Metal exposure and blood lipid biomarkers in early pregnancy: A cross-sectional study

Recognizing the risk factors for dyslipidemia during pregnancy is crucial for safeguarding the health of both the mothers and the offspring. Growing evidence emerged and suggested links between environmental factors, including metals, and alteration in lipid levels or dyslipidemia in general populations. However, knowledge of the associations during pregnancy remains extremely lacking. Herein, we aimed to explore whether elevated metal exposure constitutes a risk factor for dyslipidemia in pregnant women. Based on the Tongji-Shuangliu Birth Cohort (TSBC), a total of 663 pregnant women were recruited and their urinary levels of 17 metals and blood lipid biomarkers in early pregnancy were measured, namely triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). The multivariable linear regression models revealed that exposure to selected metals during early pregnancy was significantly associated with some important biomarkers. In particular, after natural log-transformed for the levels of lipid biomarkers and metals, copper (Cu) exposure was positively associated with HDL-C (β = 0.024, 95% CI: 0.001, 0.046), while zinc (Zn) was associated with TG (β = 0.062; 95% CI: 0.013, 0.110) and selenium with TC (β = 0.028, 95% CI: 0.004, 0.054). Exposure to rubidium (Rb) was positively associated with multiple lipid biomarkers, including HDL-C (β = 0.020, 95% CI: 0.002, 0.037) and LDL-C (β = 0.022, 95% CI: 0.001, 0.042). Mixture exposure analysis further identified significant associations between Cu and HDL-C, Zn and TG, Rb and HDL-C, when multiple metal exposures were considered in the Bayesian kernel machine regression model simultaneously. Our findings showed that exposure to several metals during early pregnancy was associated with an increased prevalence of blood lipid abnormalities in pregnant women. These findings underscore the potential impact of metal combinations on lipid metabolism and increase our understanding of the risk factors associated with abnormal lipid metabolism during pregnancy.