Biomarkers for the 21st century: listening to the microbiome.

TOXICOLOGICAL SCIENCES, 144(2), 2015, 208–216 doi: 10.1093/toxsci/kfv013 CONTEMPORARY REVIEW

Biomarkers for the 21st Century: Listening to the Microbiome *Cornell University College of Veterinary Medicine, C5 Veterinary Medical Center, Ithaca, New York 14853 and †Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland 21205 1

To whom correspondence should be addressed at Johns Hopkins University Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205. Fax: 443 955 9334. E-mail: [email protected].

ABSTRACT The field of environmental research has benefited greatly from the concept of biomarkers, which originally expanded our thinking by opening the “black box” between environmental exposures and manifestations of disease and dysfunction in exposed populations, as laid out in a highly influential article published in 1987 by an expert committee convened by the National Research Council. Advances in biomedical research now challenge us to revise this concept to include the microbiome as a critical stage in the progression from exposure to outcome. Incorporating the microbiome into the basic 1987 model can spur new advances and understanding in environmental health. The human microbiome as a whole comprises the majority of cells and genes of the super-organism (host and microbiome). Site-specific microbiomes are the first to encounter xenobiotics, prior to absorption across gut, skin, or respiratory system. A growing literature indicates that these microbial communities may participate in biotransformation and thus constitute a compartment to add to the original biomarker schematic. In addition, these microbiomes interact with the “niche” in which they are located and thus transduce responses to and from the host organism. Incorporating the microbiome into the environmental health paradigm will enlarge our concepts of susceptibility as well as the interactions between xenobiotics and other factors that influence the status and function of these barrier systems. This article reviews the complexities of host:microbiome responses to xenobiotics in terms of redefining toxicokinetics and susceptibility. Our challenge is to consider these multiple interactions between and within the microbiome, the immune system, and other systems of the host in terms of exposure to exogenous agents, including environmental toxicants. Key words: microbiome; biomarkers; health assessment; non-communicable diseases; arsenic; disease states

BACKGROUND Why do fewer than half of heavy smokers come down with lung cancer? What are the biological events by which subencephalopathic levels of lead exposures induce neurobehavioral effects in children or in mice? How can we improve the scientific basis for inferences between epidemiology and toxicology? These questions remained difficult to answer in both epidemiology and toxicology before the conceptual revolution of biomarkers, proposed in a seminal paper by Perera and Weinstein (1982) introducing the concept of molecular epidemiology. This paper, by carefully defining terms, elucidated new opportunities for reducing uncertainties between external exposures and early responses within individuals. The biomarkers proposed in this

paper were based on then-current understanding of molecular events in the pathogenesis of chemical-induced cancer. Although these researchers restricted their discussion to reducing the uncertainties of this field of epidemiology, they later noted that their concepts were of potentially wider application in improving the precision of testing associations between exposures and other health outcomes by improving exposure assessment and introducing events related to variability in individual and population responses (Perera and Weinstein, 2000). In 1987, a Committee of the National Research Council (NRC) published a defining report on the application of molecular methods to environmental health, in which the concept of biomarkers was formally incorporated into a logic plan that

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Rodney Reynolds Dietert* and Ellen Kovner Silbergeld†,1

DIETERT AND SILBERGELD

FIG. 1. The original concept of biomarkers in environmental health (NRC, 1987).

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measurement and understanding of molecular events in the pathophysiology of disease have continued to develop, the power of the biomarker concept remains a strong influence in toxicological and epidemiological research and in many fields of medicine. Interpretations, not surprisingly, have become more and more complex. Some of the internal world of the original biomarker model was made more explicit by incorporating physiologically based pharmacological (or toxicological) modeling to expand the events between internal dose and biologically effective dose or concentrations at cellular or subcellular sites of toxic action (Corley et al., 1990). The 1987 model has served both epidemiology and toxicology well. Researchers in environmental health sciences and public health more generally have been able to provide more robust insights into hitherto unresolved questions such as the variable results often observed among different strains of experimental animals as well as among human populations. The model has in many instances met the goals of the NRC committee, to improve biomonitoring of individuals and populations (not limited to humans) in terms of detecting exposures, and in increasing our confidence in the information value of early signals of adverse effect prior to increases in clinically defined diseases or serious dysfunctions. The concepts behind this proposal have significantly impacted both toxicology and epidemiology: from the period prior to 1987, when 2–4 papers were published a year, to the present (2014), almost 7000 papers have now been published incorporating molecular biomarkers (PubMed 5.3.2014). The field of air pollution research exemplifies the important contributions of biomarker-based research to improvements in population health (eg, Feretti et al., 2014). The driver of the 1987 model was, among other advances, the new genomics of the early 1980s and the combination of this knowledge with advances in molecular methods that together supported the use of genetic markers of genotoxicants in a way that informed both exposure and outcome assessment. Since this time, while the scope of biomarker-based approaches has expanded well beyond cancer and carcinogenesis, the general concepts embodied in these two figures have remained largely the same: the definition of sequential stages connecting


