👤 Shude Xu

Pancreatic cancer (PC), characterized by the absence of effective biomarkers and therapies, remains highly fatal. Data regarding the correlations between PC risk and individual plasma proteome known for minimally invasive biomarkers are scarce. Here, we analyzed 1,345 human plasma proteins using proteome-wide association studies, identifying 78 proteins significantly associated with PC risk. Of these, four proteins (ROR1, FN1, APOA5, and ABO) showed the most substantial causal link to PC, confirmed through Mendelian randomization and colocalization analyses. Data from two clinical cohorts further demonstrated that FN1 and ABO were notably overexpressed in both blood and tumor samples from PC patients, compared to healthy controls or para-tumor tissues. Additionally, elevated FN1 and ABO levels correlated with shorter median survival in patients. Multiple drugs targeting FN1 or ROR1 are available or in clinical trials. These findings suggest that plasma protein FN1 associated with PC holds potential as both prognostic biomarkers and therapeutic targets. Show less

Mercury (Hg) is a widespread environmental pollutant with known neurotoxic and cardiometabolic effects, and its influence on lipid metabolism during childhood remains insufficiently understood. Mitochondrial dysfunction is proposed as a potential mechanism linking Hg exposure to metabolic disruption. Mitochondrial DNA copy number (mtDNA-CN) is regarded as an indicator of mitochondrial biogenesis and functional capacity, where lower levels generally suggest mitochondrial damage or dysfunction. In contrast, ribosomal DNA (rDNA) and relative telomere length (RTL) reflect genomic stability and cellular aging. This study investigated the associations between blood Hg levels and serum lipid profiles in children and adolescents and assessed the mediating roles of mtDNA-CN, rDNA, and RTL. A cross-sectional study was performed among 352 children and adolescents aged 6–17 years in eastern China. Blood Hg levels were determined using inductively coupled plasma mass spectrometry (ICP-MS), and serum lipid markers, namely total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein(a), were assessed along with the genomic indicators such as mtDNA-CN, rDNA, and RTL. Multivariable linear regression and mediation analyses were conducted. Higher Hg levels were significantly related with increased TC (β = 0.144, Hg exposure in children and adolescents is linked to an atherogenic lipid profile, potentially through mitochondrial dysfunction. MtDNA-CN appears to be a sensitive molecular mediator of Hg-induced lipid disturbances, which highlights the relevance of mitochondrial health in early-life environmental epidemiology and cardiovascular risk prevention. The findings support early prevention strategies and environmentally focused health policies that reduce toxicant exposure and thus promote long-term cardiometabolic health in young populations. Show less

Diabetes mellitus and dyslipidemia are major risk factors for atherosclerosis. Hypoechoic plaques, which indicate vulnerable or unstable plaques, may rupture and lead to ischemic stroke, cognitive impairment, increased adverse cardiac events, and even death. This study aimed to investigate the correlation between plasma lipid levels and the characteristics of atherosclerotic plaques in adult patients with type 2 diabetes mellitus. A retrospective analysis was conducted on adult patients with type 2 mellitus who were hospitalized in the Department of Endocrinology at Affiliated Hospital of Hebei University between January 2017 and December 2021.Patients were categorized into two groups based on arterial ultrasound results. Statistical analyses were performed to compare plasma lipid levels and plaque characteristics across the groups. 1) Statistically significant differences were observed among the two groups in terms of gender, hypertension, age, duration of diabetes mellitus, plaque location, triglycerides (TG),total cholesterol (TC), Apolipoprotein A1 (Apo A1),very-low-density lipoprotein (VLDL), VLDL/apolipoprotein B(ApoB), high-density lipoprotein cholesterol (HDL)/ApoA1 ( In clinical practice, the characteristics of atherosclerotic plaques and lipid profiles should be jointly evaluated to guide targeted treatment and effectively reduce the risk of atherosclerotic cardiovascular disease. Show less

Myocardial infarction (MI) is one of the most serious cardiovascular diseases in the world. Nevertheless, the majority of diagnostic procedures conducted subsequent to the illness do not provide any means to prevent several risks associated with MI. Blood and urine tests are frequently employed in clinical examinations to detect cardiovascular diseases at an early stage. Mendelian randomization (MR) is commonly employed to explore disease-trait relationships and uncover therapeutic targets. Our goal was to explore the genetic links between 35 blood and urine biomarkers and MI. Blood and urine biomarker MR correlations with MI risk were studied. In version R10, the UK Biobank and Finnish databases included blood and urine marker data and MI data (26,060 cases and 343,079 controls). We performed bidirectional 2-sample MR with 4 methods: inverse variance weighted, MR-Egger, weighted median, and weighted mode. Final causal associations were determined by inverse variance weighted. Sensitivity analyses (heterogeneity, pleiotropy) were conducted. MR-PRESSO and PhenoScanner were used to exclude invalid instruments. We used multivariate MR to filter the most important genes without including other positive genes. To identify positive gene pathways and gene networks that cause MI, we employed GeneMANIA for gene prediction. The findings revealed a positive genetic association between the 8 blood and urine biomarker levels and an elevated risk of MI. There are apolipoprotein B (APOB), glycated hemoglobin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, sex hormone-binding globulin, triglycerides, and urate. Moreover, APOB, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol selectively affect MI through the rejection of other positive gene stems. Finally, APOB and numerous genes strongly impact MI development. APOB collaborates with related genes to regulate plasma lipoprotein particle levels, sterol homeostasis, organization, lipid homeostasis, and remodeling in MI. Our research further reveals the causal relationship between MI and blood/urine biomarkers, providing a new perspective for the prevention, diagnosis, and treatment of MI. Blood and urine marker tests can subsequently be conducted based on these results to detect MI and study the underlying mechanisms linking these metabolites to MI. Show less

