Seminar: Functional Exposomics and Mechanisms of Toxicity—Insights from Model Systems and NAMs
Publication: Environmental Health Perspectives
Volume 132, Issue 9
CID: 094201
Abstract
Background:
Significant progress has been made over the past decade in measuring the chemical components of the exposome, providing transformative population-scale frameworks in probing the etiologic link between environmental factors and disease phenotypes. While the analytical technologies continue to evolve with reams of data being generated, there is an opportunity to complement exposome-wide association studies (ExWAS) with functional analyses to advance etiologic search at organismal, cellular, and molecular levels.
Objectives:
Exposomics is a transdisciplinary field aimed at enabling discovery-based analysis of the nongenetic factors that contribute to disease, including numerous environmental chemical stressors. While advances in exposure assessment are enhancing population-based discovery of exposome-wide effects and chemical exposure agents, functional screening and elucidation of biological effects of exposures represent the next logical step toward precision environmental health and medicine. In this work, we focus on the use, strategies, and prospects of alternative approaches and model systems to enhance the current human exposomics framework in biomarker search and causal understanding, spanning from bench-based nonmammalian organisms and cell culture to computational new approach methods (NAMs).
Discussion:
We visit the definition of the functional exposome and exposomics and discuss a need to leverage alternative models as opposed to mammalian animals for delineating exposome-wide health effects. Under the “three Rs” principle of reduction, replacement, and refinement, model systems such as roundworms, fruit flies, zebrafish, and induced pluripotent stem cells (iPSCs) are advantageous over mammals (e.g., rodents or higher vertebrates). These models are cost-effective, and cell-specific genetic manipulations in these models are easier and faster, compared to mammalian models. Meanwhile, in silico NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by in vitro to in vivo extrapolation (IVIVE) and integrated approaches to testing and assessment (IATA) under the adverse outcome pathway (AOP) framework. Together, these alternatives offer a strong toolbox to support functional exposomics to study toxicity and causal mediators underpinning exposure–disease links. https://doi.org/10.1289/EHP13120
Introduction
The exposome complements the genome and encompasses the integrated compilation of all physical, chemical, biological, and psychosocial influences that impact biology.1 First coined in 2005, the term exposome has undergone continual developments in definition and use.2–4 These previous endeavors harbor differences but collectively point to the essential fact that humans and other organisms experience a multitude of exposures over their lifespan. Exposomics emerges as a transdisciplinary field for enabling discovery-based analysis of the environmental factors that contribute to disease.5 On the molecular level, chemical exposomics characterizes both external and internal components of the exposome, leveraging omic-scale measurement of small molecules (molecular weights Da) that are identified as chemical exposure agents, their transformation products, and associated biomolecular profiles to pave ways for unbiased and effective assessment of causes and modifiers of diseases (Figure 1).
Chemical exposomics has benefited from emerging analytical chemistry technologies, including high-resolution mass spectrometry (HRMS).6 HRMS stands out by virtue of high sensitivity, high mass resolution, accurate mass measurement, and wide dynamic ranges and has been routinely utilized for small molecule analysis.6 Meanwhile, large-scale research initiatives, programs, and infrastructures are underway with the potential to advance exposome research.7–9 With streamlined and scalable pipelines in place, HRMS-based approaches increasingly allow longitudinal exposure tracking, exposome-wide association studies (ExWAS), and retrospective etiologic search for exposome discovery. Opportunities and challenges emerge, specifically for the mining and interpretation of the omics data being generated into translational health insights. To move from association to causal understanding, we propose that functional analyses are needed in exposome-oriented research (Figure 2). Determining the mechanistic role of the chemical exposome on disease development relies on toxicity screening and basic sciences at the organismal, cellular, and molecular levels. We posit that model systems and approaches in use are key to functional exposomics success. For centuries, multicellular experimental models have been instrumental in answering the fundamental questions of biology and medicine, from the pioneering work of Darwin and Mendel in the early 19th century to modern discoveries like humoral immune responses.10 Among these, nonmammalian organismal models (e.g., roundworms, fruit flies) have been essential to geneticists for their small size, short life cycle, fully sequenced and manipulable genome (homologically similar to humans), and reduced complexity in anatomy and physiology.11,12 These whole-organism models strike a balance between feasibility and relevance to modeling effects in humans and higher mammals with good throughput and low cost compared to mammalian animals. Further, to probe biology and toxicological modes of action (MOA) at the cellular level, cell culture techniques have become increasingly accessible, from primary cell culture, cell lines, and ex vivo organ culture to the recent technological breakthroughs in cell reprogramming for improved disease hallmark recapitulation. Within the broader realm of new approach methods (NAMs), in silico and in chemico alternatives complement these bench-based approaches, providing solutions for bridging inferential and translational gaps in hazard prioritization and risk assessment.13
Here, we focus on alternative models and approaches for advancing functional exposomics. We visit some key definitions and discuss alternatives spanning from nonmammalian organismal models and cell culture techniques to in silico NAMs for toxicology and exposome research. We discuss what a good model should entail for functional exposomics, and through case studies of neurodegeneration and endocrine disruption (alongside mixture effects), we address how the combined use of these models can help complement current measurement and statistical frameworks to characterize disease processes.