proposed a pathway connecting external exposures of both human and nonhuman animal populations to health outcomes (NRC, 1987). Both the traditional “black box” of observational epidemiology and the physiological/pathological compartmental approaches of toxicology were challenged to incorporate this new model because of its promise to reduce the uncertainty and lack of predictive precision in explicating associations between exposures and detectable disease and dysfunction in individuals and populations. In addition, this report recognized that the biomarker concept opened the possibility of identifying opportunities for early intervention and disease prevention. The original conceptual scheme, as shown in Figure 1, was relatively simple but extraordinarily powerful. It exploded the existing model of epidemiology, which was limited to those events that could be externally measured, that is, the exposures that acted upon populations and individuals to increase observable disease risks. The events in between these observations were not observable and hence unknown, within a black box, as shown at the top of the figure. The domain of epidemiological research was amplified by application of new knowledge and tools related to events occurring between the external world of exposures and diseases and dysfunctions that could be diagnosed. The internal “world”—formerly considered a black box as impenetrable by the methods of epidemiology as a black hole in astronomy—was now open to investigation through measuring signals of events subsequent to exposure, starting with the absorption of agents (physical, chemical, and microbial) into the organism, distribution of these agents to target organs, early responses at the cellular and subcellular level, followed by later observable changes in cell and organ structure and physiological function. Increases in biological understanding as well as improvements and innovations in technology, such as high throughput analysis of gene expression and metabolomics, were quickly adopted as the tools for opening the black box (Spurgeon et al., 2008; Zhang et al., 2012). In addition, this schematic introduced the ability to measure other factors, independent of exposure, which could modulate these internal transitions; these were defined as “susceptibility factors,” also measured within the organism (for a full discussion, see NRC, 1987; Perera and Weinstein, 2000). As both methods for

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external exposures and expression of disease or dysfunction in organisms and populations, and the elucidation of physiological compartments and biochemical as well as molecular steps in the transformation of an exposure into an absorbed dose into critical target dose followed by molecular responses at the subcellular level and physiological events at the organ and organism levels.

OBJECTIVES

The Microbiome and the Completed Self Concept There are many definitions of the human microbiome, the most inclusive of which covers the entire microbial community ecology of humans as well as its various interactions. Stated differently, it is the combined genomes of microbial communities living on or in any part of the human body spanning all three domains of life (Eukaryota, Archaea, Bacteria) and including microbial fungi, bacteria, viruses, bacteriophage, archaea, and protozoa. This, along with the human genome, completes the human-microbial superorganism (HMP, 2012). This concept compels us to redefine what constitutes a human organism and to expand our thinking as to how we define and study health and disease in humans. This is supported by (1) the elevated risk of specific diseases connected to microbial dysbiosis and (2) the increasing evidence that components of the microbiome such as gut microbiota, exert a profound influence over behavior, immunity, metabolism, and food preferences and intolerance. Current research focuses on the role of the microbiome in human health and disease [eg, immune (Chung et al., 2012) and neurological (Borre et al., 2014) systems]. Because of inter-generational transfer of gut microbes has led some investigators to suggest that the very basis of ancestry, kinship, and societal connectivity may be vested at least as much via our microbiota as through mammalian chromosomally derived signals (Montiel-Castro et al., 2014). This is consistent with the recent observation that strain-specific gut microbiota transfer occurs during vaginal but not Cesarean delivery establishing a tight matriarchal inheritance pattern not unlike that already known for mitochondria (Sato and Sato, 2013). Because of the fundamental importance of the microbiome for the completion of human development and maturation, attention is now focused on understanding the processes by which the microbiome attains and maintains mature function at the level of each important microbial environment, or niche. A fundamental tenet is that missing microbes and lack of intended self-completion in the infant results in a subsequently compromised health status of both children and adults (Dietert, 2014) and for that reason the single most useful biomarker for this purpose is completion of the superorganism of humans and the microbiome, a mutualistic, majority microbial complex (Dietert and Dietert, 2012). A measurement reflecting effective organismal self-completion of the human–microbiome partnership in infancy would be the best single predictor of future health risk for the most significant spectrum of diseases and