Cholestasis in primary biliary cholangitis (PBC) induces delta bilirubin and lipoprotein-X (LpX), complicating biochemical interpretation. Comparative wet/dry chemistry analyses, total cholesterol (TC)/apolipoprotein B (Apo B) ratio calculation, and clinical-laboratory integration were utilized. Delta bilirubin (87.4 µmol/L) masked true bilirubin levels, while LpX falsely elevated LDL-cholesterol (LDL-C) (23.98 mmol/L) and induced pseudohyponatremia (Na⁺: 135 → 142 mmol/L). Integrated methodologies and clinician-laboratory collaboration are essential to mitigate diagnostic pitfalls in PBC. Show less

To establish a short-term high-fat/high-cholesterol (HFHC) diet-induced Metabolic dysfunction-associated steatotic liver disease (MASLD) mouse model, and evaluate the effects of rapamycin (RaPa) and chloroquine (CQ) on this model to explore their therapeutic potential and side effects. An early MASLD mouse model was constructed via short-term HFHC diet feeding. Model mice were intraperitoneally injected with RaPa or CQ. Drug effects were analyzed on body weight, liver weight, lipid metabolism-related genes (APOB, FASN, PLIN2), inflammatory factors (IL-6, IL-10), and fibrosis markers (LOX, Col-1α-1, CCL2, TGFβ1, PDGFRβ, α-SMA) at mRNA and protein levels. RaPa ameliorated body weight and liver weight in early MASLD mice, downregulated FASN and PLIN2 expression, upregulated IL-10 mRNA levels, and alleviated hepatic steatosis, but induced metabolic disorders such as Insulin resistance and hyperlipidemia. In contrast, CQ promoted FASN and PLIN2 expression, exacerbated hepatic steatosis, reduced IL-10 mRNA levels, and upregulated fibrosis-related markers (LOX, TGFβ1, PDGFRβ, α-SMA) at both mRNA and protein levels, thereby driving MASLD progression to liver fibrosis. Notably, CQ improved metabolic abnormalities in model mice, including obesity, hyperlipidemia, and Insulin resistance. RaPa and CQ exhibit dual effects on early MASLD: RaPa alleviates hepatic steatosis but exacerbates metabolic disorders, whereas CQ improves metabolic abnormalities but accelerates liver fibrosis. This paradox highlights the need to balance metabolic regulation and liver injury prevention in MASLD treatment, providing critical experimental insights for targeted drug development. Show less

End-stage renal disease (ESRD) is associated with high morbidity and mortality. Identifying patients with stage 4 chronic kidney disease (CKD) at risk of short-term progression to ESRD remains challenging. Accurate prediction can improve advanced care planning and patient outcomes. This study aimed to develop and validate a machine learning (ML) model for predicting progression within 25 weeks (approximately six months) of ESRD in patients with stage 4 CKD. Electronic health records (EHRs) of patients with stage 4 CKD were analyzed. Nine ML models including Ridge regression (Ridge), random forest (RF), and eXtreme Gradient Boosting (XGBoost) were used to predict short-term progression to ESRD within 25 weeks. The models were trained and externally validated using the data of 346 and 105 patients. Of the 451 patients with stage 4 CKD, 219 developed ESRD. Among the evaluated models, XGBoost demonstrated the best overall performance. In the internal validation, it achieved an area under the curve (AUC) of 0.93, an accuracy of 0.90, and an F1 score of 0.89. In the external validation, XGBoost maintained the highest AUC (0.85), accuracy (0.79), and F1 score (0.79), along with the highest average precision (0.89) and a low log-loss (0.48), indicating strong discriminative ability and good generalizability. The top predictive features included high-density lipoprotein cholesterol, Alb, Cys C, ApoB, FGB, Bun, Neutrophil, and Total cholesterol. This study demonstrated the feasibility of ML for assessing ESRD prognosis based on easily accessible clinical features. XGBoost demonstrated superior performance in both internal and external validation, suggesting its potential for future patient screening. Show less

Gout is a chronic inflammatory condition increasingly recognized as a risk factor for cardiovascular events (CVE). Early identification of high-risk individuals is crucial for targeted prevention and management. However, conventional risk stratification approaches often fall short in accuracy and clinical utility. This study aimed to develop and validate a robust, interpretable machine learning (ML)-based model for predicting CVE in patients with gout. This retrospective cohort study included 686 hospitalized gout patients at Xiyuan Hospital (Beijing, China) between January 1, 2013, and December 31, 2023. We applied Synthetic Minority Oversampling Technique (SMOTE) combined with random undersampling of the majority class. Then, patients were randomly divided into training (70%) and testing (30%) sets. A comprehensive set of clinical and biochemical variables (n = 39) was collected. Feature selection was performed using Boruta algorithms and Lasso to identify the most predictive variables. Multiple ML algorithms-including Decision Tree Learner, LightGBM Learner, K Nearest Neighbors Learner, CatBoost Learner, Gradient Boosting Desicion Tree Learner-were implemented to construct predictive models. SHAP values were used to assess model interpretability, and robustness was evaluated through 10-fold bootstrap resampling with enhanced standard error estimation. Of the 686 patients, 263 experienced cardiovascular events during follow-up (incidence rate: 38.3%). A logistic regression model was constructed based on eight variables selected using the Boruta feature selection algorithm: sex, age, PLT, EOS, LYM, CO2, GLU and APO-B. Among the five models evaluated, the CatBoost classifier achieved the best performance, with the highest area under the ROC curve (AUC) of 0.976 and the recall of 0.971. Furthermore, SHAP (SHapley Additive exPlanations) values were employed to provide both global and individual-level interpretability of the CatBoost model. To assess the model's generalization performance, bootstrap resampling was performed 10 times. Based on these results, the standard error was improved using machine learning-based enhancement methods, thereby optimizing the model's robustness and predictive stability. The logistic regression analysis revealed that age (OR=1.351, p<0.001), CO2 (OR=0.603, p=0.004), eosinophil count (OR=2.128, p=0.001), and platelet count (OR=0.961, p<0.001) were significantly associated with the outcome, indicating their potential roles as independent predictors. Notably, while APO_B (p=0.138) and sex (p=0.132) showed no significant association, glucose levels (OR=2.1, p=0.066) exhibited a marginal trend toward significance, warranting further investigation. This tool may support clinicians in identifying high-risk individuals, enabling early interventions and optimized management strategies. This study has several limitations. First, the analysis was based on a single-center dataset, which may limit the generalizability of the findings. External validation in multi-center and prospective cohorts, along with an expanded sample size, is warranted to confirm these results. Second, key confounding factors such as medication use, lifestyle habits, and gout flare frequency were not included in the analysis; future studies should incorporate these variables to provide a more comprehensive assessment. Show less

