Utilizing a Biology-Driven Approach to Map the Exposome in Health and Disease: An Essential Investment to Drive the Next Generation of Environmental Discovery

Abstract

Background: Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.

Objectives: We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.

Discussion: The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome-the totality of the biologically active exposures relevant to disease development-through coupling biochemical receptor-binding assays with affinity purification-mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.

Conclusions: Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327.

Figure 1.

Approaches to studying the exposure–response relationship. The exposome can be broadly divided into four distinct domains: living environment, socioeconomic factors, lifestyle, and physical-chemical exposures. The effects of exposures can be studied at the ecological, in vivo, in vitro, molecular, and in silico levels. Although exposure and response are heterogeneous, almost all causal biological effects from an exposure are explainable by the underlying molecular connections. To investigate a relationship, traditional study takes a forward approach—from exposure to response. Examples include a hypothesis-driven design with a few predefined exposures and a semi-/fully data-driven design to conduct exploratory studies. In contrast, studies using a biology-based measurement (BBM) approach work differently—from response to exposure—at the molecular level. The bait to capture the exposures can be a few predefined, a particular class, or a broad-scale selection of functional biomolecules. Certain icons in the figure were made by Freepik (www.flaticon.com).

Figure 2.

Using a biology-based measurement approach to characterize the functional exposome. The assay can be implemented in the form of affinity purification–mass spectrometry in six steps. (1) A group of individuals ($n$) is sampled. (2) Biofluids, such as plasma, are isolated from blood and (3) loaded to the microplate (each well is coated with one type of receptor) to capture circulating ligands. (4) After incubation, ligands are extracted and (5) characterized by mass spectrometry. (6) Data can be presented in three different matrices ($n$ by feature, $n$ by receptor, and receptor by feature) with signals integrating across features or receptors for downstream analyses. A key advantage of this approach is that functional analysis of the exposome is possible without upfront feature identification because molecular exposures are biophysically linked to receptors with known functions. Certain icons in the figure were made by Freepik (www.flaticon.com).

Figure 3.

Key advantages of using a biology-based measurement approach to study the functional exposome (FE), where nature meets nurture. (A) Enrichment is not required as an extra step but, rather, intrinsically provided by the pull-down assay format. (B) Each detected feature is functionally annotated by the corresponding binding receptors. (C) Health impacts can be assessed in two ways: coexposure correlation or shared mode of action. (D) Each feature can be assigned to a unique reference FE identifier (Ref. FE ID), which is characterized by an accurate mass, the functional molecules (e.g., binding receptors), and other attributes (e.g., mass spectra, detection frequency in the population). The mapping, cataloging, and sharing of exposure information allow unambiguous communication of knowns and unknowns across studies. Certain icons in the figure were made by Freepik (www.flaticon.com). Note: RT, retention time.