Suneesh Kaimala, Lidya K Yassin, Mohammad I K Hamad, Mohammed Z Allouh, Prabha Sampath, Juma AlKaabi, Melvin Khee-Shing Leow, Safa Shehab, Suraiya Anjum Ansari, Bright Starling Emerald
{"title":"Epigenetic crossroads in metabolic and cardiovascular health: the role of DNA methylation in type 2 diabetes and cardiovascular diseases.","authors":"Suneesh Kaimala, Lidya K Yassin, Mohammad I K Hamad, Mohammed Z Allouh, Prabha Sampath, Juma AlKaabi, Melvin Khee-Shing Leow, Safa Shehab, Suraiya Anjum Ansari, Bright Starling Emerald","doi":"10.1186/s12933-025-02800-x","DOIUrl":"10.1186/s12933-025-02800-x","url":null,"abstract":"<p><p>Type 2 diabetes (T2D) and cardiovascular diseases (CVD), part of the metabolic syndrome (MetS), are major contributors to the global health crisis today. A recent report from the World Health Organisation estimates that 17.9 million lives are lost each year to CVD, and one-third of these are premature. The international diabetes federation estimates that around 537 million adults aged between 20 and 79 years are living with diabetes. People with diabetes are suggested to have twice the risk of developing CVD. Epigenetic modifications are being increasingly recognised as the key mediators linking genetic and environmental conditions to metabolic dysfunction. Among these, DNA methylation plays a crucial role in modulating gene expression and influencing pathways involved in glucose homeostasis, inflammation, and vascular integrity. Despite the advances in our understanding of the role of epigenetic alterations in metabolic diseases, including that of T2D, the mechanisms driving selective methylation changes and their long-term impact on cardiovascular health are still not well understood. This review synthesises the current knowledge on DNA methylation dynamics in T2D and their role towards the progression of CVD and explores their potential as biomarkers and therapeutic targets. Understanding the interplay between metabolism and epigenetics in the pathogenesis of T2D and CVD could provide critical insights for early disease identification and the development of novel epigenome-targeted therapeutic strategies.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"231"},"PeriodicalIF":8.5,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12124063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180787","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}
Jin Wang, Wei-Feng Yan, Ke Shi, Hua-Yan Xu, Shi-Qin Yu, Ying-Kun Guo, Li Jiang, Yue Gao, Yu-Jiang, Xue-Ming Li, Yuan Li, Zhi-Gang Yang
{"title":"Comparison of right ventricular function and clinical outcomes in type 2 diabetes patients with and without obstructive coronary artery disease: insights from a CMR study.","authors":"Jin Wang, Wei-Feng Yan, Ke Shi, Hua-Yan Xu, Shi-Qin Yu, Ying-Kun Guo, Li Jiang, Yue Gao, Yu-Jiang, Xue-Ming Li, Yuan Li, Zhi-Gang Yang","doi":"10.1186/s12933-025-02755-z","DOIUrl":"10.1186/s12933-025-02755-z","url":null,"abstract":"<p><strong>Background: </strong>Obstructive coronary artery disease (OCAD) marks a high-risk group within patients with type 2 diabetes mellitus (T2DM), underscoring the need for tailored prevention and management strategies. However, limited data exist on right ventricular (RV) function and clinical outcomes in T2DM patients with versus without OCAD. This study aimed to investigate the differences in RV function and clinical outcomes between these two groups.</p><p><strong>Methods: </strong>The study included 246 T2DM patients {141 patients without OCAD [T2DM(OCAD-)] and 105 with [T2DM(OCAD+)]} and 85 control subjects. Cardiovascular magnetic resonance were utilized to assess RV structure, function, and global myocardial strain [including peak strain (PS), peak systolic (PSSR) and diastolic strain rate (PDSR) in longitudinal, circumferential, and radial directions]. The endpoints, which included all-cause mortality, heart failure hospitalization, and overall composite outcome, were evaluated over a median follow-up period of 5.7 (3.1, 6.7) years. We used linear regression to identify determinants of impaired RV myocardial strain and Cox proportional hazards models to evaluate their associations with clinical outcomes.