Among individuals diagnosed with type 2 diabetes mellitus (T2DM), an abnormal accumulation of visceral fat heightens the cardiovascular risk (CVR), and the major reason for death for these people is atherosclerotic cardiovascular disease (ASCVD). This study aimed to gain further insights into the longitudinal relationship between CVR and visceral fat area (VFA) in patients with T2DM, and to compare the predictive performance of additional abdominal obesity measures and VFA for changes in CVR. This prospective cohort study included 316 patients with T2DM who were followed up for more than one year, and VFA was measured by the bioimpedance method. This study investigated the prospective association between a VFA percentage change (∆VFA, %) and CVR, and evaluated the potential nonlinear relationships between ∆VFA (%) and the increase 10-year ASCVD risk. Furthermore, the area under the pooled curve (AUC) was contrasted for both ∆VFA (%) and other abdominal obesity indices. The excessive VFA loss group showed lower low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), triglyceride-glucose index, LDL-C/HDL-C, brachial-ankle pulse wave velocity, 10-year ASCVD risk, atherogenic index of plasma, TC/HDL-C, and apolipoproteins B/apolipoproteins A-1 than the VFA gain group (all β [Formula: see text] 0, HR [Formula: see text] 1, all P [Formula: see text] 0.05) after covariate controlling. VFA reduction of more than 14.82% led to a reduction in the stated risk. Moreover, ∆VFA (%) demonstrated superior predictive value for changes in ASCVD risk, with an AUC of 0.585 (95% CI: 0.513-0.656), compared to other obesity indices. Excessive VFA reduction improved 10-year ASCVD risk in patients diagnosed with T2DM. VFA was a more effective predictor of 10-year ASCVD risk changes than other abdominal obesity measures. This investigation has been registered with the Chinese Clinical Trial Registry (ChiCTR2400086569). Show less

Lipid metabolism abnormalities and inflammation have been implicated in gallstone disease (GSD) development, but the causal relationships and potential mediation effects among lipid metabolites, inflammatory factors, and GSD remain unclear. The aim of this study is to explore the causal relationships among these 3 factors. This study employed 2-sample Mendelian Randomization (TSMR) and 2-step MR to investigate the causal relationships and potential mediation effects among 91 inflammatory factors, 6 lipid metabolism-related molecules (HDL-C, LDL-C, TG, total cholesterol, ApoA1, and ApoB), and GSD. We opted for 4 distinct MR analysis methods including inverse variance weighted method, weighted median method, MR-Egger regression method and MR-PRESSO analysis. Sensitivity analyses included MR-Egger intercept tests, Cochran's Q statistic, Steiger tests, and leave-one-out analyses. Product of coefficients method was used to estimate mediation proportion. TSMR analysis revealed that every 1-unit increase in low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), the risk of GSD decreased by 16.5%, 10.2%, 8.4%, and 13.1%, respectively. Inflammatory factors such as Natural killer cell receptor 2B4 (CD244), Macrophage colony-stimulating factor 1 (CSF-1), and interleukin-18 receptor 1 (IL-18R1) were identified as risk factors for GSD, while Fibroblast growth factor 19 levels (FGF19), Interleukin-1-alpha levels (IL-1α), and Interleukin-8 levels (IL-8) were found to be protective. Mediation analysis through 2-step MR identified potential pathways involving ApoA1--IL-8--GSD (P = .084) and IL-1α--ApoB--GSD (P = .117). This study provides robust evidence of causal links between specific lipid metabolites and GSD, as well as suggestive causal associations for several inflammatory factors. However, mediation analysis did not support significant roles for lipids or inflammatory factors as mediators in GSD pathogenesis. Future research could be further pursued in areas such as drug target intervention and mechanistic studies. Show less

Coronary artery disease (CAD) is showing a trend toward earlier onset. Premature CAD (PCAD) is clinically defined as CAD with onset before the age of 55 in males and 65 in females. Notably, many young patients subsequently hospitalized with acute cardiovascular events had undergone annual physical examinations before hospitalization, yet were not identified as high-risk by current risk stratification guidelines or traditional risk assessment tools. This study aims to investigate the diagnostic capacity of novel inflammatory biomarkers (including the monocyte-to-high-density lipoprotein cholesterol ratio (MHR), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), apolipoprotein B to apolipoprotein A-1 ratio (apoB/apoA-1), and low-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (LDL-c/HDL-c)) for PCAD, thereby providing the evidence-based foundation for PCAD screening. A total of 1,012 young subjects (male<55 years, female<65 years) undergoing diagnostic coronary angiography (CAG) at the Third Affiliated Hospital of Zunyi Medical University (from January 2022 to February 2023) were retrospectively analyzed. We stratified 1,012 eligible participants into two groups: 521 angiographically confirmed PCAD cases and 491 controls with normal coronary arteries. Comprehensive baseline characteristics, including cardiovascular risk profiles and core laboratory-measured inflammatory markers, were recorded. The Mann-Whitney U test and binary logistic regression analysis were employed to assess the associations between inflammatory biomarkers and PCAD. The areas under the receiver operating characteristic (ROC) curves (AUCs) were calculated to evaluate their diagnostic performance for PCAD. The odds ratio (OR) values for MHR, NLR, LDL-c/HDL-c, and apoB/apoA-1 were 5.592 (95% CI: 2.886-7.836), 1.671 (95% CI: 1.500-1.861), 1.663 (95% CI: 1.419-1.950), and 6.268 (95% CI: 2.765-8.213), respectively (all The apoB/apoA-1 outperformed MHR, NLR, and LDL-c/HDL-c as an inflammatory biomarker in PCAD. Its diagnostic capacity was notably enhanced in ACS subgroups. A comprehensive model combining apoB/apoA-1 with traditional risk factors demonstrated exceptional accuracy. Incorporating this biomarker into routine screening protocols could significantly strengthen preventive strategies. Show less

