Exposome References

  • Amann, A., Costello Bde, L., Miekisch, W., Schubert, J., Buszewski, B., Pleil, J., . . . Risby, T. (2014). The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva. J Breath Res, 8(3), 034001. doi: 10.1088/1752-7155/8/3/034001
  • Amann, A., Miekisch, W., Schubert, J., Buszewski, B., Ligor, T., Jezierski, T., . . . Risby, T. (2014). Analysis of exhaled breath for disease detection. Annu Rev Anal Chem (Palo Alto Calif), 7, 455-482. doi: 10.1146/annurev-anchem-071213-020043
  • Arlt, V. M., & Schwerdtle, T. (2011). UKEMS/Dutch EMS-sponsored workshop on biomarkers of exposure and oxidative DNA damage & 7th GUM-32P-postlabelling workshop, University of Munster, Munster, Germany, 28-29 March 2011. Mutagenesis, 26(5), 679-685. doi: 10.1093/mutage/ger036
  • Balbo, S., Turesky, R. J., & Villalta, P. W. (2014). DNA adductomics. Chem Res Toxicol, 27(3), 356-366. doi: 10.1021/tx4004352
  • Bisgaard, H., Bonnelykke, K., & Stokholm, J. (2014). Immune-mediated diseases and microbial exposure in early life. Clin Exp Allergy, 44(4), 475-481. doi: 10.1111/cea.12291
  • Bisgaard, H., Vissing, N. H., Carson, C. G., Bischoff, A. L., Folsgaard, N. V., Kreiner-Moller, E., . . . Bonnelykke, K. (2013). Deep phenotyping of the unselected COPSAC2010 birth cohort study. Clin Exp Allergy, 43(12), 1384-1394. doi: 10.1111/cea.12213
  • Bogdanos, D. P., Smyk, D. S., Invernizzi, P., Rigopoulou, E. I., Blank, M., Pouria, S., & Shoenfeld, Y. (2013). Infectome: a platform to trace infectious triggers of autoimmunity. Autoimmun Rev, 12(7), 726-740. doi: 10.1016/j.autrev.2012.12.005
  • Bogdanos, D. P., Smyk, D. S., Invernizzi, P., Rigopoulou, E. I., Blank, M., Sakkas, L., . . . Shoenfeld, Y. (2013). Tracing environmental markers of autoimmunity: introducing the infectome. Immunol Res, 56(2-3), 220-240. doi: 10.1007/s12026-013-8399-6
  • Buck Louis, G. M., Schisterman, E. F., Sweeney, A. M., Wilcosky, T. C., Gore-Langton, R. E., Lynch, C. D., . . . Sundaram, R. (2011). Designing prospective cohort studies for assessing reproductive and developmental toxicity during sensitive windows of human reproduction and development–the LIFE Study.Paediatr Perinat Epidemiol, 25(5), 413-424. doi: 10.1111/j.1365-3016.2011.01205.x
  • Buck Louis, G. M., Yeung, E., Sundaram, R., Laughon, S. K., & Zhang, C. (2013). The exposome–exciting opportunities for discoveries in reproductive and perinatal epidemiology. Paediatr Perinat Epidemiol, 27(3), 229-236. doi: 10.1111/ppe.12040
  • Buhimschi, I. A., & Buhimschi, C. S. (2012). Proteomics/diagnosis of chorioamnionitis and of relationships with the fetal exposome. Semin Fetal Neonatal Med, 17(1), 36-45. doi: 10.1016/j.siny.2011.10.002
  • Burwell, R. G., Dangerfield, P. H., Moulton, A., & Grivas, T. B. (2011). Adolescent idiopathic scoliosis (AIS), environment, exposome and epigenetics: a molecular perspective of postnatal normal spinal growth and the etiopathogenesis of AIS with consideration of a network approach and possible implications for medical therapy. Scoliosis, 6(1), 26. doi: 10.1186/1748-7161-6-26
  • Chadeau-Hyam, M., Campanella, G., Jombart, T., Bottolo, L., Portengen, L., Vineis, P., . . . Vermeulen, R. C. (2013). Deciphering the complex: methodological overview of statistical models to derive OMICS-based biomarkers. Environ Mol Mutagen, 54(7), 542-557. doi: 10.1002/em.21797
