The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Complementing the Genome with an “Exposome”: The Outstanding Challenge of Environmental Exposure Measurement in Molecular Epidemiology
Abstract
The sequencing and mapping of the human genome provides a foundation for the elucidation of gene expression and protein function, and the identification of the biochemical pathways implicated in the natural history of chronic diseases, including cancer, diabetes, and vascular and neurodegenerative diseases. This knowledge may consequently offer opportunities for a more effective treatment and improved patient management. Genetic research of this kind captures the public imagination in a positive manner and attracts political attention. For example, the 2003 UK Government White Paper on genetics (1), entitled “Our inheritance, our future: realising the potential of genetics in the National Health Service,” highlighted the opportunities for tailored drug treatments and gene therapy flowing from the sequencing and mapping of the human genome. However, it was notable that this influential document also drew attention to the use of genetic testing to identify individuals at greatest susceptibility to chronic diseases and the possibilities this raises for disease prevention. Application of genetics in this context moves away from the clinic towards the population and the observational methods of epidemiology. The fruit of this research in terms of reduced morbidity and mortality is therefore to be predominantly realized through public health measures.It is well known that the majority of genetic variants or single nucleotide polymorphisms in the human genome are of low penetrance, including genes implicated in metabolism of environmental chemicals, immunity, lipid metabolism, and hemostasis among others. The high prevalence of these single nucleotide polymorphisms means that despite their low penetrance, they may substantially contribute to population disease burden (2). Nevertheless, the majority will do so only in the presence of specific environmental exposures that in themselves are of low penetrance. Environmental exposures are acknowledged to play an overwhelmingly important role in those common chronic diseases mentioned above, which constitute the major health burden in economically developed countries (3, 4). Despite this, many exposure-disease associations remain ill defined and the complex interplay with genetic susceptibility is only beginning to be addressed. This raises the question as to whether fundamental knowledge about genetics will improve understanding of disease etiology at the population level.The new generation of mega-cohort studies, including the UK Biobank or similar proposed US and Asian cohorts (5-8), provides the framework for such investigations of genetic variation, environment, lifestyle, and chronic disease. At the same time, they represent substantial investment. For example, UK Biobank will recruit half a million people at a cost of around £60 million ($110 million) in the initial phase. The proposal to establish a “Last Cohort” of 1 million people in the United States (7) or a similar-sized Asian cohort (8) would presumably exceed this sum. In each case, the high cost is heavily influenced by the collection and banking of biological material. This expense is predicated on the assumption that biochemical and molecular measures on this material will resolve the etiologic questions alluded to above. It is self-evident that unraveling of complex environmental and genetic aetiologies demands that both environmental exposures and genetic variation are reliably measured. Advances in statistical methods and in bioinformatics in relation to large data sets are also of critical importance.The development of biomarkers is one avenue to improved measurement of exposure, susceptibility (including genetic), and disease in population studies, and the field of molecular cancer epidemiology is founded on this trinity of biomarker categories (9). The characterization of disease can be improved by modern histopathology, particularly the application of sophisticated molecular markers to subcategorize tumors to homogenous groups within which etiology or therapy can be better defined (10, 11). In parallel to advances in disease classification, however, the balance of efforts to improve the measurement of genetic and environmental risk factors has dramatically changed over the last 15 years in a way that has been less than ideal.The ease of genotyping following the introduction of the PCR in the late 1980s and 1990s saw a major shift in effort and resources, away from development of accurate exposure biomarkers towards the conduct of gene-disease association studies. Allied to the relatively trivial technical demands of genotyping, these measures, by consequence of the fact that they were unchanging over time, were well suited to classic case-control study design. For laboratories involved in molecular cancer epidemiology, gene-disease association studies offered rapid gains in research output. The literature is now replete with meta-analyses of these data. The studies that have been conducted have,
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The exposome, first introduced in 2005 [1], provides a comprehensive model for understanding how cumulative environmental exposures interact with biological systems to influence health outcomes.”
In the citing paper
“Importantly, the literature suggests a range of prenatal exposures that can collectively impact fetal development [152–156].”