In Traditional Chinese Medicine (TCM), dampness is a pathogenic factor arising from impaired production and transportation of bodily fluids. While Fuling Zexie decoction (FLZXD) has demonstrated therapeutic efficacy in dampness constitution (DC) treatment, the material basis underlying its constitutional modulatory effects remains unclear. This study proposes objective indicators for the differentiation and therapeutic evaluation of DC and elucidates the material basis of FLZXD in DC treatment. Serum exosome proteomic profiling was conducted across two independent cohorts to identify DC-related indicators and assess the therapeutic efficacy of FLZXD in DC-associated hyperlipidemia (DC-hyperlipidemia). The bioactive compounds of FLZXD were prioritized through a comprehensive analysis of patent documentation and network pharmacology, with subsequent validation of DC-related targets using enzyme-linked immunosorbent assay (ELISA). Proteomic analysis of serum exosomes revealed signatures that differentiate individuals with a balanced constitution (BC) from those with DC. The differentially expressed proteins (DEPs) were enriched predominantly in pathways related to the complement cascade and cardiovascular diseases. FLZXD demonstrated therapeutic efficacy against DC-hyperlipidemia, as evidenced by the reversal of DEPs expression following treatment, which was supported by the patentable findings and network pharmacology analysis. Through experimental validation and pharmacological evidence, the active herbs of FLZXD (Fuling, Zexie and Baizhu, collectively referred to as FZB) were identified, and a total of 73 putative therapeutic targets involved in the dampness-resolving effects of FZB were revealed. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment further confirmed that FLZXD exerts its anti-dampness effects primarily through regulation of the complement and coagulation cascades. Among eight candidate indicators specifically associated with DC, four proteins were validated via ELISA, indicating potential utility for the differentiation of DC. The sensitivity (%), specificity (%), fold change (FC), p-value, and area under the curve (AUC) for each indicator were as follows: apolipoprotein B-100 (APOB) (100.00, 80.00, 0.63, 0.0051, 0.94), complement factor H-related protein 1 (CFHR1) (90.00, 100.00, 0.55, 0.0001, 0.98), alpha-1-acid glycoprotein 1 (ORM1) (100.00, 80.00, 0.71, 0.0043, 0.92), and pigment epithelium-derived factor (SERPINF1) (90.00, 70.00, 0.66, 0.0002, 0.87). The integrative approach, combining proteomic profiling, network pharmacology analysis, and clinical validation, establishes an integrative approach for research on TCM constitutions. This approach provides (1) molecular insights into the differentiation of DC, (2) a foundation for mechanism-based, targeted therapeutic strategies, and (3) enhanced patient stratification to support personalized treatment approaches. Show less

Increasing evidence underscores the driving role of coding and non-coding variants in cancer development. Analyzing gene sets in biological processes offers deeper insights into the molecular mechanisms of carcinogenesis. Here, we developed geMER to identify candidate driver genes genome-wide by detecting mutation enrichment regions within coding and non-coding elements. We subsequently designed a pipeline to identify a core driver gene set (CDGS) that broadly promotes carcinogenesis across multiple cancers. CDGS comprising 25 genes for 25 cancers displayed instability in DNA aberrations. Variants within the TTN enrichment region may influence the folding of the I-set domain by altering local polarity or side-chain chemistry properties of amino acids, potentially disrupting its antigen-binding capacity in LUAD. Multi-omics analysis revealed that APOB emerged as a candidate oncogene in LIHC, whose genetic alterations within the enrichment region may activate key TFs, upregulate DNA methylation levels, modulate critical histone modifications, and enhance transcriptional activity in the HepG2 and A549 cell lines compared to Panc1. Additionally, CDGS mutation status was an independent prognostic factor for the pan-cancer cohort. High-risk patients tended to develop an immunosuppressive microenvironment and demonstrated a higher likelihood of responding to ICI therapy. Finally, we provided a user-friendly web interface to explore candidate driver genes using geMER ( http://bio-bigdata.hrbmu.edu.cn/geMER/ ). Show less

To investigate the relationship between serum lipid levels and the risk of Chronic obstructive pulmonary disease (COPD) in the UK Biobank. We performed this prospective study in 381,938 adults without COPD from UK Biobank. Serum high-density cholesterol (HDL-C), low-density cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), apolipoprotein A (ApoA) and apolipoprotein B (ApoB) were measured and classified into quintiles. Restricted cubic spline (RCS) analysis was applied to visualize the dose-response relationship between lipids and COPD risk and Cox proportional hazard models to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). We documented 10,443 incident COPD cases. Nonlinear relationships were found between HDL-C, LDL-C, TC, ApoA, ApoB and COPD risk with RCS analysis (P values for non-linearity < 0.05). Accordingly, multivariable-adjusted regression analysis indicated abnormal HDL-C and ApoA, and low LDL-C, TC and ApoB were associated with increased risk of COPD. Compared to intermediate quintile (Q3) group, both high or low HDL-C and ApoA were associated with risk of COPD. Corresponding HRs (95% CIs) were 1.15 (1.08-1.22), 1.16 (1.09-1.23) in Q1 group and 1.08 (1.01-1.16), 1.07 (1.00-1.14) in Q5 group. For LDL-C, TC and ApoB, there were more than 29% higher risk was observed in Q1 group with HRs (95% CIs) of 1.34 (1.27-1.42), 1.38 (1.30-1.46) and 1.29 (1.21-1.37), while HRs (95% CIs) were 0.88 (0.83-0.94), 0.92 (0.86-0.98) and 0.90 (0.84-0.95) in Q5 groups. We also observed the interactions between specific lipids and age at recruitment, sex and smoking status with stratified analysis. Our study provides the first evidence demonstrating the associations between six major serum lipids and COPD risk, revealing multiple nonlinear relationships. There were U-shaped associations between serum HDL-C, ApoA and COPD risk, and L-shaped associations between LDL-C, TC, ApoB and COPD risk. Show less

