Complications significantly impact the prognosis and healthcare burden of hospitalized patients, making early identification of high-risk individuals crucial. While nutritional and metabolic status are influencing factors, existing tools struggle to provide an integrated assessment. The Triglyceride-Cholesterol-Body weight Index (TCBI) is a novel indicator that concurrently reflects both nutritional and metabolic status, yet its value in predicting in-hospital complications remains unclear. This observational study leveraged large-scale, multicenter real-world data, enrolling 8,288 eligible hospitalized patients. Demographic information, anthropometric measurements, laboratory results, and clinical outcomes were collected. Due to its skewed distribution, TCBI was analyzed using its natural logarithm-transformed value (TCBI-LN) and categorized into quartiles (Q1-Q4). The primary outcome was the occurrence of complications during hospitalization. Univariate analysis was used to compare inter-group differences. Multivariate logistic regression models were employed to analyze the independent association between TCBI-LN and complication risk. Restricted cubic splines were applied to explore the dose-response relationship. The robustness and generalizability of the association were assessed through subgroup analyses and interaction tests. We further compared five nested logistic regression models incorporating TCBI, its individual components, and existing indices (PNI and TyG) using AUC, NRI, IDI, AIC, and BIC, and performed causal mediation analysis to examine whether complications mediated the associations of TCBI with length of stay (LOS) and hospital cost. Complications occurred in 403 patients (4.9%). Patients with complications had significantly lower TCBI-LN levels compared to those without (6.83 ± 0.71 vs. 7.10 ± 0.83, P < 0.001). Multivariate logistic regression analysis revealed that a higher TCBI-LN remained independently associated with a lower risk of complications even after adjusting for multiple potential confounders, including age, sex, body mass index, disease type, comorbidities, and related prognostic factors (adjusted OR = 0.707, 95% CI: 0.553–0.930, P = 0.012). Restricted cubic spline analysis suggested a linear inverse correlation between TCBI-LN and complication risk. Subgroup analyses indicated that the protective association of TCBI-LN was statistically significant in males, patients aged < 65 years, those with a body mass index < 18.5 or ≥ 24 kg/m², and malnourished patients. No significant interactions were observed across all subgroups (P for interaction > 0.05). A risk stratification cutoff was determined based on the Youden index. The complication rate was significantly higher in the high-risk group (6.3%) compared to the intermediate- (5.1%) and low-risk groups (2.9%). In model comparison, adding TCBI-LN to a clinical model significantly improved AUC, NRI and IDI, and the model combining TCBI-LN with PNI and TyG provided the best overall performance. Mediation analysis indicated that TCBI-LN shortened LOS predominantly through reducing in-hospital complications and partially attenuated its direct cost-increasing effect. In a large-scale cohort study of hospitalized patients, lower TCBI-LN levels were independently associated with a higher risk of in-hospital complications, and this association was generalizable across different patient subgroups. As a composite index easily derived from routine laboratory tests, TCBI may serve as a practical tool for early identification of patients at high risk for in-hospital complications and ultimately improve clinical outcomes. The online version contains supplementary material available at 10.1186/s12944-026-02947-w.
Triglyceride-glucose (TyG) index, a novel surrogate marker for insulin resistance (IR), has shown emerging links to sarcopenia. Yet the comprehensive association between the TyG Index and sarcopenia risk remains inconsistent, especially regarding the role of longitudinal TyG exposure patterns. This study comprehensively examines the relationships of baseline TyG index, cumulative TyG index, and TyG index subgroups (defined by two time-point measurements) with incident sarcopenia in Chinese middle-aged and older adults. We analyzed data from two China Health and Retirement Longitudinal Study (CHARLS) subcohorts: 6033 participants (aged ≥45) for baseline TyG index and sarcopenia; 5256 individuals for cumulative TyG and TyG index subgroup analyses. Sarcopenia was defined as low muscle mass along with either low muscle strength or physical performance. Hierarchical cluster analysis using TyG values measured in 2011 and 2015 was performed to identify distinct longitudinal TyG distribution patterns. Baseline TyG index was analyzed using multivariable-adjusted Cox proportional hazards models, whereas cumulative TyG index and TyG index subgroups were assessed with multivariable logistic regression. Restricted cubic spline (RCS) models were conducted to test for linear and nonlinear shapes of each association RESULTS: The mean age of participants was 57.16 (8.43) years, with 3207 females (51.8%) in the sample. During the 4-year observational period, 566 (9.38%) participants developed sarcopenia. Following adjustments for confounders, both the baseline index and the cumulative TyG index associated with sarcopenia exhibited significant nonlinear L-shapes, with inflection points observed at approximately 9.46 and 35.49, respectively. Three distinct subgroups: persistently low, moderate, and persistently high TyG groups were identified. Compared with the persistently low TyG index group, the moderate and persistently high TyG index groups showed gradually lower odds of sarcopenia, with multivariable-adjusted ORs of 0.526 (95% CI, 0.394-0.701) and 0.273 (95% CI, 0.184-0.406), respectively. Subgroup analyses demonstrated that the associations between TyG indices and sarcopenia were more significant in males, individuals with lower BMI, and rural residents, with specific population variations across different TyG measures. This longitudinal cohort study demonstrates that TyG indices exhibit L-shaped associations with sarcopenia status in Chinese adults aged ≥45 years, with identifiable thresholds. These findings suggest that the TyG index may serve as a biomarker indicative of a potential threshold for muscle health. Validation in multi-ethnic cohorts and mechanistic studies are warranted.
