Literature DB >> 33113464

Plasma metabolites associated with exposure to perfluoroalkyl substances and risk of type 2 diabetes - A nested case-control study.

Tessa Schillemans1, Lin Shi2, Carolina Donat-Vargas3, Kati Hanhineva4, Andreas Tornevi5, Ingegerd Johansson6, Jani Koponen7, Hannu Kiviranta7, Olov Rolandsson8, Ingvar A Bergdahl5, Rikard Landberg9, Agneta Åkesson10, Carl Brunius11.   

Abstract

Perfluoroalkyl substances (PFAS) are widespread persistent environmental pollutants. There is evidence that PFAS induce metabolic perturbations in humans, but underlying mechanisms are still unknown. In this exploratory study, we investigated PFAS-related plasma metabolites for their associations with type 2 diabetes (T2D) to gain potential mechanistic insight in these perturbations. We used untargeted LC-MS metabolomics to find metabolites related to PFAS exposures in a case-control study on T2D (n = 187 matched pairs) nested within the Västerbotten Intervention Programme cohort. Following principal component analysis (PCA), six PFAS measured in plasma appeared in two groups: 1) perfluorononanoic acid, perfluorodecanoic acid and perfluoroundecanoic acid and 2) perfluorohexane sulfonic acid, perfluorooctane sulfonic acid and perfluorooctanoic acid. Using a random forest algorithm, we discovered metabolite features associated with individual PFAS and PFAS exposure groups which were subsequently investigated for associations with risk of T2D. PFAS levels correlated with 171 metabolite features (0.16 ≤ |r| ≤ 0.37, false discovery rate (FDR) adjusted p < 0.05). Out of these, 35 associated with T2D (p < 0.05), with 7 remaining after multiple testing adjustment (FDR < 0.05). PCA of the 35 PFAS- and T2D-related metabolite features revealed two patterns, dominated by glycerophospholipids and diacylglycerols, with opposite T2D associations. The glycerophospholipids correlated positively with PFAS and associated inversely with risk for T2D (Odds Ratio (OR) per 1 standard deviation (1-SD) increase in metabolite PCA pattern score = 0.2; 95% Confidence Interval (CI) = 0.1-0.4). The diacylglycerols also correlated positively with PFAS, but they associated with increased risk for T2D (OR per 1-SD = 1.9; 95% CI = 1.3-2.7). These results suggest that PFAS associate with two groups of lipid species with opposite relations to T2D risk.
Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Metabolomics; Nested case-control study; Perfluoroalkyl substances; Type 2 Diabetes

Year:  2020        PMID: 33113464     DOI: 10.1016/j.envint.2020.106180

Source DB:  PubMed          Journal:  Environ Int        ISSN: 0160-4120            Impact factor:   9.621


  6 in total

Review 1.  Non-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review.

Authors:  Pengfei Guo; Tristan Furnary; Vasilis Vasiliou; Qi Yan; Kate Nyhan; Dean P Jones; Caroline H Johnson; Zeyan Liew
Journal:  Environ Int       Date:  2022-02-26       Impact factor: 9.621

2.  Comparison of untargeted and targeted perfluoroalkyl acids measured in adolescent girls.

Authors:  Lauren M Petrick; Mary S Wolff; Dinesh Barupal; Susan L Teitelbaum
Journal:  Chemosphere       Date:  2021-12-15       Impact factor: 7.086

3.  Exposure to Perfluoro-Octanoic Acid Associated With Upstream Uncoupling of the Insulin Signaling in Human Hepatocyte Cell Line.

Authors:  Luca De Toni; Andrea Di Nisio; Maria Santa Rocca; Diego Guidolin; Alice Della Marina; Loris Bertazza; Stefania Sut; Edoardo Purpura; Micaela Pannella; Andrea Garolla; Carlo Foresta
Journal:  Front Endocrinol (Lausanne)       Date:  2021-09-03       Impact factor: 5.555

4.  Detection of the Disorders of Glycerophospholipids and Amino Acids Metabolism in Lung Tissue From Male COPD Patients.

Authors:  Qian Huang; Xiaojie Wu; Yiya Gu; Ting Wang; Yuan Zhan; Jinkun Chen; Zhilin Zeng; Yongman Lv; Jianping Zhao; Jungang Xie
Journal:  Front Mol Biosci       Date:  2022-03-03

5.  CCDB: A database for exploring inter-chemical correlations in metabolomics and exposomics datasets.

Authors:  Dinesh Kumar Barupal; Priyanka Mahajan; Sadjad Fakouri-Baygi; Robert O Wright; Manish Arora; Susan L Teitelbaum
Journal:  Environ Int       Date:  2022-04-18       Impact factor: 13.352

Review 6.  Exposure to per- and polyfluoroalkyl substances (PFAS) and type 2 diabetes risk.

Authors:  Katherine Roth; Michael C Petriello
Journal:  Front Endocrinol (Lausanne)       Date:  2022-08-05       Impact factor: 6.055

  6 in total

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