Little is known about the association of the single nucleotide polymorphism (SNP) of rs364585 near serine palmitoyl-transferase long-chain base subunit 3 gene (SPTLC3) and serum lipid profiles. The present study was detected the association of the SPTLC3 rs364585 SNP and several environmental factors with serum lipid profiles in the Han and Jing populations. Genotyping of the SPTLC3 rs364585 SNP was performed in 824 unrelated individuals of Han and 783 participants of Jing by polymerase chain reaction and restriction fragment length polymorphism combined with gel electrophoresis, and then confirmed by direct sequencing. There was no significant difference in either genotypic or allelic frequencies between Han and Jing, or between males and females of the both ethnic groups. The levels of serum low-density lipoprotein cholesterol (LDL-C) and the ratio of apolipoprotein (Apo) A1 to ApoB in Han; and total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and LDL-C in Jing were different between the A allele carriers and the A allele non-carriers (P < 0.05-0.001). Subgroup analysis according to sex showed that the levels of LDL-C in Han males; TC and LDL-C in Jing males; and HDL-C and LDL-C in Jing females were different between the A allele carriers and the A allele non-carriers (P < 0.05-0.001), the A allele carriers had higher LDL-C and TC levels, and lower HDL-C levels than the A allele non-carriers. Serum lipid traits were also associated with several environmental factors in the Han and Jing populations, or in males and females of the both ethnic groups. The present study demonstrates the association between the SPTLC3 rs364585 SNP and serum TC, HDL-C and LDL-C levels in our study populations. These associations might have ethnic- and/or sex-specificity. Retrospectively registered.

Background: Previous studies suggest that frailty increases the risk of mortality, but the risk of cardiovascular disease (CVD) and all-cause mortality in Chinese community-dwelling older adults remains understudied. Our aim was to explore the effect of frailty on cardiovascular and all-cause mortality in older adults based on a large-scale prospective survey of community-dwelling older adults in China.Methods: We utilized the 2014–2018 cohort of the Chinese Longitudinal Healthy Longevity Survey and constructed a frailty index (FI) to assess frailty status. Propensity score matching was used to equalize the baseline characteristics of participants to strengthen the reliability of the findings. Hazard ratios and 95% confidence intervals (CIs) were estimated using multivariate Cox models, adjusting for potential confounders, to assess the association between frailty and cardiovascular and all-cause mortality. The relationship between frailty and cardiovascular mortality was further explored using a competing risk model considering death as a competing event. The dose–response relationships between them were estimated using restricted cubic spline models.Results: The results of the multivariate Cox model found that the frailty group had a higher risk of CVD mortality (1.94, 95% CI: 1.43–2.63) and all-cause mortality (1.87, 95% CI: 1.63–2.14) in compared with the non-frailty group. The multivariate competing risks model suggested a higher risk of CVD mortality in the frailty group (1.94, 95% CI: 1.48–2.53). The analysis found no non-linear relationship between FI and the risk of CVD mortality but a non-linear dose–response relationship with the risk of all-cause mortality.Conclusions: Frail older adults demonstrated a stronger risk of CVD and all-cause mortality. Reversing frailty in older adults is therefore expected to reduce the risk of death in older adults.

Background: There is growing evidence that concentrations of environmental pollutants are previously associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship. Methods: We utilized a two-sample Mendelian randomization (MR) approach to investigate how environmental pollution affects the likelihood of developing cardiovascular disease. We primarily employed the inverse variance weighted (IVW) method. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These included maximum likelihood, MR-Egger regression, weighted median method and weighted model methods. Results: Inverse variance weighted estimates suggested that an SD increase in PM2.5 exposure increased the risk of heart failure (OR = 1.40, 95% CI 1.02–1.93, p = 0.0386). We found that an SD increase in PM10 exposure increased the risk of hypertension (OR = 1.45, 95% CI 1.02–2.05, p = 0.03598) and atrial fibrillation (OR = 1.41, 95% CI 1.03–1.94, p = 0.03461). Exposure to chemical or other fumes in a workplace was found to increase the risk of hypertension (OR = 3.08, 95% CI 1.40–6.78, p = 0.005218), coronary artery disease (OR = 1.81, 95% CI 1.00–3.26, p = 0.04861), coronary heart disease (OR = 3.15, 95% CI 1.21–8.16, p = 0.0183) and myocardial infarction (OR = 3.03, 95% CI 1.13–8.17, p = 0.02802). Conclusion: This study reveals the causal relationship between air pollutants and cardiovascular diseases, providing new insights into the protection of cardiovascular diseases.