Functional Exposome and Exposomics
The human exposome is massive in chemical space. A recently curated global inventory catalogs compounds and mixtures on the market worldwide.14 To better navigate environmental chemicals, the US Environmental Protection Agency (EPA) launched the CompTox Chemicals Dashboard, which houses searchable environmental compounds alongside chemical lists based on structure or category.15 Faced with such molecular complexity, two questions arise for hazard prioritization and risk assessment: a) What are the environmental exposure agents that humans are being exposed to, and b) what are their resultant health effects at population and individual levels and through what mechanistic routes? With proof of principle from metabolomics successes, the HRMS-based approach is now actively in use to address the former. While these efforts may also provide clues for the latter through population-scale statistics (e.g., ExWAS, mixture modeling, Mendelian randomization),16 we propose that individualized health sciences and intervention rely on focused functional analyses that foster mechanistic elucidation and causal understanding to pave ways for drug development and policy-making in health sciences and medicine.
The idea of “functional exposome” is recognized but has only recently been concretely defined, as represented by an effect-based definition as “the totality of biologically active exposures as identified through targeted biological tests” and a process-based definition as “all environmental exposure–phenotype interaction over a defined time period.”4,17 One common emphasis is the use of effect-based methods (e.g., enrichment and receptor-binding biological assays) to direct high-throughput screening (HTS) and complexity reduction to discover the functional constituents of the chemical exposome. Correspondingly, “functional exposomics,” a subfield of exposomics, focuses on identifying the biologically active exposome components and elucidating exposure-health links at multiple levels (Figure 1). We argue that throughput, mixture simulation, and etiologic relevance are key in selecting proper model systems and approaches for toxicity screening, toxicant prioritization, and basic biology elucidation (Figure 2).
Organismal/Cellular Models and NAMs
Organismal Models: Caenorhabditis elegans, Drosophila melanogaster, and Danio rerio
Over decades, mechanistic toxicological/biological studies have been heavily relying on mammalian models such as rodents (e.g., mice, rats) and monkeys (e.g., marmoset). These models have helped advance biology and medicine but exhibit shortcomings in exposome-oriented research, considering the sheer size, scale, and complexity of potential chemical exposures. Chemical exposures commonly occur as mixtures over a wide dynamic range. Because of the vast structural diversity and manufacture/use, individual chemicals experience distinct patterns of fate, transport, and exposure in humans.14 When throughput, mixture simulation, and operational flexibility become important, nonmammalian organismal models emerge as a solution. These organisms strike a balance between feasibility and efficacy, providing whole-organism information in a high-throughput fashion (with small size and short life cycle) while enabling in-depth mechanistic studies through versatile genetic manipulation and deep phenotyping (Figure 2). Here, we discuss three typical nonmammalian organismal models, namely, roundworm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), and zebrafish (Danio rerio). The main characteristics of these model systems are summarized in Table 1, with additional details given below.
| Category | Caenorhabditis elegans | Drosophila melanogaster | Danio rerio |
|---|---|---|---|
| Reproduction and maintenance | |||
| Common name | C. elegans | Fruit fly | Zebrafish |
| Lifecycle | days | days | days |
| Brood size | (self-fertilizing) | ||
| Reproductive features | Hermaphrodite or outcross with males | Sexual reproduction (male × female) | Sexual reproduction with external fertilization (sperm × egg) |
| Anatomy | |||
| Distinct tissues, high cell diversity, and additional features | Yes, yes, somatic transparency (whole body) | Yes, yes | Yes, yes, somatic transparency (developing larvae) and lack certain human organs (e.g., lung, breast, prostate) |
| Nervous system; structure and other features | Somatic neurons; pharyngeal neurons | Brain; ganglia | Brain; spinal cord, neurodegenerative capacity (multiple brain regions) |
| Number of neurons in adult | 302 | ||
| Connectome | Complete | Partial | Partial |
| Genetics | |||
| Genetic homology to humans | |||
| Ease of genetic manipulation | High + | High ++ | High + |
| Functional exposomics | |||
| High-throughput drug/toxicant screening | Yes | Yes | Yes (embryo and larvae) transgenerational effect |
| Routes of exposure | Ingestion, dermal | Ingestion, inhalation, dermal | Gills, dermal, ingestion |
| Hallmark recapitulation and deep phenotyping | Yes. Behavior; morphology; molecular markers | Yes. Behavior; pathology; molecular markers | Yes. Behavior; pathology; molecular markers |
| Dissecting microbiome influences | Pros: rich microbiome relatively stable across geography; worm phenotype as readouts of bacterial activity. Cons: simplicity of GI tract; lack of organ; cuticle barrier | Pros: amenable to manipulation for producing axenic flies; GI tract anatomically similar to humans. Cons: lack of adaptive immunity and organ | Pros: axenic offspring; GI tract anatomically similar to humans; microbiota complex enough. Cons: unsteady baseline; different diet from mammalians; lack of approach to create axenic adults |
Note: GI, gastrointestinal.
Caenorhabditis elegans.
