Objective: To compare the predictive performance of the novel Cholesterol, High-Density Lipoprotein, and Glucose (CHG) index for the incident type 2 diabetes mellitus (T2DM) versus the established indices—triglyceride-glucose (TyG), atherogenic index of plasma (AIP), and metabolic score for insulin resistance (METS-IR). Methods: A longitudinal cohort study was performed on 15, 453 participants from the NAGALA cohort (2004–2015) without baseline T2DM. The CHG index was calculated from total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and fasting blood glucose (FBG). Several additional indices were established, including the TyG, AIP, and METS-IR. Cox regression, Kaplan-Meier analysis, restricted cubic spline (RCS) analysis, and time-dependent receiver operating characteristic (ROC) curves were performed to determine the predictive performance, after adjusting for various confounders (e.g., obesity, liver function). Robustness was assessed through sensitivity analyses. Results: During a 6.13-year follow-up, 373 T2DM cases were recorded. In the fully adjusted models, we found that the CHG index had the highest hazard ratio (HR): 6.18 per unit (95% CI: 3.38–11.27), outperforming the TyG index (HR: 1.39), AIP (HR: 1.80), and METS-IR (HR: 1.07). Quartile analysis revealed a dose-response relationship for CHG (Q4 HR: 4.36 vs. Q1, P < 0.001). Further, the RCS analysis revealed a linear association between CHG and T2DM risk ( P for overall trend < 0.001; P for nonlinearity = 0.712). Moreover, the CHG index achieved a satisfactory discriminative accuracy (based on the area under the curve [AUC]: 0.783 vs. TyG: 0.751, AIP: 0.745, METS-IR: 0.780) and its predictive power was consisted over the 12 years (peak AUC: 0.798 at 7 years). Sensitivity analyses for various subgroups (e.g., non-obese, non-fatty liver) confirmed that the obtained results were robust. Conclusions: The CHG index that integrates cholesterol, HDL-C, and glucose metabolism, showed superior predictive performance for the incidence of T2DM. Suggesting that it effectively captures the multifactorial pathophysiology of the disease. It is based on routine biomarkers making it easily applicable in risk stratification, offering a cost-effective tool for early intervention and precise prevention in clinical and public health settings.

Objective: There is no evidence to suggest that an association exists between the remnant cholesterol (RC) to high-density lipoprotein cholesterol (HDL-C) ratio and gestational diabetes mellitus (GDM). In this study, the RC/HDL-C ratio during the first trimester was examined as a potential indicator of the onset of GDM during the second trimester. Methods: This was a secondary analysis of data from a Korea-based prospective cohort study. The study involved 582 women within 14 weeks of pregnancy who were examined between November 2014 and July 2016 at two Korean hospitals. RC was calculated as total cholesterol (TC) minus the sum of low-density lipoprotein cholesterol (LDL-C) and HDL-C. The RC/HDL-C ratio was determined by dividing the RC content by the HDL-C content. The RC/HDL-C ratio and GDM occurrence were investigated utilizing a binary logistic regression model, various sensitivity analyses, and subgroup analyses. Additionally, the RC/HDL-C ratio was evaluated using receiver operating characteristic (ROC) analysis. Results: The average age of the pregnant women was 32.07 ± 3.78 years, and the RC/HDL-C ratio had a median value of 0.39. The prevalence of GDM was 6.01%. There was a positive association between the RC/HDL-C ratio and the incidence of GDM after adjusting for potential confounding variables (odds ratio: 21.78, 95% confidence interval [CI]: 3.55–133.73, P < 0.001). Furthermore, this association was validated by subgroup and sensitivity analyses. The results indicated that the RC/HDL-C ratio was a robust predictor of GDM, with an area under the ROC curve of 0.795 (95% CI: 0.723–0.868). The optimal threshold value was 0.45, with a sensitivity of 71.4% and a specificity of 75.3%. Compared with traditional lipid markers, including LDL-C, HDL-C, triglycerides, TC, and the emerging marker RC, the RC/HDL-C exhibited higher diagnostic efficacy. Conclusion: There is an increased risk of GDM associated with higher levels of the RC/HDL-C ratio between 12 and 14 weeks of gestation, independent of traditional risk factors. The RC/HDL-C ratio is more effective in diagnosing GDM than traditional lipid markers.

