Adapting concepts from systems biology to develop systems exposure event networks for exposure science research

A state-of-the-science review and guide for measuring environmental exposure biomarkers in dried blood spots

BACKGROUND

Dried blood spot (DBS) sampling is a simple, cost-effective, and minimally invasive alternative to venipuncture for measuring exposure biomarkers in public health and epidemiological research. DBS sampling provides advantages in field-based studies conducted in low-resource settings and in studies involving infants and children. In addition, DBS samples are routinely collected from newborns after birth (i.e., newborn dried blood spots, NDBS), with many states in the United States permitting access to archived NDBS samples for research purposes.

OBJECTIVES

We review the state of the science for analyzing exposure biomarkers in DBS samples, both archived and newly collected, and provide guidance on sample collection, storage, and blood volume requirements associated with individual DBS assays. We discuss recent progress regarding analytical methods, analytical sensitivity, and specificity, sample volume requirements, contamination considerations, estimating extracted blood volumes, assessing stability and analyte recovery, and hematocrit effects.

METHODS

A systematic search of PubMed (MEDLINE), Embase (Elsevier), and CINAHL (EBSCO) was conducted in March 2022. DBS method development and application studies were divided into three main chemical classes: environmental tobacco smoke, trace elements (including lead, mercury, cadmium, and arsenic), and industrial chemicals (including endocrine-disrupting chemicals and persistent organic pollutants). DBS method development and validation studies were scored on key quality-control and performance parameters by two members of the review team.

RESULTS

Our search identified 47 published reports related to measuring environmental exposure biomarkers in human DBS samples. A total of 28 reports (37 total studies) were on methods development and validation and 19 reports were primarily the application of previously developed DBS assays. High-performing DBS methods have been developed, validated, and applied for detecting environmental exposures to tobacco smoke, trace elements, and several important endocrine-disrupting chemicals and persistent organic pollutants. Additional work is needed for measuring cadmium, arsenic, inorganic mercury, and bisphenol A in DBS and NDBS samples.

SIGNIFICANCE

We present an inventory and critical review of available assays for measuring environmental exposure biomarkers in DBS and NDBS samples to help facilitate this sampling medium as an emerging tool for public health (e.g., screening programs, temporal biomonitoring) and environmental epidemiology (e.g., field-based studies).

Exhaled volatile organic compounds in adult asthma: a systematic review

The search for biomarkers that can guide precision medicine in asthma, particularly those that can be translated to the clinic, has seen recent interest in exhaled volatile organic compounds (VOCs). Given the number of studies reporting "breathomics" findings and its growing integration in clinical trials, we performed a systematic review of the literature to summarise current evidence and understanding of breathomics technology in asthma.A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-oriented systematic search was performed (CRD42017084145) of MEDLINE, Embase and the Cochrane databases to search for any reports that assessed exhaled VOCs in adult asthma patients, using the following terms (asthma AND (volatile organic compounds AND exhaled) OR breathomics).Two authors independently determined the eligibility of 2957 unique records, of which 66 underwent full-text review. Data extraction and risk of bias assessment was performed on the 22 studies deemed to fulfil the search criteria. The studies are described in terms of methodology and the evidence narratively summarised under the following clinical headings: diagnostics, phenotyping, treatment stratification, treatment monitoring and exacerbation prediction/assessment.Our review found that most studies were designed to assess diagnostic potential rather than focus on underlying biology or treatable traits. Results are generally limited by a lack of methodological standardisation and external validation and by insufficiently powered studies, but there is consistency across the literature that exhaled VOCs are sensitive to underlying inflammation. Modern studies are applying robust breath analysis workflows to large multi-centre study designs, which should unlock the full potential of measurement of exhaled volatile organic compounds in airways diseases such as asthma.

Integrating exposure to chemicals in building materials during use stage

PURPOSE

There do not currently exist scientifically defensible ways to consistently characterize the human exposures (via various pathways) to near-field chemical emissions and associated health impacts during the use stage of building materials. The present paper thus intends to provide a roadmap which summarizes the current status and guides future development for integrating into LCA the chemical exposures and health impacts on various users of building materials, with a focus on building occupants.

METHODS

We first review potential human health impacts associated with the substances in building materials and the methods used to mitigate these impacts, also identifying several of the most important online data resources. A brief overview of the necessary steps for characterizing use stage chemical exposures and health impacts for building materials is then provided. Finally, we propose a systematic approach to integrate the use stage exposures and health impacts into building material LCA and describe its components, and then present a case study illustrating the application of the proposed approach to two representative chemicals: formaldehyde and methylene diphenyl diisocyanate (MDI) in particleboard products.