</p><p><strong>Results: </strong>RV global circumferential PS (GCPS), longitudinal PS (GLPS) and PSSR (PSSR-L) decreased progressively from control subjects to T2DM(OCAD-) patients, and further to T2DM(OCAD+) patients (all P < 0.05). The presence of OCAD was significantly correlated with impaired GRPS (β = - 0.186), GCPS (β = - 0.121), GLPS (β = - 0.153), PSSR-L (β = - 0.165), and PDSR-R (β = - 0.133) in the context of T2DM. Multivariable Cox regression analysis identified OCAD as an independent predictor of future endpoints, with T2DM (OCAD+) patients showing a 1.91-fold increased risk compared to T2DM (OCAD-) patients (hazard ratio: 1.91; 95% confidence interval: 1.06-3.44; P = 0.031).</p><p><strong>Conclusions: </strong>T2DM patients with OCAD showed distinct RV functional impairments and worse long-term outcomes compared to those without OCAD, including more severe RV systolic and diastolic dysfunction and a significantly higher risk of adverse clinical outcomes.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"229"},"PeriodicalIF":8.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12107746/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149584","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}
Thomas T Yoo, In Hae Baek, Liset Stoletniy, Anthony Hilliard, Antoine Sakr, Desislava Doycheva
{"title":"Impact of sodium-glucose transport protein-2 (SGLT2) inhibitors on the inflammasome pathway in acute myocardial infarction in type 2 diabetes mellitus: a comprehensive review.","authors":"Thomas T Yoo, In Hae Baek, Liset Stoletniy, Anthony Hilliard, Antoine Sakr, Desislava Doycheva","doi":"10.1186/s12933-025-02777-7","DOIUrl":"10.1186/s12933-025-02777-7","url":null,"abstract":"<p><p>Sodium-glucose transport protein-2 (SGLT2) inhibitors, initially developed for glycemic control in type 2 diabetes mellitus (T2DM), have emerged as potential cardioprotective agents, reducing cardiovascular mortality and improving heart failure outcomes. Recent evidence suggests that SGLT2 inhibitors exert anti-inflammatory effects, particularly through modulating the inflammasome pathway. This review explores the role of the inflammasome in acute myocardial infarction (AMI) in T2DM and discusses the mechanisms by which SGLT2 inhibitors influence this pathway. We evaluate current studies on the impact of SGLT2 inhibitors on key inflammatory mediators, particularly the NLRP3 inflammasome, and discuss their potential therapeutic implications for reducing inflammation and myocardial injury in patients with T2DM experiencing AMI. In summary, the key novelties in this review lie in its focused mechanistic approach on the inflammasome pathway, its integration of diabetes and cardiovascular research, and its potential to influence future therapeutic strategies for AMI in T2DM patients. It offers a novel angle by tying together molecular mechanisms of inflammation with clinical implications in a specific patient population that faces high cardiovascular risk.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"227"},"PeriodicalIF":8.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105141/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149592","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":"Correction: Association of different insulin resistance surrogates with all-cause and cardiovascular mortality among the population with cardiometabolic multimorbidity.","authors":"Hongqiang Zhang, Zhixin Tu, Sihua Liu, Jumei Wang, Jie Shi, Xingyu Li, Rongdongqing Shi, Minghui Chen, Tong Yue, Sihui Luo, Yu Ding, Xueying Zheng","doi":"10.1186/s12933-025-02794-6","DOIUrl":"10.1186/s12933-025-02794-6","url":null,"abstract":"","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"228"},"PeriodicalIF":8.5,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12105138/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149585","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}
Cong Liu, Bangqun Ji, Yao Liang, Juan Shi, Yufan Wang, Tingyu Ke, Li Li, Dong Zhao, Yuancheng Dai, Qijuan Dong, Fengmei Xu, Ying Peng, Weiqing Wang, Qidong Zheng, Yifei Zhang
