EDP Sciences logo
Authentification abonné
Rechercher
Menu
Accueil Tous les numéros Volume 37 / Numéro 10 (Octobre 2021) Med Sci (Paris), 37 10 (2021) 895-901 Références
Exposome
Open Access
Numéro
Med Sci (Paris)
Volume 37, Numéro 10, Octobre 2021
Exposome
Page(s) 895 - 901
Section M/S Revues
DOI https://doi.org/10.1051/medsci/2021088
Publié en ligne 14 octobre 2021
  1. 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. [PubMed] [Google Scholar]
  2. Bodmer W, Bonilla C. Common and rare variants in multifactorial susceptibility to common diseases. Nat Genet 2008 ; 40 : 695–701. [CrossRef] [PubMed] [Google Scholar]
  3. Manolio TA, Collins FS, Cox NJet al. Finding the missing heritability of complex diseases. Nature 2009 ; 461 : 747–753. [CrossRef] [PubMed] [Google Scholar]
  4. Rappaport SMGenetic factors are not the major causes of chronic diseases. PLoS One 2016 ; 11 : e0154387. [CrossRef] [PubMed] [Google Scholar]
  5. Vermeulen R, Schymanski EL, Barabasi AL, Miller GW. The exposome and health: where chemistry meets biology. Science 2020; 367 : 392–6. [Google Scholar]
  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. [CrossRef] [PubMed] [Google Scholar]
  7. Wild CPThe exposome: from concept to utility. Int J Epidemiol 2012 ; 41 : 24–32. [CrossRef] [PubMed] [Google Scholar]
  8. 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. [CrossRef] [PubMed] [Google Scholar]
  9. Dennis KK, Marder E, Balshaw DMet al. Biomonitoring in the era of the exposome. Environ Health Perspect 2017 ; 125 : 502–510. [CrossRef] [PubMed] [Google Scholar]
  10. 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. [CrossRef] [PubMed] [Google Scholar]
  11. Barouki R, Gluckman PD, Grandjean Pet al. Developmental origins of non-communicable disease: implications for research and public health. Environ Health 2012 ; 11 : 42. [CrossRef] [PubMed] [Google Scholar]
  12. 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. [CrossRef] [PubMed] [Google Scholar]
  13. Barr DB, Bishop A, Needham LLConcentrations of xenobiotic chemicals in the maternal-fetal unit. Reprod Toxicol 2007 ; 23 : 260–266. [CrossRef] [PubMed] [Google Scholar]
  14. David A, Chaker J, Léger T, et al. Acetaminophen metabolism revisited using non-targeted analyses: Implications for human biomonitoring. Environ Int 2021; 149 : 106388. [CrossRef] [PubMed] [Google Scholar]
  15. 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. [CrossRef] [PubMed] [Google Scholar]
  16. Wishart DS, Tzur D, Knox Cet al. hmdb: the human metabolome database. Nucleic Acids Res 2007 ; 35 : D521–D526. [CrossRef] [PubMed] [Google Scholar]
  17. Psychogios N, Hau DD, Peng Jet al. The human serum metabolome. PLoS One 2011 ; 6 : e16957. [CrossRef] [PubMed] [Google Scholar]
  18. Uppal K, Walker DI, Jones DPxMSannotator: an R package for network-based annotation of high-resolution metabolomics data. Anal Chem 2017 ; 89 : 1063–1067. [CrossRef] [PubMed] [Google Scholar]
  19. Tsugawa H, Cajka T, Kind Tet al. MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis. Nat Methods 2015 ; 12 : 523–526. [CrossRef] [PubMed] [Google Scholar]
  20. 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. [CrossRef] [PubMed] [Google Scholar]
  21. Schymanski EL, Jeon J, Gulde Ret al. Identifying small molecules via high resolution mass spectrometry: communicating confidence. Environ Sci Technol 2014 ; 48 : 2097–2098. [CrossRef] [PubMed] [Google Scholar]
  22. Vrijheid M, Slama R, Robinson Oet al. The human early-life exposome (helix): project rationale and design. Environ Health Perspect 2014 ; 12 : 535–544. [Google Scholar]
  23. 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. [CrossRef] [PubMed] [Google Scholar]
  24. 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. [CrossRef] [PubMed] [Google Scholar]

Les statistiques affichées correspondent au cumul d'une part des vues des résumés de l'article et d'autre part des vues et téléchargements de l'article plein-texte (PDF, Full-HTML, ePub... selon les formats disponibles) sur la platefome Vision4Press.

Les statistiques sont disponibles avec un délai de 48 à 96 heures et sont mises à jour quotidiennement en semaine.

Le chargement des statistiques peut être long.