidative stress, mitochondrial activity, glucose and cholesterol uptake, calcium signaling, procoagulant activity, and adhesion to endothelial cells. These changes correlated with circulating TNF-α, sICAM-1, and plasma-induced endothelial dysfunction. CAD monocytes showed increased NF-κB, NOX2, and NLRP3 signaling with reduced CREB/NRF2 pathways, produced elevated levels of pro-inflammatory cytokines, while CAD monocytes-conditioned medium induced endothelial oxidative stress and blunted nitric oxide production. GLP-1Ra or SGLT2i attenuated these effects, while combined treatment provided synergistic protection, reducing CAD plasma-induced endothelial oxidative stress (~ 80%) and restoring endothelial function, reducing CAD monocytes oxidative stress (~ 82%), metabolic activation and pro-thrombotic activity, reprogramming monocytes toward anti-inflammatory phenotype and preventing CAD monocytes-induced endothelial dysfunction. CONCLUSION: CAD features systemic inflammation that drives monocyte activation and endothelial dysfunction. Combined SGLT2i and GLP-1Ra synergistically suppress monocyte pro-inflammatory and pro-thrombotic activity and subsequently driven endothelial dysfunction.
Comparative performance of insulin resistance-related indices in predicting adverse cardiovascular events among individuals with NAFLD and MASLD: a multi-center cohort study.
Huang Y, Xu Y, Zhang C … +11 more , Gu W, Li Y, Zhang H, Wang T, Su T, Lhamu Y, Chen Y, Zhou L, Hao L, Yang Y, Wang H
Cardiovasc Diabetol · 2026 Jul · PMID 42401883 · Full text
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) and non-alcoholic fatty liver disease (NAFLD) are closely linked to insulin resistance and elevated cardiovascular risk, triglyceride-glucose (...
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) and non-alcoholic fatty liver disease (NAFLD) are closely linked to insulin resistance and elevated cardiovascular risk, triglyceride-glucose (TyG)-related indices, the atherogenic index of plasma (AIP), and the cardiometabolic index (CMI) have emerged as practical surrogate markers for cardiometabolic risk assessment in these populations. However, it remains unclear whether the associations of these indices with adverse cardiovascular events remain consistent when transitioning from the NAFLD to the newly defined MASLD framework, and a comprehensive comparison of these indices across both diagnostic criteria is lacking. METHODS: This study included 4693/3266, 74,173/67,864, and 7823/10,576 individuals with MASLD/NAFLD from the National Health and Nutrition Examination Survey (NHANES), UK Biobank (UKB), and China Pudong cohort, respectively. Multivariate Cox proportional hazards models, restricted cubic spline analyses, and time-dependent receiver operating characteristic curves were employed to assess associations. Linear regression models evaluated relationships between TyG-related indices and cortical/subcortical structural volumes. Mediation analyses examined the role of oxidative stress, phenotypic aging, and inflammatory markers. RESULTS: Most IR-related indices demonstrated nonlinear, predominantly J-shaped associations with cardiovascular disease (CVD) and related mortality, especially within the UKB. TyG-WC optimally predicted 3-year CVD mortality in MASLD/NAFLD across UKB and NHANES, as well as ischemic stroke (IS) in UKB-MASLD. TyG-WHTR was the strongest predictor for CVD mortality in the Pudong cohort and myocardial infarction (MI) in UKB-MASLD. Notably, elevated TyG-WHTR was consistently associated with heightened risks across all endpoints: CVD mortality (NAFLD: UKB: HR 1.60, 95%CI 1.38-1.84, NHANES: 1.90, 1.34-2.70, Pudong: 1.24, 1.10-1.40; MASLD: UKB: 1.59, 1.38-1.82, NHANES: 1.86, 1.36-2.54, Pudong: 1.70, 1.43-2.03), MI (NAFLD: 1.20, 1.09-1.33; MASLD: 1.22, 1.11-1.34), and IS (NAFLD: 1.41, 1.24-1.61; MASLD: 1.39, 1.23-1.57). Structural neuroimaging analyses revealed significant negative correlations between TyG-WC/TyG-WHTR and subcortical volumes (P < 1 × 10). Mediation analyses indicated that oxidative stress, phenotypic aging, and inflammatory markers collectively accounted for 1.4-27% of the observed associations. CONCLUSIONS: Insulin Resistance-Related Indices demonstrate robust clinical utility in predicting CVD and mortality in NAFLD/MASLD across three distinct cohorts, with oxidative stress, inflammatory activation, and accelerated aging serving as potential mechanistic pathways.
Opportunistic screening for incident cardiometabolic disease in metabolically healthy non-obese individuals: a prospective cohort study.
Bogner B, Jung M, Reisert M … +11 more , Maushagen J, Rospleszcz S, Kroencke T, Pischon T, Schulz-Menger J, Niendorf T, Völzke H, Schlett CL, Bamberg F, Taron J, Weiss J
Cardiovasc Diabetol · 2026 Jul · PMID 42387503 · Full text
BACKGROUND: Metabolically healthy non-obese (MHN) individuals are considered at low cardiometabolic risk, yet a subset may harbor unfavorable visceral adiposity not captured by conventional anthropometric measures, inclu...
BACKGROUND: Metabolically healthy non-obese (MHN) individuals are considered at low cardiometabolic risk, yet a subset may harbor unfavorable visceral adiposity not captured by conventional anthropometric measures, including waist circumference (WC) and BMI. METHODS: We conducted a prospective cohort study of 22,040 UK Biobank participants (median follow-up 4.2 years [interquartile range 3.4-5.6]) defined as MHN (BMI < 30 kg/m, absence of diabetes or concurrent hypertension and hyperlipidemia). Visceral (VAT) and subcutaneous adipose tissue (SAT) volumes were quantified from whole-body MRI using a validated deep learning framework. Sex-specific VAT/SAT ratio cutoffs were derived from the German National Cohort based on prevalent cardiometabolic disease and applied to the UK Biobank. The primary outcome was incident major adverse cardiovascular events (MACE); the secondary outcome was incident type 2 diabetes. Categorical net reclassification improvement (NRI), quantifying the net proportion of individuals correctly reclassified between predefined risk categories, compared VAT/SAT ratio versus WC as competing classification approaches. Cox proportional hazards models assessed associations with outcomes after stepwise adjustment for age, sex, smoking, WC, and BMI. Nested models with and without VAT/SAT ratio were compared to test for added value beyond other factors. RESULTS: The VAT/SAT ratio improved risk classification over WC for MACE (NRI 0.088, 95%CI 0.019-0.158, p = 0.013) and diabetes (NRI 0.102, 95% CI 0.024-0.181, p = 0.010). High VAT/SAT ratio independently predicted MACE (adjusted hazard ratio [aHR] 1.30, 95%CI 1.02-1.66, p = 0.037) and diabetes (aHR 1.77, 95% CI 1.34-2.33, p < 0.001) after full adjustment. Adding VAT/SAT to fully adjusted models improved discrimination for MACE (C-index 0.694 vs. 0.690, p = 0.036) and diabetes (C-index 0.723 vs. 0.715, p < 0.001). CONCLUSION: The VAT/SAT ratio identifies MHN individuals at elevated cardiometabolic risk beyond conventional anthropometric measures, with particularly strong associations for incident diabetes. These findings support the concept of opportunistic imaging-based risk assessment and provide the prognostic foundation for future trials investigating whether targeted intervention in VAT/SAT-reclassified individuals improves outcomes.