The small and nonparasitic nematode Caenorhabditis elegans self-fertilizes and reproduces robustly and is the first multicellular organism to have its somatic cell lineage mapped and the entire genome sequenced.18 C. elegans has been instrumental in providing whole-organism readouts of various biological end points, be it neuronal, motor, developmental, or reproductive.19–22 Ranking toxicity studies showed a consistency of C. elegans with rodent oral median lethal dose () in the relative order of toxic effects of metal salts and organophosphate pesticides, supporting its use as a surrogate for mammalian toxicity assessment.20,23 A wide range of toxicological end points in C. elegans have been explored, spanning lifespan/mortality, development, egg-laying, oxidative stress, DNA damage, mitochondrial respiration, and swimming behavior, alongside morphological changes (e.g., neuronal loss) or expression levels of specific genes or protein markers, either for life-course tracking or monitoring of transgenerational effects.24–27
Versatile genetic manipulation, molecular biology characterization, and deep behavioral phenotyping in C. elegans not only make it amenable to modeling toxicant-centric effects but facilitating disease-oriented research (as mediated by the chemical exposome). For example, studies have used transgenic C. elegans mutants to recapitulate disease hallmarks and explore how drugs and pesticides mediate health outcomes, including aging and longevity,28,29 diabetes,30 Parkinson’s disease (PD),31 and Alzheimer’s disease (AD).32 C. elegans is well-suited for modeling age-related pathologies for its short life cycle, simple biology, and high genetic homology to humans on longevity-regulating pathways (over 70 genes as discovered to influence the lifespan).33 These pathways span insulin/IGF, TOR signaling, DAF-16/FOXO transcription, germline, mitochondrial respiration, etc., and many are central to lifespan regulation and associated factors like dietary restriction.34 Since C. elegans feeds on microorganisms (mainly bacteria) through conserved alimentary routes, it can be used as a biosensor to probe the host–microbe interaction as well.35,36
C. elegans lacks major mammalian organs such as heart, lungs, liver, and an adaptive immune system, limiting related disease modeling. For functional exposomics, C. elegans possesses a thick cuticle that resists exposure uptake, rendering precise control over types, dosages, and routes of exposure a challenge; novel dosing approaches are needed to correct for cuticle-caused variation to better gauge pharmacokinetics or toxicokinetics.37,38 In addition, C. elegans or other nematodes may fall short of a logical assessment of findings that contradict those of mammalian models when the possible attribution could be any interspecies divergences by evolution, anatomical structure, metabolism, and behavioral complexity.39
Drosophila melanogaster.
The fruit fly belongs to the Drosophila genus and is a small fly that is commonly discovered near ripening/rotting fruits or vegetables. A once favored tool (“queen of genetics”) of geneticists and developmental biologists, it has been used for over a century to address fundamental questions in biology, resulting in six Nobel Prizes including chromosomal theory of inheritance (1933), discoveries of genetic control of early embryonic development (1995), activation of innate immunity (2011), molecular mechanisms controlling the circadian rhythm (2017), etc. The short lifespan and reproductive cycle of Drosophila allow toxicological monitoring over the entire lifespan and under varied dosage schemes.40 In addition, 75% of human disease-causing genes have a Drosophila ortholog.40 Since the Gal4/UAS system was invented in the 90s, sustained contributions from geneticists have made Drosophila one of the most efficient models for manipulating genes in a cell-specific manner.41
The Drosophila model has been useful in studying disease etiologies and environmental contributors. One such example area of research is neurodegenerative disorders. Current studies have been concentrated on genetics, although Mendelian genetics only account for 5–20% in explaining the neurodegenerative disease disparity (as presented in AD/PD).42–45 Hence, researchers increasingly interrogate how the environment may contribute to these disorders, with many targeting environmental chemical exposures. Since the Drosophila brain consists of both neurons and glia, one can examine responses in vivo to chemical exposure agents at specific neuronal and molecular levels.46 Meanwhile, the fruit fly has legs (as compared to the simpler roundworm), thereby enabling more sophisticated behaviors to be assessed (e.g., climbing, locomotor control). It has been used to interrogate metal-induced parkinsonism and neurotoxicity.47 Bonilla et al. demonstrated in a fly model of Mn toxicity the role of antioxidants in extending the lifespan of Mn-treated flies.48 For organic toxicants, studies in flies on pesticides (e.g., paraquat, rotenone) have revealed potential etiologic links to PD, identifying oxidative stress, reactive oxygen species (ROS) generation, and mitochondrial dysfunction as key routes toward neuronal damage and degeneration.49,50 In line with epidemiologic findings, fruit flies have been used to identify genes responsible for nicotine-induced protection against PD.51 Drosophila can also be used to model effects of the chemical exposome on the autonomic nervous system and gut microbiome owing to a gastrointestinal (GI) tract similar to that of humans by structure, physiology, and immune response with conserved microbial functions.52,53
The major shortcomings of fruit flies for toxicology and functional exposome research include the lack of an adaptive immune system, certain major organs (e.g., lung), and a missing 25% of disease-causing genetic orthologs with Homo sapiens.54 In addition, although flies are easy to handle and raise, certain reagents like antibodies are not readily available and may involve a lengthy process of tagging the endogenous protein.55
Danio rerio.