{"title":"Cumulative blood pressure load as a predictor of arterial stiffness progression and incident diabetic kidney disease: a multicenter longitudinal study.","authors":"Cong Liu, Bangqun Ji, Yao Liang, Juan Shi, Yufan Wang, Tingyu Ke, Li Li, Dong Zhao, Yuancheng Dai, Qijuan Dong, Fengmei Xu, Ying Peng, Weiqing Wang, Qidong Zheng, Yifei Zhang","doi":"10.1186/s12933-025-02785-7","DOIUrl":"10.1186/s12933-025-02785-7","url":null,"abstract":"<p><strong>Background: </strong>Elevated blood pressure (BP) is a key contributor to the progression of arterial stiffness and the incidence of diabetic kidney disease (DKD). Cumulative BP load enables the evaluation of long-term BP exposure, but the BP targets used to calculate it vary across studies. This study aimed to compare the predictive performance of cumulative BP load calculated using different clinically recommended BP targets.</p><p><strong>Methods: </strong>This multicenter longitudinal study included participants with type 2 diabetes from 10 diabetes centers. Cumulative BP load was calculated using various clinically recommended BP targets (SBP < 140 mmHg, < 130 mmHg, and < 120 mmHg). The primary outcomes were the progression of arterial stiffness, assessed by brachial-ankle pulse wave velocity (ba-PWV) changes, and the incidence of DKD, defined as an estimated glomerular filtration rate < 60 mL/min/1.73m<sup>2</sup> or urine albumin-to-creatinine ratio ≥ 3.39 mg/mmol. The predictive ability of cumulative BP load calculated under different clinically recommended targets was compared using adjusted R squared (adjusted R<sup>2</sup>) for continuous outcomes and net reclassification improvement (NRI) for binary outcomes.</p><p><strong>Results: </strong>Among the 18,168 participants included (mean age 54.5 years; 57.5% male), 13,388 met all eligibility criteria for the analysis of arterial stiffness progression, and 11,145 for the analysis of DKD incidence. Over a mean follow-up of 3.5 years, the median ba-PWV increase was 0.19 m/s per year and 2,855 (25.6%) developed DKD. When cumulative BP load was added to a model containing traditional risk factors, the adjusted R<sup>2</sup> values for predicting the absolute annual change in ba-PWV were 0.193 (95% CI 0.180-0.200), 0.184 (0.169-0.191), and 0.172 (0.158-0.180) with BP targets of SBP < 120, < 130, and < 140 mmHg, respectively. For the incidence of DKD, the NRIs were 15.8% (11.5-20.0%), 12.5% (8.3-16.7%), and 6.4% (2.3-10.6%) with BP targets of SBP < 120, < 130, and < 140 mmHg, respectively.</p><p><strong>Conclusion: </strong>Cumulative BP load is an effective indicator for predicting the progression of arterial stiffness and incidence of DKD, with the best predictive performance observed when the target SBP is set at < 120 mmHg.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"225"},"PeriodicalIF":8.5,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12103019/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144141415","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":"Metabolic profiling of frailty, associations with type 2 diabetes and interaction with genetic susceptibility.","authors":"Yuxiang Wang, Shuang Chen, Yue Li, Qi Lu, Rui Li, Jun-Xiang Chen, Ji-Juan Zhang, Hancheng Yu, Hanrui Xu, Jinchi Xie, Xianli Li, Gang Liu, An Pan, Tingting Geng, Yun-Fei Liao","doi":"10.1186/s12933-025-02776-8","DOIUrl":"10.1186/s12933-025-02776-8","url":null,"abstract":"<p><strong>Background: </strong>Individuals with frailty are at increased risk of type 2 diabetes (T2D), but the underlying mechanisms are unclear. We aimed to investigate whether the frailty-T2D association is mediated by alterations in the metabolome and assess potential interaction with genetic susceptibility to diabetes.</p><p><strong>Methods: </strong>This retrospective analysis, using data from a large prospective population-based cohort, included a total of 197,502 adults with baseline metabolomics data from the UK Biobank. Frailty was defined using the Fried frailty phenotype according to five components. Elastic net regression was applied to create a frailty-related metabolic signature. We assessed hazard ratios (HR) and its 95% confidence interval (CI) of incident T2D in relation to the baseline metabolic signature of frailty and examined the mediating role of the metabolic signature in the effect of frailty on T2D. Additive interaction between the metabolic signature and polygenic risk score for T2D (PRS-T2D) on the incidence of T2D was assessed as relative excess risk due to interaction (RERI).</p><p><strong>Results: </strong>Compared with non-frailty, the HR (95% CI) of incident T2D in pre-frailty and frailty was 1.33 (1.26, 1.40) and 1.59 (1.46, 1.74), respectively. The metabolic signature of frailty (comprised of 53 metabolites) was positively associated with T2D risk (HR per standard deviation increment: 1.45; 95% CI: 1.42, 1.48), and explained 31.0% (95% CI: 25.8, 36.8) of the association between frailty and T2D. An additive interaction between metabolic signature of frailty and PRS-T2D was found (RERI: 9.43; 95% CI: 6.06, 12.80).</p><p><strong>Conclusions: </strong>The increased risk of T2D in individuals with frailty may be mediated through effects on the metabolome, and the influence of such metabolic alterations on diabetes risk may be amplified in individuals with genetic susceptibility to T2D.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"226"},"PeriodicalIF":8.5,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12102881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144141362","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}