Background: Hypertension (HTN) progression is linked to insulin resistance (IR), yet the association between Metabolic Score for Insulin Resistance (METS-IR) and HTN remains underexplored. Methods: This study included 4,051 individuals without a history of HTN from the China Health and Retirement Longitudinal Study (CHARLS). Participants were stratified into four groups according to their baseline METS-IR values. It was the development of incident HTN that was the primary outcome. We used Cox regression to assess this association, conducted subgroup and sensitivity analyses, and evaluated METS-IR’s incremental predictive value over conventional risk factors (age, sex, systolic blood pressure) using C-statistic, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Results: Over the 9-year follow-up, 1,572 participants (38.81%) experienced their first incident of HTN. Participants were categorized into quartiles (Q1-Q4) based on their METS-IR levels. After full adjustment for confounders, the hazard ratio (HR) with a 95% confidence interval (CI) for incident HTN demonstrated a progressive increase across ascending METS-IR quartiles, with Q1 as reference: Q2, 0.99 (0.85–1.15); Q3, 1.17 (1.01–1.36); Q4, 1.31 (1.13–1.52). The restricted cubic spline (RCS) model revealed a linear dose-response relationship between METS-IR and the incidence of HTN ( P for overall trend < 0.001; P for nonlinear = 0.310). Adding METS-IR to a base model (age/sex/systolic blood pressure) improved HTN prediction (C-statistic Δ= + 0.004; NRI = 16.58%, IDI = 0.75%; all P < 0.001). DCA confirmed greater net benefit across risk thresholds. Subgroup and sensitivity analyses consistently supported the primary findings. Conclusion: Elevated METS-IR independently predicts HTN risk in Chinese adults, suggesting METS-IR as a potential indicator.

CVDs arise from the interplay of multiple factors, with genetics and environmental exposures representing key drivers. Accumulating evidence over recent decades has unequivocally established that epigenetic modifications, most prominently DNA methylation, play a pivotal, non-redundant role in the initiation, development, and progression of CVDs. As a critical molecular bridge linking genetic predisposition, environmental insults, and the pathogenesis of CVDs, DNA methylation dynamically mediates crosstalk among these three components, thereby emerging as a core focus for dissecting the underlying pathological mechanisms of CVDs. Thus, this review summarizes the functional roles of DNA methylation in common CVDs, including coronary heart disease (CHD), hypertension, and heart failure (HF). Special emphasis is placed on the regulatory mechanisms of DNA methylation in driving disease pathogenesis, as well as the associated translational potential for preventing CVDs and for clinical management. Moreover, this review delineates the specific pathways through which DNA methylation modulates CVDs onset and progression—providing a novel perspective for in-depth investigation of disease etiologies—and offers a robust theoretical basis for identifying novel therapeutic targets for CVDs. Ultimately, these insights aim to lay a foundation for the optimization and innovation of clinical diagnostic and therapeutic strategies for CVDs.