The endocannabinoid system and its extension, the endocannabinoidome (eCBome), are lipid-based signalling systems involved in regulating energy balance and metabolic homoeostasis. The eCBome includes a variety of bioactive lipids derived from fatty acids, such as N-acylethanolamines (NAEs) and 2-monoacyl-glycerols (2‑MAGs), which have been linked to different patterns of adiposity. Dietary intake, particularly fatty acid intake, plays a key role in shaping the circulating eCBome profile. Bariatric surgery and subsequent diet modifications can significantly modulate the eCBome, potentially restoring metabolic balance in individuals with obesity. The aim of the study is to identify longitudinal changes in the circulating profile of eCBome mediators in individuals living with severe obesity, before and after a sleeve gastrectomy, and to relate these changes to metabolic improvements and changes in dietary intake. The cohort includes 33 adults with severe obesity (BMI ≥ 35 kg/m²), awaiting a sleeve gastrectomy. Blood samples, anthropometric measurements, metabolic profile and dietary intakes (assessed via 24 h dietary recalls) were collected before and 4 months after surgery. Circulating eCBome mediators were quantified by liquid-chromatography tandem mass spectrometry in fasting plasma samples. Four months after sleeve gastrectomy, reductions in adiposity (BMI, body fat mass, waist and neck circumferences) and improvements in metabolic parameters (triglycerides, high-density lipoprotein cholesterol levels and fasting insulin) were accompanied by significant changes in the levels of some circulating eCBome mediators. Post-surgery circulating levels of EPEA and DHEA reduced, whereas levels of 2-AG, 2-LG, 2-DPG and 2-DHG increased after adjusting for pre-surgery levels and sex (P < 0.05). Interestingly, the circulating levels of eCBome mediators within each family (i.e., NAEs and 2-MAGs) were more closely intercorrelated after surgery than before. Adiposity measurements and dietary fatty acid intakes, such as arachidonic acid and omega-3 fatty acids, were associated with the circulating eCBome profile only after surgery. Weight loss and metabolic profile improvements induced by sleeve gastrectomy correlate with changes in the circulating eCBome profile. In severe obesity, neither adiposity nor dietary fatty acid intake appear to directly influence the circulating eCBome profile. The contribution of these factors, which had been previously observed in individuals with normal weight to moderate obesity, only becomes evident following weight loss.
Glioma recurrence after surgery remains prevalent, significantly impacting patient survival. Tumor progression is closely linked to metabolic reprogramming, especially abnormalities involving glycolipid metabolism. The triglyceride-glucose (TyG) index accurately indicates insulin resistance (IR) and metabolic disturbances. Although these metabolic indicators are prognostically valuable in various cancers, their role in forecasting glioma recurrence is still insufficiently investigated. The medical records of 302 primary glioma patients who received surgical treatment at Linyi People's Hospital from 2016 to 2024 were retrospectively reviewed. Participants admitted to one ward (n = 236) were randomly assigned to either a training set (n = 141) or an internal validation set (n = 95). Another distinct ward provided patients (n = 66) for an independent internal validation group. In the training cohort, essential glycolipid metabolic parameters were identified via Bootstrap resampling combined with Least Absolute Shrinkage and Selection Operator (LASSO) regression, yielding a stabilized Bootstrap-LASSO Score (BSL-Score). Clinical variables alongside this score were subjected to univariate Cox regression analysis, and variables with statistical significance (P < 0.05) progressed into multivariate Cox regression to pinpoint independent prognostic indicators. Subsequently, these independent indicators were integrated into a nomogram to forecast 1-, 2-, and 3-year postoperative recurrence-free survival (RFS). Model performance was confirmed through concordance index (C-index) evaluation, time-dependent receiver operating characteristic (ROC) analyses, calibration curves, and decision curve analysis (DCA), with Bootstrap correction utilized for the C-index. In the training cohort (n = 141), the nomogram achieved a C-index of 0.747 (95% CI: 0.676-0.818) and area under the curve (AUC) values of 0.832, 0.732, and 0.732 for 1‑, 2‑, and 3‑year RFS, respectively. In internal validation (n = 95), the C-index was 0.703 (95% CI: 0.584-0.807); in independent internal validation (n = 66), it was 0.785 (95% CI: 0.694-0.874). Calibration curves showed good agreement, and decision curve analysis confirmed clinical net benefit. The BSL‑Score, derived from routine metabolic parameters (TyG, triglyceride‑to‑high‑density lipoprotein cholesterol ratio (TG/HDL‑C), and TyG‑body mass index (TyG‑BMI)), was an independent predictor of recurrence (multivariate Cox, P < 0.05). Risk stratification by the median nomogram score significantly distinguished high‑risk from low‑risk patients (log‑rank P < 0.001). The established nomogram effectively integrates preoperative glycolipid metabolic indicators with key clinical factors, accurately stratifying recurrence risk in postoperative glioma patients. It serves as a valuable reference for personalized postoperative monitoring, where risk-adapted surveillance and intervention strategies could optimize patient outcomes.
