Exposure to persistent organic pollutants alters the serum metabolome in non-obese diabetic mice

Abstract

Introduction: Autoimmune disorders such as type 1 diabetes (T1D) are believed to be caused by the interplay between several genetic and environmental factors. Elucidation of the role of environmental factors in metabolic and immune dysfunction leading to autoimmune disease is not yet well characterized.

Objectives: Here we investigated the impact of exposure to a mixture of persistent organic pollutants (POPs) on the metabolome in non-obese diabetic (NOD) mice, an experimental model of T1D. The mixture contained organochlorides, organobromides, and per- and polyfluoroalkyl substances (PFAS).

Methods: Analysis of molecular lipids (lipidomics) and bile acids in serum samples was performed by UPLC-Q-TOF/MS, while polar metabolites were analyzed by GC-Q-TOF/MS.

Results: Experimental exposure to the POP mixture in these mice led to several metabolic changes, which were similar to those previously reported as associated with PFAS exposure, as well as risk of T1D in human studies. This included an increase in the levels of sugar derivatives, triacylglycerols and lithocholic acid, and a decrease in long chain fatty acids and several lipid classes, including phosphatidylcholines, lysophosphatidylcholines and sphingomyelins.

Conclusion: Taken together, our study demonstrates that exposure to POPs results in an altered metabolic signature previously associated with autoimmunity.

Keywords: Environmental exposure; Exposomics; Metabolomics; Perfluorinated alkyl substances; Persistent organic pollutants; Type 1 diabetes.

Fig. 1

Spearman’s correlations between PFAS and lipid classes (A), bile acids (B) polar metabolites (C), including values from all 22 NOD mouse blood serum samples. Significant correlations marked with *p < 0.05, **p < 0.01 and ***p < 0.001. Positive correlation showed in blue and negative in red

Fig. 2

A and B PCA plots of metabolic profiles in NOD mice after exposure to a POP mixture for control (green), low exposure (blue) and high exposure (red) groups C Heatmap of 50 significantly-altered metabolites (ANOVA, p < 0.05) with the most contrasting patterns. Samples are sorted by the exposure group and metabolites clustered based on Ward’s clustering algorithm.

Fig. 3

Spearman’s correlations between bile acids and lipid classes in NOD mouse blood serum samples. Significant correlations marked with *p < 0.05, **p < 0.01 and ***p < 0.001

Fig. 4

Pathway analysis diagram representing, significantly-elevated metabolites/lipid classes in red (p < 0.05) and pink (0.05 < p < 0.1), as well as downregulated metabolite groups in blue (p < 0.05) and light blue (0.05 < p < 0.1), in mice after exposure to POPs Metabolites showing no significant changes are marked in light gray