RESULTS AND DISCUSSION

Our proposed approach builds on the coupled near-field and far-field framework proposed by Fantke et al. (Environ Int 94:508-518, 2016), which is based on the product intake fraction (PiF) metric proposed by Jolliet et al. (Environ Sci Technol 49:8924-8931, 2015), The proposed approach consists of three major components: characterization of product usage and chemical content, human exposures, and toxicity, for which available methods and data sources are reviewed and research gaps are identified. The case study illustrates the difference in dominant exposure pathways between formaldehyde and MDI and also highlights the impact of timing and use duration (e.g., the initial 50 days of the use stage vs. the remaining 15 years) on the exposures and health impacts for the building occupants.

CONCLUSIONS

The proposed approach thus provides the methodological basis for integrating into LCA the human health impacts associated with chemical exposures during the use stage of building materials. Data and modeling gaps which currently prohibit the application of the proposed systematic approach are discussed, including the need for chemical composition data, exposure models, and toxicity data. Research areas that are not currently focused on are also discussed, such as worker exposures and complex materials. Finally, future directions for integrating the use stage impacts of building materials into decision making in a tiered approach are discussed.

Human biomarker interpretation: the importance of intra-class correlation coefficients (ICC) and their calculations based on mixed models, ANOVA, and variance estimates

Human biomonitoring is the foundation of environmental toxicology, community public health evaluation, preclinical health effects assessments, pharmacological drug development and testing, and medical diagnostics. Within this framework, the intra-class correlation coefficient (ICC) serves as an important tool for gaining insight into human variability and responses and for developing risk-based assessments in the face of sparse or highly complex measurement data. The analytical procedures that provide data for clinical and public health efforts are continually evolving to expand our knowledge base of the many thousands of environmental and biomarker chemicals that define human systems biology. These chemicals range from the smallest molecules from energy metabolism (i.e., the metabolome), through larger molecules including enzymes, proteins, RNA, DNA, and adducts. In additiona, the human body contains exogenous environmental chemicals and contributions from the microbiome from gastrointestinal, pulmonary, urogenital, naso-pharyngeal, and skin sources. This complex mixture of biomarker chemicals from environmental, human, and microbiotic sources comprise the human exposome and generally accessed through sampling of blood, breath, and urine. One of the most difficult problems in biomarker assessment is assigning probative value to any given set of measurements as there are generally insufficient data to distinguish among sources of chemicals such as environmental, microbiotic, or human metabolism and also deciding which measurements are remarkable from those that are within normal human variability. The implementation of longitudinal (repeat) measurement strategies has provided new statistical approaches for interpreting such complexities, and use of descriptive statistics based upon intra-class correlation coefficients (ICC) has become a powerful tool in these efforts. This review has two parts; the first focuses on the history of repeat measures of human biomarkers starting with occupational toxicology of the early 1950s through modern applications in interpretation of the human exposome and metabolic adverse outcome pathways (AOPs). The second part reviews different methods for calculating the ICC and explores the strategies and applications in light of different data structures.

FutureTox III: Bridges for Translation

Future Tox III, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in November 2015. Building upon Future Tox I and II, Future Tox III was focused on developing the high throughput risk assessment paradigm and taking the science of in vitro data and in silico models forward to explore the question-what progress is being made to address challenges in implementing the emerging big-data toolbox for risk assessment and regulatory decision-making. This article reports on the outcome of the workshop including 2 examples of where advancements in predictive toxicology approaches are being applied within Federal agencies, where opportunities remain within the exposome and AOP domains, and how collectively the toxicology community across multiple sectors can continue to bridge the translation from historical approaches to Tox21 implementation relative to risk assessment and regulatory decision-making.