Implications of the Microbiome for Biomarkers Microbiome-associated biomarkers have already been identified for potential use in studying metabolism and outcomes, such as autoimmune disease, asthma, metabolic syndrome, and obesity (Finucane et al., 2014). These findings are not surprising given the pivotal role of the gut microbiome in host metabolism of food. Microbial metabolism of both nutrients and other environmental factors helps to regulate the status of key organs and physiological systems including fundamental brain development and function (Selkrig et al., 2014) and behavior (Cryan and Dinan, 2012), immune-mediated intestinal homeostasis, mucosal immunity (McDermott and Huffnagle, 2014), the hypothalamic–pituitary–adrenal axis (Clarke et al., 2014), as well as hepatic and cardiovascular status. Importantly, Ba¨ckhed (2011) argues that it is the gut microbiota that largely programs host metabolism. As our microbiota play pivotal roles in developing and mediating many if not most aspects of our life, the microbiome needs to become a focal point for human health protection and that our microbial mutualistic partners may be considered as an integral organ for the host (Dietert, 2014; Putignani et al., 2014). Interactions between the human host and the microbiome are bidirectional, which justifies the ecological definition of the microbiome stated above. These interactions may raise concerns about the use of gnotobiotic mice, with transferred human materials, as a model for investigating the human microbiome (Krych et al., 2013; Smith et al., 2012). We argue that the microbiome needs to be incorporated into our concepts and research on the interactions between environmental exposures and health outcomes. This is why a revision of the current biomarker approach is needed. Regardless of the category of biomarkers (exposure, response, or susceptibility), the exclusion of the microbiome in these considerations is problematic. Stated differently, biomarkers based only on considering events in humans (or experimental animals) are not encompassing the holobiont, the human-microbial superorganism. As described below, these limitations need to be examined in light of the new understanding of the completed organism. This is particularly a concern where in vitro toxicity testing using only mammalian systems has been suggested as replacement for in vivo animal models because these systems omit the microbiome. Absence of information on the microbial portion of the holobiont and its contribution to metabolism, absorption, and intercellular signaling within the holobiont calls into question the relevance of such systems. Even with in vivo assessment models, a re-examination may be needed as to the extent to which the transfer of the human microbiome to gnotobiotic mice effectively models that of the human population. In the


The objective of this article is to propose that the new science of the microbiome is altering biomedical research to the same extent as genomics did in the 1980s. However, the biomarker concept of 1987 was based on the fundamental assumption was that the exposed human consisted solely of the physiological and genetic systems of a mammalian species. Incorporating the microbiome into the basic 1987 model can spur new advances and understanding in environmental health.

conditions (eg, non-communicable and certain infectious diseases) across the life course. Since the publication of that priority biomarker concept paper, additional information has focused attention on (1) the role of the microbiome in controlling our interface with the environment, immunological selfidentity, tissue homeostasis/dysbiosis, and risk of disease and (2) the “completed self” organism or holobiont as an evolutionary unit (Gilbert, 2014). The concept of the microbiome has also increased awareness of the importance of the environment for development and function. Not surprisingly, human populations living multiple generations within different ecological and social settings appear to develop starkly different microbiomes based on evidence suggesting that the environment has a major role in determining the diversity and functional competence of gut microbiota (Arrieta et al., 2014).