Cardiometabolic factors may influence migraine biology through metabolic, inflammatory, and vascular mechanisms, but studies examining insulin resistance and dyslipidaemia in migraine have yielded inconsistent results, partly due to heterogeneity in study design, fasting status, and timing of blood sampling relative to migraine attacks. We evaluated insulin-resistance indices and lipid profiles, including derived lipid ratios, in episodic migraine compared with healthy controls under standardised interictal fasting conditions. In this cross-sectional case-control study, 45 adults with episodic migraine and 45 healthy controls aged 18-50 years underwent 12-hour fasting blood sampling during the interictal period. Co-primary endpoints were homeostatic model assessment of insulin resistance (HOMA-IR), total cholesterol to high-density lipoprotein cholesterol ratio (TC/HDL-C ratio), and atherogenic index of plasma (AIP). Multivariable linear regression models were adjusted for age, sex, body mass index, and smoking. After adjustment for age, sex, BMI, and smoking, episodic migraine remained associated with a higher TC/HDL-C ratio (B = 0.956, p < 0.001), higher AIP (B = 0.122, p = 0.008), higher total cholesterol, LDL-C, non-HDL-C, and fasting glucose, and lower HDL-C, whereas no adjusted association was found for HOMA-IR or fasting insulin. In unadjusted analyses, triglycerides were also higher in the migraine group. Monthly migraine days and attack intensity were not associated with the co-primary metabolic indices. Exploratory subgroup analyses showed nominal lipid-related differences by aura status, which did not remain significant after false discovery rate correction. Under standardised interictal fasting conditions, episodic migraine was associated with a more atherogenic lipid profile, including higher TC/HDL-C ratio and AIP. In contrast, fasting surrogate markers of insulin resistance were not associated with episodic migraine after adjustment for selected covariates, although small effects cannot be excluded. Larger longitudinal studies with more detailed metabolic assessment are needed to confirm these findings.
Sphingolipids regulate hepatic lipid homeostasis, cell survival, inflammation, and tissue repair. In the healthy liver, balanced de novo sphingolipid synthesis, salvage pathways, and sphingosine-1-phosphate (S1P)-related signals maintain metabolic flexibility, endothelial integrity, and immune quiescence. Dysregulation of sphingolipid metabolism drives the initiation and progression of chronic liver diseases. In metabolic dysfunction-associated steatohepatitis, the acyl chain length-specific remodeling of dihydroceramides and ceramides, together with increased neutral sphingomyelinase activity, triggers lipotoxic stress, abnormal anabolic signal transduction, and hepatic lobule inflammation. Liver fibrosis involves reprogramming of the hepatic stellate cell S1P receptor signaling from regenerative toward profibrotic pathways. In hepatocellular carcinoma, tumor cells utilize sphingolipid metabolism to promote angiogenesis, evade immune surveillance, and develop therapeutic resistance. Sphingolipid remodeling in viral hepatitis links viral persistence to distinct circulating lipid signatures that correlate with disease severity and prognosis. Importantly, multiple nodes in the sphingolipid network and their downstream effectors are emerging as therapeutic targets. Promising preclinical strategies include liver-targeted small interfering RNA against key biosynthetic enzymes, selective modulation of sphingolipid receptors, and nanoliposomal formulations of bioactive ceramides. To enable clinical translation, innovative approaches are being developed to overcome key challenges in delivery, specificity, and safety. Overall, this review integrates recent mechanistic insights, emphasizing that sphingolipids act as central regulators of liver pathophysiology and are also important biomarkers and therapeutic targets in chronic liver diseases.
Dyslipidemia, impaired glucose metabolism, and obesity are established cardiovascular disease (CVD) risk factors. Composite markers like the triglyceride-glucose (TyG) index reflect lipid quantity but overlook qualitative features such as small dense low-density lipoprotein cholesterol (sdLDL-C), a highly atherogenic subfraction linked to dysglycemia. This study aimed to develop a novel sdLDL-C-glucose (sdLG) index, combine it with obesity indicators to enhance CVD risk stratification, and evaluate its predictive value for incident CVD. Adults aged ≥ 45 years without baseline CVD from the China Health and Retirement Longitudinal Study (CHARLS) were included (2011-2020). CVD (heart disease and stroke) events were identified during follow-up. The sdLG index, calculated from sdLDL-C and fasting glucose, was integrated with obesity indicators to form derived indices. The predictive performance of the indices was compared using time-dependent area under the receiver operating characteristic curve (AUC), Concordance index (C-index), and net reclassification improvement/integrated discrimination improvement (NRI/IDI) to select the optimal index. Dose-response relationships were examined via restricted cubic splines (RCS). Associations of the optimal index (baseline, cumulative exposure, and trajectory patterns) with incident CVD were evaluated using Cox proportional hazards models, supplemented by subgroup and sensitivity analyses. Among 3,969 participants, 1,029 incident CVD events occurred. The sdLG index outperformed TyG index in long-term discrimination. Among derived indices, sdLG index combined with the Chinese visceral adiposity index (sdLG-cVAI) showed the best discrimination and reclassification performance. Dose-response relationships for baseline (P for overall < 0.001; P for nonlinearity = 0.105) and cumulative sdLG-cVAI (cusdLG-cVAI) (P for overall < 0.001; P for nonlinearity = 0.522) were linear. In fully adjusted models, the highest vs. lowest quartile was associated with increased CVD risk for both baseline sdLG-cVAI (HR 1.77, 95% CI 1.44-2.16, P < 0.001) and cumulative sdLG-cVAI (HR 1.87, 95% CI 1.53-2.29, P < 0.001). Participants in the persistently high trajectory cluster faced higher risk than those in the stable low cluster (HR 1.75, 95% CI 1.46-2.10, P < 0.001). Subgroup analyses revealed some heterogeneity. Sensitivity analyses yielded results consistent with the main regression analyses. The sdLG index outperforms the traditional TyG index for long-term CVD risk prediction. The novel composite sdLG-cVAI independently predicts incident CVD and improves risk stratification in middle-aged and older adults.