From Brain structural and functional outcomes in the offspring of women experiencing psychological distress during pregnancy (2024) · cites this paper as [156]
Citations
Cites
MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia
Armstrong, S. A., Staunton, J. E., Silverman, L. B., Pieters, R., den Boer, M. L., Minden, M. D., Sallan, S. E., Lander, E. S., Golub, T. R., & Korsmeyer, S. J. (2001) · Nature Genetics · doi:10.1038/ng765 · Cited by 1,721
Tobacco carcinogens, their biomarkers and tobacco-induced cancer
Hecht, S. S. (2003) · Nature reviews. Cancer · doi:10.1038/nrc1190 · Cited by 1,551
Cancer epidemiology in the last century and the next decade
Peto, J. (2001) · Nature · doi:10.1038/35077256 · Cited by 688
Qian, G.-S., Ross, R. K., Yu, M. C., Yuan, J., Gao, Y. T., Henderson, B. E., Wogan, G. N., & Groopman, J. D. (1994) · PubMed · Cited by 666
Large-scale genotyping of complex DNA
Kennedy, G., Matsuzaki, H., Dong, S.-L., Liu, W.-M., Huang, J., Liu, G., Su, X., Cao, M., Chen, W., Zhang, J., et al. (2003) · Nature Biotechnology · doi:10.1038/nbt869 · Cited by 609
The toxicology of aflatoxins as a basis for public health decisions
Wild, C. P. (2002) · Mutagenesis · doi:10.1093/mutage/17.6.471 · Cited by 477
Self-citationChemical-induced DNA damage and human cancer risk
Poirier, M. C. (2004) · Nature reviews. Cancer · doi:10.1038/nrc1410 · Cited by 331
Amundson, S. A., Do, K. T., Shahab, S., Bittner, M. L., Meltzer, P. S., Trent, J. M., & Fornace, A. J. (2000) · Radiation Research · doi:10.1667/0033-7587(2000)154[0342:iopmbi]2.0.co;2 · Cited by 290
Wang, Y., Holmes, E. C., Nicholson, J. K., Cloarec, O., Chollet, J., Tanner, M., Singer, B. H., & Utzinger, J. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0404878101 · Cited by 272
Molecular epidemiology : principles and practices
Schulte, P. A., & Perera, F. P. (1993) · Cited by 251
Research works printed but not linked: 1
- IARC. Monographs on the evaluation of carcinogenic risks to humans: schistosomes, liver flukes and Helicobacter pylori. Vol. 61. Lyon, France: IARC; 1994.
Cited by
Sorted by citations
The Lancet Commission on pollution and health
Landrigan, P. J., Fuller, R., Acosta, N. J. R., Adeyi, O., Arnold, R., Basu, N. (., Baldé, A. B., Bertollini, R., Bose-O'Reilly, S., Boufford, J. I., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(17)32345-0 · Cited by 4,929
Epidemiology and risk factors for IBD
Ananthakrishnan, A. N. (2015) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/nrgastro.2015.34 · Cited by 1,741
The exposome: from concept to utility
Wild, C. P. (2012) · International Journal of Epidemiology · doi:10.1093/ije/dyr236 · Cited by 1,416
Self-citationRespiratory risks from household air pollution in low and middle income countries
Gordon, S. B., Bruce, N. G., Grigg, J., Hibberd, P. L., Kurmi, O. P., Lam, K.-B. H., Mortimer, K., Asante, K. P., Balakrishnan, K., Balmes, J., et al. (2014) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(14)70168-7 · Cited by 953
Krutmann, J., Bouloc, A., Sore, G., Bernard, B. A., & Passeron, T. (2017) · Journal of Dermatological Science · doi:10.1016/j.jdermsci.2016.09.015 · Cited by 768
The blood exposome and its role in discovering causes of disease
Rappaport, S. M., Barupal, D. K., Wishart, D., Vineis, P., & Scalbert, A. (2014) · Environmental Health Perspectives · doi:10.1289/ehp.1308015 · Cited by 393
Precision medicine in the era of artificial intelligence: implications in chronic disease management
Subramanian, M., Wojtusciszyn, A., Favre, L., Boughorbel, S., Shan, J., Letaief, K. B., Pitteloud, N., & Chouchane, L. (2020) · Journal of Translational Medicine · doi:10.1186/s12967-020-02658-5 · Cited by 362