Apolipoprotein B (apoB) can be measured directly and accurately, and better predicts atherogenic risk than conventional lipid profiles. We aimed to investigate whether total and regional (trunk or leg) fat deposits are associated with apoB levels in general US adults. 4585 participants were enrolled from the US National Health and Nutritional Surveys from 2011 to 2016. Overall and regional body fat were measured using dual-energy X-ray absorptiometry. The associations of total and regional fat with apoB levels were evaluated using linear regression models. Following adjustment for demographic, lifestyle, and clinical risk factors, whole-body fat percentage was positively associated with apoB levels. Additionally, percent trunk fat was positively associated (highest vs. lowest tertile beta = 17.73 for men and 14.89 for women, respectively), whereas percent leg fat was inversely associated (highest vs. lowest tertile beta = - 4.84 for men and - 6.55 for women, respectively) with apoB levels in both sexes. The association for trunk fat and leg fat remained significant after further adjustment for body mass index or waist circumference. Higher percent trunk fat combined with lower percent leg fat was associated with particularly higher apoB. In conclusion, among general US adults, both elevated trunk fat and reduced leg fat are associated with higher levels of apoB. Further research is required to elucidate the underlying pathophysiological mechanisms. Show less

To investigate the relation of glycemic and lipid metabolism with brain structure and cognitive function in people with diabetes, so as to improve cognitive function in these individuals. Based on the UK Biobank, 26,394 patients, who were diagnosed with diabetes by doctors between 2006 and 2010, were included in the study. The demographic information, clinical data of glycemic and lipid metabolism and cognitive function (brain MRI and cognitive function scores) were collected. Multiple linear regression and non-restricted cubic spline analyses were used to investigate the relations of glycemic and lipid metabolism with brain structure and cognitive function. In this study, the mean age of people with diabetes (containing 39 % females) was 59.58 ± 7.21 years. Higher random blood glucose (β = -0.116, p < 0.001) and glycosylated hemoglobin (HbA1c) (β = -0.062, p = 0.051) were associated with a smaller brain volume. Higher HbA1c (β = 0.036, p < 0.001; β = 0.023, p = 0.021) was related with worse cognitive function. Further analysis showed that HbA1c < 6.5 % had a protective effect on cognitive function, and HbA1c = 6.5 %∼8.5 % and >8.5 % was unrelated and negatively related with cognitive function, respectively. Different types of lipids had varying effects on cognitive function. Higher total cholesterol (TC) (β = 0.125, p = 0.008), low density lipoprotein-cholesterol (LDL-C) (β = 0.086, p = 0.025), and ApoB (β = 0.092, p = 0.026) were associated with more significant brain structural abnormalities. Conversely, triglyceride (TG) = 0.75∼8.0 mmol/L was positively correlated with cognitive function (β = -0.036, p < 0.001; β = -0.044, p < 0.001; β = 0.058, p = 0.001), and higher ApoA (β = -0.032, p < 0.001; β = -0.033, p < 0.001; β = 0.047, p = 0.004) was associated with better cognitive function. The age-stratified analysis revealed that the impact of lipids on cognitive function was age-dependent. TC and LDL-C were related to brain structural abnormalities in the 55-60 age group, while TG had a stronger protective effect on cognitive function in older adults, particularly those aged 65-70 years. In people with diabetes, higher HbA1c (>8.5 %), as well as elevated TC, LDL-C, and ApoB, are associated with worse brain structure and cognitive function. Conversely, HbA1c < 6.5 % and elevated TG within the range of 0.75∼8.0 mmol/L have a protective effect on cognitive function, and the later exhibited more evident impact in older adults. To prevent or delay the onset of dementia in people with diabetes, it may be necessary to intensify glycemic control, targeting an HbA1c level of <6.5 %. Additionally, the age-specific lipid-lowering strategies shall be considered, with more flexible triglyceride-lowering goals for elderly patients. Show less

This study aimed to (1) evaluate small dense low-density lipoprotein cholesterol (sdLDL-C) dynamics from prediabetes to type 2 diabetes mellitus (T2DM) with complications, (2) validate existing sdLDL-C estimation formulas (Sampson’s, Srisawasdi’s, Han’s) in Chinese populations, and (3) develop a population-specific formula for enhanced accuracy. A multicenter study recruited 1,944 participants (216 controls, 70 with prediabetes, 212 with newly diagnosed T2DM, 164 with treated T2DM, and 1,286 in validation cohorts). Lipid profiles, including sdLDL-C (measured via enzymatic assays), were analyzed. Formula performance was assessed using spearman correlation, intraclass correlation coefficients (ICC), and multivariable linear regression. A novel formula was derived via multivariable regression. Atherogenic lipid triad manifestations emerged early: sdLDL-C was significantly elevated in participants with prediabetes (1.07 [0.73, 1.40] vs. 0.57 [0.44, 0.72] mmol/L in controls, P < 0.05) and further increased in those with T2DM, correlating strongly with triglycerides (TG; sdLDL-C elevation begins in prediabetes, highlighting its value for early atherosclerotic cardiovascular disease (ASCVD) risk assessment. Current formulas show population-specific limitations, whereas the new model provides improved accuracy for Chinese T2DM patients, enabling cost-effective sdLDL-C estimation and personalized lipid management. The online version contains supplementary material available at 10.1186/s12944-025-02636-0. Show less

Kelch-like protein 12 (KLHL12) has been shown to regulate coat complex II (COPII)-mediated endoplasmic reticulum (ER)-to-Golgi trafficking of large cargos carrying procollagen or apolipoprotein B-100 containing very-low-density lipoprotein (VLDL). It is known that lipid absorption and chylomicron metabolism in enterocytes are dependent on apolipoprotein B-48 (ApoB48) and COPII-mediated trafficking. This study aimed to investigate whether KLHL12 in the intestine regulates dietary lipid absorption, chylomicron assembly, and metabolic phenotypes in mice. We generated Show less

