Environment, susceptibility windows, development, and child health

Abstract

Purpose of review: To illustrate the role of the exposome in child health while highlighting unique aspects of this research pertinent to children, such as the time dependency of environmental exposures on fetal programming, as well as the time-dependent nature of child behavior, diet, and motor function, which alter the probability of exposure to different compounds. Future environmental health research will be more hypothesis generating but will also need to heed lessons learned from other 'omic' sciences. The NIH Child Health Environmental Analysis Resource (CHEAR) is a major step toward providing the infrastructure needed to study the exposome and child health.

Recent findings: Environmental exposures have overlapping mechanisms such as endocrine disruption and oxidative stress, among others. The nature of the long-term health impact of an exposure is dependent not only on dose, but also on the timing of exposure. Advances in exposure science, toxicology, and biostatistics will create new opportunities to identify and better define windows of susceptibility to environmental exposures.

Summary: As exposure science matures, we will better understand the role of environment on health. Linking the exposome with genomics will unlock the root origins of multiple complex diseases.

Figure 1. Transdisciplinary Science in Children’s Environmental Health

Schematic of relationship between environmental exposures and clinical disease. These effects are exposure timing dependent as well.

Figure 2. Central Role of Oxidative Stress in Fetal Programming

Figure illustrates the role of oxidative stress experienced in the placenta as a mediator of programmed health effects experienced in later life.

Figure 3

Associations between weekly prenatal PM_2.5 and mtDNA content in cord blood adjusted for sex, maternal age at delivery, year of birth, maternal education, prenatal exposure to environmental tobacco smoke and batch. The y-axis represents the change in mtDNA content associated with a 10μg/m³ increase in PM_2.5; the x-axis is gestational age in weeks. Solid lines show the predicted change in mtDNA content. Gray areas indicate 95% CIs. A sensitive window is identified for the weeks where the estimated pointwise 95% CI (shaded area) does not include zero (i.e. the length of time the regression is statistically significant.)