Insulin resistance surrogate indices and incident cardiovascular disease across cardiovascular-kidney-metabolic stages 0-3: a prospective cohort study.
Xue N, Ma L, Zhou Z … +3 more , Bai T, Jia X, Wei X
Cardiovasc Diabetol · 2026 Jul · PMID 42380905 · Full text
BACKGROUND: The American Heart Association (AHA) recently proposed the concept of Cardiovascular-Kidney-Metabolic (CKM) syndrome, highlighting the strong pathophysiological links among metabolic disorders, chronic kidney...
BACKGROUND: The American Heart Association (AHA) recently proposed the concept of Cardiovascular-Kidney-Metabolic (CKM) syndrome, highlighting the strong pathophysiological links among metabolic disorders, chronic kidney disease, and cardiovascular disease (CVD). Insulin resistance (IR) is regarded as a central mechanism underlying CKM syndrome. However, studies comparing the predictive value of different IR surrogate markers for incident CVD are still limited. This study aimed to evaluate the associations between multiple IR surrogate markers and incident cardiovascular disease and to further assess their predictive performance using machine learning approaches. METHODS: Using data from the China Health and Retirement Longitudinal Study (CHARLS), this prospective cohort study included 5,528 participants. Twelve IR surrogate indices were assessed, including TyG-related indices, TG/HDL-C, METS-IR, CTI, CHG, and eGDR. Incident CVD was defined as self-reported physician-diagnosed heart disease or stroke during follow-up. Cox proportional hazards models were used to estimate associations between standardized IR indices and incident CVD. Restricted cubic splines, weighted quantile sum regression, and quantile g-computation were used to examine dose-response patterns and the relative contribution of correlated IR indices. Predictive performance was evaluated using ROC analysis, calibration, Brier score, decision curve analysis, NRI, IDI, and machine-learning models. RESULTS: During a median follow-up of 7.0 years, 741 participants developed incident CVD. In fully adjusted Cox models, several IR surrogate indices were associated with incident CVD. TyG-related composite indices incorporating adiposity-related information, particularly TyG-WC, TyG-CVAI, TyG-WHtR, and TyG-BMI, showed stronger positive associations with CVD risk, whereas eGDR showed an inverse association. Restricted cubic spline analyses showed significant overall associations for most indices, with nonlinear patterns observed for METS-IR, CTI, and eGDR. Mixture-based analyses suggested relatively larger contributions of CTI, TyG-BMI, and TyG-WC. Among individual indices, eGDR showed the highest discrimination for incident CVD, followed by TyG-CVAI and TyG-WC. Adding selected IR indices, particularly eGDR, to the covariate-based model modestly improved discrimination and reclassification. CONCLUSIONS: Among adults with CKM syndrome stages 0-3, several IR surrogate indices were prospectively associated with incident CVD, with stronger and more consistent associations observed for TyG-based indices incorporating adiposity-related measures and for eGDR. These results suggest that the combined assessment of metabolic dysfunction, adiposity, and insulin sensitivity may provide useful information for identifying individuals at higher cardiovascular risk in early-stage CKM syndrome.
Deep learning analysis of ECGs detects Cardiovascular-Kidney-Metabolic syndrome burden in people with diabetes: a report from the Silesia Diabetes-Heart Project.
Janota-Sosińska O, Yu Q, Irlik K … +11 more , Kwiendacz H, Włosowicz-Momot A, Pabis P, Wójcik W, Olejarz A, Piaśnik J, Alam U, Zheng Y, Gumprecht J, Lip GYH, Nabrdalik K
Cardiovasc Diabetol · 2026 Jun · PMID 42374510 · Full text
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome refers to the co-occurrence of obesity, diabetes, chronic kidney disease (CKD), and cardiovascular disease. However, it is underdiagnosed due to silent clinical...
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome refers to the co-occurrence of obesity, diabetes, chronic kidney disease (CKD), and cardiovascular disease. However, it is underdiagnosed due to silent clinical nature of the early stages of its components and subsequent siloed medical care. Electrocardiography (ECG) is an inexpensive and widely available diagnostic tool but its utility in automated detection of CKM syndrome has not been previously explored. OBJECTIVE: To develop and evaluate deep learning models for predicting CKM syndrome using scanned limb and augmented limb leads ECGs images in people with diabetes. METHODS: Clinical data of adults with type 1 or type 2 diabetes enrolled in the prospective Silesia Diabetes-Heart Project were analyzed. CKM syndrome was defined by the presence of either CKD [estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m and/or urine albumin to creatinine ratio (UACR) ≥ 30 mg/g) or established CVD. High-resolution scanned ECG tracings were processed into lead-specific inputs to train ResNet-50-based convolutional neural network (CNN) models, including single- and dual-channel variants. Class imbalance was addressed using resampling strategies, and model performance was evaluated using standard classification metrics, including area under the receiver operating characteristic curve (AUROC), with confidence intervals estimated by bootstrap resampling. RESULTS: Among 2779 participants, 492 (17.7%) met criteria for CKM syndrome. The best-performing individual model was a dual-channel ResNet-50 with soft voting ensemble, achieving an AUROC of 0.8199 (95% CI 0.7549-0.8795), F1-score of 0.7213 (95% CI 0.6404-0.7957), accuracy of 0.7385, and balanced precision and recall. Ensemble models consistently outperformed individual architectures, particularly in handling class imbalance and improving generalization. CONCLUSION: Deep learning applied to scanned ECG image data predicts CKM syndrome in individuals with diabetes with reasonable accuracy. This approach holds promise as a low-cost, scalable risk stratification tool and which could augment clinical decision-making in settings particularly with limited access to advanced diagnostics. Trial registration The study is registered at ClinicalTrials.gov (NCT05626413).
Association of the atherogenic index of plasma and its integrative novel adiposity-based composites with all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic syndrome: novel adiposity-derived AIP indices provide modest incremental prognostic information.
Wei S, Qiu J, Liu Y … +6 more , Xu N, Sun Z, Li S, He C, Xie X, He Y
Cardiovasc Diabetol · 2026 Jun · PMID 42374419 · Full text
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome is recognized as a progressive pathophysiological continuum linking metabolic dysfunction, dysfunctional adiposity, chronic kidney disease, and cardiovascular in...