This study aimed to evaluate the impact of combining high-intensity statins with CETP inhibitors on lipid levels, as well as to explore their potential clinical significance. We conducted a comprehensive search of relevant studies in the PubMed, Embase, Cochrane Library, and Web of Science databases. The Cochrane Risk of Bias Tool RoB 2.0 was employed to evaluate the quality of the included studies. Statistical analyses were carried out using STATA 15 software, with primary outcomes being high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C). Out of 2,552 records, 7 studies were included in the final analysis. The findings revealed that the combination of high-intensity statins with CETP inhibitors significantly raised HDL-C levels (SMD 2.47 [1.77, 3.18], p < 0.001) and lowered LDL-C levels (SMD -1.75 [-2.19, -1.31], p < 0.001). Compared to statin monotherapy, the combination of high-intensity statins and CETP inhibitors resulted in a more pronounced increase in HDL-C and ApoAI, while reducing LDL-C, triglycerides (TG), and ApoB levels, without increasing the incidence of adverse events. Show less

Growth differentiation factor 15 (GDF15) is a key regulator of food intake and energy metabolism. GDF15 mimetic drugs for the treatment of metabolic syndrome and obesity are under clinical development. While GDF15 presents a promising target for weight management, its potential cardiovascular actions remain elusive. In this study we investigated the role of GDF15 in macrophage function and atherosclerosis pathogenesis and whether GDF15 acts both as a biomarker and mediator of atherosclerosis severity. ApoE Show less

Zhigancao Decoction (ZGCD) is derived from "Treatise on Febrile Diseases" and is traditionally prescribed for treating a variety of cardiovascular conditions. As of now, there are no data to support its use as a treatment for diabetic cardiomyopathy (DCM) and the mechanism behind the effect is unclear as well. In the present study, clinical evidence for the efficacy of ZGCD in patients with DCM was examined using a meta-analysis and its underlying anti-DCM molecular mechanisms were explored via network pharmacology. The current study utilized an extensive search strategy encompassing various domestic and foreign databases databases to retrieve pertinent articles published up to June 2024. In light of this, a thorough evaluation of the benefits and safety of Zhigancao decoction (ZGCD) was conducted in this study using RevMan and Stata. Subsequently, a number of active compounds and target genes for ZGCD were gathered from the TCMSP and BATMAN-TCM databases, while the main targets for DCM were obtained from databases such as GenCards, OMIM, TTD, and DrugBank. To select core genes, protein-protein interaction networks were generated using the STRING platform, and enrichment analyses were completed using the Metascape platform. Meta-analysis results were ultimately derived from 9 studies involving 661 patients in total. In comparison with WM therapy alone, the pooled results showed that ZGCD significantly enhanced overall effectiveness. Additionally, the utilization of ZGCD was leading to a reduction in LVEDV, LVESV and LVDD, also a greater increase in LVEF. Meanwhile, the utilization of ZGCD during intervention was more effective in reducing SBP, and DBP. In addition, the ZGCD showed potential in reducing the occurrence of adverse events. In the context of network pharmacology, five constituents of ZGCD-namely lysine, quercetin, gamma-aminobutyric acid, stigmasterol, and beta-sitosterol-are posited to exert anti-diabetic cardiomyopathy (anti-DCM) effects through interactions with the molecular targets ASS1, SERPINE1, CACNA2D1, AVP, APOB, ICAM1, EGFR, TNNC1, F2, F10, IGF1, TNNI2, CAV1, INSR, and INS. The primary mechanisms by which ZGCD may achieve its anti-DCM effects are likely mediated via the AGEs/RAGE signaling pathway, as well as through pathways related to lipid metabolism and atherosclerosis. In comparison to WM therapy alone, ZGCD demonstrates greater efficacy and safety in the management of DCM. ZGCD not only significantly reduces blood pressure, but also enhances cardiac function while producing fewer adverse effects. The therapeutic effects of ZGCD on DCM can likely be ascribed to its capacity to modulate the AGEs-RAGE signaling pathway, as well as its efficacy in enhancing lipid metabolism and mitigating atherosclerosis. identifier (INPLASY202430133). Show less

The per-particle pathogenicity of very-low-density lipoprotein (VLDL) and lipoprotein(a) [Lp(a)] with risk of valvular heart diseases (VHD) other than aortic stenosis compared with low-density lipoprotein (LDL) remains unclear. Single-nucleotide polymorphism specific clusters associated with LDL cholesterol (LDL-C), VLDL cholesterol (VLDL-C) and Lp(a) were identified. The relationships of genetically predicted variation in apolipoprotein B (apoB) in these lipoproteins with risk of VHD and its major types (aortic stenosis, aortic regurgitation, and mitral regurgitation) were evaluated to determine the comparative pathogenicity by Mendelian randomization (MR) analyses. The VHD odds ratio (OR) per 1 g/L higher apoB was 1.09 [95 % confidence interval (CI) 1.04-1.15] in LDL vs. 1.45 (95 % CI 1.25-1.69) in VLDL vs. 2.71 (95 % CI 1.92-3.82) in Lp(a) based on the cluster-based MR analyses. The polygenic scores for each lipoprotein weighted by apoB similarly showed a greater OR of VHD per 1 g/L apoB in VLDL [1.20 (95 % CI 1.06-1.37)] and in Lp(a) [2.54, (95 % CI 1.95-3.32)] compared with that in LDL [1.05 (95 % CI 1.01-1.08)]. Multivariable MR analyses further revealed the strong effects of VLDL-C and Lp(a) on VHD risk independent of LDL-C. In addition, significant associations between Lp(a) and all three major types of VHD were observed, while LDL and VLDL had no impact on aortic and mitral regurgitation. VLDL and Lp(a) appear to have significantly greater per-particle pathogenicity in VHD compared to LDL. The distinct impacts of lipoproteins on different VHD subtypes suggest the inadequacy of just focusing on LDL-lowering treatment for valve disorders. Show less

