Cardiovasc Diabetol [JOURNAL]
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200 papers
Estimated glucose disposal rate outperforms inflammation surrogate markers in predicting cardiometabolic multimorbidity among middle-aged and older adults.
Cui C, Wang X, Wang L … +8 more , Xue K, Cao J, Zhang L, Yue S, Chen S, Liu L, Liu Y, Du J
Cardiovasc Diabetol · 2026 Jun · PMID 42277792 · Full text
BACKGROUND: Both estimated glucose disposal rate (eGDR) and inflammation surrogate (high-sensitivity C-reactive protein [hs-CRP]) have emerged as potential markers reflecting metabolic health. However, their comparative...
BACKGROUND: Both estimated glucose disposal rate (eGDR) and inflammation surrogate (high-sensitivity C-reactive protein [hs-CRP]) have emerged as potential markers reflecting metabolic health. However, their comparative predictive value for cardiometabolic multimorbidity remains unclear, particularly in middled-aged and older populations where both metabolic dysfunction and low-grade inflammation are highly prevalent. METHODS: This prospective cohort study included 7,589 participants aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS) with complete baseline data. The primary outcome was incident cardiometabolic multimorbidity, defined as the co-occurrence of two or more cardiometabolic conditions, including diabetes, heart disease, and stroke. Cox proportional hazards models were employed to assess separate and joint associations. Concordance index (C-index) was used to evaluate the predictive capacity. RESULTS: Over a 9-year follow-up period, 2,263 participants developed cardiometabolic multimorbidity. In models adjusting for traditional risk factors, lower eGDR (lowest vs. highest quartile: hazard ratio [HR] 2.07, 95% CI 1.80-2.38) remained significantly associated with increased risk of cardiometabolic multimorbidity. In joint associations, participants with low eGDR exhibited consistently elevated cardiometabolic multimorbidity risk regardless of inflammation surrogate status (HR 1.52 (95% CI 1.33-1.74) in those with low inflammation and HR 1.80 (95% CI 1.58-2.04) in those with high inflammation). Addition of eGDR to the basic model (which included covariates) yielded a significantly higher C-index (0.676) compared to hs-CRP (0.643, P < 0.001). CONCLUSIONS: Among middle-aged and older adults, eGDR is significantly associated with incident cardiometabolic multimorbidity regardless of inflammation status. Low eGDR demonstrates superior discriminative ability compared to hs-CRP. These findings suggest that eGDR may serve as a more comprehensive biomarker for cardiometabolic risk stratification by capturing insulin resistance and metabolic dysfunction.
Increased epicardial adipose tissue area and radiodensity in sarcopenic obesity.
He T, Wang R, Jiang W … +3 more , Lian R, Chen X, Yang M
Cardiovasc Diabetol · 2026 Jun · PMID 42271452 · Full text
BACKGROUND: Sarcopenic obesity (SO) confers substantially greater cardiometabolic risk than either sarcopenia or obesity alone, but the tissue-level structural alterations underlying this risk remain unclear. Epicardial...
BACKGROUND: Sarcopenic obesity (SO) confers substantially greater cardiometabolic risk than either sarcopenia or obesity alone, but the tissue-level structural alterations underlying this risk remain unclear. Epicardial adipose tissue (EAT) characteristics, including both area and radiodensity, may provide clinically relevant insight into the cardiometabolic burden associated with this complex muscle-fat imbalance. METHODS: We conducted a cross-sectional study of 1678 adults undergoing health examinations. Participants were categorized into normal, sarcopenia, obesity, and SO phenotypes based on the European Society for Clinical Nutrition and Metabolism and the European Association for the Study of Obesity (ESPEN/EASO) conceptual framework. Body composition and grip strength were assessed according to the Asian Working Group for Sarcopenia (AWGS) 2025 criteria. EAT area (cm) and radiodensity (attenuation, measured in Hounsfield units [HU]) were quantified via non-contrast chest computed tomography. Associations were assessed using multivariable linear regression, interaction analysis, and sex-stratified restricted cubic splines. RESULTS: The SO phenotype was identified in 45 individuals. Following multivariable adjustment, SO was independently associated with a larger EAT area (beta = 6.93 cm; 95% CI, 5.84 to 8.03) and a higher (less negative) EAT radiodensity (beta = 9.23 HU; 95% CI, 8.03 to 10.43) compared with the normal phenotype. Effect estimates were larger for SO than for isolated obesity. An interaction between sarcopenia and obesity was observed for EAT area (interaction beta = 1.53 cm; 95% CI, 0.05 to 3.01; P for interaction = 0.042), whereas no significant interaction was observed for EAT radiodensity. In sex-stratified analyses, grip strength showed a pronounced non-linear association with EAT radiodensity. CONCLUSIONS: In this cross-sectional study, SO was associated with larger EAT area and higher EAT radiodensity. These findings support the presence of a distinct EAT phenotype in SO and suggest that CT-derived EAT measures may be useful imaging markers that warrant prospective validation.
Association of the C-reactive protein-triglyceride-glucose (CTI) index and its central obesity-modified derivatives with incident cardiometabolic multimorbidity: results from two prospective cohorts in China and England.
Yue C, Wang X, Li Y … +4 more , Yuan S, Wang Z, Liu H, Yang H
Cardiovasc Diabetol · 2026 Jun · PMID 42271373 · Full text
BACKGROUND: Central obesity exacerbates cardiometabolic multimorbidity (CMM) susceptibility through insulin resistance and inflammation. We investigated the longitudinal association of C-reactive protein-triglyceride-glu...
BACKGROUND: Central obesity exacerbates cardiometabolic multimorbidity (CMM) susceptibility through insulin resistance and inflammation. We investigated the longitudinal association of C-reactive protein-triglyceride-glucose (CTI)-related indices-which integrate these mechanisms with abdominal obesity measurements-with incident CMM in middle-aged and older adults. METHODS: This study included 6,498 participants from the China Health and Retirement Longitudinal Study and 2,455 from the English Longitudinal Study of Ageing, all free of diabetes, heart disease, and stroke at baseline. Incident CMM was defined as the occurrence of at least two of these diseases during follow-up. CTI-waist circumference (CTI-WC) and CTI-waist-to-height ratio (CTI-WHtR) were prespecified as principal exposures, with CTI, triglyceride-glucose index (TyG), and corresponding obesity-related derivatives as comparators. Death before CMM was treated as a competing event. Associations and prediction were assessed using Fine-Gray models, cumulative incidence functions, restricted cubic splines, time-dependent area under the curve, C-statistic, net reclassification improvement, integrated discrimination improvement, and calibration metrics. RESULTS: During median follow-up periods of 7.00 and 9.58 years, 303 and 255 participants developed incident CMM in the Chinese and English cohorts, respectively. In the Chinese cohort, each 1-standard deviation increase in CTI-WC and CTI-WHtR was associated with higher CMM risk (CTI-WC: subdistribution HR = 1.59, 95% CI 1.44-1.75; CTI-WHtR: subdistribution HR = 1.59, 95% CI 1.44-1.76), and the highest quartile had approximately fourfold higher risk than the lowest quartile. In the English cohort, associations were weaker but directionally consistent, with CTI-WC remaining significant per 1-standard deviation increment (1.18, 1.03-1.35). In the Chinese cohort, CTI-WC and CTI-WHtR yielded the highest 7-year area under the curve values (0.693 and 0.692), and CTI-WC showed the largest reclassification improvement. Calibration and sensitivity analyses supported model stability. CONCLUSIONS: Prespecified CTI-WC and CTI-WHtR were associated with incident CMM after accounting for competing mortality. Integrating inflammatory-metabolic burden with central adiposity may improve CMM risk stratification, especially in the Chinese cohort.