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome is recognized as a progressive pathophysiological continuum linking metabolic dysfunction, dysfunctional adiposity, chronic kidney disease, and cardiovascular injury. The atherogenic index of plasma (AIP) reflects lipid-related atherogenic burden, whereas novel adiposity indices, including body roundness index (BRI), weight-adjusted waist index (WWI), and a body shape index (ABSI), capture body-shape-related adiposity burden. However, the associations of AIP and AIP-based adiposity composite indices with mortality outcomes across the CKM spectrum remain unclear. This study aimed to evaluate the associations of AIP and integrative AIP-based composite indices, including AIP-BRI, AIP-WWI, and AIP-ABSI, with all-cause and cardiovascular mortality among individuals across CKM stages. METHODS: We conducted a retrospective cohort analysis using prospectively collected data from 22,587 US adults in the National Health and Nutrition Examination Survey (NHANES) 1999-2018. Following the 2023 American Heart Association (AHA) Presidential Advisory, participants were classified into a hierarchical staging framework (Stages 0-4) to reflect the CKM disease continuum. Primary outcomes were all-cause and cardiovascular mortality, identified through linkage to the National Death Index. Integrative AIP-based composite indices were constructed by directly multiplying AIP by each adiposity index, including BRI, WWI, and ABSI, yielding AIP-BRI, AIP-WWI, and AIP-ABSI, respectively. These indices were evaluated as integrated exposure variables reflecting the combined burden of atherogenic dyslipidemia and adiposity-related body shape. All analyses incorporated complex survey weights to ensure national representativeness. Survey-weighted Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Model 2 adjusted for demographic and socioeconomic characteristics, lifestyle factors, blood pressure, and total cholesterol. Nonlinear associations were examined using restricted cubic splines (RCS). Incremental prognostic value was assessed using net reclassification improvement (NRI) and integrated discrimination improvement (IDI). RESULTS: During follow-up, non-survivors exhibited significantly higher baseline integrative composites than survivors (P < 0.001). In the fully adjusted model (Model 2), which adjusted for demographic and socioeconomic characteristics, lifestyle factors, blood pressure, and total cholesterol, each standard deviation increase in the integrative composites was independently associated with a higher risk of all-cause mortality: AIP-BRI (HR, 1.09; 95% CI, 1.05-1.14), AIP-WWI (HR, 1.07; 95% CI, 1.02-1.11), and AIP-ABSI (HR, 1.07; 95% CI, 1.02-1.11). These point estimates were numerically slightly higher than that of stand-alone AIP (HR, 1.06; 95% CI, 1.01-1.10), but the differences should be interpreted cautiously. For cardiovascular mortality, the corresponding HRs were 1.17 (95% CI, 1.09-1.27) for AIP-BRI, 1.11 (95% CI, 1.03-1.21) for AIP-WWI, and 1.11 (95% CI, 1.02-1.20) for AIP-ABSI, compared with 1.10 (95% CI, 1.02-1.20) for AIP. RCS analyses revealed J-shaped associations, with a clinical risk threshold for AIP-BRI at 1.57. Subgroup analyses indicated that these associations were most evident in participants aged < 50 years. Adding BRI to AIP assessment yielded a statistically significant but modest NRI of 3.10% for cardiovascular mortality. CONCLUSION: Across the CKM spectrum, higher AIP-based adiposity composite indices, particularly AIP-BRI, were associated with increased risks of all-cause and cardiovascular mortality, especially among younger individuals. However, their incremental predictive improvement was modest, suggesting that these indices may serve as supplementary exploratory markers rather than stand-alone tools for CKM risk stratification.
Correlation between surrogate indicators of insulin resistance and all-cause mortality in patients with severe hemorrhagic stroke: a multicenter retrospective cohort study in the United States.
Zou D, Lin B, Wu B … +5 more , Yu W, Zhang G, Jiang H, Shao C, Wu N
Cardiovasc Diabetol · 2026 Jun · PMID 42366337 · Full text
BACKGROUND: Hemorrhagic stroke (HS), including non-traumatic intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH), accounts for approximately 30% of all stroke cases and over 40% of stroke-related deaths. Wit...
BACKGROUND: Hemorrhagic stroke (HS), including non-traumatic intracerebral hemorrhage (ICH) and subarachnoid hemorrhage (SAH), accounts for approximately 30% of all stroke cases and over 40% of stroke-related deaths. With high mortality and disability rates, HS imposes a heavy global health burden. As a core metabolic disorder, insulin resistance (IR) has been proven to be associated with all-cause mortality (ACM) in patients with ischemic stroke in previous studies. Nevertheless, its prognostic value remains unclear in critically ill HS patients admitted to the intensive care unit (ICU). Given the markedly higher mortality and morbidity of HS compared with ischemic stroke, it is essential to explore this association. This study aimed to investigate the correlations between multiple surrogate markers of insulin resistance and all-cause mortality among critically ill HS patients in the ICU setting. METHODS: Data were extracted from the public eICU-CRD database. Patients with severe HS were identified based on the International Classification of Diseases (ICD)-9/10 diagnostic codes. A total of 1538 ICU-admitted patients with severe HS were enrolled and stratified according to quartiles of various IR surrogate markers. The primary endpoint was in-hospital mortality. Cox regression analysis, Kaplan-Meier survival curves, restricted cubic splines (RCS) and receiver operating characteristic (ROC) curves were adopted for statistical analyses. RESULTS: Among the 1538 enrolled patients, males accounted for 54.6%, and the overall in-hospital all-cause mortality was 26.59%. Multivariate Cox regression analyses revealed that all IR surrogate markers were significantly correlated with all-cause mortality in severe HS patients. SPISE was negatively correlated with all-cause mortality, while other indicators showed positive correlations. Restricted cubic spline analyses demonstrated non-linear relationships between TyG, SPISE, TG_HDL, METS_IR, TyG_BMI, TyG_RC and mortality. No significant effect modification was observed in interaction analyses. ROC curve analysis indicated that TyG exhibited the highest predictive accuracy. CONCLUSION: In conclusion, insulin resistance surrogate markers were significantly associated with all-cause mortality in critically ill HS patients. Despite their weak-to-moderate discriminative performance, these indices may serve as auxiliary prognostic references for risk stratification. Clinical application of these indicators is expected to optimize therapeutic strategies and disease progression management. Furthermore, this study enriches current evidence regarding the association between insulin resistance surrogate markers and hemorrhagic stroke, and clarifies their roles in predicting mortality across different stroke subtypes.
Integrating lipometabolic and adiposity indices to enhance risk stratification for metabolic dysfunction-associated steatotic liver disease in type 2 diabetes: clinical utility and interplay between triglyceride-glucose body mass index and low-density lipoprotein cholesterol.
Yang Y, Qu X, Shi M … +9 more , Huang J, Li G, Lu X, You E, Qian J, Xu J, Jiang M, Jiang G, Xie Q
Cardiovasc Diabetol · 2026 Jun · PMID 42365329 · Full text
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) significantly exacerbates the prognosis of patients with type 2 diabetes mellitus (T2DM). We aimed to compare metabolic and adiposity-related s...
