Cardiovascular Diabetology最新文献

{"title":"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.","authors":"Wei Zhao, Rongjie Tang, Jing Tian, Dengfeng Gao","doi":"10.1186/s12933-026-03230-z","DOIUrl":"10.1186/s12933-026-03230-z","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13551721/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148307107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interpretable machine learning model for predicting postoperative hypotension in type 2 diabetes mellitus undergoing non‑cardiac surgery.","authors":"Yu Gao, Guojiang Yin, Zheng Qi, Xiaoyang Song, Xiang Zhou, Kun Li","doi":"10.1186/s12933-026-03256-3","DOIUrl":"10.1186/s12933-026-03256-3","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13536729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"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).","authors":"ZhenKun Xiao, LiangJie Deng, YongHong Duan, Bing Wang, AiHua Liu","doi":"10.1186/s12933-026-03269-y","DOIUrl":"10.1186/s12933-026-03269-y","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13551825/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148292980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"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.","authors":"Mengtong Sun, Qida He, Yu Wang, Jiazhen Yao, Yueping Shen, Zhifen Liu, Qiang Han","doi":"10.1186/s12933-026-03264-3","DOIUrl":"10.1186/s12933-026-03264-3","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13536613/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing early triage for subclinical cardiovascular-kidney-metabolic syndrome: longitudinal associations, incremental value, and clinical utility of nine insulin resistance surrogates.","authors":"Yingxiu Huang, Xiaoxiao Qu, Shenrui Xu, Peng Zhen, Mei Yao, Jiachao Luo, Ruyu Cui, Chi-E Qiu, Guosong Jiang, Jing Cheng","doi":"10.1186/s12933-026-03266-1","DOIUrl":"10.1186/s12933-026-03266-1","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13551699/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomics of multimorbidity progression across cardiometabolic diseases and cancer in a multinational cohort.","authors":"Michael J Stein, Vivian Viallon, Michael F Leitzmann, Marc J Gunter, Karl Smith-Byrne, Peggy Ler, Fulvio Ricceri, Giovanna Masala, Sara Beigrezaei, Yvonne Koop, Raúl Zamora-Ros, Ana Jiménez-Zabala, Christina M Lill, Elio Riboli, Pietro Ferrari, Heinz Freisling","doi":"10.1186/s12933-026-03263-4","DOIUrl":"10.1186/s12933-026-03263-4","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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).</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13288577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"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).","authors":"Xiao Chen, Chaochao Wang, Yuan Luo, Qi Huang, Haibo Gong, Jing Chen","doi":"10.1186/s12933-026-03257-2","DOIUrl":"https://doi.org/10.1186/s12933-026-03257-2","url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeted proteomics of extreme vascular phenotypes in type 1 diabetes: the ESCAPER study.","authors":"Ola Ekström, Cecilia Kennbäck, Valeriya Lyssenko, Magnus Löndahl, Anders Christensson, Peter M Nilsson, Anders Gottsäter","doi":"10.1186/s12933-026-03261-6","DOIUrl":"10.1186/s12933-026-03261-6","url":null,"abstract":"<p><p>Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in Type 1 Diabetes (T1D), but a subset of individuals remains free from macrovascular or renal complications despite decades of hyperglycaemia and a significant risk factor burden. We used a targeted proteomic approach (Olink Cardiovascular panel III, targeting 92 proteins) to characterize the proteomic profile of cardiovascular resilience in T1D by comparing 92 patients with long-standing T1D (age 59.8 [53.2, 69.1], duration 40.0 [35.0, 45.2] years) free from macrovascular complications or nephropathy against a reference group of 57 T1D patients with accelerated vascular pathology (age 42.0 [32.0, 56.0], duration 22.0 [18.0, 27.0] years), proliferative retinopathy and/or nephropathy in relation to diabetes duration, termed Rapid Progressors (RP). Twenty proteins differed significantly between RP and Escapers (False Discovery Rate [FDR] < 0.05) after adjustment for age, sex, HbA1c, and eGFR: Caspase-3 was significantly higher in RP (Adjusted difference: + 2.12 Normalized Protein eXpression [NPX], p < 0.001). Proteins associated with platelet activation and leukocyte adhesion with increased levels in RP included Junctional Adhesion Molecule A (+ 1.40 NPX), Glycoprotein VI (GP6: + 1.29 NPX), and P-Selectin (+ 0.82 NPX) (all p < 0.001). PECAM-1 (+ 0.55 NPX) and TNFRSF14 (+ 0.43 NPX), were also elevated. RP also showed