Perfluoroalkyl Substances (PFAS) and Red Blood Cell Folate Levels in the U.S. Adult Population, NHANES

Abstract

BACKGROUND AND AIM: Adequate folate is essential for many physiological processes, and low folate levels have been associated with cardiovascular disease, anemia, and various health outcomes, including developmental outcomes in relation to low folate status during pregnancy. On the other hand, perfluoroalkyl substance (PFAS) have been associated with multiple health outcomes, with scarce data on the mechanistic pathways by which these substances exert their effects. Our objective is to investigate the individual and joint associations of a mixture of PFAS with red blood cell (RBC) folate concentrations in the adult U.S. population. METHODS: We assessed associations of five chemical biomarkers of 8961 participants ages 18-80 from the U.S. National Health and Nutrition Examination Survey (2007-2016). RBC folate were quantified using a micro bioassay and mass spectrometry. We estimated covariate-adjusted independent and joint associations between PFAS and RBC folate concentrations and triangulated evidence from three approaches developed to examine chemical mixtures: Exposome Wide Association (ExWAS), Bayesian Kernel Regression (BKMR), and Quantile G-Computation (QgComp). We additionally evaluated potential effect modification by sex. RESULTS:The geometric mean RBC folate was 468 µg/L (geometric standard deviation: 1.5 µg/L). In ExWAS analyses, all PFAS were associated with lower RBC folate concentrations. For instance, a twofold increase in Perfluorononanoic acid was associated with a 10% (95% CI: 9%, 11%) decrease in RBC folate concentrations. BKMR and QgComp showed convergent results with a one quartile increase in the PFAS mixture associated with comparable decreases in RBC folate concentrations. Associations did not differ between males and females. CONCLUSIONS:This study is the first to examine the associations between PFAS and RBC folate concentrations in a nationally representative sample. These results may deepen our understanding of the mechanistic pathways by which PFAS impact health outcomes. KEYWORDS: PFAS,Folate,Methods,BKMR,ExWAS,G-Computation