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) significantly exacerbates the prognosis of patients with type 2 diabetes mellitus (T2DM). We aimed to compare metabolic and adiposity-related surrogates for MASLD using data-driven feature selection and to validate a parsimonious risk model across distinct populations. METHODS: We included 449 T2DM patients from the WMU cohort (discovery) and 306 from the Japanese NAGALA cohort (external validation). A two-stage data-driven feature-selection framework (Boruta and LASSO) was implemented to identify a parsimonious two-variable signature (TyG-BMI and SGLT2i). Based on these results, TyG-BMI was prioritized for systematic evaluation. Association and dose-response relationships were assessed via multivariate logistic regression and restricted cubic splines. Multiplicative and additive interactions between TyG-BMI and LDL-C were further explored. Clinical utility was evaluated via AUC, NRI, IDI, and decision curve analysis. RESULTS: The Boruta algorithm ranked TyG-BMI as the feature with the highest importance score for MASLD classification. Subsequently, LASSO regression (utilizing the 1-standard-error criterion λ1se) identified a parsimonious two-variable signature comprising TyG-BMI and SGLT2i. In the WMU cohort, TyG-BMI exhibited a potent association with MASLD (T3 vs. T1: OR = 7.36, 95% CI 3.89-13.94) and a significant linear dose-response relationship (P for overall < 0.001). Incorporation of TyG-BMI into the baseline model improved discriminative performance (AUC increased from 0.7288 to 0.7920) and was associated with improved continuous reclassification (NRI: 0.6088, P < 0.001). DCA and calibration plots confirmed high clinical net benefit and accuracy. Furthermore, a significant synergistic interaction was observed between TyG-BMI and low-density lipoprotein cholesterol (LDL-C). CONCLUSIONS: TyG-BMI, selected through data-driven feature selection, may serve as a practical candidate predictor of MASLD in patients with T2DM. The observed interaction between TyG-BMI and LDL-C suggests that their joint assessment may further refine MASLD risk stratification. The derived parsimonious model offers a high-performing, non-invasive tool for early MASLD risk stratification across Asian populations.
Myeloid Cdc42 deficiency-mediated macrophage pyroptosis exacerbates diabetic cardiomyopathy in type 1 diabetes mellitus.
Liu LX, He J, Zhang F … +13 more , Li XQ, Xiao XY, Zhou XY, Yang QK, Wu MH, Qiao XH, Lu BQ, Pang ZY, Sun HW, Chen ZX, HongShu YJ, Xin HB, Deng KY
Cardiovasc Diabetol · 2026 Jun · PMID 42363173 · Full text
BACKGROUND: Diabetic cardiomyopathy (DCM) is one of the severe complications in type 1 diabetes mellitus (T1DM) patients with impaired cardiac function and faster progression to heart failure due to systolic malfunction....
BACKGROUND: Diabetic cardiomyopathy (DCM) is one of the severe complications in type 1 diabetes mellitus (T1DM) patients with impaired cardiac function and faster progression to heart failure due to systolic malfunction. It has been demonstrated that macrophage-mediated chronic inflammation is closely associated with DCM. Cell division cycle 42 (Cdc42) plays a crucial role in regulating the polarization, migration and phagocytosis of macrophages, however, the underlying mechanism of Cdc42 in DCM remains to be elucidated. METHODS: Mouse DCM models with T1DM were generated using myeloid-specific Cdc42-knockout (Cdc42) and Cdc42 (Cdc42) male mice at 10-12 weeks old by injection of streptozotocin (STZ, 50 mg/kg/day) for 6 continuous days and then following the observation of 16 weeks. Cardiac functions were assessed by echocardiography in vivo, and cardiac morphological and histopathological alterations were evaluated by hematoxylin and eosin (HE), Masson's trichrome, Picrosirius red, and immunohistochemistry staining, respectively. The infiltration of myeloid macrophages was examined by multiplex immunofluorescence tyramide signal amplification (TSA) assay or Rosa mTmG fluorescent myeloid tracking reporter in mice. Macrophage pyroptosis, cardiomyocyte damage and myofibroblast activation were evaluated by Western blot and immunofluorescence analysis. Additionally, single-cell RNA-seq (scRNA-seq) data analysis was performed to explore macrophage-mediated signaling in DCM using publicly available GSE datasets from STZ-induced T1DM mice. RESULTS: Myeloid Cdc42 deletion exacerbated T1DM-induced cardiac dysfunctions and histopathological changes including cardiac fibrosis, and promoted T1DM-induced macrophage infiltration and M1 polarization of macrophages, and facilitated T1DM-induced pyroptosis by activating NLRP3 inflammasome in the hearts in mice. Notably, there were no significant differences between Cdc42 and Cdc42 mice under normal condition. In addition, gene set enrichment analysis (GSEA) of scRNA-seq data indicated that low Cdc42 expression in macrophages was positively associated with the NF-κB signaling pathway in DCM. Mechanistically, we demonstrated that Cdc42 deficiency or inhibition aggravated T1DM-induced cardiomyocyte injury and cardiac fibrosis by activating ERK-NF-κB-interleukin-1β signaling pathway-mediated macrophage pyroptosis. CONCLUSIONS: This study demonstrates that myeloid Cdc42 deficiency or inhibition aggravates T1DM-induced cardiomyocyte injury and cardiac fibrosis of DCM by promoting macrophage pyroptosis and inflammatory responses, which might provide a novel therapeutic target for immunomodulatory intervention in DCM of type 1 diabetes mellitus.
Associations of cumulative exposure and longitudinal change patterns of the triglyceride glucose-Chinese visceral adiposity index with incident cardiovascular disease in middle-aged and older adults: evidence from CHARLS.
Liu H, Zhang X, Tang K … +9 more , Zhang X, Li S, Li Z, Dong X, Liao H, Long W, Zhuang Z, Ni S, Yang Z
Cardiovasc Diabetol · 2026 Jun · PMID 42363125 · Full text
BACKGROUND: The triglyceride glucose-Chinese visceral adiposity index (TyG-CVAI), an integrated marker of insulin resistance and visceral adiposity, has been associated with cardiovascular outcomes. However, the longitud...
BACKGROUND: The triglyceride glucose-Chinese visceral adiposity index (TyG-CVAI), an integrated marker of insulin resistance and visceral adiposity, has been associated with cardiovascular outcomes. However, the longitudinal cardiovascular implications of cumulative TyG-CVAI exposure and directional changes in TyG-CVAI remain insufficiently characterized. This study aimed to examine the associations of cumulative TyG-CVAI exposure and longitudinal TyG-CVAI change patterns with incident cardiovascular disease (CVD) among middle-aged and older Chinese adults. METHODS: This prospective study included 4,338 participants from the China Health and Retirement Longitudinal Study (CHARLS) who were free of CVD during the exposure assessment period from 2011 to 2015 and had complete TyG-CVAI data in 2011 and 2015. Participants were categorized into four TyG-CVAI change patterns (low-low, low-high, high-low, and high-high). Cumulative TyG-CVAI was calculated using repeated measurements from 2011 to 2015 and analyzed as both a standardized continuous variable and quartiles. Incident CVD was defined as new-onset heart disease or stroke during follow-up. Kaplan-Meier analysis, multivariable Cox proportional hazards models, and restricted cubic spline (RCS) analysis were performed. RESULTS: During a mean follow-up of 5 years, 845 incident CVD events occurred among 4,338 participants. Compared with the low-low group, the fully adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD were 1.50 (1.21-1.88) for the low-high group, 1.64 (1.20-2.25) for the high-low group, and 1.77 (1.49-2.09) for the high-high group. When cumulative TyG-CVAI was analyzed as a standardized continuous variable, each 1-SD increase was associated with a higher risk of incident CVD after full adjustment (HR 1.10, 95% CI 1.06-1.14). When categorized into quartiles, participants in the highest quartile had a higher CVD risk than those in the lowest quartile (HR 1.91, 95% CI 1.56-2.33; P for trend < 0.001). RCS analysis revealed a significant nonlinear association between cumulative TyG-CVAI and incident CVD. CONCLUSION: Higher cumulative TyG-CVAI burden and unfavorable longitudinal change patterns were associated with an increased risk of incident CVD among middle-aged and older Chinese adults. These findings suggest that repeated TyG-CVAI assessment may help identify individuals with sustained or worsening metabolic-visceral burden and support longitudinal cardiovascular risk stratification.