Cardiovascular-kidney-metabolic (CKM) syndrome integrates metabolic, renal, and cardiovascular dysregulation into a unified construct. Current CKM staging systems rely on categorical thresholds that can obscure within-stage heterogeneity, leading to misclassification due to population-specific cut-offs. This study aimed to develop and validate a continuous CKM severity score (cCKMS-S) to mitigate these limitations of categorical staging as a continuous adjunct severity index. Using data from 7,343 adults aged 20-80 years in phase III (2005-2008) of Tehran Lipid and Glucose Study (TLGS), confirmatory factor analysis (CFA) was applied to derive age- and sex-specific latent CKM constructs. Temporal validation was performed in TLGS VI, and independent external validation in National Health and Nutrition Examination Survey (NHANES) 1999-2018. Within-stage heterogeneity was assessed by stratifying Stage 2 into tertiles. Discrimination was evaluated using receiver operating characteristic (ROC) curves and mortality associations using Cox models. In temporal external validation, area under the curves (AUCs) for stage classification were ≥ 0.83 for identifying CKM stage ≥ 2 and ≥ 0.90 for stage ≥ 3, across population subgroups. Similar discriminative performance was observed in NHANES (AUC 0.90 for stage ≥ 2 and 0.84 for stage ≥ 3). Each 1-SD increase in cCKMS-S was associated with a higher risk of all-cause (HR = 3.2;95%CI:2.7-3.9) and cardiovascular (CVD) mortality (HR = 4.7;95%CI:3.6-6.2). In NHANES, cCKMS-S also demonstrated consistent associations with mortality outcomes, with each 1-SD increase associated with a higher risk of all-cause (HR = 1.2;95%CI:1.2-1.3) and CVD mortality (HR = 1.4;95%CI:1.3-1.5), with adjusted C-indices for all-cause and CVD mortality (0.83 and 0.86, respectively) comparable to those observed in the TLGS cohort. Within Stage 2, cCKMS-S identified a marked gradient in all-cause mortality risk across tertiles (HR = 2.16, 3.33, and 9.43). Time-dependent ROC analysis for all-cause mortality in TLGS showed AUCs of 0.71 and 0.77 for cCKMS-S versus 0.66 and 0.69 for CKM staging at 10 and 18 years, improving to 0.85 and 0.84 after adjustment. cCKMS-S introduces a continuous severity score that complements CKM staging by capturing within-stage heterogeneity and demonstrating generalizability across populations. It provides a practical tool for longitudinal monitoring and assessment of intervention efficacy, and preventive risk stratification in clinical practice. The developed online calculator of cCKMS-S is available at safdar-masoumi.github.io/ckm-calc.
In clinical practice, integrating biochemical markers with anthropometric parameters has become a prevalent approach to optimizing disease forecasting. While the cholesterol-high-density lipoprotein-glucose index (CHG) has emerged as a novel metric for quantifying metabolic stress, its prognostic utility for stroke risk-especially when synergized with obesity-related measures-remains to be fully elucidated. This research systematically evaluates the predictive efficacy of CHG-based obesity indices for stroke, utilizing the traditional triglyceride-glucose (TyG) index as a benchmark for comparison. Data for this prospective investigation were derived from the China Health and Retirement Longitudinal Study (CHARLS), encompassing 7,905 individuals aged 45 years who were stroke-free at study inception. A set of seven composite indicators-integrating the CHG index with various obesity metrics (specifically CHG-BMI, CHG-WC, CHG-WHtR, CHG-WWI, CHG-BRI, CHG-ABSI, and CHG-CVAI)-underwent rigorous evaluation.. The discriminative power was quantified via the area under the receiver operating characteristic curve (AUC) and net reclassification improvement. Statistical associations with incident stroke were modeled using multivariate logistic regression, longitudinal trajectory clustering, and restricted cubic splines. During follow-up, stroke was reported in 739/7905 (9.3%) participants. Among all CHG-derived indices, CHG-CVAI and CHG-WC demonstrated the best stroke prediction with an identical AUC value of 0.664 and outperformed TyG-related indices. After full adjustment for confounders, stroke risk for subjects in the highest quartile (Q4) of CHG-CVAI and CHG-WC was 2.44 times (OR = 2.44, 95% CI: 1.66-3.60) and 2.06 times (OR = 2.06, 95% CI: 1.43-2.95) higher compared to those in the Q1 quartile, respectively. Longitudinal analysis demonstrated that stroke risk significantly increased among individuals with high cumulative exposure levels or sustained high levels over time. In the middle-aged and older Chinese population, CHG-CVAI and CHG-WC are significantly and linearly associated with an elevated risk of incident stroke. The predictive accuracy of these markers surpasses that of TyG and its related indicators. Given these findings, routine surveillance of CHG-CVAI or CHG-WC levels is recommended to facilitate the early screening of susceptible individuals, enabling more effective targeted prevention strategies in healthcare and community settings.
Dyslipidemia (DLP) is linked to adverse abdominal fat distribution; however, its relationship with bone mineral density (BMD) and muscle fat infiltration (MFI) remains unclear. This study aimed to assess, using quantitative computed tomography (QCT), whether DLP is associated with abdominal fat depots, and if it independently correlates with BMD or MFI. This cross-sectional study included participants aged ≥ 40 years from a health check-up cohort. Demographic data and fasting blood lipid measurements were collected for analysis. QCT imaging at the L2 vertebral level was employed to assess lumbar BMD at L1-L2, subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), liver fat fraction (LFF), and paravertebral extensor muscle fat fraction (MFF). Participants were categorized into DLP and non-DLP groups based on lipid profiles or the use of lipid-lowering medication. Sex-specific analyses were conducted in both male and female participants, with adjustment for age, body mass index (BMI), and waist circumference (WC); menstrual status was additionally included as a covariate in analyses of female participants. The study included 2,115 participants: 1,426 males (53.3 ± 2.9 years; 48.7% DLP) and 689 females (48.9 ± 2.5 years; 29.0% DLP). Participants in the DLP group were younger on average (males: 52.6 ± 2.4 vs. 53.9 ± 3.1 years; females: 47.8 ± 1.9 vs. 49.4 ± 2.6 years), and had higher weight, BMI, and WC. However, increases in weight and WC were statistically significant only in males. The proportion of postmenopausal women was higher in the non-DLP group (32.5%). Age was the main factor influencing BMD, MFF, and VAT area in males, and BMD and LFF in females. Unadjusted comparisons revealed higher MFF in males and greater BMD, LFF, and SAT areas in females with DLP. After adjusting for confounders, especially age, differences in BMD and MFF were no longer significant in either sex. In fully adjusted models, no significant differences in body composition parameters were observed in males. In females, however, the DLP group had significantly higher LFF (P < 0.001), SAT (P = 0.012), and VAT areas (P = 0.022). This study confirms a sex-specific association between DLP and abdominal fat depots, with females showing higher liver fat and larger subcutaneous and visceral adipose areas. Critically, it demonstrates that DLP is not independently associated with BMD or MFI, as these parameters were primarily influenced by age. This dissociation underscores distinct pathophysiological pathways connecting DLP to different body composition compartments. The online version contains supplementary material available at 10.1186/s12944-026-02899-1.