Zebrafish (D. rerio) is a vertebrate model with its genome fully sequenced in 2013.56 The latest genomics analyses showed that of human genes have a zebrafish ortholog, and for disease-causing genes, zebrafish possesses higher homology (84%) to humans compared to C. elegans (65%) and D. melanogaster (75%).57 The zebrafish genome can be modified through electroporation, liposomes, gene guns, and microinjection, which have proved resourceful for targeting specific genes or regulatory pathways.58 Zebrafish also possess unique regenerative capacities for organs like the heart, fins, and even parts of the central nervous system (CNS) and, therefore, have been considered indispensable for developmental and/or regeneration studies.59,60
Zebrafish has been instrumental in exploring toxicology topics spanning bioaccumulation, pharmacokinetics, reproductive toxicity, and developmental effects.61 The small size and bodily permeability of the embryo and larvae () make zebrafish well-suited for HTS of toxicants (e.g., in 96-well formats).62 The somatic transparency allows for in vivo imaging; transgenic zebrafish strains expressing fluorescent proteins have been conducive to the discovery of response elements to exposome agents at early life embryonic/larval stages toward adulthood, with the latter being enabled by transgenic casper and crystal lines generated through mutations affecting skin pigmentation.63,64 In addition, zebrafish is amenable to HTS due to the high differentiation and growth rates. The recent automation of behavioral and other phenotypic characterization in zebrafish has allowed hundreds of toxicants such as per- and polyfluoroalkyl substances (PFAS) to be screened with high throughput; disparate patterns were identified in bioaccumulation, metabolism, and toxicity among PFAS species and individual chemicals.65,66
Beyond HTS, transgenerational effects have been assessed in zebrafish for prenatal exposures to toxicants such as polycyclic aromatic hydrocarbon,67 tris(2-chloroethyl) phosphate (TCEP),68 and cadmium.69 The phenotypic readouts examined in first generation () offspring of exposed fish included development, oxidative stress, apoptosis, and swimming behaviors. Gene expression profiles shed further light on these effects. In one study, RNA sequencing revealed global transcriptomic changes in offspring of bisphenol A (BPA)-exposed parents, singling out pathways in apoptosis, oxidative stress, epigenetic regulation, and DNA damage.70 Likewise, 24-h exposure to lead () in zebrafish embryos induced expression changes of 648 genes even in brains of the second generation (),71 demonstrating a transgenerational effect of prenatal lead exposures and neurotoxicity.
Zebrafish has been used to study disease etiology and pathogenesis. For example, zebrafish can model neurological diseases due to anatomical and physiological similarities to the human brain, with chemical-induced models developed to recapitulate neurodegenerative hallmarks in vivo.72,73 Specifically, for modeling PD, research has been hampered because humans are the only species that develop PD. Treatment with certain neurotoxicants (e.g., MPTP, rotenone), intriguingly, was able to induce parkinsonian phenotypes in animals, including zebrafish.74,75 Second, zebrafish helps dissect microbiota’s roles in the gut–brain axis and exposome–disease interplay; the pros and cons are outlined in Table 1. Recent data suggested a link between gut microbial perturbation and biotransformation and neurotoxicity of xenobiotics including triclosan,76 BPA,77 methylmercury,78 and oxytetracycline,79 raising the question of whether such a link is implicated in neurotoxicant-driven diseases as well.80,81 Third, zebrafish may expedite drug development paths with reduced cost compared to rodent models, on which toxicity/safety tests often are based long after the four classical stages of drug discovery (i.e., early discovery, preclinical phase, clinical phases, and regulatory approval); thus, we argue that use of rodent models often fail to eliminate candidate pharmacological “probes” (asking a specific biology question) before testing of the drug (safe and effective) at the front end.
The drawbacks of using the vertebrate zebrafish for functional exposomics include the difficulty in controlling dosage or uptake in the aqueous phase,82 lack of certain major organs (e.g., lung, breast, and prostate),83 and the fast regenerative capacity (as maintained in multiple regions of the adult brain)60 that challenges assessing localized neuronal loss under exposure to neuro-modulatory agents. In zebrafish-based modeling of microbiome-mediated toxicity, caution should be exercised considering different diets (from mammals), unsteady gut microbiome baseline, lack of approaches to creating axenic adult fish, and the distinct intestinal dissection that reduces analysis throughput (Table 1).81
Cellular Models: From Primary Cell Culture and Cell Lines to iPSC Technologies
To decipher the exposure–disease link, multilevel approaches are needed; as opposed to whole-organism model systems, cultured cells or tissues represent a key piece to solving the toxicology puzzle, supplementing human-based approaches in addressing species-specific data discrepancies in nonhuman in vivo models (Figure 2). Cell culture, such as primary culture, cell lines, and ex vivo culture, has enabled studies at the cellular and molecular levels under controllable conditions, physically and physiologically.84 The recent breakthroughs in cellular reprogramming and the use of induced pluripotent stem cells (iPSCs) provide new solutions to advance biology and medicine, from disease modeling, drug screening, regenerative medicine, to the emerging field of functional exposomics.85
Primary culture and cell lines.
The primary cell culture comprises cells directly isolated from an organism and represents the stage at which cells are physiologically most similar to their in vivo state than cell lines. Typically, physical and/or enzymatic disaggregation procedures are performed on the explanted tissues to yield dispersed individual live cells that further grow in adherent or suspension substrates/media.84 Primary cells, if passaged multiple times, may lose some of their native properties and behave more like a cell line. Cell lines, including the immortal ones that continue to divide even after reaching the Hayflick limit (of cellular aging),86 cater to areas that require large quantities of identical cells, such as genetics, cancer research, and biotechnology. Meanwhile, several cell culture approaches, including two-dimensional (2D) co-culture, three-dimensional (3D) co-cultures from primary or hi-PSC-derived cells, ex vivo options of 3D organoids, and “organ-on-chip” systems have become accessible for modeling cell–cell interaction toward higher organismal levels in biology and toxicology.87,88
Screening in vitro has been widely applied in basic signaling science, drug discovery, and toxicological research for its cost-effectiveness and reproducibility. Human or mammalian cell lines, as well as nonmammalian cell lines can be genetically modified and propagated easily, and phenotypic readouts can be assessed systematically (e.g., cell viability, morphology, and metabolic function).89 However, hurdles may be encountered, from genomic instability and phenotypic shifts over extended cell line generations, to the lack of availability for specific differentiated tissues; for instance, certain primary cells are not easily accessible from patients (e.g., neurons, cardiac cells) or not expandable over differentiation stages.90
iPSC-derived cell culture.
