The study of the potential contribution of low-dose exposure to environmental chemicals on the development of chronic conditions in human populations is often hampered by methodological issues, including exposure misclassification and the inability to assess biological effects in target organs. White adipose tissue (WAT) presents the unique feature of being both an advantageous matrix for assessing long-term exposure to mixtures of persistent organic pollutants and an interesting tissue to investigate early preclinical effects. Moreover, other lipophilic non-persistent chemicals and heavy metals have been recently quantified in fat, suggesting that human WAT contains chemical mixtures more complex than initially thought. However, WAT has been scarcely used in environmental epidemiology due to collection difficulties. In this essay we discuss the potential of using human WAT as a source of both exposure and effect biomarkers, with the aim of advancing the epidemiological research of obesity-related diseases, including metabolic syndrome and cancer. Overall, we discuss the implications of investigating WAT in a multidisciplinary framework combining toxicological and epidemiological knowledge in order to improve the inference of causal relationships in observational settings. We finalise by suggesting feasible designs and scenarios in which WAT samples may be reasonably collected.
- environmental epidemiology
- epidemiology of chronic diseases
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Contributors Both authors planned, discussed, wrote, reviewed and edited the intellectual content, and agreed to publish this essay.
Funding JPA is under contract within Ramon y Cajal program (RYC-2016-20155, Ministerio de Economía, Industria y Competitividad, Spain). VM is under contract within the Human Biomonitoring for Europe Project (European Union Commission H2020-EJP-HBM4EU). The authors acknowledge the funding received from Instituto de Salud Carlos III (FIS-PI16/01858).
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Commissioned; externally peer reviewed.
Data availability statement There are no data in this work. Data sharing not applicable as no data sets generated and/or analysed for this study.