The objective was to assess the clinical efficacy of long non-coding RNA (lncRNA) alpha-2-macroglobulin-antisense 1 (A2M-AS1) in acute myocardial infarction (AMI). One hundred patients with AMI and eighty patients with chest pain were recruited in the case-control study. A2M-AS1 expression was examined by quantitative real-time polymerase chain reaction (qRT-PCR). Receiver operating characteristic (ROC) analysis was utilized for evaluating the diagnostic value. Pearson's correlation analysis was used to analyze the correlation between A2M-AS1 and conventional AMI biomarkers. AMI-associated risk indicators were identified using logistic regression analysis. A significant reduction of serum A2M-AS1 was measured in AMI patients relative to chest pain patients. A2M-AS1 had an area under the curve (AUC) of 0.927 to distinguish AMI patients from those with chest pain. Pearson's correlation analysis showed that A2M-AS1 was adversely correlated with white blood cell (WBC) (r=-0.6682, P < 0.001), low density lipoprotein cholesterol (LDL-C) (r=-0.5795, P < 0.001), creatine kinase MB (CK-MB) (r=-0.6022, P < 0.001) and cTnl (r=-0.5473; P < 0.001), while positively correlated with high density lipoprotein cholesterol (HDL-C) (r = 0.6445, P < 0.001). Relative to non-Major Adverse Cardiovascular Events (non-MACE) group, serum A2M-AS1 was obviously declined in the MACE group of AMI patients with high capacity to distinguish the MACE group from the non-MACE patients (AUC = 0.802). Additionally, A2M-AS1 (P = 0.013; OR = 0.268; 95%CI = 0.095-0.760) was a risk indicator for predicting MACE with AMI patients, as well as age (P = 0.014; OR = 3.478; 95%CI = 1.285-9.414). A reduction in A2M-AS1 expression was observed in AMI patients, suggesting its potential as an underlying indicator for AMI diagnosis. Show less

Neuromyelitis optica spectrum disorder (NMOSD) is a group of immune-mediated disorders that often lead to severe disability. The diagnosis and monitoring of NMOSD can be challenging, particularly in seronegative cases, highlighting the need for reliable biomarkers to enhance clinical management. This study aimed to identify serum lipid biomarkers for the diagnosis and monitoring of NMOSD and to assess their potential to improve clinical decision-making. We conducted a comprehensive serum proteomic analysis in a discovery cohort of NMOSD patients and controls to identify lipid-related proteins associated with NMOSD. Subsequently, we validated the candidate biomarkers in the retrospective cohort and developed diagnostic models using a random forest algorithm. The association between these lipid biomarkers and disease activity was further evaluated in longitudinal analysis. Our analysis identified a panel of serum lipid-related biomarkers that demonstrated significant differences between NMOSD patients and controls. The diagnostic models achieved the impressive accuracy of 72% for the full NMOSD spectrum, 72% for AQP4-IgG+ NMOSD, and 68% for double seronegative NMOSD. Importantly, these biomarkers showed a correlation with disease activity, with levels changing from relapse to remission. Additionally, a combination of these lipid biomarkers was found to predict relapse with the AUC of 0.861. A user-friendly smartphone application was developed to facilitate the straightforward "input-index, output-answer" screening process, enhancing both clinical decision-making and patient care. The diagnostic model based on the serum lipid-related indexes (TC, TG, LDL, HDL, ApoA1, and ApoB) may be the useful tool for NMOSD in diagnosis and monitoring of disease stage, thereby improving the treatment outcome for patients. Future studies should focus on integrating these biomarkers into routine clinical practice to realize their full potential in enhancing NMOSD management. Show less

The associations between screen time exposure, blood lipids, and Atherosclerotic Cardiovascular Disease (ASCVD) incidence have been less studied. We aimed to examine the associations of exposure to screen time with blood total cholesterol (TC), HDL-C, LDL-C, triglycerides (TG), apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and ASCVD risk score, and risk of subsequent ASCVD incidence. A nationwide sample of 7124 China Health and Nutrition Survey 2009 participants were followed up to 2015 for ASCVD incidence. The stationary screen time exposure was assessed through self-reported daily hours of using television, and computers. A total of 292 ASCVD events occurred during 35,310 follow-up person-years. Per 1-h increases in daily screen time exposure were associated with a higher 0.34% (0.12% to 0.56%), 0.47% (0.09% to 0.86%), and 0.51% (0.19% to 0.83%) increases in blood TC, LDL-C, and ApoB levels. A higher risk of incident ASCVD was associated with per log-transformed unit increase in blood LDL-C (adjusted HR = 1.51, 95% CI 1.04 to 2.18), and ApoB (adjusted HR = 1.80, 95% CI 1.12 to 2.92). The elevated blood TC, blood LDL-C, blood ApoA1 and ApoB levels significantly mediated the association between screen time exposure and ASCVD incidence. Urban dwellers, middle-aged adults, and females were particularly associated with a higher ASCVD risk with screen time exposure. The results of this nationwide cohort supported the associations of screen time exposure with elevated blood LDL-C, and ApoB levels, which consistently contributed to an increased risk of subsequent ASCVD incidence. Show less

The gut microbiota plays a crucial role in human health, but its impact on lipid metabolism remains unclear. Understanding the causal relationship between gut bacteria and lipid profiles is essential for developing strategies to prevent and treat dyslipidemia and cardiovascular diseases. This study aimed to assess this relationship using two-sample Mendelian randomization (MR). Data for both exposure and outcomes were obtained from the IEU-GWAS database, with lipid profile data sourced from a publication. Genome-wide significant single nucleotide polymorphisms (SNPs), which were independent of outcome factors but correlated with exposure variables, were identified as instrumental variables. Several MR methods, including weighted analysis, maximum likelihood, inverse variance weighting (IVW), MR-Egger, and weighted median, were applied. Colocalization analysis further validated the findings. The analysis revealed microbial groups with causal relationships to ApoA1, ApoB, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, and triglycerides. Reverse MR and colocalization analysis provided additional confirmation of these results. This study offers new evidence of the causal link between gut microbiota and lipid profiles, providing insights for improving lipid profiles and reducing cardiovascular disease risk. Show less