Hypertension (HTN), a primary driver of cardiovascular disease (CVD) progression, shares etiological links with dyslipidemia. While low-density lipoprotein cholesterol (LDL-C) remains a cornerstone biomarker for CVD risk, emerging evidence implicates remnant cholesterol (RC)-a triglyceride-rich lipoprotein component-in HTN pathogenesis. This study aimed to examine the association between RC (independent of LDL-C) and incident HTN among Chinese adults aged 45 years and older. We analyzed 4,508 normotensive participants from the China Health and Retirement Longitudinal Study (CHARLS). Incident HTN served as the primary endpoint. RC was derived by subtracting directly measured LDL-C from non-high-density lipoprotein cholesterol (non-HDL-C). Adjusted Cox proportional hazards models evaluated the relationship between natural log-transformed RC (ln RC) levels and HTN risk. Discordance analyses categorized participants into RC-LDL-C concordant/discordant groups using percentile differences (> 15 units), median splits, and guideline-based LDL-C thresholds. Subgroup analyses validated the robustness of the results. During a median follow-up of 9 years, 39.88% (n = 1,798) of participants developed incident HTN. RC-LDL-C discordance was observed in 58.23% of the cohort, comprising 37.18% with discordantly low RC and 21.05% with discordantly high RC. After multivariable adjustment, each 1 standard deviation increase in baseline ln RC was associated with a 7% elevated HTN risk (hazard ratio [HR] 1.07, 95% confidence interval [CI] 1.02-1.12). Restricted cubic spline (RCS) analysis revealed a linear dose-response relationship between continuous ln RC levels and HTN risk (P for trend = 0.013; P for nonlinearity = 0.233). Participants in the discordantly high RC group exhibited a 17% higher HTN risk compared with the discordantly low group (HR 1.17, 95% CI 1.04-1.32). Stratification by three LDL-C clinical thresholds and the median value showed that low LDL-C/high RC individuals had higher HTN risk than the low LDL-C/low RC reference group in the fully adjusted model, with statistically significant associations at 113 and 130 mg/dL. Subgroup analyses supported these findings. In normotensive populations, higher RC concentrations were independently linked to incident HTN, irrespective of LDL-C levels. The pathophysiological pathways underlying this RC-HTN association-distinct from LDL-C-mediated mechanisms-and the clinical utility of RC-targeted interventions in primary prevention strategies warrant further investigation.

Epidemiological studies have yielded inconsistent findings regarding the relationship between conventional low-density lipoprotein cholesterol (LDL-C) and stroke, revealing limitations in its utility as a predictive biomarker. Small dense LDL-C (sdLDL-C), a highly atherogenic lipoprotein subclass, may better capture residual cardiovascular risk; however, direct measurement of sdLDL-C is restricted by limited assay standardization, and large prospective evidence for estimated sdLDL-C (esdLDL-C)—a practical surrogate derivable from standard lipid profiles—remains limited. This prospective analysis included 7,503 participants from the China Health and Retirement Longitudinal Study. esdLDL-C was calculated from standard lipid parameters using Sampson’s equation. Three analytical strategies were employed—percentile-based differences (≥ 15 percentile), cohort-derived and guideline-based clinical thresholds, and continuous model-based residual and percentage-threshold analyses—to evaluate the independent association of esdLDL-C with stroke risk relative to conventional LDL-C. The analysis was further extended to incorporate high-sensitivity C-reactive protein (hsCRP) for comprehensive risk stratification. Subgroup and sensitivity analyses validated the strength of the findings. Incremental predictive performance was assessed using C-statistics, integrated discrimination improvement, and net reclassification index (NRI). Over a median follow-up of 9.0 years, during which 860 incident stroke cases occurred, elevated esdLDL-C was modestly but significantly associated with an increase in stroke risk after full adjustment (hazard ratio [HR] per standard deviation increment: 1.26, 95% confidence interval [CI]: 1.05–1.50), with risk estimates exceeding those of other lipid parameters. Discordance analyses—percentile-based (HR: 1.40, 95% CI: 1.14–1.73), clinical threshold-based (HR: 1.46 at LDL-C < 130 mg/dL; HR: 1.06 at LDL-C < 100 mg/dL), and continuous model-based—generally demonstrated elevated stroke risk associated with high esdLDL-C relative to LDL-C, with graded risk observed across 2%–30% discordance (HRs: 1.23–1.40), although the association was not statistically significant at the more stringent LDL-C < 100 mg/dL threshold. Among individuals with optimal LDL-C (< 130 mg/dL) and low hsCRP (< 2 mg/L), high esdLDL-C (≥ 36 mg/dL) remained significantly associated with stroke risk (HR: 1.53, 95% CI: 1.23–1.89). Incorporation of esdLDL-C significantly enhanced risk reclassification (NRI: 0.1503; P < 0.001). esdLDL-C may confer incremental prognostic value for stroke risk beyond conventional LDL-C and hsCRP in Chinese adults. Derivable from routine lipid panels, it represents a practical adjunct marker for population-level risk assessment, pending external validation and head-to-head comparisons with directly measured sdLDL-C and apolipoprotein B.