While the Lipid Accumulation Product (LAP) and Visceral Adiposity Index (VAI) offer improved assessment of visceral fat distribution compared to traditional measures, their connection with rheumatoid arthritis (RA) has not been thoroughly explored. This research aimed to assess the links between LAP, VAI, and RA occurrence using nationally representative datasets. This cross-sectional study analyzed information from the National Health and Nutrition Examination Survey (NHANES) covering the years 1999-2018. RA status was determined based on self-reported physician diagnosis. Sex-specific formulas were employed to calculate LAP and VAI. Statistical techniques included weighted multivariable logistic regression with three progressive models, restricted cubic spline (RCS) analysis, piecewise linear regression, and subgroup analyses. The study comprised 15,918 individuals, including 1,988 RA cases and 13,930 non-RA controls. RA patients demonstrated distinct demographic and clinical profiles compared to non-RA participants, exhibiting older age, greater female representation, reduced educational attainment (P = 0.03), and elevated frequencies of smoking, hypertension, and diabetes (all P < 0.001). Both LAP and VAI measurements were markedly elevated in the RA group (P < 0.001). After comprehensive covariate adjustment, LAP maintained a significant association with RA prevalence (OR = 1.002, P < 0.001). Individuals in the highest LAP tertile displayed 41.0% greater RA prevalence (OR = 1.410, P < 0.001), demonstrating a clear dose-response pattern (P for trend < 0.001). RCS analysis identified a significant nonlinear LAP-RA relationship (P for nonlinearity < 0.001), with a threshold effect at LAP = 43.45. Below this value, the association was notably stronger (OR = 1.0028, P < 0.001), whereas above it the relationship plateaued (P = 0.096). In contrast, VAI exhibited no significant association with RA (P for overall = 0.397) or nonlinear pattern (P for nonlinearity = 0.864). Stratified analyses revealed that hypertension status significantly modified the LAP-RA association (P for interaction = 0.040), with hypertensive individuals showing more pronounced effects. Borderline age-related differences were also noted, with stronger associations among younger participants (< 60 years) and in non-Hispanic White and non-Hispanic Black subgroups. This research indicates a potential link between LAP and RA occurrence, possibly highlighting the influence of abdominal fat deposition in RA development. Being an easily obtainable indicator that solely necessitates waist measurement and triglyceride assessment, LAP could function as an efficient preliminary screening method for identifying RA susceptibility in general healthcare environments. Additionally, it might contribute valuable insights for developing preventive approaches targeting metabolic factors in RA management. Not applicable.
Atherosclerosis (AS), the fundamental pathological basis of most cardiovascular diseases, is a chronic and progressive inflammatory disorder characterized by lipid deposition and plaque formation within the arterial wall. Despite significant advances in pharmacological and interventional therapies, the global burden of AS remains substantial, emphasizing the need to identify novel molecular regulators and therapeutic targets. Caveolin-1 (Cav-1), a key scaffolding protein of plasma membrane caveolae, has emerged as a context-dependent modulator of lipid handling and vascular homeostasis in AS. Evidence from experimental and clinical studies indicates that Cav-1 participates in endothelial low-density lipoprotein (LDL) transcytosis and barrier function in endothelial cells (ECs), regulates cholesterol efflux and inflammatory signaling in macrophages (MΦs), and influences phenotypic plasticity in vascular smooth muscle cells (VSMCs). These coordinated actions position Cav-1 at the intersection of lipid metabolism and vascular inflammation. Notably, while global Cav-1 deficiency markedly attenuates atherosclerotic lesion formation in animal models, the cell type-specific and stage-dependent mechanisms underlying these effects remain incompletely understood. Cav-1 activity is further modulated by post-translational modifications (PTMs), particularly tyrosine-14 phosphorylation, which can influence its membrane localization, stability, and protein-protein interactions. In addition, emerging evidence suggests dynamic interplay between Cav-1 and autophagy-related pathways, highlighting its role in maintaining lipid and cellular homeostasis under metabolic stress. In this review, we systematically summarize current evidence regarding Cav-1 and caveolae across vascular cell types, delineate existing controversies and knowledge gaps, and evaluate the translational potential of targeting Cav-1-associated lipid regulatory pathways in AS.