  • Chen, C. K., Bruce, M., Tyler, L., Brown, C., Garrett, A., Goggins, S., . . . Skelton, T. (2013). Analysis of an environmental exposure health questionnaire in a metropolitan minority population utilizing logistic regression and Support Vector Machines. J Health Care Poor Underserved, 24(1 Suppl), 153-171. doi: 10.1353/hpu.2013.0046
  • Colafrancesco, S., Agmon-Levin, N., Perricone, C., & Shoenfeld, Y. (2013). Unraveling the soul of autoimmune diseases: pathogenesis, diagnosis and treatment adding dowels to the puzzle. Immunol Res, 56(2-3), 200-205. doi: 10.1007/s12026-013-8429-4
  • Coughlin, S. S. (2014). Toward a road map for global -omics: a primer on -omic technologies. Am J Epidemiol, 180(12), 1188-1195. doi: 10.1093/aje/kwu262
  • Ellis, J. K., Athersuch, T. J., Thomas, L. D., Teichert, F., Perez-Trujillo, M., Svendsen, C., . . . Keun, H. C. (2012). Metabolic profiling detects early effects of environmental and lifestyle exposure to cadmium in a human population. BMC Med, 10, 61. doi: 10.1186/1741-7015-10-61
  • Fiocchi, C. (2012). Towards a ‘cure’ for IBD. Dig Dis, 30(4), 428-433. doi: 10.1159/000338148
  • Fiocchi, C. (2014). Integrating Omics: The Future of IBD? Dig Dis, 32 Suppl 1, 96-102. doi: 10.1159/000367836
  • Gari, M., Bosch, C., Grimalt, J. O., & Sunyer, J. (2014). Impacts of atmospheric chlor-alkali factory emissions in surrounding populations. Environ Int, 65, 1-8. doi: 10.1016/j.envint.2013.12.008
  • Go, Y. M., & Jones, D. P. (2014). Redox biology: interface of the exposome with the proteome, epigenome and genome. Redox Biol, 2, 358-360. doi: 10.1016/j.redox.2013.12.032
  • Go, Y. M., Walker, D. I., Soltow, Q. A., Uppal, K., Wachtman, L. M., Strobel, F. H., . . . Jones, D. P. (2014). Metabolome-wide association study of phenylalanine in plasma of common marmosets. Amino Acids. doi: 10.1007/s00726-014-1893-x
  • Golding, J., Gregory, S., Iles-Caven, Y., Lingam, R., Davis, J. M., Emmett, P., . . . Hibbeln, J. R. (2014). Parental, prenatal, and neonatal associations with ball skills at age 8 using an exposome approach. J Child Neurol, 29(10), 1390-1398. doi: 10.1177/0883073814530501
  • Grosdidier, S., Ferrer, A., Faner, R., Pinero, J., Roca, J., Cosio, B., . . . Furlong, L. I. (2014). Network medicine analysis of COPD multimorbidities. Respir Res, 15(1), 111. doi: 10.1186/s12931-014-0111-4
  • Hochard, A., Oumata, N., Bettayeb, K., Gloulou, O., Fant, X., Durieu, E., . . . Meijer, L. (2013). Aftins increase amyloid-beta42, lower amyloid-beta38, and do not alter amyloid-beta40 extracellular production in vitro: toward a chemical model of Alzheimer’s disease? J Alzheimers Dis, 35(1), 107-120. doi: 10.3233/jad-121777
  • Hoeke, H., Roeder, S., Bertsche, T., Lehmann, I., Borte, M., von Bergen, M., & Wissenbach, D. K. (2014). Monitoring of drug intake during pregnancy by questionnaires and LC-MS/MS drug urine screening: evaluation of both monitoring methods. Drug Test Anal. doi: 10.1002/dta.1767
  • Jones, D. P., Park, Y., & Ziegler, T. R. (2012). Nutritional metabolomics: progress in addressing complexity in diet and health. Annu Rev Nutr, 32, 183-202. doi: 10.1146/annurev-nutr-072610-145159
  • Juarez, P. (2013). Sequencing the public health genome. J Health Care Poor Underserved, 24(1 Suppl), 114-120. doi: 10.1353/hpu.2013.0035
  • Juarez, P. D., Matthews-Juarez, P., Hood, D. B., Im, W., Levine, R. S., Kilbourne, B. J., . . . Lichtveld, M. Y. (2014). The public health exposome: a population-based, exposure science approach to health disparities research. Int J Environ Res Public Health, 11(12), 12866-12895.