Nicola Riccardo Pugliese, Francesco Paneni, Domenico Tricò, Alessandra Violet Bacca, Nicolò De Biase, Hermann Dalpiaz, Alessandro Mengozzi, Agostino Virdis, Lorenzo Ghiadoni, Stefano Taddei, Reinhold Kreutz, Konstantinos Tsioufis, Stefano Masi
{"title":"Refining the link between obesity and heart failure: insights from GLP-1 receptor agonist trials and studies adopting direct adiposity measures.","authors":"Nicola Riccardo Pugliese, Francesco Paneni, Domenico Tricò, Alessandra Violet Bacca, Nicolò De Biase, Hermann Dalpiaz, Alessandro Mengozzi, Agostino Virdis, Lorenzo Ghiadoni, Stefano Taddei, Reinhold Kreutz, Konstantinos Tsioufis, Stefano Masi","doi":"10.1186/s12933-025-02778-6","DOIUrl":"10.1186/s12933-025-02778-6","url":null,"abstract":"<p><p>Overweight and obesity are major risk factors for heart failure (HF), contributing to its development through metabolic, neurohormonal, haemodynamic, and inflammatory alterations. While overweight/obesity increases the risk of developing HF, its impact on patient outcomes remains complex. The \"obesity paradox\" suggests that a higher BMI may be associated with improved survival in patients with established HF. However, recent GLP-1 receptor agonist (GLP-1 RA) trials suggest that intentional weight loss positively influences outcomes in overweight/obese patients with HF. This seemingly contradictory evidence highlights the need for a deeper understanding of the mechanisms linking adiposity to HF outcomes. A more precise characterization of adiposity phenotypes using alternative and accurate measures of pathological fat accumulation is crucial in identifying individuals who may benefit most from anti-obesity treatments. In this context, recent research underscores the role of epicardial adipose tissue (EAT) in HF pathophysiology, as it directly influences cardiac function and structure through inflammatory, metabolic, and mechanical effects. This narrative review summarises current evidence on the impact of weight loss on HF outcomes, focusing on recent GLP-1 RA trial results. Additionally, it highlights epidemiological and molecular data supporting EAT as a novel adiposity measure that might allow refining patient selection for pharmacological weight-loss treatments. Finally, it emphasizes the need for future research to identify causal pathways linking alternative measures of visceral fat accumulation to HF outcomes. These efforts will be essential in optimizing the benefits of novel weight-loss treatments, ensuring effective and individualized therapeutic strategies for overweight or obese patients with HF.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"224"},"PeriodicalIF":8.5,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12096527/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126844","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":"The predictive significance of the triglyceride-glucose index in forecasting adverse cardiovascular events among type 2 diabetes mellitus patients with co-existing hyperuricemia: a retrospective cohort study.","authors":"Jianyong Zhao, Na Li, Shiqi Li, Jiaqing Dou","doi":"10.1186/s12933-025-02783-9","DOIUrl":"10.1186/s12933-025-02783-9","url":null,"abstract":"<p><strong>Background: </strong>The triglyceride-glucose (TyG) index serves as a crucial indicator for evaluating insulin resistance (IR) and cardiovascular risk among patients with type 2 diabetes mellitus (T2DM). Concurrently, hyperuricemia (HUA) strongly correlates with adverse cardiovascular outcomes. However, the prognostic value of the TyG index, particularly in patients exhibiting both conditions, remains inadequately defined. This study assessed the association between TyG index measurements and the incidence of major adverse cardiovascular events (MACEs) among patients simultaneously diagnosed with T2DM and HUA.