Cardiovascular disease (CVD) remains a leading cause of mortality globally. Environmental pollutants, specifically volatile organic compounds (VOCs), have been identified as significant risk factors. This study aims to develop a machine learning (ML) model to predict CVD risk based on VOC exposure and demographic data using SHapley Additive exPlanations (SHAP) for interpretability. We utilized data from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2018, comprising 5098 participants. VOC exposure was assessed through 15 urinary metabolite metrics. The dataset was split into a training set (70 %) and a test set (30 %). Six ML models were developed, including Random Forest (RF), Light Gradient Boosting Machine (LightGBM), Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Multi-Layer Perceptron (MLP), and Support Vector Machines (SVM). Model performance was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUROC), accuracy, balanced accuracy, F1 score, J-index, kappa, Matthew's correlation coefficient (MCC), positive predictive value (PPV), negative predictive value (NPV), sensitivity (sens), specificity (spec) and SHAP was applied to interpret the best-performing model. The RF model exhibited the highest predictive performance with an ROC of 0.8143. SHAP analysis identified age and ATCA as the most significant predictors, with ATCA showing a protective effect against CVD, particularly in older adults and those with hypertension. The study found a significant interaction between ATCA levels and age, indicating that the protective effect of ATCA is more pronounced in older individuals due to increased oxidative stress and inflammatory responses associated with aging. E-values analysis suggested robustness to unmeasured confounders. This study is the first to utilize VOC exposure data to construct an ML model for predicting CVD risk. The findings highlight the potential of combining environmental exposure data with demographic information to enhance CVD risk prediction, supporting the development of personalized prevention and intervention strategies.

The triglyceride glucose body mass index (TyG-BMI) is a potential indicator for insulin resistance, but its association with mortality in diabetic patients is unclear. This study investigates the relationship between TyG-BMI and all-cause and cardiovascular mortality in diabetics. The study included 3109 diabetic patients from the National Health and Nutrition Examination Survey (2001–2018). Mortality data were obtained from National Death Index records until 31 December 2019. Multivariate Cox models analyzed the association between TyG-BMI and mortality. Non-linear correlations were assessed using restricted cubic splines, and a two-piecewise Cox model evaluated the relationship on both sides of the inflection point. Over a median 7.25-year follow-up, 795 total and 238 cardiovascular deaths occurred. A U-shaped link was found between initial TyG-BMI and mortality in diabetic patients. Low TyG-BMI (< 279.67 for all-cause, < 270.19 for CVD) reduced death risks (all-cause: HR 0.77, 95% CI 0.69–0.86; CVD: HR 0.64, 95% CI 0.48–0.86). High TyG-BMI (> 279.67 for all-cause, > 270.19 for CVD) increased these risks (all-cause: HR 1.26, 95% CI 1.10–1.44; CVD: HR 1.33, 95% CI 1.06–1.68). In the NHANES study population, a U-shaped association was observed between the baseline TyG-BMI index and all-cause mortality or CVD in diabetic patients.

(1) Background: Existing lipid-lowering therapies have difficulty in achieving lipid target levels in patients with familial hypercholesterolemia (FH), especially in the treatment of patients with homozygous familial hypercholesterolemia. (2) Method: All of the literature data containing “Familial hypercholesterolemia” and “Gene Therapy” in PubMed and Clinical Trials from 2018 to 2022 were selected. (3) Results: The rapid development of gene therapy technology in recent years is expected to change the treatment status of FH patients. As emerging gene therapy vectors, the optimized adeno-associated viruses, exosomes, and lipid nanoparticles have demonstrated an improved safety and higher transfection efficiency. Various RNA-targeted therapies are in phase 1–3 clinical trials, such as small interfering RNA-based drugs inclisiran, ARO-ANG3, ARO-APOC3, olpasiran, SLN360, and antisense oligonucleotide-based drugs AZD8233, vupanorsen, volanesorsen, IONIS-APO(a)Rx, etc., all of which have demonstrated excellent lipid-lowering effects. With gene editing technologies, such as CRISPR-Cas 9 and meganuclease, completing animal experiments in mice or cynomolgus monkeys and demonstrating lasting lipid-lowering effects, patients with FH are expected to reach a permanent cure in the future. (4) Conclusion: Gene therapy is being widely used for the lipid-lowering treatment of FH patients and has shown excellent therapeutic promise, but the current delivery efficiency, economic burden, immunogenicity and the precision of gene therapy can be further optimized.