To elucidate the independent and joint effects of plasma Lipoprotein(a) [Lp(a)] concentration and Kringle IV-2 (KIV-2) repeat copy number in genomic DNA on the risk of acute myocardial infarction (AMI) in a Chinese population, to estimate their population attributable risks (PAR), and to explore interactions with metabolic and psychosocial factors, thereby providing evidence for precise cardiovascular prevention and control. Based on the INTERHEART China subgroup case-control study, 4,479 participants from 26 centers in China were included (2,100 first-onset AMI patients, 2,379 age- and sex-matched controls). Risk factors (lifestyle, metabolic indicators, psychosocial factors) were collected using standardized questionnaires. Lp(a) concentration was measured using an isoform-insensitive immunoassay, and KIV-2 repeat copy number in genomic DNA was quantified using quantitative PCR (qPCR) (represented as ΔCT value, lower values indicate fewer repeats). Multivariable logistic regression models were used to analyze risk associations, restricted cubic splines assessed dose-response relationships, PAR was calculated, and interactions were tested. Elevated Lp(a) concentration (highest vs. lowest quintile; OR = 1.784, 95% CI: 1.402–2.270) and fewer KIV-2 repeats (lowest vs. highest quintile; OR = 2.421, 95% CI: 1.905–3.086) were significantly associated with AMI risk. Dose-response analysis revealed that Lp(a) concentration showed a monotonically increasing relationship with AMI risk, while KIV-2 repeats showed a continuous negative association. Both factors remained independent predictors after mutual adjustment, and were moderately negatively correlated (r=-0.323, P < 0.001). The PAR was 10.3% for the highest Lp(a) quintile (> 17.6 mg/dL) and 10.4% for the lowest KIV-2 repeat quintile (ΔCT < 4.1). No significant interactions were found between Lp(a) or KIV-2 and sex, diabetes, smoking, or psychological factors (P-interaction > 0.00625). In the Chinese population, both Lp(a) concentration and KIV-2 repeat copy number in genomic DNA independently predict AMI risk, with PARs exceeding 10% for both. This study reveals for the first time that KIV-2 repeat copy number may have pathophysiological implications independent of Lp(a) concentration regulation, suggesting the need to incorporate this genetic marker into high-risk screening and to adopt a lower Lp(a) risk threshold of > 18 mg/dL (approximately the 80th percentile) for this population. The online version contains supplementary material available at 10.1186/s12944-026-02929-y.
The Mediterranean diet is widely recognized for its cardiovascular benefits, but its specific effects on atherogenic indices remain unclear, particularly in individuals seeking a weight-loss dietary program, where excess fat mass may mitigate the diet's protective effects. To explore this relationship, a cross-sectional study was conducted involving 10,286 participants enrolled in a weight-loss dietary program. Anthropometric and biochemical data were collected, and adherence to the Mediterranean diet was assessed using the 14-item Mediterranean Diet Adherence Screener questionnaire. Lipid profiles, including total cholesterol, LDL-C, HDL-C, and triglycerides, were analyzed to calculate the following atherogenic indices: atherogenic index of plasma, Castelli risk indices I and II, lipoprotein combine index, atherogenic coefficient, and atherogenic combined index. Multivariate linear regression models, adjusted for sex, age, body mass index, smoking, physical activity, sociodemographic factors, and use of lipid-lowering medications, showed that each one-point increase in the Mediterranean diet adherence score was significantly associated with reductions in the atherogenic index of plasma (- 0.003, 95%CI: 0.006, - 0.000), the atherogenic coefficient (- 0.013, 95%CI: - 0.024, - 0.001), Castelli risk index I (- 0.013, 95%CI: - 0.024, - 0.001), and the atherogenic combined index (- 0.004, 95%CI: - 0.007, - 0.000), with a marginal association observed for Castelli risk index II (- 0.009, 95%CI: - 0.019, 0.000). Significant associations were also observed for total cholesterol (- 3.453 mg/dl, 95%CI: -5.911, -0.995), LDL (- 3.225 mg/dl, 95%CI: -5.402, -1.048), and HDL-C concentrations (+ 0.255 mg/dl, 95%CI: 0.098, 0.412). However, except for HDL, these associations lost statistical significance after adjusting for body fat percentage. Significant interactions between Mediterranean diet adherence score and body fat percentage were observed for several atherogenic indices, including the atherogenic coefficient, Castelli risk index I, Castelli risk index II, and the atherogenic combined index as well as for total cholesterol and LDL, suggesting that the protective effects of the Mediterranean diet diminish as fat mass increases. Although adherence to the Mediterranean diet is associated with more favorable lipid profiles and atherogenic indices, these benefits are modulated by body composition, particularly fat mass. These findings highlight the importance of integrated dietary strategies that combine nutritional quality with body fat reduction to support cardiovascular prevention.