Association between insulin resistance surrogate markers and cardiovascular disease risk in individuals with subclinical metabolic disorders: a prospective cohort study based on baseline levels, cumulative exposure, and longitudinal trajectories.
Zhao W, Tang R, Tian J … +1 more , Gao D
Cardiovasc Diabetol · 2026 Jun · PMID 42337758 · Full text
BACKGROUND: Cardiovascular disease (CVD) has become an increasingly severe global public health issue, with its disease burden continuing to rise worldwide. Insulin resistance (IR) is a key metabolic process underlying C...
BACKGROUND: Cardiovascular disease (CVD) has become an increasingly severe global public health issue, with its disease burden continuing to rise worldwide. Insulin resistance (IR) is a key metabolic process underlying CVD, but direct measurement is challenging in large populations.Various composite cardiometabolic indices are used to reflect IR-related metabolic alterations.Prediabetes, prehypertension, and predyslipidemia are early manifestations of subclinical metabolic dysfunction associated with CVD. However, their contributions to CVD risk and their relationship with dynamic changes in IR remain unclear.Therefore, this study aimed to comprehensively evaluate multiple insulin resistance-related surrogate markers and explore the associations of baseline IR, cumulative IR (cuIR), and IR trajectories with CVD risk in middle-aged and older adults. METHODS: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS, 2011-2020), with relevant information collected via standardized questionnaires during follow-up.Eleven IR-related surrogate markers (TyG, TyG-WC, TyG-WWI, TyG-BMI, TyG-ABSI, TyG-BRI, TyG-WHtR, METS-IR, AIP, CTI, CHG) were analyzed, with covariates pre-specified based on established cardiovascular risk factors. The primary outcome was the incidence of newly diagnosed CVD. In the CHARLS cohort, IR-related indicators were available at two time points (Wave 1: 2012 and Wave 3: 2015). Therefore, cumulative insulin resistance exposure (cuIR) was calculated as: cuIR = (IR2012 + IR2015) / 2 × time. Due to the limited number of repeated measurements, clustering analysis (K-means) was applied to classify cumulative exposure patterns of IR-related indicators.Multivariate Cox proportional hazards regression models estimated hazard ratios (HR) with 95% confidence intervals (95% CI), and restricted cubic splines (RCS) examined nonlinear associations. Predictive performance of IR-related surrogate indicators was assessed using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Subgroup analyses further tested robustness of findings. Additionally, external validation of baseline IR findings was conducted using the English Longitudinal Study of Ageing (ELSA, 2004-2016). In the ELSA cohort, longitudinal trajectories of IR-related surrogate markers were constructed using group-based trajectory modeling (GBTM) based on repeated measurements (Waves 2, 4, and 6). RESULTS: In the study examining the association between baseline IR-related surrogate markers and the risk of CVD occurrence, 7,299 participants were enrolled, with 1,870 new CVD events occurring during an 8-year follow-up period. Across three Cox proportional hazards models, all 11 surrogate markers were significantly associated with increased CVD risk. In Model 3, fully adjusted for confounders, TyG-ABSI demonstrated the strongest association with CVD risk (HR = 4.92, 95% CI 3.13-7.74). After stratification by quantiles, higher quantiles were associated with increased CVD risk (P for trend < 0.05). In the external validation cohort ELSA, all IR indicators except TyG showed positive correlations with CVD risk in unadjusted models; After multivariable adjustment TyG-WC, TyG-BMI, TyG-BRI, TyG-WHtR, METS-IR, and and CTI remained independently associated with CVD risk. Participants in the highest quantile showed significantly increased risk (P for trend < 0.05). In the study of cuIR and CVD risk, 773 out of 3,847 participants ultimately developed CVD. In the multivariable Cox proportional hazards model, all 11 cuIR-related surrogate markers significantly increased CVD risk. Compared to Q1, both Q2 and Q3 groups showed elevated risk, with a significant linear trend (P for trend < 0.05). Clustering pattern analysis based on cumulative exposure showed that individuals in the high-level groups had significantly higher CVD risk than those in the low-level groups. Trajectory analysis of the ELSA cohort revealed unique longitudinal patterns of insulin resistance-related indicators. In the fully adjusted model, compared with the low-risk trajectory group, individuals in the high-risk trajectory groups for TyG-WC, TyG-BMI, TyG-BRI, METS-IR, and CTI had a significantly increased risk of developing CVD. Among these, CTI showed the strongest association with CVD risk (HR = 1.90, 95% CI 1.25-2.89).In contrast, associations for TyG, TyG-WHtR, TyG-WWI, and TyG-ABSI were not significant after multivariable adjustment. No significant associations were observed for the trajectory groups of AIP and CHG. CONCLUSION: This study demonstrates that baseline IR, cuIR, and longitudinal trajectory patterns are significantly associated with CVD risk in middle-aged and older populations. These measures provide incremental predictive value beyond traditional risk factors. Early identification and long-term monitoring of IR-related surrogate markers during the subclinical metabolic stage may enhance CVD risk stratification and support precision prevention and intervention strategies.
Cardiovascular-liver-metabolic multimorbidity: preliminary insights into the associations with the triglyceride glucose index (TyG), its obesity-derived indices and their effects on long-term survival.
He S, Liu Y, Sheng G … +5 more , Xie G, Wang W, Lai H, Zou Y, Wang C
Cardiovasc Diabetol · 2026 Jun · PMID 42337737 · Full text
BACKGROUND: The triglyceride-glucose (TyG) and its obesity‑derived indices are important composite parameters of insulin resistance coupled with obesity, and have been associated with cardiometabolic diseases. However, t...