Environmental determinants of allergy and asthma in early life
Burbank, A. J., Sood, A. K., Kesic, M. J., Peden, D. B., & Hernandez, M. L. (2017) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2017.05.010 · Cited by 299
Biological embedding of experience: a primer on epigenetics
Aristizabal, M. J., Anreiter, I., Halldorsdottir, T., Odgers, C. L., McDade, T. W., Goldenberg, A., Mostafavi, S., Kobor, M. S., Binder, E. B., Sokolowski, M. B., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1820838116 · Cited by 268
Environmentally-Induced (Extrinsic) Skin Aging: Exposomal Factors and Underlying Mechanisms
Krutmann, J., Schikowski, T., Morita, A., & Berneburg, M. (2021) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2020.12.011 · Cited by 253
An exposome perspective: Early-life events and immune development in a changing world
Renz, H., Holt, P. G., Inouye, M., Logan, A. C., Prescott, S. L., & Sly, P. D. (2017) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2017.05.015 · Cited by 226
Sbihi, H., Boutin, R. C., Cutler, C., Suen, M., Finlay, B. B., & Turvey, S. E. (2019) · Allergy · doi:10.1111/all.13812 · Cited by 199
Oakden-Rayner, L., Carneiro, G., Bessen, T., Nascimento, J. C., Bradley, A. P., & Palmer, L. J. (2017) · Scientific Reports · doi:10.1038/s41598-017-01931-w · Cited by 154
Bagot, K. S., Matthews, S. A., Mason, M., Squeglia, L. M., Fowler, J., Gray, K., Herting, M., May, A., Colrain, I., Godino, J., et al. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.008 · Cited by 145
Wu, Y., De Asis-Cruz, J., & Limperopoulos, C. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02449-0 · Cited by 124
“Importantly, the literature suggests a range of prenatal exposures that can collectively impact fetal development [152 – 156].”
BackgroundBiomarkers intersect with the exposome
Rappaport, S. M. (2012) · Biomarkers · doi:10.3109/1354750x.2012.691553 · Cited by 114
The Importance of the Biological Impact of Exposure to the Concept of the Exposome
Dennis, K. K., Auerbach, S. S., Balshaw, D. M., Cui, Y., Fallin, M. D., Smith, M. T., Spira, A., Sumner, S., & Miller, G. W. (2016) · Environmental Health Perspectives · doi:10.1289/ehp140 · Cited by 103
Toyokuni, S. (2019) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2018.10.401 · Cited by 96
Environmental factors in primary biliary cirrhosis
Juran, B., & Lazaridis, K. (2014) · Seminars in Liver Disease · doi:10.1055/s-0034-1383726 · Cited by 89
Bennett, D. A., Landry, D., Little, J., & Minelli, C. (2017) · BMC Medical Research Methodology · doi:10.1186/s12874-017-0421-6 · Cited by 85
Understanding the Chemical Exposome During Fetal Development and Early Childhood: A Review
Krausová, M., Braun, D., Buerki-Thurnherr, T., Gundacker, C., Schernhammer, E., Wisgrill, L., & Warth, B. (2023) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-051922-113350 · Cited by 61
Clinical and epidemiological observations on individual radiation sensitivity and susceptibility
Seibold, P., Auvinen, A., Averbeck, D., Bourguignon, M., Hartikainen, J. M., Hoeschen, C., Laurent, O., Noël, G., Sabatier, L., Salomaa, S., et al. (2020) · International Journal of Radiation Biology · doi:10.1080/09553002.2019.1665209 · Cited by 56
Recent advancements in the atopic dermatitis mechanism
Savva, M., Papadopoulos, N. G., Gregoriou, S., Katsarou, S., Papapostolou, N., Makris, M., & Xepapadaki, P. (2024) · Frontiers in Bioscience-Landmark · doi:10.31083/j.fbl2902084 · Cited by 53