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past, the concern was whether particular rodent strains appropriately reflected human sensitivities; however, it is clear that more attention is needed to the diversity and relevance of the microbiota within rodent strains as compared to humans (Wos-Oxley et al., 2012; Zhang et al., 2014). For that reason, some recent studies have utilized gnotobiotic mice into which the human gut microbiome is transferred to represent a more humanized model. Introducing the Microbiome into the Environmental Health Paradigm In this commentary, we suggest that just as new advances in both knowledge and methodologies inspired the model of 1987, we are now at a similar point where new knowledge and its enabling technologies merit a revision of the 1987 model. We propose the following 2014 model shown in Figure 2. In this figure, we incorporate the microbiome, with its diversity of organisms and large metagenome that encodes multiple metabolic and sequestration functions, at the interface between the external environment (literally outside the organism as defined physiologically) and the internal environment inside the organism. In this position, the microbiome exerts its influence at the portal of entry and prior to absorption and converts an external exposure into a presented external exposure at sites of absorption in the gut. The addition of the microbiome also adds to the complexity of understanding susceptibility, as the community taxonomy and functionality can vary and thus modulate the conversation of external exposure to presented external exposure. This has immediate implications for the classic toxicological ADME model of absorption, distribution, metabolism, and excretion (Fig. 2) based on the assumption that these events only take place within the organism after absorption. Because this has been most fully described for the gut (and thus is most immediately relevant to pathways of ingestion) we will frame this article within that context, but similar “gatekeeper functions” are performed by the microbiomes of the nares, skin, and airway. In addition, the microbiome, like other barrier organs such as skin and lung, may be affected by contact with external exposures, as has been shown in several studies of toxic agents as discussed below and this can also contribute to toxicity in the host and also affect gut absorption

(Faber and Baumler, 2014; Snedeker and Hay, 2012). In this article we focus on the microbiome as a critical component in metabolism by the human superorganism because of the lack of considering microbial pathways in gene:environment studies of environmental chemicals. In addition to metabolism gut microbiota can also sequester metals and other agents and thus alter absorption kinetics (Ackland et al., forthcoming). The Role of the Gut Microbiome in Xenobiotic Metabolism and Sequestration The microbiome is highly active metabolically not only for processing nutrients and other food substances in food and water but also in terms of broader metabolic competencies. This is not a new realization, although it is newly incorporated into the model we are proposing. For at least 30 years, environmental scientists have recognized the role of environmental microbes in toxicant processing, such as the conversion of inorganic metals to organometal species, notably mercury into methylmercury and organoarsenicals into inorganic species. Microbiologists and environmental engineers have long harnessed the metabolic machinery of environmental microbes to detoxify contaminants in the environment including complex polycyclic aromatic hydrocarbons. What has not been fully realized in biomarker based research is that many of these same microbial populations are present within the microbiome of the human gut. The example of bacterial arsenic methylation, in addition to extrusion by several arsenic extrusion proteins, is described below. Many of the same genes and proteins are involved in arsenic metabolism by both prokaryotic and eukaryotic cells as shown in Figure 3. An analysis of the Human Microbiome Project database reported the presence of arsenic-associated genes in Escherichia coli, Staphylococcus sp, and other Bacteroides genomes (Isokpehi et al., 2014). This alone suggests that some portion of the methylated species of As that are measured in host urine in both toxicological and epidemiological studies may in fact derive from microbial metabolism external to the host, prior to absorption, and not exclusively from metabolic pathways within internal organs of the host as currently assumed. The relative contribution of microbial processing of inorganic arsenic by the external compartment of the gut microbiome is not clear, but it is no longer


FIG. 2. The completed host model of biomarkers in environmental health. The original paradigm (Figure 1) is amplified by the addition of the microbiome (in this case, the gut microbiome) at the portal of entry prior to absorption into the host (see Ackland et al., forthcoming for an example related to metals and infectious disease).

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possess similar enzymatic capacity for arsenic reductases, but likely by different proteins (Wu et al., 2014; Isokpehi et al., 2014).

tenable to focus only on host metabolism and polymorphisms in host genes associated with methylation of arsenic measured after excretion. The first study to suggest that the gut microbiome could play an important role in the transformation of arsenic from external exposure to internal dose came, appropriately, from an environmental scientist. Prof. Tom van de Wiele, who had conducted research related to environmental remediation using microbes, long the hype of microbiome research, established an ex vivo model of gut metabolism, which he called a simulator of the human intestinal microbial ecosystem. Adapting the protocols of macro and microcosm experiments widely used in environmental research, he explanted human colonic microbes into a multicompartment flow through system to which he could add test agents and metabolic substrates. Using this method, he reported that when supplemented with a methyl donor this simulated mammalian gut microbiome was able to transform arsenate and arsenite, two forms of inorganic arsenic, into mono methylated species as well as thiolated metabolites (Van de Wiele et al., 2010). His paper did not use the word “microbiome” and the world of microbiome research was first introduced to his work at a meeting held at the Institute of Medicine in 2011. Lu et al. (2014b) were the first to study gut microbiome metabolism of arsenic in an in vivo model of the human gut microbiome, the inbred gnotobiotic mouse in which the human gut microbiome is transferred under gnotobiotic conditions. They tested two hypotheses (1) that alterations in the gut microbiota induced by an infection would alter metabolism of arsenic as measured in urine and (2) that arsenic would also induce changes in the gut microbiome. This study was an effective way to focus on the contribution of the gut microbiome as there were no changes in exposure to arsenic or in host