BACKGROUND: The triglyceride-glucose (TyG) and its obesity‑derived indices are important composite parameters of insulin resistance coupled with obesity, and have been associated with cardiometabolic diseases. However, their associations with cardiovascular‑liver‑metabolic multimorbidity (CLMM) remain unclear. This study aims to systematically compare TyG and its obesity-derived indices to identify the optimal surrogate marker for CLMM, and to explore the potential impact of CLMM status on mortality. METHODS: Based on a multi-stage sampling design of a national cohort, weighted logistic and Cox regression models were applied to evaluate the associations of each index with CLMM and long-term mortality. Discriminatory performance was compared using the area under the receiver operating characteristic curve (AUROC), net reclassification improvement, and integrated discrimination improvement. Additionally, weighted quantile sum regression, and mediation analysis were employed to explore the underlying disease mechanisms. RESULTS: The study included 20,235 adults. Weighted logistic regression analyses for the individual indices revealed that the TyG and its obesity‑derived indices were all positively associated with CLMM, with TyG‑WHtR, TyG‑WWI, and TyG‑CVAI showing the strongest associations. Further longitudinal weighted interaction analyses revealed that CLMM status significantly amplified the mortality risk associated with the TyG and its obesity-derived indices. For CLMM identification, all indices showed favorable diagnostic performance (AUROC > 0.76), with TyG‑WWI and TyG‑CVAI achieving the best performance (AUROC > 0.83) and exhibiting the largest net reclassification improvement and integrated discrimination improvement. Joint XGBoost-SHAP analyses further indicated that TyG-CVAI and TyG-WWI were the major contributing variables for discriminating CLMM status. Exploratory mechanistic analyses suggested glucose metabolism as a core driver underlying CLMM development, with inflammatory factors partially mediating these associations. CONCLUSION: The TyG and its obesity-derived indices, particularly TyG-WWI and TyG-CVAI, exhibited significant incremental value for identifying CLMM, with CLMM status also conferring elevated subsequent mortality risk. Incorporating these indices into primary prevention monitoring systems for chronic diseases could facilitate the identification of individuals at high risk for CLMM and mortality.
Optimizing early triage for subclinical cardiovascular-kidney-metabolic syndrome: longitudinal associations, incremental value, and clinical utility of nine insulin resistance surrogates.
Huang Y, Qu X, Xu S … +7 more , Zhen P, Yao M, Luo J, Cui R, Qiu CE, Jiang G, Cheng J
Cardiovasc Diabetol · 2026 Jun · PMID 42324581 · Full text
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome stage 3 represents a critical, yet highly insidious, window of subclinical target organ damage. We aimed to comprehensively compare nine baseline non-insulin-bas...
BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome stage 3 represents a critical, yet highly insidious, window of subclinical target organ damage. We aimed to comprehensively compare nine baseline non-insulin-based surrogate indices of insulin resistance to predict progression to CKM stage 3 and determine their scenario-specific clinical utility. METHODS: This longitudinal study included 2958 adults initially at CKM stages 0-2 from the China Health and Retirement Longitudinal Study. Independent associations were assessed using multivariable logistic regression and restricted cubic splines. Discriminative ability was evaluated using the area under the receiver operating characteristic curve (AUC). Incremental predictive values over a basic clinical model were quantified via continuous net reclassification improvement (NRI) and integrated discrimination improvement (IDI). The net clinical benefit was further evaluated through decision curve analysis (DCA). RESULTS: During follow-up, 497 (16.8%) participants progressed to CKM stage 3. After adjusting for comprehensive covariates, all nine indices were independently associated with the outcome. Notably, composite indices coupling systemic glucolipotoxicity with central adiposity exhibited preferable predictive superiority. Triglyceride-glucose index combined with waist-to-height ratio (TyG-WHtR) and triglyceride-glucose index combined with waist circumference (TyG-WC) yielded the highest odds ratios per 1-SD increment (1.86 and 1.82, respectively). Incorporating them into the basic model significantly increased the AUC and provided the most substantial improvements in patient reclassification (NRI: 0.524 and 0.512, respectively; both P < 0.001) and discrimination (IDI). Furthermore, DCA confirmed that models augmented with TyG-WC or TyG-WHtR provided the highest net clinical benefit across varying threshold probabilities. This prognostic dominance remained robust across four stringent sensitivity analyses. CONCLUSIONS: TyG-WC and TyG-WHtR are the most robust, independent predictors of incident CKM stage 3. They offer a highly actionable, scenario-adaptable screening strategy: TyG-WC serves as an ultra-accessible "first-pass" filter for large-scale public health triage, while TyG-WHtR provides a calibrated prognostic anchor for high-threshold, individualized clinical decision-making.
An interpretable machine learning model for predicting postoperative hypotension in type 2 diabetes mellitus undergoing non‑cardiac surgery.
Gao Y, Yin G, Qi Z … +3 more , Song X, Zhou X, Li K
Cardiovasc Diabetol · 2026 Jun · PMID 42324531 · Full text
BACKGROUND: Postoperative hypotension (POH) is a common and serious complication in patients with type 2 diabetes mellitus (T2DM) undergoing non‑cardiac surgery, yet predictive tools tailored to this high‑risk population...
BACKGROUND: Postoperative hypotension (POH) is a common and serious complication in patients with type 2 diabetes mellitus (T2DM) undergoing non‑cardiac surgery, yet predictive tools tailored to this high‑risk population remain scarce. METHODS: This single‑center cohort study developed and validated a machine learning (ML) model to predict the risk of postoperative hypotension (POH) occurring during the post‑anaesthesia care unit (PACU) stay, defined as systolic blood pressure < 90 mmHg after leaving the operating theatre and before transfer to the general ward, consistent with the Perioperative Quality Initiative (POQI) consensus. Data from 34,012 retrospective (2012-2022) and 10,528 prospective (2023-2025) T2DM patients undergoing non‑cardiac surgery were used. Following rigorous preprocessing and a four‑step feature selection, 13 predictors were retained. Fourteen ML models were trained and evaluated using area under the curve (AUC), sensitivity, specificity, and calibration. Model interpretability was enhanced using SHapley Additive exPlanations (SHAP). RESULTS: Random Forest achieved the best overall performance, with AUCs of 0.843 (95% CI 0.837-0.849) on training, 0.854 (95% CI 0.848-0.860) on internal validation, and 0.847 (95% CI 0.840-0.854) on prospective validation. External validation on an independent hospital cohort (n = 2156) yielded an AUC of 0.822 (95% CI 0.805-0.839), confirming generalisability. It demonstrated high sensitivity (0.932) and reliable calibration. SHAP analysis identified intraoperative blood loss, age, heart failure, obstructive sleep apnoea, and body mass index as the top predictors, providing transparent global and local explanations for individual risk. CONCLUSION: An interpretable ML model based on routinely collected clinical data accurately predicts POH risk in T2DM patients after non‑cardiac surgery. The model combines strong discriminative performance with clinical explainability, suggesting its potential as a practical tool for preoperative risk stratification and personalized postoperative monitoring in T2DM patients within similar clinical settings.
Burden trajectories of stroke attributable to lipid-glucose dysfunction and biomarker validation: evidence from the global burden of disease (GBD) 2023 and the China health and retirement longitudinal study (CHARLS).
Xiao Z, Deng L, Duan Y … +2 more , Wang B, Liu A
Cardiovasc Diabetol · 2026 Jun · PMID 42324526 · Full text
BACKGROUND: Metabolic dysfunction is an important contributor to stroke burden and may also help identify individuals at higher future risk of stroke. However, the population-level burden attributable to major metabolic...