Cell reprogramming, featuring the use of induced pluripotent stem cells (iPSCs), has sparked widespread enthusiasm in regenerative research and health sciences,91 among other synergistic technological developments in precise gene editing, organ-on-chip systems, and microfabricated devices. Notably, a seminal 2006 paper determined that differentiated somatic cells, which are common and accessible (e.g., skin fibroblast cells from patients), can be reprogrammed to turn pluripotent through introducing the Yamanaka factors (i.e., Oct3/4, Sox2, Klf4, and c-Myc).92 When paired with gene-editing technology CRISPR-Cas9, a multitude of issues related to in vitro models, be it technical or ethical, may be resolved concerning cell types, genetics, differentiation stages, and organismal complexity.93
Emerging data has demonstrated the potential of iPSCs to advance exposome research, including HTS.94,95 In a recent study, PD-associated pesticide exposures with discernible co-exposure effects were identified through a field-to-bench approach combining iPSC dopaminergic neuron screen and epidemiological analyses in the Parkinson’s environment and genes (PEG) cohort.96 In another work of ToxCast HTS, HepaRG was used—a pluripotent cell line derived from a human liver tumor that can differentiate into a culture of two liver-relevant cell types, namely cholangiocytes (bile-producing) and hepatocytes (driving metabolism).97 The HepaRG cell line has been discovered to recapitulate multiple hepatocyte functionality hallmarks for a rich repertoire of xenobiotic sensing receptors, transporters, and metabolizing enzymes and has proven an effective surrogate for human primary hepatocytes as employed in ToxCast Phase I.97,98 Besides, the HepaRG cell lines are more advantageous for large-scale long-term HTS over primary hepatocytes, which have limited intrapersonal supply and interpersonal variability.97,99
Certain challenges exist in yield, efficacy, and long-term stability of the differentiated iPSCs.100 Reprogramming differentiated cells into iPSCs may introduce unwanted genetic mutations (partly due to the retrovirus used for DNA insertion) and epigenetic alterations. For certain cell types, reprogramming also tends to be incomplete.101 In addition, some iPSCs retain their epigenetic “memory” from the primary origins, which hinders further target differentiation. For long-term use, the iPSC stability is not fully understood; more studies are warranted to monitor cellular aging processes and examine how closely iPSC-derived cells mimic the age and functional state of cells of the original sources. We believe that high experimental rigor and efficacy validation are required for its long-term use in biology, health sciences, and medicine.
New Approach Methods
To what extent are these bench-based organismal/cellular models of practical use in chemical exposome research and health sciences in general? From a risk assessment standpoint, new approach methods (NAMs) emerge as a useful umbrella term that broadly incorporates approaches as they comply with the “3R” principle of reduction, replacement, and refinement.102,103 By operational definition, NAMs refer to any alternative technology, methodology, approach, be it experimental or computational, or combination thereof that provide information on chemical hazard, exposure, and risk assessment. NAMs do not necessarily require newly developed methods but represent innovative efforts to substitute mammalian organisms (e.g., rodents) with alternatives for hazard prioritization and risk assessment,13 from a) profiling exposure occurrences and dosage and b) gauging exposure uptake, metabolism, and bioavailability in vivo (toxicokinetics) to c) elucidating modes of action through quantitative modular frameworks such as the adverse outcome pathway (AOP).104–106 Beyond risk assessment, we believe that NAMs are conducive to tackling the large chemical spaces of exposome in other related areas, such as pharmaceutical development, biotechnology, and food safety and nutrition.
The alternatives to mammalian organisms can encompass any models, approaches, or their combinations, be it in silico, in vitro, in chemico, in vivo (invertebrate or vertebrate), or ex vivo.13,103 In functional exposomics, a combined use may be preferred where in silico NAMs can complement, enhance, and/or scale up bench-based data for screening, assessment, and predictions of toxicity, biosafety, and etiologic attributions. First, quantitative structure–activity relationship (QSAR) models, routinely used by risk assessors, have helped gather physicochemical property information directly from chemical structures. QSAR models are not only predictive of chemicals’ fate and transport in ambient environments but help inform biotransformation, toxicity, and health risks in vivo.107,108 Furthermore, physiologically based kinetic (PBK) modeling delves into pharmacokinetics (and/or toxicokinetics) in the live body that is projected as a set of interconnected compartments (e.g., organs, biofluids), allowing for quantitative modeling of absorption, distribution, metabolism, and excretion (ADME) of xenobiotics and in vitro to in vivo extrapolation (IVIVE), which relates human exposures to test system exposures from a bottom-up angle.109–111 However, inferential gaps may be encountered when addressing interindividual variability by age, sex, life stages, genetic susceptibility, and microbiome function.112
The concerted efforts in developing wide-ranging NAMs have helped form the basis of Integrated Approaches to Testing and Assessment (IATA), a strategic framework for integrating data streams from various approaches to make informed decisions on health risks, safety, and efficacy of chemicals, biological agents, and other substances.113 The versatility of IATA lies in the diverse data sources and toxicological end points, tiered testing methods and read-across, weighted evidence, and broad decision-making tools (e.g., AOPs, expert system).113,114 Meanwhile, burgeoning omics techniques (e.g., genomics, metabolomics, exposomics), microbiome analysis, and machine learning-driven capacities have enabled new molecular readouts for cellular network construction to probe multi-omics signaling and cross-species interaction (e.g., host–microbe crosstalk).115,116 The integrated use of NAMs combining experimental biology and toxicology, omics profiling, and in silico modeling, and molecular epidemiology holds the potential to advance functional exposomics by bridging causal inferential gaps between organismal/cellular models and humans.
