Metabolomics as a powerful tool to decipher the biological effects of environmental contaminants in humans

Current Opinion in Toxicology

Volumn 8, Issue , 2018, Pages 48-56

  Bonvallot, Nathalie ^a,b   David, Arthur ^a,b   Chalmel, Frédéric ^a,c   Chevrier, Cécile ^a,c   Cordier, Sylvaine ^a,c   Cravedi, Jean Pierre ^d   Zalko, Daniel ^d  

^a UNIVERSITÉ DE RENNES 1   (France)

^b EHESP SCHOOL OF PUBLIC HEALTH   (France)

^c UNIVERSITÉ DE RENNES 1   (France)

^d TOXALIM RESEARCH CENTRE IN FOOD TOXICOLOGY   (France)

Author keywords

Biomarkers; Environmental contaminants; Human exposure; Metabolomics

Indexed keywords

METAL; NEUROTRANSMITTER; PESTICIDE; PLASTICIZER; POLYCYCLIC AROMATIC HYDROCARBON; REACTIVE OXYGEN METABOLITE; VOLATILE ORGANIC COMPOUND;

ENVIRONMENTAL EXPOSURE; GAS CHROMATOGRAPHY; HOMEOSTASIS; HORMONE SYNTHESIS; HUMAN; LIQUID CHROMATOGRAPHY; METABOLOMICS; MITOCHONDRIAL RESPIRATION; NUCLEAR MAGNETIC RESONANCE IMAGING; PERSISTENT ORGANIC POLLUTANT; POLLUTANT; POLLUTION; PRIORITY JOURNAL; REVIEW; STEROIDOGENESIS; ULTRA PERFORMANCE LIQUID CHROMATOGRAPHY;

EID: 85040360854     PISSN: None     EISSN: 24682020     Source Type: Journal    
DOI: 10.1016/j.cotox.2017.12.007     Document Type: Review

References (44)