Aim    Aortic aneurysm is characterized by localized expansion and damage to the vessel wall. While apolipoprotein B (ApoB) has been linked to atherosclerosis, its causal relationship with aortic aneurysm remains unclear. This study used a Mendelian randomization (MR) approach to explore the causal relationships between ApoB, aortic aneurysm, and potential mediators.Material and methods    Single nucleotide polymorphism (SNP) data related to ApoB, apolipoprotein A1 (ApoA1), triglycerides, frailty index, and aortic aneurysm were obtained from large-scale genome-wide association studies. MR analysis was conducted to evaluate causal relationships, using inverse variance weighting (IVW) as the primary statistical method. Additionally, we assessed whether the frailty index mediates the relationship between ApoB and aortic aneurysm.Results    Univariate MR analysis revealed that ApoB is significantly associated with aortic aneurysm (IVW odds ratio (OR) = 1.443, 95 % confidence interval (CI) = 1.273-1.637, p < 0.001). Multivariable MR (MVMR) analysis, adjusted for ApoA1 and triglycerides, confirmed these results. In mediation analysis, the frailty index was found to partially mediate the effect of ApoB on aortic aneurysm (mediation contribution: 20.1 %-23.1 %). The ORs for ApoB and the frailty index with respect to aortic aneurysm were 1.325 (95 % CI = 1.168-1.505) and 4.188 (95 % CI = 1.859-9.435), respectively.Conclusion    ApoB has a causal relationship with aortic aneurysm, with the frailty index acting as a partial mediator in this pathway. Show less

Pre-eclampsia (PE) is a common complication of pregnancy and there is an urgent need for new drug targets. We performed whole proteome-wide Mendelian randomisation (MR) and colocalisation analyses to identify potential therapeutic targets for PE. A two-sample MR study was conducted using summary-level statistics of 734 plasma proteins retrieved from large genome-proteome-wide association studies. The summary statistics of PE or eclampsia were obtained from the FinnGen consortium. Wald ratio and Inverse variance weighted (IVW) were used to assess the causal association between proteins and PE. Colocalisation analyses were conducted to examine whether the identified proteins and PE shared incidental variants. Genetically predicted circulating levels of 42 proteins were associated with PE risk after Benjamini-Hochberg correction. Nineteen of the gene-predicted proteins showed evidence of increased PE risk (CRELD1, CPA4, AHSG, NFASC, QDPR, NTM, PZP, FAM171B, RTN4R, FLRT2, ADH4, ADM, SPINK5, LGALS4, CKM, SPON2, UROS, CXCL10 and APOBEC3G); 23 proteins reduced the risk of PE (CLIC5, NEO1, SWAP70, KLK8, VWA2, FSTL1, CXCL11, APOB, NPPB, CNTN4, IL12B, ACHE, TCN1, GFRA2, GNMT, HPGDS, DPT, MANBA, SPARCL1, ACE, FUT8, BST1 and ACP1). Bayesian colocalisation indicated that six proteins (VWA2, ACHE, CXCL10, PZP, AHSG and UROS) and PE, which were identified as high evidence of colocalisation with PE. This study provides evidence of the causal association between genetically predicted 42 proteins associated with PE risk, which might be promising drug targets for PE. Show less

Sudden sensorineural hearing loss (SSNHL) has serious harm to human hearing health, where blood lipid and inflammatory levels may play a key role in it. Thus, the purpose of this investigation was to assess the connection between inflammatory and lipid variables and SSNHL. Patients diagnosed with SSNHL had an analysis of serum lipid parameters, such as total cholesterol (TC), triglycerides, HDL-C, LDL-C, apolipoprotein A (apo A), apolipoprotein B (apo B), and lipoprotein A (Lp(a)), as well as inflammatory factors like TNF-α and IL-10. After that, risk factor analysis was carried out utilizing univariate, multivariate regression, and LASSO retrospective modeling. In all, 72 SSNHL patients and 67 healthy control individuals were involved. The LDL/HDL, total cholesterol, ApoB, LP(a), IL-10, TNF-α, and IFN-γ considerably higher in the SSNHL group than in the healthy control group, however, nervonic acid and coenzyme Q were decreased significantly in SSNHL than Control group. The multivariate logistic regression model's analysis using multifactorial retrospective modeling revealed significant changes in LDL, LDL/HDL, IL-10, and TNF-α. In addition, in the LASSO regression model, the model demonstrated high discrimination, as evidenced by the C-index for the cohort's prediction nomogram, which was 0.998 (95% CI, 0.154-1.115) and confirmed to be 0.925 following bootstrapping validation. Finally, IL-10 and LDL/HDL were the main risk factors in SSNHL. LDL/HDL and IL-10 may be closely related to SSNHL's progress and should be evaluated promptly before treating patients with SSNHL. Show less

Vascular calcification (VC) significantly increases the incidence and mortality of many diseases. The causal relationships of dyslipidaemia and lipid-lowering drug use with VC severity remain unclear. This study explores the genetic causal associations of different circulating lipids and lipid-lowering drug targets with coronary artery calcification (CAC) and abdominal aortic artery calcification (AAC). We obtained single-nucleotide polymorphisms (SNPs) and expression quantitative trait loci (eQTLs) associated with seven circulating lipids and 13 lipid-lowering drug targets from publicly available genome-wide association studies and eQTL databases. Causal associations were investigated by univariable, multivariable, drug-target, and summary data-based Mendelian randomization (MR) analyses. Potential mediation effects of metabolic risk factors were evaluated. MR analysis revealed that genetic proxies for low-density lipoprotein cholesterol (LDL-C), triglycerides (TC) and Lipoprotein (a) (Lp(a)) were causally associated with CAC severity, and apolipoprotein B (apoB) level was causally associated with AAC severity. A significant association was detected between hepatic Lipoprotein(A) (LPA) gene expression and CAC severity. Colocalisation analysis supported the hypothesis that the association between LPA expression and CAC quantity is driven by different causal variant sites within the ±1 Mb flanking region of LPA. Serum calcium and phosphorus had causal associations with CAC severity. Inhibitors targeting LPA might represent CAC drug candidates. Moreover, T2DM, hypercalcemia, and hyperphosphatemia are positively causally associated with CAC severity, while chronic kidney disease and estimated glomerular filtration rate are not. Show less