Discussion
What Makes a Good Model for Functional Exposomics?
Is there an “ideal” model system, and by what criteria would this be judged, to probe the functional effects of the chemical exposome, be it in vivo, in vitro, ex vivo, in silico, or in chemico? George Box once said, “all models are wrong, but some are useful,” which points to the fact that any complex systems and processes in the real world could not be exactly represented by any simple model.117 A more valid question, then, is how one can make the models less wrong to be sufficiently useful for resolving the problems or research questions at hand. The complexity of human exposome lies in the human body system per se, dynamic contacts and exposure to toxicants, and molecular mechanistic network as well as the variations among individuals as affected by demographic factors such as age, sex, and race. Combined strategies and approaches are thus warranted, raising the question how one should make such combination choices. The roadmaps for navigating these models/approaches have not yet been created; the selection would depend on the specific questions or issues at hand. These entail a) a well-defined research question that outlines actionable analysis goals; b) a quantifiable set of effect-related events at the targeted biological level(s) (e.g., organism-, organ-, cellular-, molecular-), as represented by the AOP framework delineating an adverse outcome (AO) (such as a toxicological end point or disease hallmark), a molecular initiating event (MIE), and the serial causally connected key events (KE) between MIE and AO118; and c) an interpretable framework for translating model-derived data into health implications and interventive strategies in humans.
Model selection for functional exposomics depends on the detailing of specifics for the hazards at play, exposure events, disease outcomes, and the hypothesized modes of action. To map out key elements of the research narrative, the six “H” questions may serve as a guideline (Figure 3). For example, epidemiological studies have long associated air pollution as a major risk factor for mortality and morbidity.119,120 Only recently was it observed in humans (donors in a persistent vegetative state) that particulate matter accumulated in lung-associated lymph nodes; this was positively associated with age and reduced immune function.121 For the first time, tissue/cell-specificity of such exposure–immune interface was identified—lung lymph nodes (rather than gut lymph nodes) and, specifically, the subset of lung macrophages constitute a major site of air particulate exposure/accumulation and immune responses over the lifespan.121 The lung lymph node, we argue, therefore, can serve as an air exposome reservoir/proxy to study the respiratory route of exposure and, here specifically, how air (particulate) pollution exerts health effects in vivo over age. Such critical information regarding “where” (lung lymph nodes) and “who” ( macrophage) helps formulate important hypotheses of “who” on the other side (e.g., chemical exposome components) and “how”—the cellular and molecular signaling pathways of air pollutant–immunity interplay.
From the standpoint of research output, by Weick’s clock face, a framework for assessing the quality/use of research, no theory or hypothesis can be simultaneously “general” (12 o’clock), “simple” (8 o’clock), and “accurate” (4 o’clock)—a tradeoff will occur among the three (Figure 3).122 For example, an actionable (and usually the most popular) theory/hypothesis typically strikes a balance between general and simple (at 10 o’clock) but may fall short of accuracy (or validity) when applied to specific scenarios. Likewise, an accurate hypothesis/theory laden with details may serve goals well in addressing a specific question at hand but lacks the simplicity or generality to adapt to a different hypothesis. Faced with the complexity of the exposome, not only do models and approaches need to be combined, but a tiered or multistage strategy may be needed (Figure 3) from both hypothesis formulation to experimental design and implementation. More specifically, on one hand, high-throughput screening and in silico prediction may be conducive to generating results of simplicity and generality; on the other hand, focused functional analysis helps accurately delineate the molecular underpinnings that may form important basis for effective therapy.
Integrated Solutions to Study Hallmarks of Environmental Insults and Disease: Notable Case Studies
Hallmarks of environmental exposures at the cellular and molecular level can manifest in distinct forms, with many potentially implicated in chronic diseases spanning cancer, respiratory diseases, metabolic syndrome, and neurological disorders.123 Operationally, eight hallmarks have been proposed as actionable readouts to capture key toxicological/etiologic processes, including oxidative stress and inflammation, mitochondrial dysfunction, genomic alterations and mutation, endocrine disruption, microbiome perturbation, impaired nervous system function, epigenetic alterations, and altered intercellular communication.123 These point to challenges and a need for integrated solutions to tackle the complexity in functional exposome concerning cellular networks, tissue/cellular specificity, and multi-omics signaling cascades.