1. Johnson, C.H., Ivanisevic, J., Siuzdak, G., Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol 17:7 (2016), 451–459.
2. Fiehn, O., Metabolomics – the link between genotypes and phenotypes. Plant Mol Biol 48 (2002), 151–171.
3. Diaz, S.O., Pinto, J., Graça, G., Duarte, I.F., Barros, A.S., Galhano, E., et al. Metabolic biomarkers of prenatal disorders: an exploratory NMR metabonomics study of 2nd trimester maternal urine and blood plasma. J Proteome Res 10:8 (2011), 3732–3742.
4. Kenny, L.C., Broadhurst, D.I., Dunn, W., Brown, M., North, R.A., McCowan, L., et al. Robust early pregnancy prediction of later preeclampsia using metabolomic biomarkers. Hypertension 56:4 (2010), 741–749.
5. Mamas, M., Dunn, W., Neyses, L., Goodacre, R., The role of metabolites and metabolomics in clinically applicable biomarkers of disease. Arch Toxicol 85:1 (2011), 5–17.
6. Kim, K., Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Mol Cell Proteomics 8 (2009), 558–570.
7. Bonvallot, N., Tremblay-Franco, M., Chevrier, C., Canlet, C., Debrauwer, L., Cravedi, J.P., et al. Potential input from metabolomics for exploring and understanding the links between environment and health. J Toxicol Environ Health B Crit Rev 17 (2014), 21–44.
8. Ellis, J., Athersuch, T., Thomas, L., Teichert, F., Perez-Trujillo, M., Svendsen, C., et al. Metabolic profiling detects early effects of environmental and lifestyle exposure to cadmium in a human population. BMC Med, 10(1), 2012, 61.
9. Bonvallot, N., Tremblay-Franco, M., Chevrier, C., Canlet, C., Warembourg, C., Cravedi, J.P., et al. Metabolomics tools for describing complex pesticide exposure in pregnant women in Brittany (France). PLoS One, 8(5), 2013, e64433.
10. Gao, Y., Lu, Y., Huang, S., Gao, L., Liang, X., Wu, Y., et al. Identifying early urinary metabolic changes with long-term environmental exposure to cadmium by mass-spectrometry-based metabolomics. Environ Sci Technol 48:11 (2014), 6409–6418.
11. Zhang, J., Shen, H., Xu, W., Xia, Y., Barr, D.B., Mu, X., et al. Urinary metabolomics revealed arsenic internal dose-related metabolic alterations: a proof-of-concept study in a Chinese male cohort. Environ Sci Technol 48:20 (2014), 12265–12274.
12. Wang, Z., Zheng, Y., Zhao, B., Zhang, Y., Liu, Z., Xu, J., et al. Human metabolic responses to chronic environmental polycyclic aromatic hydrocarbon exposure by a metabolomic approach. J Proteome Res 14:6 (2015), 2583–2593.
13. Jeanneret, F., Tonoli, D., Hochstrasser, D., Saurat, J.-H., Sorg, O., Boccard, J., et al. Evaluation and identification of dioxin exposure biomarkers in human urine by high-resolution metabolomics, multivariate analysis and in vitro synthesis. Toxicol Lett 240:1 (2016), 22–31.
14. Salihovic, S., Ganna, A., Fall, T., Broeckling, C.D., Prenni, J.E., van Bavel, B., et al. The metabolic fingerprint of p,p’-DDE and HCB exposure in humans. Environ Int 88 (2016), 60–66.
15. Xu, Y., Wang, J., Liang, X., Gao, Y., Chen, W., Huang, Q., et al. Urine metabolomics of women from small villages exposed to high environmental cadmium levels. Environ Toxicol Chem 35:5 (2016), 1268–1275.
16. Yuan, T.-H., Chung, M.-K., Lin, C.-Y., Chen, S.-T., Wu, K.-Y., Chan, C.-C., Metabolic profiling of residents in the vicinity of a petrochemical complex. Sci Total Environ 548 (2016), 260–269.
17. Zhang, J., Liu, L., Wang, X., Huang, Q., Tian, M., Shen, H., Low-level environmental phthalate exposure associates with urine metabolome alteration in a Chinese male cohort. Environ Sci Technol 50:11 (2016), 5953–5960.
18. Carrizo, D., Chevallier, O.P., Woodside, J.V., Brennan, S.F., Cantwell, M.M., Cuskelly, G., et al. Untargeted metabolomic analysis of human serum samples associated with exposure levels of Persistent organic pollutants indicate important perturbations in sphingolipids and glycerophospholipids levels. Chemosphere 168 (2017), 731–738.
19. Chen, C.-H.S., Yuan, T.-H., Shie, R.-H., Wu, K.-Y., Chan, C.-C., Linking sources to early effects by profiling urine metabolome of residents living near oil refineries and coal-fired power plants. Environ Int 102 (2017), 87–96.
20. Eguchi, A., Sakurai, K., Watanabe, M., Mori, C., Exploration of potential biomarkers and related biological pathways for PCB exposure in maternal and cord serum: a pilot birth cohort study in Chiba, Japan. Environ Int 102 (2017), 157–164.
21. Khan, A., Park, H., Lee, H.A., Park, B., Gwak, H.S., Lee, H.-R., et al. Elevated metabolites of steroidogenesis and amino acid metabolism in preadolescent female children with high urinary bisphenol A levels: a high-resolution metabolomics study. Toxicol Sci, 2017, 10.1093/toxsci/kfx189.
22. Laine, J.E., Bailey, K.A., Olshan, A.F., Smeester, L., Drobna, Z., Styblo, M., et al. Neonatal metabolomic profiles related to prenatal arsenic exposure. Environ Sci Technol 51:1 (2017), 625–633.
23. Li, H., Wang, M., Liang, Q., Jin, S., Sun, X., Jiang, Y., et al. Urinary metabolomics revealed arsenic exposure related to metabolic alterations in general Chinese pregnant women. J Chromatogr A 1479 (2017), 145–152.