  • Juarez, P. D., Matthews-Juarez, P., Hood, D. B., Im, W., Levine, R. S., Kilbourne, B. J., . . . Lichtveld, M. Y. (2014). The public health exposome: a population-based, exposure science approach to health disparities research. Int J Environ Res Public Health, 11(12), 12866-12895. doi: 10.3390/ijerph111212866
  • Kortenkamp, A. (2014). Low dose mixture effects of endocrine disrupters and their implications for regulatory thresholds in chemical risk assessment. Curr Opin Pharmacol, 19, 105-111. doi: 10.1016/j.coph.2014.08.006
  • Langston, M. A., Levine, R. S., Kilbourne, B. J., Rogers, G. L., Kershenbaum, A. D., Baktash, S. H., . . . Juarez, P. D. (2014). Scalable combinatorial tools for health disparities research. Int J Environ Res Public Health, 11(10), 10419-10443. doi: 10.3390/ijerph111010419
  • Leroy, B., Fournier, J. L., Ishioka, C., Monti, P., Inga, A., Fronza, G., & Soussi, T. (2013). The TP53 website: an integrative resource centre for the TP53 mutation database and TP53 mutant analysis. Nucleic Acids Res, 41(Database issue), D962-969. doi: 10.1093/nar/gks1033
  • Lewis, R. M., Demmelmair, H., Gaillard, R., Godfrey, K. M., Hauguel-de Mouzon, S., Huppertz, B., . . . Desoye, G. (2013). The placental exposome: placental determinants of fetal adiposity and postnatal body composition. Ann Nutr Metab, 63(3), 208-215. doi: 10.1159/000355222
  • Li-Pook-Than, J., & Snyder, M. (2013). iPOP goes the world: integrated personalized Omics profiling and the road toward improved health care. Chem Biol, 20(5), 660-666. doi: 10.1016/j.chembiol.2013.05.001
  • Lochhead, P., Chan, A. T., Nishihara, R., Fuchs, C. S., Beck, A. H., Giovannucci, E., & Ogino, S. (2015). Etiologic field effect: reappraisal of the field effect concept in cancer predisposition and progression. Mod Pathol, 28(1), 14-29. doi: 10.1038/modpathol.2014.81
  • Lopez-Campos, G., Bellazzi, R., & Martin-Sanchez, F. (2013). INDIV-3D. A new model for INdividual Data Integration and Visualisation using spatial coordinates. Stud Health Technol Inform, 190, 172-174.