In line with Weick’s clock face for effective hypothesis formulation and model selection, we propose that one needs to weave together both arms of high-throughput screening and focused functional analysis. The former should be comprehensive, nontargeted, and unbiased by nature to widely identify toxicants and mixtures or associated biomolecules at play, address the six “H” questions for delineating the research narrative (Figure 3), and produce testable hypotheses in abundance. For the latter, follow-up functional studies involve biology and basic sciences, demanding more sophisticated and in-depth experimental study design, models, and approaches for testing specific hypotheses on effects of exposures on biology and health. Studies have started to demonstrate the potential of NAMs (in their combined uses) for functional exposomics, as shown in emerging case studies relating to hallmarks of environmental insults and disease, including neurodegeneration and endocrine disruption (with mixture effects).96,124–126
For a case study of neurodegeneration, we have recently shown that an adult Drosophila model of manganese (Mn) toxicity is able to recapitulate Parkinson’s disease phenotypes (parkinsonism) in vivo.127 High-coverage global metabolomics was conducted on heads and bodies of these fruit flies, featuring comparative metabolite profiling, cheminformatics, and pathway enrichment analyses that collectively led us to the discovery of biotin as an early master modifier of Mn-induced neurodegeneration, among multiple other perturbed pathways. To determine the functional roles of biotin, focused functional analyses came into play, leveraging novel in vivo and in vitro alternative models, including use of genetic fly mutant strains with dopaminergic neuronal knockdown of the Btnd gene responsible for biotin recycling and use of human midbrain dopaminergic neurons differentiated from iPSCs (as derived from skin fibroblasts of PD patients).127 The combined use of these alternative models and approaches supported an ameliorative effect of the biotin pathway with gut-brain crosstalk possibly involved, forming a new basis for therapeutic design to combat Mn-induced pathologies and neurodegeneration.127
Endocrine disrupting chemicals (EDCs) and reproductive toxicants remain a challenge to study. For one thing, EDCs typically exert systemic hormonal effects involving multiple glands and organs that are endocrine responsive.128 The adverse health effects are hard to dissect and define; only recently has a consensus of 10 “key characteristics” (KC) been reached that relate to the operational definition of an EDC.129 For another, real-life EDC exposures occur in chemical mixtures with compounded effects (e.g., additive, synergistic, or antagonistic) and have been associated with major human diseases even at regulation-compliant concentration levels.130 A recent study by Caporale et al. set out to address this, leveraging a mixture-centered approach for risk assessment of individual EDC.131 From cohorts to molecules, the study employed a suite of NAMs, including statistical tools, Xenopus larvae, zebrafish, and organoids, innovatively integrating experimental and epidemiological data to gather mechanistic and correlative evidence for a role of mixture EDCs in neurodevelopmental impairments associated with language delay in offspring.131 In another recent work, Wang et al. demonstrated the use of an integrated solution, combining in silico NAMs [integrated physiologically based pharmacokinetic (PBPK)-based forward dosimetry and in vitro bioassays] to improve risk assessments of organophosphate esters (OPEs), a kind of EDC. The individual human equivalent doses were derived via in vitro to in vivo extrapolation (IVIVE) based on PBPK bioactivity data.132
On a broader scale, challenges exist in human-predictive assessment of reproductive toxicity using NAMs.133 The challenges are mainly rooted in the complexity and broadness of reductive biology itself and the dynamic EDC exposome, spanning but not limited to: a) diversity of reproductive end point, b) difficulty in reaching a consensus on defining endocrine disruptors given the broad spectrum of the effects, c) capturing multigenerational effects, d) interindividual variability in exposure patterns and disease susceptibility, as well as e) technical hurdles in NAMs to fully replicate the in vivo processes of the reproductive system. Beyond endocrine disruption and reproductive adversity, the area of mixture effects of chemical exposome agents remains largely unfledged as well. Many prior studies are based on toxicological analysis of a limited number of predetermined chemicals while lacking a disease-specific context. NAMs hold promise to advance this, as backed by proof-of-concept from the aforementioned seminal study associating mixture EDCs with neurodevelopmental effects, alongside other efforts leveraging high-throughput in vivo and in vitro screening134,135 and chemical identification of mixture components, either through multi-omics data mining136 or through advanced mixture modeling.137–139
New Era, New Framework
Recent technological advances open up new doors to measure the chemical exposome and uncover exposure–disease links. In our opinion, with prospective and longitudinal design, exposome-wide measurement, and advanced statistics, systems analyses of large-scale population-based studies will set the stage for identifying environmental risk contributors, population susceptibility, and critical windows of exposure over the lifespan. We believe that functional exposomics that delve into the mechanistic inner workings constitute the next critical step to move forward from association toward causation, providing actionable framework for scientific advancement, health care improvement, industrial guideline redesign, and governmental policy-making. Team science and transdisciplinary fusion are key in this endeavor, prompting certain methodological gaps to be addressed. For example, epidemiologists usually seek “biomarkers” with a less-than-sufficient mechanistic interpretation, molecular toxicologists pursue in-depth basic biology revolving around toxicants not entirely relevant to exposure occurrences and disease etiology, and chemists determine compounds without a clear health-oriented context with outlined priorities or removal of biases.
Ideally, functional exposomics iteratively employs both arms of high-throughput screening and focused functional analysis (experimental and/or computational) to investigate mechanism at the molecular levels (Figure 1). Under such iterative inquiry, emerging technologies [e.g., HRMS, geographical information system (GIS), passive sampler] can enrich our ways of tracking the chemical exposome in situ and their biological responses in vivo. Large longitudinal cohorts and research initiatives (e.g., the NIH “All of Us”)7 open doors for long-term source tracking, high-power ExWAS, and mixture modeling, resulting in biomarker findings to be replicated in follow-up/independent cohorts. These findings can be statistically tested through causal analysis frameworks using emerging approaches spanning Mendelian randomization, causal mediation analysis, and multi-omics integration and network analysis.140
We argue that to investigate the mechanistic basis of diseases driven or mediated by the chemical exposome, HTS, toxicological assays, and basic science will come into play collectively, leveraging nonmammalian organismal models, cell culture techniques (particularly human iPSC-derived cells), as well as computational NAMs. Disease-associated features in genetic homology, organismal/tissue specificity, pathological hallmarks, and convergent signaling pathways need to be heeded when choosing between models and deriving insights translatable to humans.123 Therefore, it is crucial to establish cross-disciplinary communication and consult with biologists, geneticists, informaticians, environmental chemistry modelers, physician-scientists, and risk assessors who are better versed in handling the alternative models in use. In our opinion, caution needs to be taken when interpreting data that involve phylogenic scaling across species or in silico predictive read-across (Figure 3).