Differential associations between novel triglyceride-glucose-obesity indices and incident stroke in individuals with early-stage cardiovascular-kidney-metabolic syndrome: a longitudinal cohort study.
Fu ZQ, An L, Zhang W … +2 more , Lyu Y, Li S
Cardiovasc Diabetol · 2026 Jun · PMID 42260604 · Full text
BACKGROUND: The triglyceride-glucose (TyG) index combined with advanced anthropometric measures has emerged as a promising tool for cardiovascular risk assessment. However, evidence comparing the predictive utility of va...
BACKGROUND: The triglyceride-glucose (TyG) index combined with advanced anthropometric measures has emerged as a promising tool for cardiovascular risk assessment. However, evidence comparing the predictive utility of various novel TyG-obesity indices for incident stroke in individuals with early-stage cardiovascular-kidney-metabolic (CKM) syndrome remains limited. This study aimed to investigate and compare the associations of six novel TyG-obesity indices (TyG-Chinese visceral adiposity index [CVAI], -body roundness index [BRI], -conicity index [CI], -weight-adjusted waist index [WWI], -a body shape index [ABSI], and -relative fat mass [RFM]) with stroke in individuals with CKM stages 0-3. METHODS: This prospective cohort study included 3400 participants from the China Health and Retirement Longitudinal Study. K-means clustering was used to identify longitudinal change patterns, and the Boruta algorithm ranked feature importance. We used Cox proportional hazards models to evaluate the strength of associations, restricted cubic splines (RCS) to explore dose-response relationships, receiver operating characteristic (ROC) curves to assess discriminative ability, and net reclassification improvement (NRI) and integrated discrimination improvement (IDI) to quantify incremental predictive performance. RESULTS: During a median follow-up of 8.6 years, 232 incident strokes were documented. Using a multidimensional analytical framework incorporating baseline, cumulative, and longitudinal change-based approaches, six indices were differentially associated with stroke risk, with TyG-CVAI and TyG-BRI showing stronger and more consistent associations. Each standard deviation increase in baseline TyG-CVAI and TyG-BRI corresponded to hazard ratios (HRs) of 1.36 (95% CI 1.17-1.57) and 1.32 (1.14-1.53). The corresponding cumulative HRs were 1.31 (1.14-1.52) and 1.29 (1.11-1.49). Compared with the stable low-level group, sustained high-level group yielded HRs of 2.28 (1.54-3.39) for TyG-CVAI and 2.01 (1.35-2.99) for TyG-BRI. Stage-specific analyses revealed stronger associations in CKM stage 2. Both indices demonstrated positive linear dose-response relationships. ROC analyses showed that TyG-CVAI and TyG-BRI had relatively better discrimination, and NRI/IDI analyses demonstrated incremental predictive value over the baseline model. CONCLUSION: Among the six novel TyG-obesity indices evaluated, TyG-CVAI and TyG-BRI emerged as stronger predictors of incident stroke in individuals with early-stage CKM syndrome, particularly in stage 2. These findings highlight the potential utility of these two indices for stroke risk stratification and may inform early detection strategies in this vulnerable population.
Predictive value of the triglyceride glucose index-a body shape index (TyG-ABSI) for cardiovascular disease and its comparison with other TyG-related obesity indices: a study based on the China health and retirement longitudinal study (CHARLS) cohort.
Liu X, Yang S, Fu Q … +5 more , Sun Y, Jing S, Liu M, Liu L, Yang X
Cardiovasc Diabetol · 2026 Jun · PMID 42252472 · Full text
BACKGROUND: Insulin resistance (IR) and obesity are recognized as major drivers of cardiovascular disease (CVD). The triglyceride-glucose index-a body shape index (TyG-ABSI), a novel metric integrating lipid metabolism w...
BACKGROUND: Insulin resistance (IR) and obesity are recognized as major drivers of cardiovascular disease (CVD). The triglyceride-glucose index-a body shape index (TyG-ABSI), a novel metric integrating lipid metabolism with body morphology, may enhance risk stratification. Although this index has been verified in Western cohorts, its long-term prognostic value and prospective incremental benefit over conventional indices remain uncharacterized in the Chinese population, who present a distinct East Asian adiposity phenotype. METHODS: Utilizing follow-up data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, we enrolled participants free of CVD at baseline with complete essential information. Cox proportional hazards models were employed to estimate the associations between TyG-ABSI and incident CVD, while restricted cubic splines (RCS) were utilized to characterize dose-response relationships. The discriminative power of TyG-ABSI was evaluated using time-dependent receiver operating characteristic (ROC) curves and C-indices, with comparisons against other related indices, including ABSI, triglyceride-glucose (TyG), TyG-body mass index (TyG-BMI), TyG-Chinese visceral adiposity index (TyG-CVAI), TyG-waist circumference (TyG-WC) and TyG-waist-to-height ratio (TyG-WHtR). Predictive increments were quantified via net reclassification improvement (NRI) and integrated discrimination improvement (IDI), and clinical utility was assessed through decision curve analysis (DCA). Cross-parameter correlation testing was executed to evaluate index collinearity. RESULTS: Among 7197 participants, 1267 incident CVD cases occurred during the follow-up. In the fully adjusted model, baseline TyG-ABSI was independently associated with an increased risk of composite CVD (HR = 1.08, 95% CI 1.01-1.14, P = 0.016) and incident stroke (HR = 1.16, 95% CI 1.05-1.28, P = 0.003), whereas no independent correlation was identified for heart conditions. RCS analysis revealed no significant non-linear association for either CVD (P = 0.855) or stroke (P = 0.728). TyG-ABSI improved prediction over ABSI alone, but it offered no advantage over traditional indices. DCA confirmed that traditional indices had better net benefit than TyG-ABSI or its components. The independent predictive value remained highly consistent across sensitivity analyses. Correlation analysis revealed that while traditional indices exhibited severe multicollinearity clustering (r: 0.751-0.890), ABSI achieved near-perfect orthogonal independence from BMI (r = - 0.056). CONCLUSIONS: TyG-ABSI was significantly and positively associated with an increased risk of incident CVD. Although TyG-ABSI as an isolated screening tool did not surpass traditional parameters like TyG-BMI in overall prospective accuracy, it exhibited only a negligible correlation with BMI, demonstrating that this metric is not redundant. Consequently, TyG-ABSI retains the potential to capture specific pathogenic signals independent of gross body mass. Future risk stratification toolkits should consider transitioning toward an integrated Anthropometric Risk Indicator (ARI) framework that couples the metabolic sensitivity of TyG-BMI with the specific body shape risks indicated by TyG-ABSI.