Residual atherosclerotic cardiovascular disease (ASCVD) risk often remains even after low-density lipoprotein cholesterol (LDL-C) levels have been brought down to target levels. Remnant cholesterol (RC) and inflammation have been increasingly linked to the residual risk. We aimed to investigating whether the discriminative value of RC the ability of RC to discriminate and its claimed interactions with LDL-C are due to a real clinical phenotype or are affected by formula-dependent biases between the Friedewald and Sampson-NIH equations. We performed a cross-sectional analysis of consecutively tested adults (n = 3,342) using residual serum samples from routine clinical monitoring. To reduce analytical variability, all lipid profiles were analyzed using a single, dedicated reagent lot. We contrasted risk models with Friedewald-calculated versus Sampson-NIH-calculated LDL-C to assess equation-dependent differences. Lipid parameters, hemoglobin A1c (HbA1c), estimated glomerular filtration rate (eGFR), and C-reactive protein (CRP) were measured. ASCVD was defined using International Classification of Diseases, 10th Edition (ICD-10) codes. Missing covariate data were handled using multiple imputation by chained equations (m = 50), with additional complete-case sensitivity analyses for CRP-related models. To reduce bias, the observed ASCVD status was included as an auxiliary variable; the outcome itself was not imputed. The discriminative performance of nested logistic regression models was assessed through the pooled area under the receiver operating characteristic curve (AUC) and pooled DeLong p-values. The primary clinical focus was the presence of documented pre-existing ASCVD diagnoses, identified in 11.4% of the cohort, while 9.4% of participants met the criteria for atherogenic dyslipidemia (AD). In the primary analysis with Friedewald LDL-C, we detected a statistically significant (p < 0.001) negative interaction between LDL-C and RC, while logCRP remained an independent correlate in the adjusted model. Interestingly, when we verified this using the more accurate Sampson-NIH equation to minimize the possibility that the result would be solely due to calculation bias, the paradoxical interaction was still statistically significant (p = 0.003) along with a strong model performance (AUC: 0.729). This indicates that the interaction is not entirely explained by the mathematical artifact of the Friedewald formula, but rather represents a consistent statistical pattern in this cohort. RC adds statistically significant value to risk discrimination. The continuous inverse relationship of LDL-C with high RC identifies a statistical pattern consistent with persistent atherogenic burden despite apparently optimal calculated LDL-C levels. Awareness of this potential suppressor effect may aid in refining risk stratification in tertiary-care settings.
Whether long-term trajectories of central adiposity indices predict cardiometabolic diseases better than BMI remains uncertain. We compared trajectories of central adiposity indices and BMI in relation to cardiometabolic outcomes and estimated potential population benefits from trajectory improvement. Among 4,295 adults from the China Health and Retirement Longitudinal Study, group-based trajectory modeling identified three trajectories for each obesity index. BMI, waist circumference (WC), waist-to-height ratio (WHtR), and body roundness index (BRI) showed Low-stable, Moderate-stable, and High-stable patterns, whereas the high ABSI (a body shape index) group followed a High-to-low pattern. Cox models examined associations with incident diabetes, heart disease, stroke, and cardiometabolic multimorbidity (CMM) between 2015 and 2020. Δβ bootstrap tests compared association strength across indices, and two one-sided tests (TOST) assessed equivalence within ± 10–15%. Population impact fractions (PIFs) estimated preventable events under counterfactual trajectory-shift scenarios. During follow-up, 379 diabetes, 458 heart disease, 252 stroke, and 84 CMM events occurred. Compared with the Low-stable group, the High-stable groups of BMI, WC, WHtR, and BRI were associated with higher risks of all outcomes, with hazard ratios of approximately 2.7–3.5 for diabetes and broadly elevated risks for heart disease, stroke, and CMM, whereas ABSI showed no significant associations. Δβ contrasts indicated that WHtR and BRI had significantly stronger associations with diabetes than BMI and WC, while differences among indices for heart disease and stroke were small and often within TOST equivalence margins. Under the realistic partial-shift scenario, PIFs suggested that improving trajectories could avert about 6% of diabetes cases and 4–7% of CMM events, with smaller but meaningful reductions in heart disease and stroke. Central adiposity indices, particularly WHtR and BRI, demonstrated favorable trajectory-based discrimination for diabetes, whereas differences among anthropometric measures were modest for cardiovascular outcomes. These findings support an outcome-specific and context-sensitive approach to adiposity assessment. The online version contains supplementary material available at 10.1186/s12944-026-02948-9.
The safe intake range for iodine is narrow, and abnormal nutritional status (deficiency or excess) may affect children's lipid metabolism by interfering with thyroid function. Following the widespread implementation of iodized salt in China, urinary iodine levels in children in some regions have exceeded the appropriate range. Nonetheless, the connection between iodine nutritional status and childhood dyslipidemia remains unclear. This study examined the associations between iodine status and lipid profiles among 6-17-year-old children and adolescents residing in regions of China where iodized salt is supplemented. The correlation between urinary iodine concentration (UIC), serum iodine concentration (SIC), and total cholesterol (TC) and triglyceride (TG) was explored using kernel density plots and chi-square tests. The logistic regression model incorporated covariates (age, sex, BMI) to control for potential confounding factors and examined the relationship between UIC, SIC, and lipid profile; meanwhile, stratified analysis and interaction analysis were conducted to test the effect modification of these variables on the aforementioned associations. Restricted cubic splines models based on logistic regression were utilized to examine dose-response relationships involving UIC, SIC and dyslipidemia. The results revealed that hypertriglyceridemia followed a U-shaped pattern across UIC groups, whereas hypercholesterolemia rose steadily with increasing UIC. Both outcomes showed U-shaped associations with SIC. After adjustment, UIC ≥ 300 µg/L was linked with elevated TC [OR 1.455 (1.175-1.802)]. Elevated TG was also more likely when the SIC was < 63.50 µg/L [OR 1.305(1.022,1.665)] or ≥ 82.28 µg/L [1.536(1.204,1.960)]. SIC is in a U-relationship with TG levels, whereas SIC values > 74.66 µg/L appeared to interact synergistically with TG. In conclusion, high urinary iodine is a risk factor for hypercholesterolemia, but this association is modified by BMI. Both low serum iodine and high serum iodine are linked to a higher likelihood of hypertriglyceridemia, exhibiting a non-linear relationship.