We feel that certain specifics and circumstances (e.g., time and space) need to be addressed for toxicological evaluation and disease etiologic elucidation. These span dosage, acute/chronic timespan, routes of exposure, localization, tissue-specificity, etc. Effects arising from exposure to chemical mixtures can be assessed and dissected through in vivo HTS and in silico modeling before more focused in vivo studies set in. The hallmarks of disease manifestation and etiology of diseases from environmental factors are varied. Hence, in our opinion, the initial cellular and molecular categorizations of chemicals or mixtures can be useful (e.g., it may be critical to know if a chemical is pro- or anti-inflammatory, or if it activates a particular cellular pathway, or if it is genotoxic, to begin with).123 Furthermore, in our opinion, studies on individual disease susceptibility should consider the demographical effects of age, race, sex, etc., alongside genetic/epigenetic factors. Taken together, the functional exposomics frameworks in the forthcoming years should aim for both throughput and focus/depth (iteratively or simultaneously), leveraging epidemiologic discovery, toxicant/therapeutic screening, mechanistic elucidation, and in silico extrapolation on population and individual levels. The many alternative model systems and approaches reviewed in this article hold the potential to advance functional exposomics and enable high-throughput, mixture-oriented, and effect-directed analyses. Innovative and integrated use of these alternatives will not only help uncover environmental drivers and/or modifiers of disease, but set the stage for bridging interdisciplinary gaps in methodology and interpretation for environmental health sciences and medicine.
Acknowledgments
The authors thank Pan Chen, PhD, Hong Cheng, MD, and the Michael Aschner Lab at the Albert Einstein College of Medicine for stimulating discussions.
This work was supported by the National Institutes of Health through awards to S.S. (R00ES033723 and P30ES001247) and to G.W.M. (UL1TR001873, U2CES030163, R01AG067501, and RF1AG066107).
Article Notes
Gary W. Miller is the editor for the Journal Exposome and also the writer of the book The Exposome: A New Paradigm for the Environment and Health for which he receives royalties.
Appendix
Terminologies in Functional Exposomics and Alternative Models/Approaches
Exposome & exposomics: the exposome is the integrated compilation of all physical, chemical, biological, and psychosocial influences that impact biology and exposomics refers to the transdisciplinary field that studies the exposome. Exposomics is designed to enable discovery-based analysis of the environmental factors that contribute to disease.
Functional exposome & functional exposomics: the functional exposome encompasses all biologically active exposures over the lifespan as manifested in the exposome-phenotype interaction. Functional exposomics is a subfield of exposomics that focuses on identifying the biologically active exposome components and elucidating environmental exposure–health links at multiple levels.
High-resolution mass spectrometry (HRMS): an advanced analytical chemistry technology to separate, identify, and quantify molecules based on their mass-to-charge ratios (m/z) and related chemical transformation with high-mass resolution, accuracy, and sensitivity.
Exposome-wide association studies (ExWAS): a statistical approach equivalent to the genome-wide association study (GWAS) to screen and identify environmental factors contributing to health and diseases.
New approach methods (NAMs): an umbrella term for approaches and models in compliance with the “3R” principle (of reduction, replacement, and refinement) that aim to substitute mammal or higher vertebrate models with alternatives for hazard identification and risk assessment. NAMs may refer to any technology, methodology, approach, be it in vivo, ex vivo, in vitro, in silico, in chemico, or a combination thereof that provide information on chemical hazard, exposure, and risk assessment.
Induced pluripotent stem cells (iPSCs): a kind of stem cell that can be directly generated from differentiated somatic/adult cells. The iPSC technology involves reprogramming these somatic cells back into a pluripotent state (i.e., iPSCs) that is amenable to differentiating into any cell type at different differentiation stages.
High-throughput screening (HTS): a technology that enables standardized assessment and screening of a large number of readouts at the molecular level (biological, chemical, or pharmacological) over a vast array of chemicals or substances. HTS constitutes one arm of functional exposomics for hypothesis generation through efficient identification of exposome components linked to health/disease, paving the way for the other arm of focused basic sciences for elucidating the etiologic underpinnings and mechanism of toxicity.
Adverse outcome pathway (AOP): a conceptual framework used to depict and understand the progression of a biological event, starting from a molecular initiating event (MIE) induced by a chemical/biological stressor through serial causally connected key events (KE), eventually leading to an adverse outcome (AO).
Physiologically based kinetic (PBK) modeling: a computational model used to describe and predict the pharmacokinetics/toxicokinetics of chemical exposures in vivo, including absorption, distribution, metabolism, and excretion (ADME).
Integrated approaches to testing and assessment (IATA): a strategic framework to integrate data streams generated from a variety of approaches to make informed decisions on health risks, safety, and efficacy of chemicals, biological agents, and other substances. The diversity lies in data sources, testing methods (e.g., tiered testing, weight of evidence, read-across), and decision-making tools (e.g., AOPs, expert system).
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Received: 4 April 2023
Revision received: 22 July 2024
Accepted: 12 August 2024
Published online: 4 September 2024
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