Background: The relationship between the serum creatinine to cystatin C ratio (sarcopenia index [SI]) and the risk of incident cardiovascular disease (CVD) remains unclear. Therefore, this study aims to explore the association between SI and the risk of incident CVD in middle‐aged and older Chinese adults using nationally representative data. Methods and Results: We analyzed data from participants in CHARLS (China Health and Retirement Longitudinal Study) conducted in 2015 and 2018. The exposure variable was SI, calculated as the ratio of serum creatinine to cystatin C, multiplied by 100. The outcome variable was self‐reported CVD (heart disease or stroke). A cross‐sectional analysis was first performed using 2015 CHARLS data, which included 11 115 eligible participants (46.1% men; mean±SD age, 60.28±9.60 years). Logistic regression was used to estimate the association between SI and CVD. Longitudinal analysis was then conducted using the 2018 follow‐up data, which included 8589 participants (46.4% men; mean±SD age, 59.57±9.42 years), with a median follow‐up period of 3.0 years. Cox proportional hazard models were used to assess the relationship between SI and the risk of incident CVD, and a multivariate‐adjusted restricted cubic spline model was used to explore the dose–response relationship. In the cross‐sectional analysis, multivariate logistic regression revealed a significant negative association between SI and CVD. The longitudinal analysis identified 854 (9.94%) new CVD cases. Cox models showed that lower SI was significantly associated with an increased risk of incipient CVD. The multivariable adjusted hazard ratios for participants in the quartile 2 to quartile4 groups compared with those in the quartile 1 group were 0.94 (95% CI, 0.79–1.12), 0.63 (95% CI, 0.51–0.78), and 0.60 (95% CI, 0.47–0.75), respectively. Restricted cubic spline curves demonstrated a significant linear relationship between SI and CVD incidence (all P ‐nonlinear>0.05). Conclusions: A lower SI was significantly associated with an increased risk of new‐onset CVD in middle‐aged and older Chinese adults. This suggests that SI has an important potential application as a serum marker of sarcopenia in predicting CVD.

Diabetic cardiomyopathy (DCM) is a leading cause of mortality in patients with diabetes. DCM is a leading cause of mortality in patients with diabetes. We used both in vitro and in vivo experiments to investigate the hypothesis that sophocarpine (SPC), a natural quinolizidine alkaloid derived from a Chinese herb, could protect against DCM. We used hyperglycemic myocardial cells and a streptozotocin (STZ)-induced type 1 diabetes mellitus mouse model. SPC protected myocardial cells from hyperglycemia-induced injury by improving mitochondrial function, suppressing inflammation, and inhibiting cardiac apoptosis. The SPC treatment significantly inhibited the activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling in high-glucose-stimulated inflammatory responses. Moreover, SPC significantly slowed the development and progression of DCM in STZ-induced diabetic mice. These results show that SPC suppresses NF-κB-mediated inflammation both in vitro and in vivo and may be used to treat DCM.

Triglyceride glucose index (TyG) and waist circumstance have been well documented to be highly correlated with hypertension. However, the joint effect of waist circumstance and TyG on the risk of hypertension is unknown in middle-aged and elderly Chinese adults. The purpose of this study was to investigate the association between TyG and the risk of new-onset hypertension in middle-aged and elderly Chinese individuals with different waist circumstances. The multicentred prospective cohort study was conducted in 28 provinces of China including a total of 5865 eligible participants aged ≥ 45 years old. Cox regression was performed to examine the relationship of TyG index and hypertension with adjustments for the pertinent variables. Besides, the relationship was explored in different groups on the basis of waist circumstance. There was no significant correlation between TyG index and new-onset hypertension after adjustment for pertinent variables (hazards ratio [HR]: 0.99; 95% confidence interval [CI]: 0.80–1.24). When the association was explored in different waist circumstance groups, multivariate cox regression analyses revealed that TyG was an independent factor positively associated with the risk of hypertension in central obesity prophase group (HR: 1.57; 95% CI 1.13–2.16). Among individuals with central obesity, relative to population with lower TyG (Q1: 4.96–8.18), people who had higher TyG (Q3: 8.52–8.95; Q4: 8.95–12.14) were associated with significantly lower HR for hypertension. There was no conspicuous correlation between TyG index with new-onset hypertension in normal waist circumstance (HR: 1.05; 95% CI 0.84–1.30). The research demonstrated the positive relationship of TyG with risk of hypertension among individuals with central obesity prophase, negative relationship of TyG with hypertension among population with central obesity and inconspicuous correlation of TyG with hypertension among individuals with normal waist. In conclusion, the study findings supported the combined effects of TyG index and waist circumference in predicting hypertension in middle-aged and elderly Chinese individuals.