The effects of chemical mixtures on lipid profiles in the Korean adult population: threshold and molecular mechanisms for dyslipidemia involved

Abstract

A scarcity of research assesses the effects of exposure to a combination of chemicals on lipid profiles as well as molecular mechanisms related to dyslipidemia. A cross-sectional study of 3692 adults aims to identify the association between chemical mixtures, including blood and urine 26 chemicals, and lipid profiles among Korean adults (aged ≥ 18) using linear regression models, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR). In silico toxicogenomic data-mining, we assessed molecular mechanisms linked with dyslipidemia, including genes, miRNAs, pathways, biological processes, and diseases. In the linear regression models, heavy metals, volatile organic compound metabolites, and phthalate metabolites were found to be related to HDL-C, triglycerides, LDL-C, total lipids, and total cholesterol, and significant trends were observed for these chemical quartiles (p < 0.01). The WQS index was significantly linked with HDL-C, triglycerides, LDL-C, total cholesterol, and total lipids. The qgcomp index also found a significant association between chemicals and HDL-C, triglycerides, and total lipids. In BKMR analysis, the overall effect of the chemical mixture was significantly associated with HDL-C, triglycerides, total cholesterol, and total lipids. We found that mixed chemicals interacted with the PPARA gene and were linked with dyslipidemia. Several pathways ("SREBF and miR33 in cholesterol," "estrogen receptor pathway and lipid homeostasis," and "regulation of PGC-1α"), "negative regulation of hepatocyte apoptotic process," "negative regulation of sequestering of triglycerides," "regulation of hepatocyte apoptotic process," and "negative regulation of cholesterol storage," and "abdominal obesity metabolic syndrome" were identified as key molecular mechanisms that may be affected by mixed chemicals and implicated in the development of dyslipidemia. The highest interaction and expression of miRNAs involved in the process of dyslipidemia were also described. Especially, the cutoff levels for chemical exposure levels related to lipid profiles were also provided.

Keywords: Chemical mixture; Dyslipidemia; Lipid profiles; Modeling; Molecular mechanism.