New frontiers for studies of the effects of early life exposures and later health effects (DOHaD) in humans

Abstract

Background: The widespread use of information technologies and the development of exposure (including those based on ‘omics) biomarkers constitute opportunities for studies related to DOHaD (the Developmental origins of health and disease) hypothesis. Aim: We present some possible futures for human studies aiming at characterizing the mid and long-term effects of early life environmental exposures Discussion: We argue that historical gene-environment interaction studies, which considered possible synergy between exposures and genetic polymorphisms, will be replaced by gene expression-environment (mediation) studies considering possible synergy and mediation of environmental effects by epigenetic, transcriptomic, proteomic, metabolic or microbiome markers. In order to tackle this question efficiently and to address the need to consider an increasing number of exposures (the Exposome vision), one way will be to conduct huge cohorts analyzed in an agnostic way. Currently, large information technology firms seem better prepared to conduct such studies with continuous follow-up of health, behavior, location, than academic epidemiologists. Therefore, such cohorts might soon originate from the Silicon Valley (“Google Epidemiology”) and risk having less consideration of key issues such as exposure misclassification and correction for multiple testing. A complementary approach would be for epidemiologists to team up with toxicologists and system biologists who would, from animal or in-vitro or in-silico studies, generate hypotheses to be tested in (possibly smaller) human cohorts. This appears as an appealing way to circumvent the risk of being drowned in data that ‘omics epidemiology might otherwise imply. Conclusion: Epidemiologists should team up with relevant disciplines to maintain a major role in the huge cohorts required to understand the interplay between the Exposome, (epi)genetics, effect/pathway biomarkers and health in childhood and later.