  • Lyon, D. E., Starkweather, A. R., Montpetit, A., Menzies, V., & Jallo, N. (2014). A biobehavioral perspective on telomere length and the exposome. Biol Res Nurs, 16(4), 448-455. doi: 10.1177/1099800414522689
  • Maitre, L., Fthenou, E., Athersuch, T., Coen, M., Toledano, M. B., Holmes, E., . . . Keun, H. C. (2014). Urinary metabolic profiles in early pregnancy are associated with preterm birth and fetal growth restriction in the Rhea mother-child cohort study. BMC Med, 12, 110. doi: 10.1186/1741-7015-12-110
  • Martin Sanchez, F., Gray, K., Bellazzi, R., & Lopez-Campos, G. (2014). Exposome informatics: considerations for the design of future biomedical research information systems. J Am Med Inform Assoc, 21(3), 386-390. doi: 10.1136/amiajnl-2013-001772
  • Miller, D. B., & O’Callaghan, J. P. (2015). Biomarkers of Parkinson’s disease: Present and future. Metabolism, 64(3 Suppl 1), S40-46. doi: 10.1016/j.metabol.2014.10.030
  • Nakamura, J., Mutlu, E., Sharma, V., Collins, L., Bodnar, W., Yu, R., . . . Swenberg, J. (2014). The endogenous exposome. DNA Repair (Amst), 19, 3-13. doi: 10.1016/j.dnarep.2014.03.031
  • Nieuwenhuijsen, M. J., Donaire-Gonzalez, D., Foraster, M., Martinez, D., & Cisneros, A. (2014). Using personal sensors to assess the exposome and acute health effects. Int J Environ Res Public Health, 11(8), 7805-7819. doi: 10.3390/ijerph110807805
  • Ogino, S., Lochhead, P., Giovannucci, E., Meyerhardt, J. A., Fuchs, C. S., & Chan, A. T. (2014). Discovery of colorectal cancer PIK3CA mutation as potential predictive biomarker: power and promise of molecular pathological epidemiology. Oncogene, 33(23), 2949-2955. doi: 10.1038/onc.2013.244
  • Paoloni-Giacobino, A. (2011). Post genomic decade–the epigenome and exposome challenges. Swiss Med Wkly, 141, w13321. doi: 10.4414/smw.2011.13321
  • Patel, C. J., & Ioannidis, J. P. (2014). Placing epidemiological results in the context of multiplicity and typical correlations of exposures. J Epidemiol Community Health, 68(11), 1096-1100. doi: 10.1136/jech-2014-204195
  • Patel, C. J., & Manrai, A. K. (2015). Development of exposome correlation globes to map out environment-wide associations. Pac Symp Biocomput, 20, 231-242.
  • Pavanello, S., & Lotti, M. (2012). Biological monitoring of carcinogens: current status and perspectives. Arch Toxicol, 86(4), 535-541. doi: 10.1007/s00204-011-0793-z
  • Peters, A., Hoek, G., & Katsouyanni, K. (2012). Understanding the link between environmental exposures and health: does the exposome promise too much? J Epidemiol Community Health, 66(2), 103-105. doi: 10.1136/jech-2011-200643
  • Pleil, J. D. (2012). Categorizing biomarkers of the human exposome and developing metrics for assessing environmental sustainability. J Toxicol Environ Health B Crit Rev, 15(4), 264-280. doi: 10.1080/10937404.2012.672148
  • Pleil, J. D., & Stiegel, M. A. (2013). Evolution of environmental exposure science: using breath-borne biomarkers for “discovery” of the human exposome.Anal Chem, 85(21), 9984-9990. doi: 10.1021/ac402306f
  • Pleil, J. D., Stiegel, M. A., & Sobus, J. R. (2011). Breath biomarkers in environmental health science: exploring patterns in the human exposome. J Breath Res, 5(4), 046005. doi: 10.1088/1752-7155/5/4/046005
  • Pleil, J. D., Stiegel, M. A., Sobus, J. R., Liu, Q., & Madden, M. C. (2011). Observing the human exposome as reflected in breath biomarkers: heat map data interpretation for environmental and intelligence research. J Breath Res, 5(3), 037104. doi: 10.1088/1752-7155/5/3/037104
  • Polacco, B. J., Purvine, S. O., Zink, E. M., Lavoie, S. P., Lipton, M. S., Summers, A. O., & Miller, S. M. (2011). Discovering mercury protein modifications in whole proteomes using natural isotope distributions observed in liquid chromatography-tandem mass spectrometry. Mol Cell Proteomics, 10(8), M110.004853. doi: 10.1074/mcp.M110.004853