BACKGROUND: Metabolic dysfunction is an important contributor to stroke burden and may also help identify individuals at higher future risk of stroke. However, the population-level burden attributable to major metabolic risks and the individual-level predictive value of lipid-glucose metabolic biomarkers have not been well characterized within a complementary analytical framework. This study assessed temporal trends in stroke burden attributable to high FPG and high LDL-C in China and compared the prognostic performance of lipid-glucose metabolic biomarkers for incident stroke. METHODS: GBD 2023 estimates were used to evaluate stroke burden attributable to high FPG and high LDL-C in China from 1990 to 2023. Individual-level analyses were conducted in CHARLS (2011-2020) as the discovery cohort and HRS (2016-2022) as an external-validation cohort. Network and correlation analyses were used to describe interrelationships among predictors. Cox proportional hazards models were applied to assess associations between biomarkers and incident stroke, with component-aware covariate adjustment and FDR correction. Machine-learning models with SHAP interpretation were used to evaluate predictor contribution. The incremental predictive value of eGDR was further assessed by adding it to conventional clinical risk models, with evaluation of discrimination, calibration, and decision-curve performance. RESULTS: From 1990 to 2023, age-standardized mortality and DALY rates for stroke attributable to high FPG and high LDL-C declined in China, whereas the absolute burden remained substantial. In 2023, high FPG accounted for 216.80 thousand stroke deaths and 4,378.51 thousand DALYs, while high LDL-C accounted for 233.09 thousand deaths and 5,642.72 thousand DALYs. In CHARLS, eGDR showed a consistent inverse association with stroke risk and ranked as the leading predictor in SHAP analyses. Similar patterns were observed in HRS. Adding eGDR to conventional clinical risk models modestly improved discrimination and reclassification in both cohorts, with AUC improvements of 0.017-0.025 in CHARLS and 0.009-0.013 in HRS. CONCLUSION: Age-standardized stroke burden attributable to high FPG and high LDL-C in China has declined, but the absolute burden remains substantial. eGDR showed consistent associations with incident stroke and modest incremental predictive value across CHARLS and HRS, supporting its potential relevance for future stroke risk-stratification research.
Associations of insulin resistance-related indices with the risk and progression of cardiometabolic multimorbidity in individuals with metabolic dysfunction-associated steatotic liver disease: a prospective cohort study.
Sun M, He Q, Wang Y … +4 more , Yao J, Shen Y, Liu Z, Han Q
Cardiovasc Diabetol · 2026 Jun · PMID 42324458 · Full text
BACKGROUND: Insulin resistance (IR) is thought to be a major metabolic driver of both metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiometabolic diseases (CMD). Although several IR-related indic...
BACKGROUND: Insulin resistance (IR) is thought to be a major metabolic driver of both metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiometabolic diseases (CMD). Although several IR-related indices have been linked to individual CMD, their associations with cardiometabolic multimorbidity (CMM) and stage-specific disease progression in individuals with MASLD remain unclear. METHODS: A total of 109,604 UK Biobank participants with MASLD who were free of CMD at baseline were included in this study. The analysis covered nine IR-related metrics, including the triglyceride-glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), TyG-body roundness index (TyG-BRI), TyG-a body shape index (TyG-ABSI), TyG-visceral adiposity index (TyG-VAI), TyG-weight-adjusted waist index (TyG-WWI), and the triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C). Associations with incident CMM were estimated using Cox models. Multi-state models were applied to evaluate stage-specific transitions. Incremental predictive performance was evaluated using time-dependent ROC analyses, C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Exploratory mediation analyses were further performed to explore possible biological pathways. RESULTS: Over a median follow-up of 15.9 years, 4944 participants developed CMM. Higher levels of all IR-related indices were linked to a greater risk of CMM. In the fully adjusted model, the strongest associations were observed for TyG-WHtR, TyG-BMI, and TyG-WC, with HRs (95% CIs) of 2.70 (2.45-2.97), 2.36 (2.16-2.58), and 2.33 (2.12-2.56), respectively, for the highest versus lowest quartile. Multistate analyses indicated that these indices showed stage-specific associations across the CMM trajectory. For transitions from a CMD-free state to single CMDs, the strongest associations were observed for T2D. Transitions from CHD or stroke were more likely to progress to CMM when exposed to higher IR-related indices. All indices modestly improved CMM prediction beyond conventional risk factors (all P < 0.001), with TyG-WHtR showing the best performance. Exploratory mediation analyses suggested that inflammatory, hepatic, and renal biomarkers jointly accounted for 11-23% of the associations. CONCLUSIONS: Among individuals with MASLD, IR-related indices were significantly associated with the incidence and progression of CMM. Indices incorporating central adiposity, especially TyG-WHtR, provided the most informative risk estimates and modest incremental predictive value.
Proteomics of multimorbidity progression across cardiometabolic diseases and cancer in a multinational cohort.
Stein MJ, Viallon V, Leitzmann MF … +13 more , Gunter MJ, Smith-Byrne K, Ler P, Ricceri F, Masala G, Beigrezaei S, Koop Y, Zamora-Ros R, Jiménez-Zabala A, Lill CM, Riboli E, Ferrari P, Freisling H
Cardiovasc Diabetol · 2026 Jun · PMID 42323685 · Full text
BACKGROUND: Multimorbidity, defined here as the co-occurrence of cardiovascular disease (CVD), type 2 diabetes (T2D), and/or cancer is a major public health challenge. However, its underlying biological mechanisms remain...
BACKGROUND: Multimorbidity, defined here as the co-occurrence of cardiovascular disease (CVD), type 2 diabetes (T2D), and/or cancer is a major public health challenge. However, its underlying biological mechanisms remain unclear, limiting progress toward identifying shared interventional targets. METHODS: We applied large-scale plasma proteomics (SomaScan 7k; 7,289 aptamers) in 13,270 European Prospective Investigation into Cancer and Nutrition (EPIC) participants to identify protein signatures of multimorbidity. We modelled multimorbidity progression as sequential disease transitions, i.e., from the disease-free state at baseline to a first disease and from the first disease to a second disease. Using weighted multivariable Cox regression, we estimated hazard ratios (HR) and 95% confidence intervals (CI) for risk of cancer, CVD, and T2D. Risk associations were replicated using Olink proteomics in UK Biobank (N = 44,567). RESULTS: We identified 422 aptamers associated with more than one disease (FDR-corrected P < 0.05), e.g., 265 aptamers were shared between CVD and T2D. Thirty-eight aptamers were associated with multimorbidity progression. Among these, 27 aptamers showed consistent positive associations across sequential disease transitions, including SEMA6A (disease-free to cancer HR: 1.14; 95% CI 1.05, 1.23; cancer to T2D HR: 2.61; 95% CI 1.76, 3.80). Four aptamers showed consistent inverse associations, including NLGN1 (disease-free to T2D HR: 0.72; 95% CI 0.61, 0.84; T2D to cancer HR: 0.57; 95% CI 0.43, 0.75). Nineteen of the identified proteins were also measured in UK Biobank, with broadly consistent associations. CONCLUSIONS: This study identifies candidate proteins that may indicate molecular pathways to multimorbidity of cardiometabolic diseases and cancer. Future studies should evaluate the causal roles of these proteins for targeted interventions and risk stratification.