Combination of GLP-1 receptor agonists and SGLT2 inhibitors in cardiometabolic disease: synergistic, additive, or non-additive effects? A narrative review.
Stamouli E, Trakatelli CM, Sarigianni M … +2 more , Kitsios K, Kotsis V
Cardiovasc Diabetol · 2026 Jun · PMID 42252454 · Full text
BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors) are two novel classes of glucose-lowering agents with proven cardiometabolic benefits bey...
BACKGROUND: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors) are two novel classes of glucose-lowering agents with proven cardiometabolic benefits beyond glycaemic control. Both are now recommended in international guidelines for patients with type 2 diabetes mellitus (T2DM) and high cardiovascular risk. As they operate through complementary mechanisms, their combined use may confer additive or synergistic benefits on cardiometabolic outcomes. AIM: This narrative review examines and summarizes the available evidence on the synergistic effects of GLP-1 RAs and SGLT2 inhibitors in cardiometabolic disease, encompassing their effects on glycaemic control, body weight, blood pressure, cardiovascular events, renal outcomes, and mortality. METHODS: A narrative review of randomised clinical trials, observational studies, post-hoc analyses, and meta-analyses evaluating the combination of GLP-1 RAs and SGLT2 inhibitors in patients with T2DM was conducted. Individual drug class evidence from landmark cardiovascular and renal outcome trials is also reviewed to contextualise the potential for synergy. Evidence from trials conducted in non-diabetic populations with obesity or heart failure with preserved ejection fraction (HFpEF) is also examined where relevant to the combination therapy rationale. RESULTS: The combination of GLP-1 RAs and SGLT2 inhibitors consistently produced greater reductions in HbA1c (- 1.0 to - 1.5%), body weight (- 3 to - 9 kg), and systolic blood pressure (- 4 to - 10 mmHg) compared with either agent alone across multiple randomised trials, including DURATION-8, AWARD-10, SUSTAIN-9, and LIRA-ADD2SGLT2. Observational studies suggest a significant reduction in major adverse cardiovascular events and heart failure hospitalisations with combination therapy versus individual agents taken separately, while both classes also confer cardiovascular and renal benefits in non-diabetic populations at standard doses. However, randomised trial data do not consistently confirm superiority in cardiovascular event rates. Effects on renal outcomes are inconsistent across studies. Combination therapy appears well tolerated, with no significant increase in serious adverse events beyond those expected from each agent individually. CONCLUSIONS: The combination of GLP-1 RAs and SGLT2 inhibitors exerts additive benefits on glycaemic control, body weight, and blood pressure reduction. Evidence for synergistic cardiovascular and renal protection is promising but remains limited, largely derived from observational data and secondary analyses. Larger, dedicated randomised trials are needed to determine whether combination therapy confers superior cardiometabolic outcomes beyond either agent alone.
Associations of cumulative exposure and dynamic trajectories of the combined atherogenic and frailty index with incident cardiometabolic multimorbidity: a longitudinal analysis based on the China Health and Retirement Longitudinal Study (CHARLS).
Feng X, Deng B, Pan Y … +4 more , Liu K, Lei W, Tang X, Xia J
Cardiovasc Diabetol · 2026 Jun · PMID 42251331 · Full text
BACKGROUND AND OBJECTIVE: The atherogenic index of plasma (AIP) reflects atherogenic dyslipidemia and insulin resistance, whereas the frailty index (FI) quantifies cumulative physiological deficits across multiple organ...
BACKGROUND AND OBJECTIVE: The atherogenic index of plasma (AIP) reflects atherogenic dyslipidemia and insulin resistance, whereas the frailty index (FI) quantifies cumulative physiological deficits across multiple organ systems. Although both the AIP and FI are independently associated with cardiometabolic multimorbidity (CMM), the joint impact of the atherogenic index of plasma-frailty index (AIPFI) on the risk of CMM remains unclear. In this study, the associations between baseline levels, cumulative AIPFI and longitudinal changes of AIPFI and the incidence of CMM were evaluated. METHODS: Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). A total of 7995 participants were included in the baseline analysis, and 4,483 participants with repeated biomarker measurements in 2012 and 2015 were included in the longitudinal analysis. AIPFI was calculated via the following formula: AIPFI = AIP × FI. Multivariate Cox proportional hazards models and restricted cubic splines were applied to evaluate the associations of AIPFI with the incidence of CMM. K-means clustering characterized longitudinal AIPFI patterns. The clinical prediction model was performed in both the training and validation cohorts, as validated by receiver operating characteristic curve analysis, calibration curve analysis, and decision curve analysis. The shapley additive explanations (SHAP) method was employed to provide further explanation. RESULTS: A total of 7995 participants were included and followed for a median of 9.0 years, during which 747 (9.3%) incident CMMs occurred. Across quartiles of the AIPFI, the risk of CMM increased progressively, with adjusted HR of 2.46 (95% CI 1.77-3.43) for Q4 compared with those for Q1. In longitudinal analyses (n = 4,483), participants in cluster 2, with persistently high and increasing AIPFI values, presented increased risks of CMM (HR 1.54, 95% CI 1.19-2.01). An elevated cumulative AIPFI was associated with an increased incidence of CMM (HR 1.01, 95% CI 1.01-1.01). The RCS revealed a significant positive nonlinear relationship between the baseline AIPFI and cumulative AIPFI with the risk of CMM (all P < 0.05, and all P for nonlinear values < 0.05). SHAP model analysis revealed hypertension, heart disease, and AIPFI as the most influential predictors. CONCLUSIONS: Both baseline and longitudinal changes in the AIPFI were independently associated with the risk of CMM. The incorporation of longitudinal monitoring of the AIPFI into routine health evaluations may enhance population-level CMM risk prediction and support more effective prevention strategies.
Association of 14 triglyceride-glucose (TyG)-related indices with new-onset cardiovascular disease in middle-aged and older adults: evidence from the CHARLS and ELSA aging cohorts.
Zhu ZL, Hu HF
Cardiovasc Diabetol · 2026 Jun · PMID 42243929 · Full text
BACKGROUND: Cardiovascular disease (CVD) continues to be a predominant contributor to global illness and death rates.Insulin resistance and adiposity are closely linked to cardiometabolic risk, but the comparative value...
