[Chemical exposome and non-targeted approaches].
Exposome chimique et approches « non ciblées » - Un changement de paradigme pour évaluer l’exposition des populations aux contaminants chimiques.
Journal
Medecine sciences : M/S
ISSN: 1958-5381
Titre abrégé: Med Sci (Paris)
Pays: France
ID NLM: 8710980
Informations de publication
Date de publication:
Oct 2021
Oct 2021
Historique:
entrez:
14
10
2021
pubmed:
15
10
2021
medline:
4
2
2022
Statut:
ppublish
Résumé
The technological advances in high-resolution mass spectrometry (HRMS), associated with the development of bioinformatics tools, allows the simultaneous detection of tens of thousands of chemical signals in biological matrices, including exogenous (i.e. xenobiotics) and endogenous molecules. These novel approaches based on HRMS, called "non-targeted" approaches, provide a unique opportunity to capture exposures to a wide range of chemicals (i.e. the internal chemical exposome) in populations, and to better understand the links between chemical exposures and the occurrence of chronic diseases. Exposome chimique et approches « non ciblées » - Un changement de paradigme pour évaluer l’exposition des populations aux contaminants chimiques. Les avancées techniques en spectrométrie de masse à haute résolution (SMHR), concomitantes au développement d’outils bio-informatiques, permettent aujourd’hui la détection simultanée de plusieurs dizaines de milliers de signaux chimiques dans des matrices biologiques, correspondant à des molécules d’origine exogène (dont les xénobiotiques) et à des molécules endogènes. Ces nouvelles approches reposant sur la SMHR, dites « non ciblées » car sans a priori, représentent une opportunité unique pour caractériser à grande échelle l’exposition de populations humaines aux composés chimiques (ce que l’on appelle exposome chimique interne), et ainsi mieux appréhender leur rôle dans la survenue de maladies chroniques.
Autres résumés
Type: Publisher
(fre)
Exposome chimique et approches « non ciblées » - Un changement de paradigme pour évaluer l’exposition des populations aux contaminants chimiques.
Identifiants
pubmed: 34647878
doi: 10.1051/medsci/2021088
pii: msc200481
doi:
Types de publication
Journal Article
Langues
fre
Sous-ensembles de citation
IM
Pagination
895-901Informations de copyright
© 2021 médecine/sciences – Inserm.
Références
Cui Y, Balshaw DM, Kwok RK, et al. The exposome: embracing the complexity for discovery in environmental health. Environ Health Perspect 2016 ; 124 : A137–A140.
Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet 2008 ; 40 : 695–701.
Manolio TA, Collins FS, Cox NJet al. Finding the missing heritability of complex diseases. Nature 2009 ; 461 : 747–753.
Rappaport SMGenetic factors are not the major causes of chronic diseases. PLoS One 2016 ; 11 : e0154387.
Vermeulen R, Schymanski EL, Barabasi AL, Miller GW. The exposome and health: where chemistry meets biology. Science 2020; 367 : 392–6.
Wild CP. Complementing the genome with an exposome: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol Biomarkers Prev 2005 ; 14 : 1847–1850.
Wild CPThe exposome: from concept to utility. Int J Epidemiol 2012 ; 41 : 24–32.
Rappaport SM, Barupal DK, Wishart Det al. The blood exposome and its role in discovering causes of disease. Environ Health Perspect 2014 ; 122 : 769–774.
Dennis KK, Marder E, Balshaw DMet al. Biomonitoring in the era of the exposome. Environ Health Perspect 2017 ; 125 : 502–510.
Bessonneau V, Gerona RR, Trowbridge J, et al. Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites. Sci Rep 2021; 11 : 7607–22.
Barouki R, Gluckman PD, Grandjean Pet al. Developmental origins of non-communicable disease: implications for research and public health. Environ Health 2012 ; 11 : 42.
Chevrier C, Limon G, Monfort Cet al. Urinary biomarkers of prenatal atrazine exposure and adverse birth outcomes in the PELAGIE birth cohort. Environ Health Perspect 2011 ; 119 : 1034–1041.
Barr DB, Bishop A, Needham LLConcentrations of xenobiotic chemicals in the maternal-fetal unit. Reprod Toxicol 2007 ; 23 : 260–266.
David A, Chaker J, Léger T, et al. Acetaminophen metabolism revisited using non-targeted analyses: Implications for human biomonitoring. Environ Int 2021; 149 : 106388.
Neveu V, Moussy A, Rouaix Het al. Exposome-explorer: a manually-curated database on biomarkers of exposure to dietary and environmental factors. Nucleic Acids Res 2017 ; 45 : D979–D984.
Wishart DS, Tzur D, Knox Cet al. hmdb: the human metabolome database. Nucleic Acids Res 2007 ; 35 : D521–D526.
Psychogios N, Hau DD, Peng Jet al. The human serum metabolome. PLoS One 2011 ; 6 : e16957.
Uppal K, Walker DI, Jones DPxMSannotator: an R package for network-based annotation of high-resolution metabolomics data. Anal Chem 2017 ; 89 : 1063–1067.
Tsugawa H, Cajka T, Kind Tet al. MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat Methods 2015 ; 12 : 523–526.
Chaker J, Gilles E, Léger T, et al. From metabolomics to HRMS-based exposomics: adapting peak picking and developing scoring for MS1 suspect screening. Anal Chem 2021; 93 : 1792–800.
Schymanski EL, Jeon J, Gulde Ret al. Identifying small molecules via high resolution mass spectrometry: communicating confidence. Environ Sci Technol 2014 ; 48 : 2097–2098.
Vrijheid M, Slama R, Robinson Oet al. The human early-life exposome (helix): project rationale and design. Environ Health Perspect 2014 ; 12 : 535–544.
Vineis P, Chadeau-Hyam M, Gmuender Het al. The exposome in practice: design of the EXPOsOMICS project. Int J Hyg Environ Health 2017 ; 220 : 142–151.
Balshaw DM, Collman GW, Gray KA, Thompson CLThe children’s health exposure analysis resource (chear): enabling research into the environmental influences on children’s health outcomes. Curr Opin Pediatr 2017 ; 29 : 385–389.