Inflammatory Cytokines and White Blood Cell Counts Response to Environmental Levels of Diesel Exhaust and Ozone Inhalation Exposures

Epidemiological observations of urban inhalation exposures to diesel exhaust (DE) and ozone (O3) have shown pre-clinical cardiopulmonary responses in humans. Identifying the key biological mechanisms that initiate these health bioindicators is difficult due to variability in environmental exposure in time and from person to person. Previously, environmentally controlled human exposure chambers have been used to study DE and O3 dose-response patterns separately, but investigation of co-exposures has not been performed under controlled conditions. Because a mixture is a more realistic exposure scenario for the general public, in this study we investigate the relationships of urban levels of urban-level DE exposure (300 μg/m3), O3 (0.3 ppm), DE + O3 co-exposure, and innate immune system responses. Fifteen healthy human volunteers were studied for changes in ten inflammatory cytokines (interleukins 1β, 2, 4, 5, 8, 10, 12p70 and 13, IFN-γ, and TNF-α) and counts of three white blood cell types (lymphocytes, monocytes, and neutrophils) following controlled exposures to DE, O3, and DE+O3. The results show subtle cytokines responses to the diesel-only and ozone-only exposures, and that a more complex (possibly synergistic) relationship exists in the combination of these two exposures with suppression of IL-5, IL-12p70, IFN-γ, and TNF-α that persists up to 22-hours for IFN-γ and TNF-α. The white blood cell differential counts showed significant monocyte and lymphocyte decreases and neutrophil increases following the DE + O3 exposure; lymphocytes and neutrophils changes also persist for at least 22-hours. Because human studies must be conducted under strict safety protocols at environmental levels, these effects are subtle and are generally only seen with detailed statistical analysis. This study indicates that the observed associations between environmental exposures and cardiopulmonary effects are possibly mediated by inflammatory response mechanisms.

Estimating central tendency from a single spot measure: A closed-form solution for lognormally distributed biomarker data for risk assessment at the individual level

Exposure-based risk assessment employs large cross-sectional data sets of environmental and biomarker measurements to predict population statistics for adverse health outcomes. The underlying assumption is that long-term (many years) latency health problems including cancer, autoimmune and cardiovascular disease, diabetes, and asthma are triggered by lifetime exposures to environmental stressors that interact with the genome. The aim of this study was to develop a specific predictive method that provides the statistical parameters for chronic exposure at the individual level based upon a single spot measurement and knowledge of global summary statistics as derived from large data sets. This is a profound shift in exposure and health statistics in that it begins to answer the question "How large is my personal risk?" rather than just providing an overall population-based estimate. This approach also holds value for interpreting exposure-based risks for small groups of individuals within a community in comparison to random individuals from the general population.

Blood-borne biomarkers and bioindicators for linking exposure to health effects in environmental health science

Environmental health science aims to link environmental pollution sources to adverse health outcomes to develop effective exposure intervention strategies that reduce long-term disease risks. Over the past few decades, the public health community recognized that health risk is driven by interaction between the human genome and external environment. Now that the human genetic code has been sequenced, establishing this "G × E" (gene-environment) interaction requires a similar effort to decode the human exposome, which is the accumulation of an individual's environmental exposures and metabolic responses throughout the person's lifetime. The exposome is composed of endogenous and exogenous chemicals, many of which are measurable as biomarkers in blood, breath, and urine. Exposure to pollutants is assessed by analyzing biofluids for the pollutant itself or its metabolic products. New methods are being developed to use a subset of biomarkers, termed bioindicators, to demonstrate biological changes indicative of future adverse health effects. Typically, environmental biomarkers are assessed using noninvasive (excreted) media, such as breath and urine. Blood is often avoided for biomonitoring due to practical reasons such as medical personnel, infectious waste, or clinical setting, despite the fact that blood represents the central compartment that interacts with every living cell and is the most relevant biofluid for certain applications and analyses. The aims of this study were to (1) review the current use of blood samples in environmental health research, (2) briefly contrast blood with other biological media, and (3) propose additional applications for blood analysis in human exposure research.

Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms

Small molecules are indispensable to modern medical therapy. However, their use may lead to unintended, negative medical outcomes commonly referred to as adverse drug reactions (ADRs). These effects vary widely in mechanism, severity, and populations affected, making ADR prediction and identification important public health concerns. Current methods rely on clinical trials and postmarket surveillance programs to find novel ADRs; however, clinical trials are limited by small sample size, whereas postmarket surveillance methods may be biased and inherently leave patients at risk until sufficient clinical evidence has been gathered. Systems pharmacology, an emerging interdisciplinary field combining network and chemical biology, provides important tools to uncover and understand ADRs and may mitigate the drawbacks of traditional methods. In particular, network analysis allows researchers to integrate heterogeneous data sources and quantify the interactions between biological and chemical entities. Recent work in this area has combined chemical, biological, and large-scale observational health data to predict ADRs in both individual patients and global populations. In this review, we explore the rapid expansion of systems pharmacology in the study of ADRs. We enumerate the existing methods and strategies and illustrate progress in the field with a model framework that incorporates crucial data elements, such as diet and comorbidities, known to modulate ADR risk. Using this framework, we highlight avenues of research that may currently be underexplored, representing opportunities for future work.