Associations between the C-reactive protein-triglyceride-glucose index and its derived indices and the incidence and progression of cardiometabolic multimorbidity in participants with metabolic dysfunction-associated steatotic liver disease: a large-scale prospective cohort study.
Tian Z, Yan X, Xue F … +2 more , Yang J, Li N
Cardiovasc Diabetol · 2026 Jun · PMID 42323654 · Full text
BACKGROUND: The C-reactive protein-triglyceride-glucose index (CTI), a composite biomarker reflecting insulin resistance and systemic inflammation, has been linked to metabolic dysfunction-associated steatotic liver dise...
BACKGROUND: The C-reactive protein-triglyceride-glucose index (CTI), a composite biomarker reflecting insulin resistance and systemic inflammation, has been linked to metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiometabolic diseases (CMDs). However, the role of CTI and its obesity-related derivatives in cardiometabolic multimorbidity (CMM) development and progression among MASLD patients remains unclear. The study evaluated associations of CTI-related indices with the incidence and progression of CMM, assessed their incremental predictive value, and explored potential biomarkers. METHODS: This cohort study included 109,181 UK Biobank participants with MASLD and without CMDs at baseline. CMM was defined as the coexistence of ≥ 2 CMDs, including type 2 diabetes mellitus (T2DM), ischemic heart disease (IHD), and stroke. Four CTI-related indices were calculated: CTI, CTI-body mass index (CTI-BMI), CTI-waist circumference (CTI-WC), and CTI-waist-to-height ratio (CTI-WHtR). Associations with CMM incidence and progression were analyzed using traditional Cox and multistate models. Predictive performance was assessed using the C-index, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Exploratory mediation analyses were conducted to examine whether metabolic, inflammatory, hepatic, and renal biomarkers statistically accounted for part of the associations. RESULTS: Over a median follow-up of 16 years, 4,219 participants developed CMM. All four indices were positively associated with incident CMM, with CTI-WHtR and CTI-WC showing more pronounced associations. Hazard ratios (HRs) (95% confidence interval) per 1-SD increase were 1.62 (1.58-1.66) for CTI-WHtR, 1.57 (1.53-1.61) for CTI-WC, 1.53 (1.49-1.57) for CTI-BMI, and 1.50 (1.45-1.54) for CTI (all P < 0.001). Multistate analyses indicated consistent positive associations with transitions from baseline to first CMD (FCMD) (HRs: 1.41-1.53), FCMD to CMM (HRs: 1.17-1.24), and CMM to death (HRs: 1.07-1.21), particularly for CTI-WHtR and CTI-WC. Subtype-specific analyses confirmed their pronounced associations, notably for T2DM incidence and IHD-to-CMM progression. Adding CTI-related indices to the conventional model resulted in modest but statistically significant improvements in predictive performance, with CTI-WC and CTI-WHtR showing the greatest improvements in the C-index, NRI, and IDI. Biomarkers of glycemic dysregulation, lipid metabolism, systemic inflammation, and organ dysfunction may partly account for the associations between CTI indices and incident CMM. CONCLUSION: CTI-related indices, particularly CTI-WHtR and CTI-WC, were significantly associated with the incidence and progression of CMM in individuals with MASLD. These indices provided modest incremental predictive value and may serve as complementary markers for risk stratification. Further external validation and clinical utility assessment are needed before their routine use in clinical practice.
Cumulative exposure and longitudinal exposure pattern of C-reactive protein-triglyceride-glucose index combined with Chinese visceral adiposity index (CTI-CVAI) and the risk of new-onset cardiovascular disease in middle-aged and older Chinese adults: a prospective cohort study based on the China Health and Retirement Longitudinal Survey (CHARLS).
Chen X, Wang C, Luo Y … +3 more , Huang Q, Gong H, Chen J
Cardiovasc Diabetol · 2026 Jun · PMID 42323630 · Full text
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death globally. The C-reactive protein-triglyceride-glucose index (CTI) integrates inflammation and insulin resistance. However, research on cumulative eff...
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death globally. The C-reactive protein-triglyceride-glucose index (CTI) integrates inflammation and insulin resistance. However, research on cumulative effects and longitudinal patterns of CTI combined with body shape indices for CVD risk assessment is limited. We examined association of cumulative CTI-CVAI (CumCTI-CVAI) exposure and longitudinal patterns with new-onset CVD, heart disease, and stroke in middle-aged and older Chinese adults. METHODS: Data were from the CHARLS. A two-stage design (cross-sectional screening + longitudinal validation) was employed. Cross-sectional analysis (n = 9,475) identified CTI-CVAI as the optimal composite indicator. In longitudinal analysis (n = 3,803; median follow-up 56.6 months), cumulative CTI-CVAI was calculated using time-weighted averages (2011-2015). The landmark time was set at 2015 to avoid immortal time bias. Cox regression, RCS, K-means clustering, subgroup analyses, and sensitivity analyses (lag analysis, interval deletion analysis, competing risk model, etc.) were performed. NRI and IDI were calculated. A nomogram was constructed using LASSO regression, with AUC for discrimination and calibration/DCA for clinical utility. RESULTS: Cross-sectional analysis identified CTI-CVAI as the optimal indicator (AUC = 0.617). In longitudinal analysis, each 1-SD increase in CumCTI-CVAI was associated with a 9% higher CVD risk (HR = 1.09, 95%CI:1.04-1.14, P < 0.001). The highest tertile had a 63% higher risk than the lowest (HR = 1.63, 95%CI:1.33-2.00). A nonlinear dose-response relationship was observed (P < 0.001; inflection point:6192.15). For secondary outcomes, each 1-SD increase in CumCTI-CVAI was associated with a 7% higher risk of heart disease (HR = 1.07, 95%CI:1.01-1.14) and a 16% higher risk of stroke (HR = 1.16, 95%CI:1.06-1.27). K-means clustering identified three exposure patterns: low-stable, moderate-stable, and high-stable. Compared to the low-stable group, the high-stable group had 68% higher CVD risk (HR = 1.68), 43% higher heart disease risk (HR = 1.43), and 133% higher stroke risk (HR = 2.33). Hierarchical NRI/IDI analysis showed that adding inflammation to TyG-CVAI significantly improved reclassification (IDI: from 0.018 to 0.090, P < 0.001). The nomogram (age, lung disease, CumCTI-CVAI) achieved AUCs of 0.618-0.638. CONCLUSION: Elevated cumulative CTI-CVAI exposure and unfavorable longitudinal patterns are independently associated with increased CVD risk in middle-aged and older Chinese adults. CTI-CVAI provides incremental predictive value beyond obesity and insulin resistance alone, supporting its potential as an adjunctive screening tool in primary care.
About
- Frequency
- Sun
- Papers found
- 200
- RSS feed
- Subscribe