Background: There is growing evidence that concentrations of DNA methylation are associated with cardiovascular disease; however, it is unclear whether this association reflects a causal relationship. Methods: We utilized a two-sample Mendelian randomization (MR) approach to investigate whether DNA methylation can affect the risk of developing cardiovascular disease in human life. We primarily performed the inverse variance weighted (IVW) method to analyze the causal effect of DNA methylation on multiple cardiovascular diseases. Additionally, to ensure the robustness of our findings, we conducted several sensitivity analyses using alternative methodologies. These analysis methods included maximum likelihood, MR-Egger regression, weighted median method, and weighted model methods. Results: Inverse variance weighted estimates suggested that an SD increase in DNA methylation Hannum age acceleration exposure increased the risk of cardiac arrhythmias (OR = 1.03, 95% CI 1.00–1.05, p = 0.0290) and atrial fibrillation (OR = 1.03, 95% CI 1.00–1.05, p = 0.0022). We also found that an SD increase in DNA methylation PhenoAge acceleration exposure increased the risk of heart failure (OR = 1.01, 95% CI 1.00–1.03, p = 0.0362). Exposure to DNA methylation-estimated granulocyte proportions was found to increase the risk of hypertension (OR = 1.00, 95% CI 1.00–1.0001, p = 0.0291). Exposure to DNA methylation-estimated plasminogen activator inhibitor-1 levels was found to increase the risk of heart failure (OR = 1.00, 95% CI 1.00–1.00, p = 0.0215). Conclusion: This study reveals a causal relationship between DNA methylation and CVD. Exposed to high levels of DNA methylation Hannum age acceleration inhabitants with an increased risk of cardiac arrhythmias and atrial fibrillation. DNA methylation PhenoAge acceleration levels exposure levels were positively associated with the increased risk of developing heart failure. This has important implications for the prevention of cardiovascular diseases.

The Modified Cardiometabolic Index (MCMI), a new composite indicator, combines glucose, lipid metabolism, and fat accumulation levels and serves as an alternative predictor of cardiovascular disease (CVD). However, no prospective evidence exists linking long-term MCMI change patterns to Incident CVD. This study evaluated the association and dose–response relationship between MCMI change patterns and cumulative MCMI (cumMCMI) with incident CVD in middle-aged and older adults from the China Health and Retirement Longitudinal Study (CHARLS, N = 4324) and the English Longitudinal Study of Ageing (ELSA, N = 2707), and compared its predictive ability with cumulative triglyceride-to-glucose (TyG) index. Using K-means and group-based trajectory models, three MCMI change patterns were identified: stable low, moderate, and high-level groups. The Cox model adjusting for covariates revealed that moderate and high-level groups in both cohorts were associated with a significant increased incident CVD risk compared to stable low-level (CHARLS adjusted HR for high-level = 1.33, 95% CI 1.04 to 1.70; ELSA adjusted HR = 1.96, 95% CI 1.08 to 3.56). Restricted mean survival time (RMST) analysis revealed that participants with higher MCMI had a significantly shorter mean CVD-free survival time over the next 5 years (RMST = -0.070, 95% CI -0.119 to -0.021) in CHARLS. Restricted cubic spline (RCS) analysis demonstrated a significant positive linear association between cumMCMI and increased incident CVD risk. Furthermore, time-dependent ROC analyses across 5- to 6-year horizons indicated that cumulative MCMI exhibited slightly better discrimination for incident CVD than cumulative TyG in both CHARLS (AUC = 0.618 vs. 0.599, P = 0.005) and ELSA (AUC = 0.668 vs. 0.633, P = 0.004). These findings indicate that persistently elevated MCMI change patterns and higher cumulative MCMI exposure are independently associated with an increased risk of incident CVD and reduced CVD-free survival among middle-aged and older adults. Compared with cumulative TyG, cumulative MCMI demonstrated slightly better discrimination for CVD risk. Tracking dynamic changes in MCMI over time may serve as an informative, non-invasive surrogate approach to aid in long-term cardiometabolic risk stratification in primary care.