Probe molecule (PrM) approach in adverse outcome pathway (AOP) based high-throughput screening (HTS): in vivo discovery for developing in vitro target methods

Efficient and accurate adverse outcome pathway (AOP) based high-throughput screening (HTS) methods use a systems biology based approach to computationally model in vitro cellular and molecular data for rapid chemical prioritization; however, not all HTS assays are grounded by relevant in vivo exposure data. The challenge is to develop HTS assays with unambiguous quantitative links between in vitro responses and corresponding in vivo effects, which is complicated by metabolically insufficient systems, in vitro to in vivo extrapolation (IVIVE), cross-species comparisons, and other inherent issues correlating IVIVE findings. This article introduces the concept of ultrasensitive gas phase probe molecules (PrMs) to help bridge the current HTS assay IVIVE gap. The PrM concept assesses metabolic pathways that have already been well-defined from intact human or mammalian models. Specifically, the idea is to introduce a gas phase probe molecule into a system, observe normal steady state, add chemicals of interest, and quantitatively measure (from headspace gas) effects on PrM metabolism that can be directly linked back to a well-defined and corresponding in vivo effect. As an example, we developed the pharmacokinetic (PK) parameters and differential equations to estimate methyl tertiary butyl ether (MTBE) metabolism to tertiary butyl alcohol (TBA) via cytochrome (CYP) 2A6 in the liver from human empirical data. Because MTBE metabolic pathways are well characterized from in vivo data, we can use it as a PrM to explore direct and indirect chemical effects on CYP pathways. The PrM concept could be easily applied to in vitro and alternative models of disease and phenotype, and even test for volatile chemicals while avoiding liquid handling robotics. Furthermore, a PrM can be designed for any chemical with known empirical human exposure data and used to assess chemicals for which no information exists. Herein, we propose an elegant gas phase probe molecule-based approach to in vitro toxicity testing.

Analysis of inflammatory cytokines in human blood, breath condensate, and urine using a multiplex immunoassay platform

A change in the expression of cytokines in human biological media indicates an inflammatory response to external stressors and reflects an early step along the adverse outcome pathway (AOP) for various health endpoints. To characterize and interpret this inflammatory response, methodology was developed for measuring a suite of 10 different cytokines in human blood, exhaled breath condensate (EBC), and urine using an electrochemiluminescent multiplex Th1/Th2 cytokine immunoassay platform. Measurement distributions and correlations for eight interleukins (IL) (1β, 2, 4, 5, 8, 10, 12p70 and 13), interferon-γ (IFN-γ), and tumor necrosis factor-α (TNF-α) were evaluated using 90 blood plasma, 77 EBC, and 400 urine samples collected from nominally healthy adults subjects in North Carolina in 2008-2012. The in vivo results show that there is sufficient sensitivity for characterizing all 10 cytokines at levels of 0.05-0.10 ρg/ml with a dynamic range up to 100 ng/ml across all three of these biological media. The measured in vivo results also show that the duplicate analysis of blood, EBC and urine samples have average estimated fold ranges of 2.21, 3.49, and 2.50, respectively, which are similar to the mean estimated fold range (2.88) for the lowest concentration (0.610 ρg/ml) from a series of spiked control samples; the cytokine method can be used for all three biological media. Nine out of the 10 cytokines measured in EBC were highly correlated within one another with Spearman ρ coefficients ranging from 0.679 to 0.852, while the cytokines measured in blood had a mix of negative and positive correlations, ranging from -0.620 to 0.836. Almost all correlations between EBC and blood were positive. This work also represents the first successful within- and between-person evaluation of ultra trace-level inflammatory markers in blood, EBC, and urine.