</p><p><strong>Methods: </strong>This retrospective, single-center cohort study included 628 patients diagnosed with both T2DM and HUA at the Chaohu Hospital (Anhui Medical University) between 2019 and 2024. Participants were stratified into tertiles based on their TyG index values. Kaplan-Meier survival curves with log-rank tests estimated the risk of MACEs, and Cox regression analyses calculated hazard ratios. The additional predictive contribution of the TyG index was evaluated using C statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) metrics.</p><p><strong>Results: </strong>During the 38.00 ± 8.78 months follow-up period, 74 MACEs were recorded. A significant proportional relationship emerged between the TyG index and cardiovascular events-patients in the highest tertile demonstrated markedly increased risk compared with those in the lowest tertile (HR = 2.45, 95% CI 1.23-4.95). A pivotal threshold was identified at TyG > 8.40, beyond which each standard deviation increase corresponded to a 66% higher probability of MACEs (HR = 1.66, 95% CI 1.36-2.36, P = 0.014). Integrating the TyG index into traditional risk models significantly improved predictive performance (C statistic increase: 0.64 → 0.67, P = 0.029; NRI = 0.14, IDI = 0.02, both P < 0.05).</p><p><strong>Conclusion: </strong>The TyG index constitutes an autonomous MACE predictor specifically within the distinctive cohort of patients manifesting both T2DM and HUA. This study is the first to validate the TyG > 8.40 threshold in T2DM patients with HUA and identify a synergistic interaction between serum uric acid (SUA) and TyG, providing a novel stratification tool for managing dual metabolic disorders.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"218"},"PeriodicalIF":8.5,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12093811/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118841","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}
Xianli Qiu, Yong Han, Changchun Cao, Yuheng Liao, Haofei Hu
{"title":"Association between atherogenicity indices and prediabetes: a 5-year retrospective cohort study in a general Chinese physical examination population.","authors":"Xianli Qiu, Yong Han, Changchun Cao, Yuheng Liao, Haofei Hu","doi":"10.1186/s12933-025-02768-8","DOIUrl":"10.1186/s12933-025-02768-8","url":null,"abstract":"<p><strong>Background and objective: </strong>Atherogenicity indices have emerged as promising markers for cardiometabolic disorders, yet their relationship with prediabetes risk remains unclear. This study aimed to comprehensively evaluate the associations between six atherogenicity indices and prediabetes risk in a Chinese population, and explore the predictive value of these atherosclerotic parameters for prediabetes.</p><p><strong>Methods: </strong>This retrospective cohort study included 97,151 participants from 32 healthcare centers across China, with a median follow-up of 2.99 (2.13, 3.95) years. Six atherogenicity indices were calculated: Castelli's Risk Index-I (CRI-I), Castelli's Risk Index-II (CRI-II), Atherogenic Index of Plasma (AIP), Atherogenic Index (AI), Lipoprotein Combine Index (LCI), and Cholesterol Index (CHOLINDEX). To address the natural relationships between the atherogenicity indices and risk of prediabetes, we applied Cox proportional hazards regression with cubic spline functions and smooth curve fitting, using a recursive algorithm to calculate inflection points. Machine learning approach (XGBoost and Boruta methods) to address the high collinearity among indices and assess their relative importance, combined with time-dependent ROC analysis to evaluate the predictive performance at 3-, 4-, and 5-year follow-up.</p><p><strong>Results: </strong>During follow-up, 11,199 participants developed prediabetes (incidence rate: 3.71 per 100 person-years). Significant nonlinear associations were observed between all atherogenicity indices and prediabetes risk. Through Z-score standardization of atherogenicity indices and comprehensive Cox proportional hazards regression and advanced machine learning techniques, we identified AIP as the most significant predictor of prediabetes [HR = 1.057 (95% CI 1.035-1.080, P < 0.0001)], with LCI emerging as a secondary important marker [HR = 1.020 (95% CI 1.002-1.038, P = 0.0267)]. Our innovative XGBoost and Boruta analysis uniquely validated these findings, providing robust evidence of AIP and LCI's critical role in prediabetes risk assessment. Time-dependent ROC analysis further validated these findings, with LCI and AIP demonstrating comparable discrimination, with overlapping AUC ranges of 0.5952-0.6082. Notably, the combined indices model achieved enhanced predictive performance (AUC: 0.6753) compared to individual indices, suggesting the potential benefit of using multiple atherogenicity indices for prediabetes risk prediction.