Abdominal obesity (AO) significantly contributes to cardiometabolic diseases and poses an increasing public health challenge. Composite lipid-derived indices have been proposed as simple indicators of atherogenic dyslipidemia, but their relative importance for identifying AO at the population level remains incompletely understood. This study aimed to evaluate the link between various atherogenic lipid indices and AO, identifying key lipid-related predictors through interpretable machine learning methods. This cross-sectional study analyzed 5,612 adults from a population-based survey in Guangdong Province, China. Atherogenic lipid indices encompass the atherogenic index of plasma (AIP), non-high-density lipoprotein cholesterol (non-HDL-C), atherogenic coefficient (AC), Castelli risk indices I and II (CRI-I and CRI-II), lipid composite index (LCI), and the triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C). Feature selection was conducted using Boruta and Least Absolute Shrinkage and Selection Operator (LASSO) methods prior to machine learning modeling. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, and F1 score. SHapley Additive exPlanations (SHAP) analysis was applied to quantify feature importance. Individuals with AO were generally older and more likely to exhibit lower education levels, reduced physical activity, cardiometabolic comorbidities, and unfavorable metabolic profiles. Feature selection identified 15 key predictors. Logistic regression demonstrated the most stable performance (training AUC: 0.767; testing AUC: 0.768; accuracy: 0.712; F1 score: 0.667) with good calibration and clinical utility. SHAP analysis consistently identified AIP, sex, CRI-II, uric acid, and diastolic blood pressure as the most influential predictors of AO. Composite lipid indices, particularly AIP and CRI-II, are strongly associated with AO and may serve as practical indicators for identifying individuals at elevated metabolic risk. Because these indices are derived from routinely measured lipid parameters, they may support scalable approaches for metabolic risk screening and monitoring in both clinical and community health settings.
Circadian syndrome (CircS) augments the conventional metabolic syndrome construct by adding disturbed sleep and depressive features. Whether composite metabolic indices that combine insulin-resistance, atherogenic-lipid, and inflammatory signals can forecast CircS prior to its onset has not been systematically investigated. The present work evaluated eight such composite markers in a population-based sample of Chinese adults aged 45 years or older. Drawing on the China Health and Retirement Longitudinal Study (CHARLS), we followed 4,325 CircS-free adults from 2011 through 2015. Eight baseline metabolic composites were analysed through robust-variance modified Poisson regression, four-knot restricted cubic splines, incremental receiver operating characteristic (ROC) metrics, bidirectional mediation under a quasi-Bayesian framework, multiple sensitivity checks, and a head-to-head benchmarking of 10 machine-learning algorithms complemented by SHapley Additive exPlanations (SHAP) interpretation. Over 4 years, 1,025 incident CircS cases (23.7%) accrued. Every index remained independently linked to CircS once multivariable adjustment was applied. The steepest positive gradient belonged to the triglyceride-glucose body mass index (TyG-BMI; extreme-quartile risk ratio [RR] 4.56, 95% CI 3.35-6.21; per-standard-deviation RR 1.87, 95% CI 1.66-2.10), whilst the estimated glucose disposal rate (eGDR) demonstrated the most pronounced inverse gradient (RR 0.28, 95% CI 0.20-0.38). The largest discrimination gain belonged to the cholesterol-HDL-C-glucose (CHG) index (area under the curve [AUC] 0.737; continuous net reclassification improvement 0.379; DeLong P < 0.001). Reverse-path mediation indicated that the CHG index and the metabolic score for insulin resistance (METS-IR) jointly carried part of the high-sensitivity C-reactive protein (hs-CRP)-CircS signal. On the held-out test set, logistic regression reached the top area under the curve (0.746), and the XGBoost SHAP ranking placed eGDR first among predictors. Eight non-traditional metabolic composites anticipated incident CircS, and within this panel eGDR, TyG-BMI, and the CHG index carried the most consistent predictive information. Incorporating such readily obtainable indices into routine assessment could facilitate earlier CircS risk identification in ageing populations.
Early prevention of dyslipidemia is critical for reducing the future onset of atherosclerosis and atherosclerotic cardiovascular diseases. Although lifestyle interventions have been recommended, the interactions between common genetic variants and modifiable habits in young populations remain unclear. Membrane-bound O-acyltransferase domain-containing 7 (MBOAT7) has been implicated in lipid metabolism and steatotic liver disease; however, its role in early atherosclerosis is poorly understood. Associations between the MBOAT7 rs641738 genotype, lifestyle habits, and atherogenic lipid profiles were assessed in young adults and adolescents. This cross-sectional study included 402 university students (200 adolescents and 202 young adults) who underwent health checkups, genotyping, and lifestyle assessments (dietary habits, alcohol intake, and physical activity). Participants were genotyped for MBOAT7 rs641738 (C > T), categorized as CC versus non-CC (CT/TT), and stratified by MBOAT7 genotype and low-density lipoprotein cholesterol (LDL-C)/high-density lipoprotein cholesterol (HDL-C) ratios. Logistic regression was used to identify lifestyle factors related to elevated LDL-C/HDL-C ratios using a threshold of 2.0. Sex-stratified analysis was also performed. Young adults with the CC genotype exhibited significantly higher LDL-C/HDL-C ratios than those with the non-CC genotype, despite similar lifestyle habits; no genotype differences were observed in adolescents. High soft drink consumption (OR, 1.29; 95% CI, 1.08-1.58; P = 0.004) and low alcohol intake (OR, 0.38; 95% CI, 0.15-0.79; P = 0.005) were independently related to LDL-C/HDL-C ≥ 2.0, with stronger effects in males. These associations were not observed in the non‑CC group. Sex differences were evident, with females more sensitive to low alcohol intake. Genetic susceptibility to atherogenic lipid profiles in young adults is linked to the MBOAT7 CC genotype and modifiable habits, particularly soft drink intake, with sex-specific effects. These findings suggest the importance of early genetic screening and personalized lifestyle interventions in preventing dyslipidemia and cardiovascular diseases. However, alcohol consumption has not been recommended as a preventive measure. These findings provide public health insights into early life interventions to reduce the future onset of dyslipidemia and cardiovascular diseases.