BACKGROUND: Cardiovascular disease (CVD) continues to be a predominant contributor to global illness and death rates.Insulin resistance and adiposity are closely linked to cardiometabolic risk, but the comparative value of single-time and cumulative average triglyceride-glucose (TyG)-based indices for predicting new-onset CVD remains uncertain. This study aimed to compare multiple TyG-based indicators, evaluate the contribution of cumulative exposure, and develop a clinically accessible risk-stratification tool. METHODS: This longitudinal cohort study incorporated a total of 5,028 middle-aged and older adult participants, drawn from two major national aging surveys: the China Health and Retirement Longitudinal Study (CHARLS) and the English Longitudinal Study of Ageing (ELSA). Cumulative average TyG-based indicators were constructed using two pre-follow-up measurement waves, with follow-up beginning in 2015 for CHARLS and 2008 for ELSA. Seven single-time TyG-based indicators and seven cumulative average indices were evaluated. Cox regression analysis, restricted cubic splines(RCS), random-effects meta-analysis, subgroup analyses, mediation analyses, and predictive performance assessments were performed. A nomogram and web-based prediction tool were developed for 5-year CVD risk estimation. RESULTS: During a median follow-up of 5.0 years in CHARLS and 13.5 years in ELSA, 1,067 incident CVD events occurred. In the pooled cohort, all 14 TyG-based indicators were significantly associated with incident CVD. Composite indices integrating TyG with obesity-related measures generally showed stronger associations and better predictive performance than the TyG index alone. Cumulative average indices provided only modest improvement over their single-time counterparts, with heterogeneity across cohorts. Restricted cubic spline analyses showed nonlinear associations for TyG-BMI and cumTyG-BMI, whereas other indices showed approximately linear associations. CumTyG-BRI showed relatively robust cross-cohort performance, with an HR of 1.54 (95%CI, 1.27-1.86) for Q4 versus Q1 and low between-cohort heterogeneity (I² = 6.6%). Mediation analysis suggested that hypertension partly mediated the association between CumTyG-BRI and CVD risk, accounting for 20.6% of the total effect. A TyG-BRI-based nomogram showed moderate discrimination, with a C-index of 0.679, and was deployed as an online tool for preliminary 5-year CVD risk estimation. CONCLUSIONS: CumTyG-BRI may be a relatively robust TyG-related indicator for predicting new-onset CVD across cohorts, with low heterogeneity and an approximately linear association. Hypertension may partly mediate this association. The online tool may support preliminary CVD risk stratification, but further validation is needed before routine clinical use.
Systematic comparison of triglyceride-glucose (TYG)-index with other mortality predictive models in obese patients with different mortality rates.
La Sala L, Magnani S, Carlini V … +3 more , Rigoni M, Pontiroli AE, Zanoni I
Cardiovasc Diabetol · 2026 Jun · PMID 42237320 · Full text
BACKGROUND: The Triglyceride-Glucose (TYG)-Index has been increasingly used as a simple surrogate marker of insulin resistance and has been associated with adverse cardiometabolic outcomes in several populations. TYG has...
BACKGROUND: The Triglyceride-Glucose (TYG)-Index has been increasingly used as a simple surrogate marker of insulin resistance and has been associated with adverse cardiometabolic outcomes in several populations. TYG has gained great attention as a predictive index for mortality, but comparisons with other predictive indexes are unexplored, except for TYG-derived indexes such as TYG-body mass index (TYG-BMI). METHODS: We conducted a comparative prognostic study in two independent cohorts of adults with obesity: a general obesity cohort (n = 1,359) and a bariatric surgery cohort (n = 854), both with long-term follow-up approaching 14 years and with different mortality rates (11.5 vs. 5.5%, respectively). We compared TYG index, TYG-BMI index, blood glucose, age, Charlson Index, metabolic syndrome, glucose tolerance, diabetes mellitus, through Cox proportional hazard models with Harrell'C index, and through ROC analysis. We also evaluated the possible incremental predictive value of the above prognostic indexes when combined with blood glucose, the TYG-index, and TYG-BMI index. RESULTS: Across both cohorts, several metabolic and clinical indices were significantly associated with all-cause mortality in univariable analyses. However, age and Charlson Comorbidity Index consistently showed the strongest discrimination and prognostic performance. The various indexes significantly predicted mortality at Cox proportional hazard models (p always < 0.001). Harrell'C index correlated with ROC area under the curves of each index (p < 0.001), and both Harrell and ROC correlated with quality indexes of Cox analysis (LR, p < 0.001) and with quality indexes of linear regression (F, p < 0.001). Findings were directionally consistent in the bariatric surgery cohort, although lower event rates attenuated overall discrimination. The combined use of more indices together was not uniformly useful to increase the predictive value of the above indices. CONCLUSION: In obesity, TyG-based indices are associated with long-term mortality risk but add limited prognostic value beyond age and multimorbidity burden. These markers may be considered complementary tools for metabolic characterization rather than primary instruments for mortality risk stratification. This study reinforces the concept that various mortality indexes are as valid as, or even more predictive than, TYG index.
Effects of adiposity, insulin resistance, and inflammation on cardiometabolic multimorbidity: insights from interaction analyses and metabolic phenotyping in the China health and retirement longitudinal study 2011-2018.
You L, Zhao W, Zheng M … +3 more , Hong X, Ren M, Li W
Cardiovasc Diabetol · 2026 Jun · PMID 42237293 · Full text
BACKGROUND: Cardiometabolic multimorbidity (CMM) burdens aging populations. Obesity drives CMM via insulin resistance and inflammation, but their nonlinear and combined effects remain unclear. We elucidated how these fac...
BACKGROUND: Cardiometabolic multimorbidity (CMM) burdens aging populations. Obesity drives CMM via insulin resistance and inflammation, but their nonlinear and combined effects remain unclear. We elucidated how these factors contribute to CMM incidence. METHODS: From CHARLS 2011 to 2018, 6,510 participants were enrolled. CMM was defined as ≥ 2 of diabetes, heart disease, and stroke. Cox regression, Kaplan-Meier, and Fine-Gray models were used. Restricted cubic splines (RCS) evaluated nonlinear relationships. Multiplicative and additive interactions were assessed, and mediation analysis with 1,000 bootstraps estimated indirect effects. K-means clustering based on eight standardized variables, including age, body mass index (BMI), waist circumference (WC), triglyceride-glucose (TyG), high-sensitivity C-reactive protein (hs-CRP), systolic blood pressure (SBP), high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose (FPG), identified metabolic phenotypes carried high CMM risk. RESULTS: Over 7 years, 212 (3.26%) developed CMM. RCS revealed a J-shaped association between WC and CMM. Optimal cut-offs were 60 years for age, 25.6 kg/m² for BMI, 90.6 cm for WC, 8.7 for the TyG index, 154.3 mg/dL for LDL-C, and 0.86 mg/L for hs-CRP. All six parameters independently predicted CMM. No significant additive interactions were found, but dual elevation markedly increased risk. The TyG index mediated 14.6% of the BMI effect and 10.0% of the WC effect on CMM. Clustering identified insulin-resistant and obese-insulin-resistant phenotypes. CONCLUSION: Optimal cut-offs offer practical screening tools. Dual elevation markedly increases CMM risk and insulin resistance mediates adiposity effects. Clustering identified insulin-resistant and obese-insulin-resistant phenotypes, supporting phenotype-based prevention.
