Associations of PFAS-related plasma metabolites with cholesterol and triglyceride concentrations.

Schillemans T, Bergdahl IA, Hanhineva K, Shi L, Donat-Vargas C, Koponen J, Kiviranta H, Landberg R, Åkesson A, Brunius C

Environ. Res. 216 (Pt 2) 114570 [2023-01-01; online 2022-10-13]

The wide-spread environmental pollutants per- and polyfluoroalkyl substances (PFAS) have repeatedly been associated with elevated serum cholesterol in humans. However, underlying mechanisms are still unclear. Furthermore, we have previously observed inverse associations with plasma triglycerides. To better understand PFAS-induced effects on lipid pathways we investigated associations of PFAS-related metabolite features with plasma cholesterol and triglyceride concentrations. We used 290 PFAS-related metabolite features that we previously discovered from untargeted liquid chromatography-mass spectometry metabolomics in a case-control study within the Swedish Västerbotten Intervention Programme cohort. Herein, we studied associations of these PFAS-related metabolite features with plasma cholesterol and triglyceride concentrations in plasma samples from 187 healthy control subjects collected on two occasions between 1991 and 2013. The PFAS-related features did not associate with cholesterol, but 50 features were associated with triglycerides. Principal component analysis on these features indicated that one metabolite pattern, dominated by glycerophospholipids, correlated with longer chain PFAS and associated inversely with triglycerides (both cross-sectionally and prospectively), after adjustment for confounders. The observed time-trend of the metabolite pattern resembled that of the longer chain PFAS, with higher levels during the years 2004-2010. Mechanisms linking PFAS exposures to triglycerides may thus occur via longer chain PFAS affecting glycerophospholipid metabolism. If the results reflect a cause-effect association, as implied by the time-trend and prospective analyses, this may affect the general adult population.

Bioinformatics Support for Computational Resources [Service]

Chalmers Mass Spectrometry Infrastructure [Collaborative]

PubMed 36243049

DOI 10.1016/j.envres.2022.114570

Crossref 10.1016/j.envres.2022.114570

pii: S0013-9351(22)01897-7