  • Rappaport, S. M. (2012). Biomarkers intersect with the exposome. Biomarkers, 17(6), 483-489. doi: 10.3109/1354750x.2012.691553
  • Rappaport, S. M. (2012). Discovering environmental causes of disease. J Epidemiol Community Health, 66(2), 99-102. doi: 10.1136/jech-2011-200726
  • Rappaport, S. M., Barupal, D. K., Wishart, D., Vineis, P., & Scalbert, A. (2014). The blood exposome and its role in discovering causes of disease. Environ Health Perspect, 122(8), 769-774. doi: 10.1289/ehp.1308015
  • Rappaport, S. M., Li, H., Grigoryan, H., Funk, W. E., & Williams, E. R. (2012). Adductomics: characterizing exposures to reactive electrophiles. Toxicol Lett, 213(1), 83-90. doi: 10.1016/j.toxlet.2011.04.002
  • Rogler, G., & Vavricka, S. (2015). Exposome in IBD: Recent Insights in Environmental Factors that Influence the Onset and Course of IBD. Inflamm Bowel Dis, 21(2), 400-408. doi: 10.1097/mib.0000000000000229
  • Shen, H., Xu, W., Peng, S., Scherb, H., She, J., Voigt, K., . . . Schramm, K. W. (2014). Pooling samples for “top-down” molecular exposomics research: the methodology. Environ Health, 13(1), 8. doi: 10.1186/1476-069x-13-8
  • Simon, E., van Velzen, M., Brandsma, S. H., Lie, E., Loken, K., de Boer, J., . . . Lamoree, M. H. (2013). Effect-directed analysis to explore the polar bear exposome: identification of thyroid hormone disrupting compounds in plasma.Environ Sci Technol, 47(15), 8902-8912. doi: 10.1021/es401696u
  • Smolders, R., & De Boever, P. (2014). Perspectives for environment and health research in Horizon 2020: dark ages or golden era? Int J Hyg Environ Health, 217(8), 891-896. doi: 10.1016/j.ijheh.2014.05.003
  • Stahler, G. J., Mennis, J., & Baron, D. A. (2013). Geospatial technology and the “exposome”: new perspectives on addiction. Am J Public Health, 103(8), 1354-1356. doi: 10.2105/ajph.2013.301306
  • Su, L. J., Fiehn, O., Maruvada, P., Moore, S. C., O’Keefe, S. J., Wishart, D. S., & Zanetti, K. A. (2014). The use of metabolomics in population-based research.Adv Nutr, 5(6), 785-788. doi: 10.3945/an.114.006494
  • Sugimura, H., Tao, H., Suzuki, M., Mori, H., Tsuboi, M., Matsuura, S., . . . Matsuda, T. (2011). Genetic susceptibility to lung cancer. Front Biosci (Schol Ed), 3, 1463-1477.
  • Vrijens, K., Bollati, V., & Nawrot, T. S. (2015). MicroRNAs as Potential Signatures of Environmental Exposure or Effect: A Systematic Review. Environ Health Perspect. doi: 10.1289/ehp.1408459
  • Vrijheid, M. (2014). The exposome: a new paradigm to study the impact of environment on health. Thorax, 69(9), 876-878. doi: 10.1136/thoraxjnl-2013-204949
  • Vrijheid, M., Slama, R., Robinson, O., Chatzi, L., Coen, M., van den Hazel, P., . . . Nieuwenhuijsen, M. J. (2014). The human early-life exposome (HELIX): project rationale and design. Environ Health Perspect, 122(6), 535-544. doi: 10.1289/ehp.1307204
  • Wagner, M., Schlusener, M. P., Ternes, T. A., & Oehlmann, J. (2013). Identification of putative steroid receptor antagonists in bottled water: combining bioassays and high-resolution mass spectrometry. PLoS One, 8(8), e72472. doi: 10.1371/journal.pone.0072472
  • Wild, C. P. (2011). Future research perspectives on environment and health: the requirement for a more expansive concept of translational cancer research.Environ Health, 10 Suppl 1, S15. doi: 10.1186/1476-069x-10-s1-s15
  • Wild, C. P., Scalbert, A., & Herceg, Z. (2013). Measuring the exposome: a powerful basis for evaluating environmental exposures and cancer risk. Environ Mol Mutagen, 54(7), 480-499. doi: 10.1002/em.21777
  • Wishart, D., Arndt, D., Pon, A., Sajed, T., Guo, A. C., Djoumbou, Y., . . . Rappaport, S. M. (2015). T3DB: the toxic exposome database. Nucleic Acids Res, 43(Database issue), D928-934. doi: 10.1093/nar/gku1004
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