Adolescent obesity and risk of serious chronic morbidity and mortality in young adulthood: a systematic review of cohorts from national registries.
Fliss Isakov N, Balmakov Y, Grinshpan LS … +7 more , Tsur E, Issler N, Blaychfeld Magnazi M, Beer Z, Pinhas-Hamiel O, Twig G, Shina A
Cardiovasc Diabetol · 2026 Jun · PMID 42237280 · Full text
BACKGROUND: The rising prevalence of adolescent obesity necessitates a precise understanding of its corresponding risks for severe chronic morbidity and premature mortality during young adulthood and midlife. METHODS: We...
BACKGROUND: The rising prevalence of adolescent obesity necessitates a precise understanding of its corresponding risks for severe chronic morbidity and premature mortality during young adulthood and midlife. METHODS: We conducted a systematic review of nationwide longitudinal cohort studies, using validated national registries, aimed at assessing the short- and long-term risk of morbidity and mortality associated with adolescent overweight and obesity. RESULTS: We included 38 studies in this systematic review. Adolescent overweight and obesity were associated with severe morbidity and disease related mortality, from young adulthood. Within < 4 years of follow-up and before the age of 25 years, severe adolescent obesity was associated with increased risk of serious morbidity (hazard ratio (HR) = 5.1 among men and HR = 7.3 among women), type 2 diabetes (HR = 27.0 among men, and HR = 45.3 among women), and obesity was associated with type 1 diabetes (HR = 2.0). Before the age of 30 years, adolescent severe obesity was associated with chronic kidney disease (CKD), obesity was associated with colorectal cancer (CRC) and with cardiovascular disease (CVD) mortality. Before the age of 40 years adolescent overweight and obesity were associated with ischemic stroke. Last, before the age of 50 years, adolescent severe obesity was associated with all-cause mortality, obesity was associated with diabetes mortality, and cancer. CONCLUSIONS: Adolescent obesity is strongly and immediately associated with an elevated hazard for severe disease morbidity and mortality beginning in young adulthood, with associations progressing with obesity severity and time. The findings of this study demonstrate the need for public health mitigation and preventive strategies, which may yield substantial short, and long-term health benefits in this population.
Association between C-reactive protein-triglyceride glucose related indices and all-cause and cardiovascular mortality in individuals with cardiovascular-kidney-metabolic syndrome.
Lai W, Zhou Y, Xiao L … +5 more , Zhang T, He W, He J, Gu W, Lin Y
Cardiovasc Diabetol · 2026 Jun · PMID 42237138 · Full text
BACKGROUND: The C-reactive protein-triglyceride glucose index (CTI) has been proposed as a biomarker for insulin resistance and inflammation, which contribute to the development of cardiovascular-kidney-metabolic (CKM) s...
BACKGROUND: The C-reactive protein-triglyceride glucose index (CTI) has been proposed as a biomarker for insulin resistance and inflammation, which contribute to the development of cardiovascular-kidney-metabolic (CKM) syndrome. Waist- circumference-based anthropometric indices have been extensively studied as measures of abdominal obesity, which is strongly associated with mortality risk. This study evaluates the association with mortality of CTI and its combination with several waist circumference based anthropometric indices across stages of CKM. METHODS: A total of 10,941 participants were included from NHANES database. CTI and its derivatives (CTI-waist-to-height ratio [CTI-WHtR], CTI-weight-adjusted waist index [CTI-WWI], and CTI-a body shape index [CTI-ABSI]) were calculated. Study outcomes were all-cause and cardiovascular mortality. Cox regression model and restricted cubic spline (RCS) were used to assess the association between the CTI-related indices and outcomes. Receiver operating characteristic (ROC) analyses were performed to show their predictive ability for outcomes. Subgroup analyses were conducted to verify the robustness. RESULTS: During a median follow-up of 12.83 years, 20.3% of patients (n = 2223) died, including 6.3% (n = 693) from cardiovascular causes. After adjustment, higher CTI-related indices were associated with higher risk of all-cause mortality (CTI: HR = 1.21, 95%CI 1.14-1.28; CTI-WHtR: HR = 1.14, 95%CI 1.08-1.21; CTI-WWI: HR = 1.25, 95%CI 1.18-1.33; CTI-ABSI: HR = 1.29, 95%CI 1.22-1.37) and cardiovascular mortality (CTI: sHR = 1.31, 95%CI 1.18-1.45; CTI-WHtR: sHR = 1.29, 95%CI 1.16-1.42; CTI-WWI: sHR = 1.39, 95%CI 1.25-1.55; CTI-ABSI: sHR = 1.40, 95%CI 1.26-1.55). RCS analysis showed that CTI was nonlinearly associated with both all-cause and cardiovascular mortality, whereas CTI-WWI and CTI-ABSI showed linear associations with both outcomes; CTI-WHtR was nonlinearly associated with all-cause mortality but linearly with cardiovascular mortality. ROC analyses revealed that CTI-ABSI had the highest predictive efficacy for all-cause mortality (AUC = 0.711) and cardiovascular mortality (AUC = 0.690). Notably, subgroup analyses revealed that the association between CTI-related indices and mortality was more pronounced in early CKM stages (stages 0-2) than in advanced stages (stages 3-4). CONCLUSION: Higher CTI-related indices were significantly associated with a higher risk of all-cause and cardiovascular mortality in individuals with CKM syndrome. Among these indices, CTI-ABSI exhibits superior predictive performance, suggesting its potential as practical prognostic biomarkers for CKM patients.
Cardiac remodeling after bariatric surgery associates with systemic metabolic reprogramming: a longitudinal untargeted metabolomics study.
Carmine I, Martina L, Rosaria RM … +11 more , Alessio T, Cristina G, Visco V, Carrizzo A, Masarone M, Persico M, Vincenzo P, Luigi S, Vecchione C, Jacopo T, Michele C
Cardiovasc Diabetol · 2026 Jun · PMID 42231427 · Full text
BACKGROUND: Obesity is a major contributor to adverse cardiac remodeling, particularly concentric left ventricular remodeling (LVCR), which is associated with diastolic dysfunction and increased cardiovascular risk. Bari...