genetics. As expected infection by a murine Helicobacter species had important effects of the microbiome as assessed with metagenomic methods, and over the same time course infection altered the metabolism of arsenic as measured in urine. There are indications of similar roles for microbiota in the metabolism of other contaminants, including polycyclic aromatic hydrocarbons, which like arsenic are widely assumed to be activated and deactivated in the human host after absorption. Bacteria within the skin microbiome, including Staphylococcus, Pseudomonas, and Micrococcus metabolize benzo(a)pyrene (B(a)P), one of the most widely studied carcinogens in cigarette smoke and other complex mixtures (Sowada et al., 2014). Microbial metabolism of B(a)P, a major air pollutant, demonstrates that bacteria can generate metabolites identified as carcinogenic prior to absorption into an exposed host. These two case studies are important to our understanding of human risks of disease: because epidemiological studies measuring biomarkers of either B(a)P or arsenic have focused exclusively on genetic polymorphisms in the human host genome to explain variations in metabolism as well as population differences in disease risk (eg, Marnell et al., 2003; Schla¨wicke Engstro¨m et al., 2009). This new perspective does not displace the role of polymorphisms within the human genome in the metabolism of toxic agents such as B(a)P and arsenic after absorption and distribution. However, it is increasingly unlikely that human genes are the only genetic determinants of individual or population differences in terms of toxicity or disease risk based on our new understanding of the microbiome. The Impact of the Microbiome on PBPK Modeling Incorporating the microbiome into the environmental health paradigm of 1987 will have important implications for current


FIG. 3. Bacterial processing of arsenic, including extrusion by membrane carriers (ArsA/B) shown on the left or by stepwise methylation within the cell (figure reproduced with permission from Kruger et al., 2013). The genetically conserved enzymatic pathway involves arsenic methyltransferase (ArsM); bacteria and humans also


The Host Remains in the Picture Incorporating the microbiome into the causal concepts and biomarker-based schematics of epidemiology and toxicology does not remove the human or other host from the picture. The microbiome, defined as microbiota, should be considered within a specific physioogical and acolobical space. Just as environmental microbiomes are responsive to and interact with the biochemical and biological milieux of their ecological niches, the microbiomes of the host are interactive with the cellular milieu of the host such that these cells are properly considered part of the microbial world (Faber and Baumler, 2014). The immediate milieu of the gut microbiome is the luminal surface of the gut, a complex architecture comprised of a diverse population of epithelial cells, some of which contact the circulating cells of the host immune system including T cells, B cells, dendritic cells, and macrophages. The evolution of the mammalian gut microbiome reflects a complex interaction between the host immune system and the microbiome to a state of mutualism, or complementary advantage (Dishaw et al., 2014). The microbiome is said to “teach” the human immune system to maintain this mutualism, and this relationship is a main pathway by which the status of the gut microbiome influences both distal organ systems such as the brain and dispersed systems such as the immune system. In this way events within the gut microbiome—still outside the body of the host—can transduce toxic effects without being absorbed. Through this relationship, mammalian allelic variation can affect microbiota ecology and, as a result, the host genomic contribution interacts with the microbial genomic contribution to the superorganism. Among the first descriptions of the interaction between the human and microbial genomes was the finding that inheritance of mutant alleles for production of the protein pyrin (a regulator of innate immunity) and resulting in the autoinflammatory disorder, familial Mediterranean fever, also resulted in loss of both gut bacterial diversity and bacterial numbers (Khachatryan et al., 2008). Immunogenetic variants in mice alter the gut microbiome and affect microbial metabolism of xenobiotics as shown for arsenic (Lu et al., 2014a,b). Because of these interactions, it is important for research into the microbiome to include the status of the host as an important influence on the status of the microbiome and the susceptibility of the cells that directly interact with the microbiome in the gut and other surfaces and also transduce signals from the microbiome to other host organs.