higher levels of metabolic and tissue-remodelling proteins; Transferrin Receptor (+ 0.53 NPX) and Fatty Acid Binding Protein 4 (+ 0.52 NPX), as well as higher Bleomycin Hydrolase, Trefoil Factor 3, GDF-15, U-PAR, and Cystatin B. Conversely, von Willebrand Factor (vWF) levels (- 1.35 NPX, p < 0.001) and Paraoxonase 3 (PON3) was lower in RP (- 0.34 NPX, p = 0.003). In conclusion, escaping complications in long-term T1D appears to be associated with active molecular mechanisms. Progression is marked by apoptosis (Caspase-3), fibrosis (CHI3L1) and platelet activation (GP6), whereas resilience is associated with a distinct signature involving higher vWF and PON3. These findings highlight a profound biological divergence between extreme T1D phenotypes and provide a foundation for further research into vascular resilience.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"25 1","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13282855/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148293429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"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.","authors":"Zhenyu Tian, Xuefang Yan, Fei Xue, Jianmin Yang, Na Li","doi":"10.1186/s12933-026-03260-7","DOIUrl":"10.1186/s12933-026-03260-7","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;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 &lt; 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.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion: &lt;/strong&gt;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 ","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13508244/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148292989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal variability of lipoprotein(a) in youth-onset type 1 diabetes: implications for cardiovascular risk stratification.","authors":"Fanny Iafrate-Luterbacher, Cecilia Jimenez-Sanchez, Maria Loukia Anastasiadou, Julien Prados, Frida Renström, Michael Brändle, Stefan Bilz, Valerie M Schwitzgebel","doi":"10.1186/s12933-026-03252-7","DOIUrl":"10.1186/s12933-026-03252-7","url":null,"abstract":"<p><strong>Background: </strong>Lipoprotein(a) [Lp(a)] is a genetically determined and independent cardiovascular risk factor, traditionally considered stable across the lifespan, supporting a single lifetime measurement strategy. However, its longitudinal behaviour during childhood and adolescence remains poorly characterised, particularly in individuals with type 1 diabetes who face a markedly increased lifetime risk of coronary artery disease. We therefore aimed to characterise intra- and inter-individual trajectories of Lp(a) in a paediatric type 1 diabetes cohort and to assess the implications of Lp(a) variability for cardiovascular risk classification.</p><p><strong>Methods: </strong>We conducted a retrospective single-centre cohort study of children and adolescents with type 1 diabetes attending Geneva University Hospitals between 2012 and 2023. Annual fasting Lp(a) concentrations were analysed longitudinally. Variability was assessed in participants with ≥ 2 measurements. Clinically relevant thresholds were used to evaluate cardiovascular risk reclassification. Paired Wilcoxon tests, Pearson and Kendall correlations, and Holm-adjusted p-values (P < 0.05) were applied. Analyses were conducted in R.</p><p><strong>Results: </strong>A total of 286 participants contributed 1403 Lp(a) measurements, with observation periods varying across individuals (median 6.2 years, IQR 2.9-9.6) and between 1 and 13 measurements per participant. At baseline, 26% had elevated Lp(a) (≥ 300 mg/l). Among participants with serial measurements, 32% showed intraindividual fluctuations exceeding 50% of their individual maximum value. Reclassification across the 300 mg/l cardiovascular risk threshold occurred in 11.9% of participants. Lp(a) concentrations peaked between ages 10 and 13 years and declined thereafter. Modest seasonal variation was observed, with higher concentrations in autumn and winter (P < 0.05).</p><p><strong>Conclusions: </strong>In youth with type 1 diabetes, Lp(a) is not as stable as previously assumed, exhibiting clinically relevant variability over time. These findings challenge the current paradigm of a single lifetime Lp(a) measurement and suggest that repeated assessment, particularly during adolescence, may improve early cardiovascular risk stratification.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":" ","pages":""},"PeriodicalIF":15.6,"publicationDate":"2026-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13523341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148283327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}