BACKGROUND: Obesity is a major contributor to adverse cardiac remodeling, particularly concentric left ventricular remodeling (LVCR), which is associated with diastolic dysfunction and increased cardiovascular risk. Bariatric surgery reverses many obesity-related comorbidities, including structural myocardial alterations. However, the molecular underpinnings of cardiac recovery, particularly metabolomic correlates, remain poorly understood. OBJECTIVE: This study aimed to characterize longitudinal changes in the serum metabolome of patients undergoing bariatric surgery and to investigate the relationship between these metabolic shifts and the regression of concentric cardiac remodeling. METHODS: A cohort of 127 adults with severe obesity was evaluated at baseline and 4, 12, and 24 weeks post-surgery. Echocardiographic parameters were assessed to define cardiac remodeling. Untargeted GC-MS-based metabolomic profiling was performed on serum samples. Multivariate models (PLS-DA), LASSO regression, and pathway enrichment analyses were employed to identify discriminant metabolites and predictors of remodeling outcomes. RESULTS: Changes in cardiac geometry primarily occurred within the first 12 weeks after the intervention and were mainly driven by reductions in relative wall thickness (RWT). Left ventricular mass index (LVMI) showed only modest, non-significant changes at the cohort level, consistent with the predominantly non-hypertrophic baseline profile. Metabolomic profiling showed time-dependent shifts involving amino acid, fatty acid, and ketone metabolism. Patients who experienced early favorable cardiac remodeling after bariatric surgery demonstrated enriched signatures of mitochondrial substrate flexibility, including short-chain fatty acids, branched-chain amino acid metabolites, and dicarboxylic acids. LASSO regression identified specific sets of metabolites associated with reductions in LVMI and RWT. CONCLUSION: Early geometric cardiac adaptation following bariatric surgery-primarily reflected by reductions in relative wall thickness (RWT), with modest and non-significant changes in LVMI at the cohort level-is associated with coordinated changes in systemic metabolic profiles. These findings suggest potential metabolic correlates of early cardiac adaptation while highlighting substantial interindividual variability. Metabolomic profiling provides insights into individual metabolic trajectories and may inform future strategies for cardiometabolic risk stratification.
Composite C-reactive protein-triglyceride-glucose-adiposity indices and incident cardiovascular disease in the CHARLS cohort: a prospective cohort study.
Wang P, Zheng Z, Wang S … +1 more , Qi J
Cardiovasc Diabetol · 2026 Jun · PMID 42231405 · Full text
BACKGROUND & AIMS: Cardiovascular disease (CVD) is influenced by metabolic dysfunction, chronic inflammation, and adiposity. The C-reactive protein-triglyceride-glucose index (CTI) integrates inflammatory and metabolic i...
BACKGROUND & AIMS: Cardiovascular disease (CVD) is influenced by metabolic dysfunction, chronic inflammation, and adiposity. The C-reactive protein-triglyceride-glucose index (CTI) integrates inflammatory and metabolic information, but the associations of CTI-derived adiposity indices with incident CVD remain insufficiently characterized. We aimed to examine the associations of several CTI-derived adiposity indices with incident CVD and compare their relative performance in a nationwide cohort of middle-aged and older adults. METHODS: We analyzed data from 6,161 participants aged ≥ 45 years without baseline CVD from the China Health and Retirement Longitudinal Study (CHARLS). Four CTI-derived adiposity indices were evaluated: CTI-WHtR, CTI-BMI, CTI-BRI, and CTI-WWI. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for incident CVD. Dose-response relationships were assessed using restricted cubic splines (RCS). Kaplan-Meier, discrimination and reclassification, cumulative exposure, trajectory, subgroup, component-outcome, mediation, and sensitivity analyses were also performed. RESULTS: During a median follow-up of 9 years, 1,503 participants (24.39%) developed CVD. Higher levels of CTI-derived adiposity indices were associated with increased CVD risk. In fully adjusted models, participants in the highest quartile had higher CVD risk than those in the lowest quartile for CTI-WHtR (HR = 1.57, 95% CI 1.24-2.00), CTI-BMI (HR = 1.55, 95% CI 1.23-1.97), CTI-BRI (HR = 1.40, 95% CI 1.11-1.78), and CTI-WWI (HR = 1.37, 95% CI 1.08-1.74), with significant trends across quartiles. RCS analyses showed predominantly linear dose-response relationships. Discrimination was modest, with AUCs ranging from 0.558 for CTI-WWI to 0.573 for CTI-WHtR, compared with 0.522 for CTI. All CTI-derived indices improved continuous net reclassification improvement and integrated discrimination improvement beyond the conventional risk factor model. Higher cumulative exposure and higher trajectory clusters of CTI-derived indices were also associated with increased CVD risk. Mediation analyses suggested interrelationships between metabolic-inflammatory dysregulation and adiposity in relation to CVD. CONCLUSIONS: CTI-derived adiposity indices were associated with incident CVD in middle-aged and older adults, with CTI-WHtR showing the most consistent overall performance among the evaluated indices. These findings support the epidemiological relevance of integrating metabolic-inflammatory burden with adiposity-related phenotypes in cardiovascular risk assessment.
Estimated glucose disposal rate outperforms thirteen other insulin resistance indices in predicting new-onset cardiometabolic multimorbidity: a longitudinal study from the china health and retirement longitudinal study (CHARLS) and cross-sectional replication from the national health and nutrition examination survey (NHANES).
Zhao E, Xie H, Wang R … +2 more , Dong B, Zhang C
Cardiovasc Diabetol · 2026 Jun · PMID 42226282 · Full text
BACKGROUND: The co-occurrence of multiple cardiometabolic conditions has been mechanistically linked to impaired insulin signaling, yet the relative utility of surrogate insulin resistance (IR) markers in stratifying car...