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CONCLUSIONS This article presents the case for including the microbiome as an integral part of how we study environmental influences on human health, with a focus on expanding our concepts of the transition from external to internal dose and on biotransformation of chemicals and other toxicants. The importance of the microbiome challenges the 1987 model of environmental proposed by the NRC, which divides the domain of events into those external and internal to the organism. Recent advances in research on the microbiome compel us to examine this dichotomy and to consider the human organism as a holobiont, a complex community that includes the resident microbiota that comprise most of the cells and genes in the host:microbiome complex. In addition, the microbiome occupies the external surface of most if not all of the portals of entry by which environmental agents are absorbed into the organism. The microbiome has been called the “fifth organ,” and as such evidence is accumulating that it has significant influences on the process by which external exposures are absorbed by and distributed within the organism. Given this importance, our definition of gene:environment interactions should be expanded beyond the host genome to include the metagenome of the microbiome, which can mediate the transformation of xenobiotics and also be transformed by exposure to xenobiotics (Tralau et al., 2014). It is more complicated than we have thought, but also more exciting in opening new domains for understanding exposure:response relationships as well as developing effective strategies for diagnosis and intervention. For toxicology, incorporating the microbiome into the picture will revise our concepts of PBPK modeling beyond the human, and for epidemiology, incorporating the microbiome will introduce new covariates, such as infections and antibiotic use, into analyses of associations between external exposures and health risks. Although we have focused on the role of the microbiome in transducing external exposures to internal dose, in keeping with the complex interactions between the microbiome and human hosts, we recognize that the microbiome can be a target for xenobiotic action and also be a pathway for transducing the effects of xenobiotics prior to absorption to internal organ systems. Here, we expand on this idea to include the role of the microbiome in a central position of driving host internal exposure to external stressors, which then affects both risk for disease and potential further changes in toxicant vulnerability. Figure 4 provides an overview of the multiple interconnections that exist among environmental exposures, microbiome status, disease processes, and disease-associated changes in host vulnerability. In this example, several environmental exposures and conditions (including antibiotic exposure in early life) can alter microbiome diversity and metabolism and increase the risk of later-life obesity. In turn, processes associated with obesity can result in altered host vulnerability to environmental exposures as well as additional co-morbid health risks. Once the obesity pattern processes are underway, several host-chemical interactions can shift including (1) iron distribution and utilization among macrophages (Orr et al., 2014), (2) nutrient-driven protein acetylation patterns supporting inflammation-driven cancer (Lee et al., 2013), (3) the impact of air pollution on risk of cardiovascular health, and (4) body burdens and distribution of arsenic (Yu et al., 2014). In light of these downstream connections, microbiome-associated biomarkers can serve several purposes.


toxicological and pharmacological models of ADME—absorption, distribution, metabolism, excretion—usually assumed to occur in this order (Fig. 2). These models require reconsideration in light of the research summarized earlier indicating that metabolism of both drugs and toxicants can occur prior to absorption by the host organism, as shown in a new schematic by Klu¨nemann et al. (2014) that incorporates the gut microbiome. In this system, “first pass” metabolism can occur prior to absorption, involving interactions between ingested xenobiotics and the gut microbiome on the external side of the portal of entry. Both metabolites and the parent compound may then be absorbed and further processed by enzyme pathways within the organs of the host yielding active and inactive compounds, some of which may be excreted. A PBPK model that incorporates this new compartment is an important priority for research and will be highly relevant to understanding the relative contribution of the gut microbiome (and other portal of entry microbial systems) to the overall evaluation of toxicokinetics of the host/microbiome system.

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host environmental vulnerability (eg, risk of air pollution leading to hypertension).

Our challenge is to consider these multiple interactions between and within the microbiome, the immune system, and other systems of the host in terms of exposure to exogenous agents, including environmental toxicants. Understanding of role of environmental toxicants in modulating risks of most significant human diseases has made great strides in recent decades, with most research on non-communicable diseases (NCDs) (Norman et al., 2013). Models of environmental risk of NCD have yet to incorporate the microbiome as central to the continuum of events from exposure to health outcomes.

ACKNOWLEDGMENTS The authors thank the Ernst Stru¨ngmann Forum for supporting our participation in the recent forum on “Heavy Metals and Infectious Disease,” as well as our colleagues in this forum for stimulating some of the ideas in this commentary. We have also acknowledged this meeting in the text. Figures 1 and 2 were created by Sharon Blackburn, Graphic Designer, Department of Pathology, The Johns Hopkins Medical Institutions, Baltimore, Maryland. The authors thank Janice Dietert for her editorial assistance.

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FIG. 4. Interconnections among environmental exposures, microbiome status, microbiome-connected disease states (eg, obesity), and disease-associated changes in


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