24. Dudka, I., Kossowska, B., Senhadri, H., Latajka, R., Hajek, J., Andrzejak, R., et al. Metabonomic analysis of serum of workers occupationally exposed to arsenic, cadmium and lead for biomarker research: a preliminary study. Environ Int 68 (2014), 71–81.
25. Kuo, C.H., Wang, K.C., Tian, T.F., Tsai, M.H., Chiung, Y.M., Hsiech, C.M., et al. Metabolomic characterization of laborers exposed to welding fumes. Chem Res Toxicol 25:3 (2012), 676–686.
26. Wei, Y., Wang, Z., Chang, C., Fan, T., Su, L., Chen, F., et al. Global metabolomic profiling reveals an association of metal fume exposure and plasma unsaturated fatty acids. PLoS One, 8(10), 2013, e77413.
27. Hosnijeh, F.S., Pechlivanis, A., Keun, H.C., Portengen, L., Bueno-de-Mesquita, H.B., Heederik, D., et al. Serum metabolomic perturbations among workers exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Environ Mol Mutagen 54:7 (2013), 558–565.
28. Jeanneret, F., Boccard, J., Badoud, F., Sorg, O., Tonoli, D., Pelclova, D., et al. Human urinary biomarkers of dioxin exposure: analysis by metabolomics and biologically driven data dimensionality reduction. Toxicol Lett 230:2 (2014), 234–243.
29. Walker, D.I., Uppal, K., Zhang, L., Vermeulen, R., Smith, M., Hu, W., et al. High-resolution metabolomics of occupational exposure to trichloroethylene. Int J Epidemiol 45:5 (2016), 1517–1527.
30. Kaluarachchi, M.R., Boulange, C.L., Garcia-Perez, I., Lindon, J.C., Minet, E.F., Multiplatform serum metabolic phenotyping combined with pathway mapping to identify biochemical differences in smokers. Bioanalysis 8:19 (2016), 2023–2043.
31. Fall, T., Salihovic, S., Brandmaier, S., Nowak, C., Ganna, A., Gustafsson, S., et al. Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes. Diabetologia 59:10 (2016), 2114–2124.
32. Park, W.H., Kang, S., Lee, H.K., Salihovic, S., van, Bavel B., Lind, P.M., et al. Relationships between serum-induced AhR bioactivity or mitochondrial inhibition and circulating polychlorinated biphenyls (PCBs). Sci Rep, 7, 2017, 9383.
33. Bonvallot N, Canlet C, Blas-Y-Estrada F, Gautier R, Tremblay-Franco M, Chevolleau S, et al. Metabolome disruption of pregnant rats and their offspring resulting from repeated exposure to a low dose of a pesticide mixture representative of environmental contamination in Brittany. Under review.
34. Cabaton, N.J., Canlet, C., Wadia, P.R., Tremblay-Franco, M., Gautier, R., Molina, J., et al. Effects of low doses of Bisphenol A on the metabolome of perinatally exposed CD-1 mice. Environ Health Perspect 121:5 (2013), 586–593.
35. Tremblay-Franco, M., Cabaton, N.J., Canlet, C., Gautier, R., Schaeberle, C.M., Jourdan, F., et al. Dynamic metabolic disruption in rats perinatally exposed to low doses of Bisphenol A. PLoS One, 10(10), 2015, e0141698.
36. David, A., Abdul-Sada, A., Lange, A., Tyler, C.R., Hill, E.M., A new approach for plasma (xeno)metabolomics based on solid-phase extraction and nanoflow liquid chromatography-nanoelectrospray ionisation mass spectrometry. J Chromatogr A, 2014, 72–85.
37. David, A., lange, A., Abdul-Sada, A., Tyler, C.R., Hill, E.M., Disruption of the prostaglandin metabolome and characterization of the pharmaceutical exposome in fish exposed to wastewater treatment works effluent as revealed by nanoflow-nanospray mass spectrometry-based metabolomics. Environ Sci Technol 51:1 (2017), 616–624.
38. Chetwynd, A.J., David, A., Hill, E.M., Abdul-Sada, A., Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome. J Mass Spectrom 49:10 (2014), 1063–1069.
39. Southam, A.D., Lange, A., Al-Salhi, R., Hill, E.M., Tyler, C.R., Viant, M.R., Distinguishing between the metabolome and xenobiotic exposome in environmental field samples analysed by direct-infusion mass spectrometry based metabolomics and lipidomics. Metabolomics, 2014, 1050–1058.
40. Crockford, D.J., Maher, A.D., Ahmadi, K.R., 1H NMR and UPLC-MS(E) statistical heterospectroscopy: characterization of drug metabolites (xenometabolome) in epidemiological studies. Anal Chem, 2008, 6835–6844.
41. Jamin, E., Bonvallot, N., Tremblay-Franco, M., Cravedi, J.P., Chevrier, C., Cordier, S., et al. Untargeted profiling of pesticide metabolites by LC-HRMS: an exposomics tool for human exposure evaluation. Anal Bioanal Chem 406 (2014), 1149–1161.
42. Darde, T., Lecluze, E., Becker, E., Potdevin, V., Collin, O., Jégou, B., et al. ChemPSy: identification, classification and prioritization of novel endocrine disruptors by integrating massive toxicogenomics datasets. November 2016, Ten years of “Programme National de Recherche – Environnement Santé Travail, ANSES, Paris.
43. Darde T, Gaurdiault P, Beranger R, Lancien C, Caillarec-Joly A, Sallou O, et al. TOXsIgN: a cross-species repository for toxicogenomics signatures. In revision.
44. National Academies of Sciences, Engineering, and Medicine, Using 21st century science to improve risk-related evaluations. 2017, The National Academies Press, Washington, DC, 10.17226/24635.