BACKGROUND: The co-occurrence of multiple cardiometabolic conditions has been mechanistically linked to impaired insulin signaling, yet the relative utility of surrogate insulin resistance (IR) markers in stratifying cardiometabolic multimorbidity (CMM) risk has not been systematically established. This study aimed to systematically evaluate and compare the associations of 14 IR indices with CMM incidence in a longitudinal Chinese cohort, with external replication in a U.S. nationally representative sample. METHODS: This study included 8,522 participants from the China Health and Retirement Longitudinal Study (CHARLS) without CMM at baseline (2011). CMM was defined as the concurrent presence of at least two of the following three cardiometabolic conditions: type 2 diabetes, heart disease, and stroke. All 14 IR indices were evaluated both at baseline and as cumulative time-weighted averages derived from repeated measurements in 2011 and 2015. Associations between IR indices and CMM risk were examined using multivariable logistic regression, with dose-response relationships characterized through restricted cubic spline (RCS) modeling. Discriminatory capacity was quantified via receiver operating characteristic (ROC) curve analysis, complemented by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) metrics. To verify the robustness of primary findings, Cox proportional hazards regression and pre-defined subgroup analyses were performed as supplementary sensitivity analyses. External cross-sectional replication was performed in the National Health and Nutrition Examination Survey (NHANES; 1999-2018). RESULTS: During follow-up through 2020, 591 CHARLS participants (6.9%) developed incident CMM. After comprehensive covariate adjustment, each of the 14 surrogate IR indices demonstrated statistically significant and independent associations with incident CMM risk. eGDR and SPISE demonstrated significant inverse associations, indicating that higher values reflect greater insulin sensitivity and lower CMM risk (cumulative eGDR per SD: OR 0.51, 95% CI 0.41-0.65; cumulative SPISE per SD: OR 0.64, 95% CI 0.54-0.75), whereas the remaining 12 indices showed significant positive associations. RCS analyses revealed predominantly linear dose-response relationships across most indices, except for TyHGB and TyG-AIP, which exhibited significant non-linearity. eGDR achieved the highest discriminatory performance at both baseline (AUC: 0.716) and cumulative (AUC: 0.727) assessments, significantly outperforming TyG (all P < 0.001), and yielded the greatest NRI and IDI improvements among all 14 indices. These findings were consistently replicated in the NHANES cross-sectional validation: eGDR and SPISE again demonstrated the strongest inverse associations (eGDR per SD: OR 0.598, 95% CI 0.499-0.717; SPISE per SD: OR 0.704, 95% CI 0.614-0.807), and eGDR achieved the highest AUC (0.756) and the greatest NRI and IDI improvements among all indices. CONCLUSIONS: Across both the Chinese and U.S. study populations, statistically significant and independent associations with CMM were consistently observed for all 14 evaluated IR indices. Among these, eGDR consistently demonstrated the most superior discriminatory performance and risk reclassification capability across longitudinal and cross-sectional settings, single time-point and cumulative assessments, and ethnically distinct populations, supporting its adoption as a preferred, clinically accessible marker for CMM risk stratification. The convergent findings across two large, nationally representative populations of distinct ethnic backgrounds further underscore the cross-population generalizability of eGDR and its potential translational utility in diverse clinical settings.
Unraveling 'F' factor: towards a genetic-clinical framework for the musculoskeletal-heart crosstalk in metabolic aging.
Zhou Y, Huang J, Chen X … +11 more , Xu L, Zhang F, Bai C, Yang J, Fan F, Wang Y, Fang B, Wang T, Li J, Mu X, Li J
Cardiovasc Diabetol · 2026 Jun · PMID 42226250 · Full text
BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain po...
BACKGROUND: The rising co-occurrence of cardiometabolic diseases and musculoskeletal degeneration poses a critical challenge to healthy aging, yet the shared biological mechanisms underlying this multimorbidity remain poorly defined. This study aimed to establish an integrative clinical-genetic framework to elucidate the common frailty factor, the 'F' factor, that captures the systemic vulnerability linking cardiometabolic multimorbidity (CMM) and musculoskeletal aging. METHODS: Utilizing the prospective China Health and Retirement Longitudinal Study (CHARLS) cohort, we developed and validated novel Frailty-Integrated Indices for CMM risk prediction, evaluated with machine learning models interpreted via SHapley Additive exPlanations (SHAP). Independently, we applied genomic structural equation modeling (Genomic-SEM) to integrate genome-wide association data from six traits-coronary artery disease, type 2 diabetes, hypertension, bone mineral density, frailty, and telomere length-to model a shared latent genetic factor ('F' factor). This was followed by multivariate GWAS, fine-mapping, transcriptome-wide association study (TWAS), gene-based analysis, and functional annotation to prioritize causal genes, pathways, and cell types. RESULTS: Clinically, several Frailty-Integrated Indices significantly improved CMM risk prediction, with the optimal model achieving an AUC of 0.727. Genetically, we modeled a significant shared latent genetic factor ('F' factor), pinpointing novel risk loci and implicating key genes such as APOE and SLC22A3. These genes were enriched in pathways including cellular senescence and cholesterol metabolism and showed specific expression patterns in developmental brain stages and across multi-organ endothelial cells. CONCLUSION: Our findings provide converging evidence for Musculoskeletal‑Heart crosstalk of metabolic aging and inferred the 'F' factor as a genetic correlate of a transdiagnostic state, which links genetic predisposition to metabolic dysregulation, and systemic functional decline. This work provides a multi-level biological characterization of multimorbidity liability, informing early-risk detection and preventive strategies for complex aging-related comorbidities.
Associations of the atherogenic index of plasma and its modified indices with the incidence and progression of cardiovascular-liver-metabolic multimorbidity: a prospective cohort study from UK Biobank.
He Q, Sun M, Yao J … +2 more , Wang Y, Shen Y
Cardiovasc Diabetol · 2026 May · PMID 42219489 · Full text
BACKGROUND: The atherogenic index of plasma (AIP) and its modified indices integrate atherogenic dyslipidaemia with overall or central adiposity and have been associated with cardiovascular-liver-metabolic (CLM) diseases...
BACKGROUND: The atherogenic index of plasma (AIP) and its modified indices integrate atherogenic dyslipidaemia with overall or central adiposity and have been associated with cardiovascular-liver-metabolic (CLM) diseases. However, their associations with cardiovascular-liver-metabolic multimorbidity (CLMM) remain unclear. This study examined the relationships of AIP and its modified indices with the incidence and progression of CLMM and further explored whether selected biomarkers explained part of these associations. METHODS: A total of 370,258 participants without baseline CLM diseases were included in this prospective cohort analysis. AIP and its seven modified indices were evaluated: AIP, AIP-BMI, AIP-WC, AIP-WHtR, AIP-ABSI, AIP-WWI, AIP-BRI, and AIP-VAI. Multivariable Cox models were applied to evaluate associations between these indices and both the incidence and progression of CLMM. Exploratory mediation analyses were further conducted to estimate the contributions of inflammatory, hepatic, and renal biomarkers. Predictive ability was evaluated using C-index, net reclassification improvement, and integrated discrimination improvement. RESULTS: During the median 16.0-year follow-up, 8646 participants developed CLMM, and each of the eight indices was associated with a higher risk of incident CLMM, with fully adjusted hazard ratios per standard deviation (SD) increase ranging from 1.18 for AIP-VAI to 1.68 for AIP and AIP-BMI. Consistent associations were also observed for CLMM progression, particularly for AIP-BMI, AIP-WC, and AIP-WHtR. Per 1-SD increase in each index, the risks of transition from a healthy state to the first CLM disease increased by 38%, 36%, and 37%, the risks of progression from the first disease to CLMM increased by 28%, 26%, and 27%, and the risks of progression from CLMM to triple diseases increased by 20%, 17%, and 18%, respectively. Exploratory mediation analyses indicated that biomarkers of systemic inflammation and impaired liver and kidney function jointly accounted for 28.28 to 45.45% of the observed associations. All indices improved predictive performance, with AIP-BRI and AIP-BMI showing the highest overall performance, followed by AIP-WC and AIP-WHtR. CONCLUSIONS: Higher AIP and its modified indices were independently associated with increased risks of both incident CLMM and its progression. These indices may help improve CLMM risk stratification and early identification of individuals at elevated risk.