Barzilay, R., Moore, T. M., Calkins, M. E., Maliackel, L., Jones, J. D., Boyd, R. C., Warrier, V., Benton, T. D., Oquendo, M. A., Gur, R. C., et al. (2021) · Neurobiology of Stress · doi:10.1016/j.ynstr.2021.100314 · Cited by 43
Dermocosmetics: beneficial adjuncts in the treatment of acne vulgaris
Araviiskaia, E., Lopez Estebaranz, J. L., & Pincelli, C. (2021) · Journal of Dermatological Treatment · doi:10.1080/09546634.2019.1628173 · Cited by 47
Grandi, C., & D’Ovidio, M. C. (2020) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17041357 · Cited by 46
Assessing and enhancing the utility of low-cost activity and location sensors for exposure studies
Asimina, S., Chapizanis, D., Karakitsios, S., Kontoroupis, P., Asimakopoulos, D. N., Maggos, T., & Sarigiannis, D. (2018) · Environmental Monitoring and Assessment · doi:10.1007/s10661-018-6537-2 · Cited by 40
The Role of Genetic, Environmental, and Dietary Factors in Alzheimer’s Disease: A Narrative Review
Mertaş, B., & Boşgelmez, İ. İ. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26031222 · Cited by 35
Gut microbiota resilience and recovery after anticancer chemotherapy
Roggiani, S., Mengoli, M., Conti, G., Fabbrini, M., Brigidi, P., Barone, M., D'Amico, F., & Turroni, S. (2023) · Microbiome Research Reports · doi:10.20517/mrr.2022.23 · Cited by 31
Aliberti, S. M., & Capunzo, M. (2025) · Nutrients · doi:10.3390/nu17040722 · Cited by 29
Zhang, P., Arora, M., Chaleckis, R., Isobe, T., Jain, M., Meister, I., Melén, E., Perzanowski, M., Torta, F., Wenk, M. R., et al. (2019) · Metabolites · doi:10.3390/metabo9060106 · Cited by 27
Molina-García, M., Malvehy, J., Granger, C., Garre, A., Trullàs, C., & Puig, S. (2022) · Dermatology and Therapy · doi:10.1007/s13555-021-00644-3 · Cited by 15
“As the very first barrier between our body and the environment, the skin is exposed to many environmental, lifestyle and host factors from conception onwards which have been defined as the exposome [29, 30].”
BackgroundIgnoring the planet: A critical blind spot for research on ageing
Shiels, P., Neytchev, O., Borland, G., Germushkina, P., Johnson, R., Stenvinkel, P., & Woods, T. (2025) · Journal of Internal Medicine · doi:10.1111/joim.70032 · Cited by 4
Interaction of solar radiation with the human skin
Rajan, R. (2024) · Sunscreens for Skin of Color · doi:10.1007/978-981-97-3195-4_2 · Cited by 2
Metadata
- Authors
- Wild, C. P.
- Affiliations
- University of Leeds (GB)
- Corresponding author
- Wild, Christopher Paul
- Venue
- Cancer Epidemiology, Biomarkers & Prevention
- Published
- 2005-08-01
- Volume
- 14
- Issue
- 8
- Pages
- 1847-1850
- ISSN
- 1055-9965 (ISSN-L)
- 1538-7755
- OpenAlex
- W2138649409
- Cited by
- 2,562
- References
- 34
- Citations by year
- 2026: 314 · 2025: 260 · 2024: 288 · 2023: 231 · 2022: 211 · 2021: 243 · 2020: 185 · 2019: 168 · 2018: 139 · 2017: 102 · 2016: 94 · 2015: 88 · 2014: 63 · 2013: 47 · 2012: 53
- FWCI
- 0.47
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Cancer Epidemiology Biomarkers & Prevention (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institute of Environmental Health Sciences (ES 06052, P01ES006052)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Carcinogens and Genotoxicity Assessment
- Keywords
- exposome, environmental exposure measurement, molecular epidemiology, genetic susceptibility, chronic disease etiology, single nucleotide polymorphisms, UK Biobank, exposure-disease association, public health genetics, disease prevention
- MeSH terms
- Environmental Exposure, Humans, Genome, Human, Molecular Epidemiology, Genetic Predisposition to Disease
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