</p><p><strong>Conclusion: </strong>This study identifies statistically significant associations between atherogenicity indices and prediabetes risk, highlighting their nonlinear relationships and combined effects. While the predictive performance of these indices is modest (AUC 0.55-0.68), these findings may contribute to improved risk stratification when incorporated into comprehensive assessment strategies.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"220"},"PeriodicalIF":8.5,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12096774/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118808","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}
Zhenguo Wang, Wenjuan Mu, Ruiyan Xu, Juan Zhong, Wenhao Xiong, Xiangjie Zhao, Xiubin Liang, Yanhong Guo, Jifeng Zhang, Zhi-Sheng Jiang, Bo Yang, Y Eugene Chen, Lin Chang
{"title":"Perivascular adipose tissue dysfunction contributes to thoracic aortic aneurysm development.","authors":"Zhenguo Wang, Wenjuan Mu, Ruiyan Xu, Juan Zhong, Wenhao Xiong, Xiangjie Zhao, Xiubin Liang, Yanhong Guo, Jifeng Zhang, Zhi-Sheng Jiang, Bo Yang, Y Eugene Chen, Lin Chang","doi":"10.1186/s12933-025-02765-x","DOIUrl":"10.1186/s12933-025-02765-x","url":null,"abstract":"<p><strong>Background: </strong>Thoracic aortic aneurysm (TAA) is a life-threatening disease with high morbidity and mortality rates due to fatal complications such as aortic rupture. However, molecular mechanisms underlying TAA pathogenesis remain to be fully elucidated. The aorta is naturally surrounded by perivascular adipose tissue (PVAT), which produces and releases adipokines and other factors in a paracrine manner that are pivotal for vascular physiology and pathophysiology. Under healthy conditions, thoracic PVAT resembles brown adipose tissue (BAT) and maintains vascular homeostasis. In response to pathogenic stimuli, PVAT can undergo whitening and become dysfunctional, contributing to the development of vascular diseases. However, a causal relationship between PVAT dysfunction and TAA pathogenesis, as well as the underlying mechanisms, remain unknown. This study investigated the roles of PPARg (a key determinant of adipogenesis) and PRDM16 (a key determinant of brown adipocyte development) in PVAT on TAA development.</p><p><strong>Methods: </strong>PVAT samples from TAA patients were collected and evaluated. Mice lacking PVAT and those with dysfunctional PVAT were generated by crossbreeding Ucp1 promoter-driven Cre mice with Pparg floxed mice (brown adipocyte-specific Pparg knockout, Pparg<sup>BAKO</sup>) and Prdm16 floxed mice (brown adipocyte-specific Prdm16 knockout, Prdm16<sup>BAKO</sup>), respectively. TAA formation was induced by perivascular application of porcine pancreatic elastase (PPE) and evaluated through histological staining. Luciferase reporter assays and chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) were used to determine PRDM16 target genes.</p><p><strong>Results: </strong>We found that PVAT near TAA lesions in patients exhibited reduced expression of browning markers and increased expression of whitening markers. Pparg<sup>BAKO</sup> mice showed impaired PVAT development, while Prdm16<sup>BAKO</sup> mice displayed a loss of browning in PVAT. Both Pparg<sup>BAKO</sup> and Prdm16<sup>BAKO</sup> mice exhibited aggravated TAA formation. We identified decorin, a small proteoglycan of the extracellular matrix, as a transcriptional repressive target gene of PRDM16. The expression of decorin was increased in dysfunctional PVAT and the plasma of TAA patients.</p><p><strong>Conclusions: </strong>The development and maintenance of brown-like characteristics in PVAT are necessary to protect against TAA formation. PVAT dysfunction contributes to TAA development. Our study provides a promising therapeutic strategy for preventing TAA progression by inducing PVAT browning.</p>","PeriodicalId":9374,"journal":{"name":"Cardiovascular Diabetology","volume":"24 1","pages":"223"},"PeriodicalIF":8.5,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12096520/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144118840","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}