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Epigenetics and Epidemiology: Models of Study and Examples

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Advances in Nutrition and Cancer

Part of the book series: Cancer Treatment and Research ((CTAR,volume 159))

Abstract

Epidemiological studies have successfully identified several environmental causes of disease, but often these studies are limited by methodological problems (e.g. lack of sensitivity and specificity in exposure assessment; confounding). Proposed approaches to improve observational studies of environmental associations are Mendelian randomization and the meet-in-the-middle (MITM) approach. The latter uses signals from the growing field of -omics as putative intermediate biomarkers in the pathogenetic process that links exposure with disease. The first part of this approach consists in the association between exposure and disease. The next step consists in the study of the relationship between (biomarkers of) exposure and intermediate -omic biomarkers of early effect; thirdly, the relation between the disease outcome and intermediate -omic biomarkers is assessed. We propose that when an association is found in all three steps it is possible that there is a casual association. One of the associations that have been investigated extensively in the recent years but is not completely understood is that between environmental endocrine disruptors and breast cancer. Here we present an example of how the "meet-in-the-middle" approach can be used to address the role of endocrine disruptors, by reviewing the relevant literature.

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Acknowledgments

This work has been made possible by a grant from Compagnia di San Paolo to PV and KVV.

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Correspondence to Paolo Vineis .

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van Veldhoven, K., Rahman, S., Vineis, P. (2014). Epigenetics and Epidemiology: Models of Study and Examples. In: Zappia, V., Panico, S., Russo, G., Budillon, A., Della Ragione, F. (eds) Advances in Nutrition and Cancer. Cancer Treatment and Research, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38007-5_14

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  • DOI: https://doi.org/10.1007/978-3-642-38007-5_14

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