The shared pathoetiological effects of particulate air pollution and the social environment on fetal-placental development

Exposure to particulate air pollution and socioeconomic risk factors are shown to be independently associated with adverse pregnancy outcomes; however, their confounding relationship is an epidemiological challenge that requires understanding of their shared etiologic pathways affecting fetal-placental development. The purpose of this paper is to explore the etiological mechanisms associated with exposure to particulate air pollution in contributing to adverse pregnancy outcomes and how these mechanisms intersect with those related to socioeconomic status. Here we review the role of oxidative stress, inflammation and endocrine modification in the pathoetiology of deficient deep placentation and detail how the physical and social environments can act alone and collectively to mediate the established pathology linked to a spectrum of adverse pregnancy outcomes. We review the experimental and epidemiological literature showing that diet/nutrition, smoking, and psychosocial stress share similar pathways with that of particulate air pollution exposure to potentially exasperate the negative effects of either insult alone. Therefore, socially patterned risk factors often treated as nuisance parameters should be explored as potential effect modifiers that may operate at multiple levels of social geography. The degree to which deleterious exposures can be ameliorated or exacerbated via community-level social and environmental characteristics needs further exploration.

Estimating common parameters of lognormally distributed environmental and biomonitoring data: harmonizing disparate statistics from publications

The progression of science is driven by the accumulation of knowledge and builds upon published work of others. Another important feature is to place current results into the context of previous observations. The published literature, however, often does not provide sufficient direct information for the reader to interpret the results beyond the scope of that particular article. Authors tend to provide only summary statistics in various forms, such as means and standard deviations, median and range, quartiles, 95% confidence intervals, and so on, rather than providing measurement data. Second, essentially all environmental and biomonitoring measurements have an underlying lognormal distribution, so certain published statistical characterizations may be inappropriate for comparisons. The aim of this study was to review and develop direct conversions of different descriptions of data into a standard format comprised of the geometric mean (GM) and the geometric standard deviation (GSD) and then demonstrate how, under the assumption of lognormal distribution, these parameters are used to answer questions of confidence intervals, exceedance levels, and statistical differences among distributions. A wide variety of real-world measurement data sets was reviewed, and it was demonstrated that these data sets are indeed of lognormal character, thus making them amenable to these methods. Potential errors incurred from making retrospective estimates from disparate summary statistics are described. In addition to providing tools to interpret "other people's data," this review should also be seen as a cautionary tale for publishing one's own data to make it as useful as possible for other researchers.

Post-operative elimination of sevoflurane anesthetic and hexafluoroisopropanol metabolite in exhaled breath: pharmacokinetic models for assessing liver function

Sevoflurane (SEV), a commonly used anesthetic agent for invasive surgery, is directly eliminated via exhaled breath and indirectly by metabolic conversion to inorganic fluoride and hexafluoroisopropanol (HFIP), which is also eliminated in the breath. We studied the post-operative elimination of SEV and HFIP of six patients that had undergone a variety of surgeries lasting between 2.5 to 8.5 h using exhaled breath analysis. A classical three compartments pharmacokinetic model developed for the study of environmental contaminants was fitted to the breath data. We found that SEV kinetic behavior following surgery (for up to six days) is consistent across all subjects whereas the production and elimination of HFIP varies to some extent. We developed subject specific parameters for HFIP metabolism and interpreted the differences in the context of timing and dose of anesthesia, type of surgery, and specific host factors. We propose methods for assessing individual patient liver function using SEV as a probe molecule for assessing efficiency of liver metabolism to HFIP. This work is valuable not only for the clinical study of metabolism recovery, but potentially also for the study of the interaction of other manufactured and environmental compounds with human systems biology in controlled exposure and observational studies.

Categorizing biomarkers of the human exposome and developing metrics for assessing environmental sustainability

The concept of maintaining environmental sustainability broadly encompasses all human activities that impact the global environment, including the production of energy, use and management of finite resources such as petrochemicals, metals, food production (farmland, fresh and ocean waters), and potable water sources (rivers, lakes, aquifers), as well as preserving the diversity of the surrounding ecosystems. The ultimate concern is how one can manage Spaceship Earth in the long term to sustain the life, health, and welfare of the human species and the planet's flora and fauna. On a more intimate scale, one needs to consider the human interaction with the environment as expressed in the form of the exposome, which is defined as all exogenous and endogenous exposures from conception onward, including exposures from diet, lifestyle, and internal biology, as a quantity of critical interest to disease etiology. Current status and subsequent changes in the measurable components of the exposome, the human biomarkers, could thus conceivably be used to assess the sustainability of the environmental conditions with respect to human health. The basic theory is that a shift away from sustainability will be reflected in outlier measurements of human biomarkers. In this review, the philosophy of long-term environmental sustainability is explored in the context of human biomarker measurements and how empirical data can be collected and interpreted to assess if solutions to existing environmental problems might have unintended consequences. The first part discusses four conventions in the literature for categorizing environmental biomarkers and how different types of biomarker measurements might fit into the various grouping schemes. The second part lays out a sequence of data management strategies to establish statistics and patterns within the exposome that reflect human homeostasis and how changes or perturbations might be interpreted in light of external environmental stressors. The underlying concept is to identify probative outliers from the "unremarkable exposome" in individuals or subpopulations that could be used for discerning deviations from the healthy environment, much like current diagnostic medicine uses batteries of blood and urine tests to screen for preclinical disease conditions. Such empirically derived human in vivo data could subsequently be integrated into high-throughput in vitro and in silico testing of environmental and manufactured chemicals to support real-world toxicity evaluations.