Large-scale multi-omics enhance risk prediction for type 2 diabetes.
Xie R, Herder C, Schöttker B
Cardiovasc Diabetol · 2026 May · PMID 42210368 · Full text
BACKGROUND: Polygenic risk scores (PRS), metabolomics, and proteomics have each shown promise in improving type 2 diabetes risk prediction, but their combined utility beyond established clinical models remains unclear. W...
BACKGROUND: Polygenic risk scores (PRS), metabolomics, and proteomics have each shown promise in improving type 2 diabetes risk prediction, but their combined utility beyond established clinical models remains unclear. We aimed to evaluate whether integrating multi-omics biomarkers enhances 10-year type 2 diabetes risk prediction beyond single-omics extensions and the clinical Cambridge Diabetes Risk Score (CDRS), which includes HbA measurements. METHODS: We analysed data from 42,840 UK Biobank participants without diagnosed diabetes at baseline. The study population was split into a derivation set (Phase 1 metabolomics release, N = 23,108) to fit models and an independent validation set (Phase 2 release, N = 19,732) to evaluate performance. Data for a PRS for type 2 diabetes, 11 metabolites, and 15 proteins were added to the CDRS to develop multi-omics prediction models. Model performance was evaluated using Harrell's C-index and the net reclassification index (NRI). RESULTS: During 10 years of follow-up, 1090 participants developed incident type 2 diabetes. Among individual omics layers, proteomics contributed the greatest improvement in predictive performance, increasing the C-index from 0.862 (clinical CDRS) to 0.884 (ΔC-index; + 0.022; P < 0.001), with a continuous NRI of 42.0%. The full multi-omics model further significantly increased the C-index compared to a model combining the clinical CDRS with proteomics data (C-index, 0.891; ΔC-index; + 0.007; P < 0.001). CONCLUSION: Integrating proteomics, metabolomics, and a diabetes-PRS into a clinical model substantially improves type 2 diabetes risk prediction beyond single-omics extensions. Several of the selected proteins and metabolites are on cardiovascular disease pathways, highlighting the link between diabetes and cardiovascular risk. However, the C-index difference between the proteomics extended and full multi-omics extended models is small, and the clinical models extended with proteomics data would be easier to translate into routine care because it needs only the measurement of 15 proteins. External validation and cost-effectiveness analyses are needed to support clinical adoption.
Incidence, risk factors and sequelae of long/post-COVID in people with diabetes compared to people without diabetes in Germany (longcovid-diab): a study protocol.
Kvitkina T, Narres M, Andrich S … +3 more , Wilm S, Icks A, Claessen H
Cardiovasc Diabetol · 2026 May · PMID 42210276 · Full text
BACKGROUND: Several studies have shown that people with diabetes are at higher risk of experiencing a severe course of COVID-19 infection. However, it remains unclear whether diabetes per se is a risk factor for the deve...
BACKGROUND: Several studies have shown that people with diabetes are at higher risk of experiencing a severe course of COVID-19 infection. However, it remains unclear whether diabetes per se is a risk factor for the development of Long/Post-COVID. In addition, there is a lack of nationwide, population-based studies on the epidemiology of Long/Post-COVID in people with diabetes. The aim of this project is to analyze: (1) incidence and time trends of Long/Post-COVID in people with and without diabetes between 2021 and 2023 in Germany as well as potential risk factors; (2) mortality, any hospitalization and hospitalization due to acute myocardial infarction, stroke, amputation and diabetic foot syndrome (DFS) after a Long/Post-COVID diagnosis, including an analysis of potential risk factors. METHODS: This study is planned as a non-interventional longitudinal observational study based on statutory health insurance (SHI) data in Germany. The data holder is the Health Data Lab (HDL: data pool of billing data for all persons with statutory health insurance). The incidence rates of Long/Post-COVID will be estimated separately in the populations with and without diabetes and compared as corresponding relative risk. Moreover, we will analyse age- and sex-standardized mortality and hospitalization rates within 12, 24, and 36 months after a Long/Post-COVID diagnosis in the years 2021 to 2024. Potential uncertainties in diagnosing Long/Post-COVID (e.g., underreporting) will be addressed in sensitivity analyses. DISCUSSION: The expected results will have high potential for use in epidemiological research on Long/Post-COVID, including the identification of potential risk factors in people with diabetes. The findings will serve to provide optimized healthcare for Long/Post-COVID patients with diabetes. Trial registration The study has been registered in the German Clinical Trials Register with identifier DRKS00036279. Registration Date 15.05.2025.
Changes in cardiac myosin acetylation disrupt the super-relaxed state in genotype-negative hypertrophic cardiomyopathy with type 2 diabetes.
Nollet EE, Chaami C, Bogdanovic Keleman H … +15 more , Gerlach Melhedegaard E, Lewis CTA, Seaborne RAE, Visch JE, Schoonvelde SAC, Feng M, Wang Q, Hessel AL, Kuehn MN, Schomakers BV, van Weeghel M, Michels M, Kuster DWD, van der Velden J, Ochala J
Cardiovasc Diabetol · 2026 May · PMID 42192426 · Full text
BACKGROUND: Patients with hypertrophic cardiomyopathy (HCM) and type 2 diabetes (T2D) have a more severe cardiac phenotype and worse clinical course than non‑diabetic patients. To identify how T2D aggravates the disease...
BACKGROUND: Patients with hypertrophic cardiomyopathy (HCM) and type 2 diabetes (T2D) have a more severe cardiac phenotype and worse clinical course than non‑diabetic patients. To identify how T2D aggravates the disease and whether the most abundant cardiac protein, myosin, is involved, we combined functional, structural and mass spectrometry analyses of human samples. METHODS: Left ventricular septal myectomy samples from genotype‑negative (G-) HCM patients without T2D (G- , N = 19) and with T2D (G-T2D, N = 15) were analyzed mainly using fluorescent ATP chase experiments, small‑angle X‑ray diffraction and targeted myosin heavy chain proteomics. RESULTS: Mant‑ATP chase measurements showed a lower fraction of myosin heads in the energy‑conserving super‑relaxed (SRX) state in G-T2D compared to non-diabetic myocardium. In parallel, X‑ray diffraction showed trends toward structural alterations in myosin organization in G-T2D tissue, consistent with altered OFF/ON state equilibrium. Targeted mass spectrometry identified hyperacetylation of several myosin lysine residues in G-T2D, including K847 within the S2 region. All‑atom molecular dynamics simulations indicated that K847 acetylation disrupts stabilizing electrostatic interactions in the interacting‑heads motif, which is associated with the OFF state. CONCLUSIONS: Disruption of myosin super‑relaxation emerges as a central cellular defect in G-T2D HCM myocardium and can be mechanistically linked to site‑specific myosin hyperacetylation at K847, providing a potential therapeutic target for genotype‑negative HCM with T2D.
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