A biomonitoring framework to support exposure and risk assessments

BACKGROUND

Biomonitoring is used in exposure and risk assessments to reduce uncertainties along the source-to-outcome continuum. Specifically, biomarkers can help identify exposure sources, routes, and distributions, and reflect kinetic and dynamic processes following exposure events. A variety of computational models now utilize biomarkers to better understand exposures at the population, individual, and sub-individual (target) levels. However, guidance is needed to clarify biomonitoring use given available measurements and models.

OBJECTIVE

This article presents a biomonitoring research framework designed to improve biomarker use and interpretation in support of exposure and risk assessments.

DISCUSSION

The biomonitoring research framework is based on a modified source-to-outcome continuum. Five tiers of biomonitoring analyses are included in the framework, beginning with simple cross-sectional and longitudinal analyses, and ending with complex analyses using various empirical and mechanistic models. Measurements and model requirements of each tier are given, as well as considerations to enhance analyses. Simple theoretical examples are also given to demonstrate applications of the framework for observational exposure studies.

CONCLUSION

This biomonitoring framework can be used as a guide for interpreting existing biomarker data, designing new studies to answer specific exposure- and risk-based questions, and integrating knowledge across scientific disciplines to better address human health risks.

Heat map visualization of complex environmental and biomarker measurements

Over the past decade, the assessment of human systems interactions with the environment has permeated all phases of environmental and public health research. We are invoking lessons learned from the broad discipline of Systems Biology research that focuses primarily on molecular and cellular networks and adapting these concepts to Systems Exposure Science which focuses on interpreting the linkage from environmental measurements and biomonitoring to the expression of biological parameters. A primary tool of systems biology is the visualization of complex genomic and proteomic data using "heat maps" which are rectangular color coded arrays indicating the intensity (or amount) of the dependent variable. Heat maps are flexible in that both the x-axis and y-axis can be arranged to explore a particular hypothesis and allow a fast overview of data with a third quantitative dimension captured as different colors. We are now adapting these tools for interpreting cumulative and aggregate environmental exposure measurements as well as the results from human biomonitoring of biological media including blood, breath and urine. This article uses existing EPA measurements of environmental and biomarker concentrations of polycyclic aromatic hydrocarbons (PAHs) to demonstrate the value of the heat map approach for hypothesis development and to link back to stochastic and mixed effects models that were originally used to assess study results.

Observing the human exposome as reflected in breath biomarkers: heat map data interpretation for environmental and intelligence research

Over the past decade, the research of human system biology and the interactions with the external environment has permeated all phases of environmental, medical and public health research. Similar to the fields of genomics and proteomics research, the advent of new instrumentation for measuring breath biomarkers and their associated meta-data also provide very useful, albeit complex, data structures. The biomarker research community is beginning to invoke tools from system biology to assess the impact of environmental exposures, as well as from internal health states, on the expression of suites of chemicals in exhaled breath. This new approach introduces the concept of the exposome as a complement to the genome in exploring the environment-gene interaction. In addition to answering questions regarding health status for the medical community, breath biomarker patterns are useful for assessing public health risks from environmental exposures. Furthermore, breath biomarker patterns can inform security risks from suspects via covert interrogation of blood borne chemical levels that reflect previous activities. This paper discusses how different classes of exhaled breath biomarker measurements can be used to rapidly assess patterns in complex data. We present exhaled breath data sets to demonstrate the value of the graphical 'heat map' approach for hypothesis development and subsequent guidance for stochastic and mixed effect data interpretation. We also show how to graphically interpret exhaled breath measurements of exogenous jet fuel components, as well as exhaled breath condensate measurements of endogenous chemicals.