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Pneumonia is a significant risk for critically ill, mechanically ventilated (CIMV) patients. Diagnosis of pneumonia generally requires a combination of clinician-guided diagnoses and clinical scoring systems. Exhaled breath condensate (EBC) can be safely collected non-invasively from CIMV patients. Hundreds of biomarkers in EBC are associated with acute disease states, including pneumonia. We evaluated cytokines in EBC from CIMV patients and hypothesized that these biomarkers would correlate with disease severity in pneumonia, sepsis, and death. EBC IL-2 levels were associated with chest radiograph severity scores (odds ratio = 1.68; 95% confidence interval = 1.09–2.60; P = 0.02). EBC TNF-α levels were also associated with pneumonia (odds ratio = 3.20; 95% confidence interval = 1.19–8.65; P = 0.02). The techniques and results from this study may be useful for all mechanically ventilated patients.

Human breath, along with urine and blood, has long been one of the three major biological media for assessing human health and environmental exposure. In fact, the detection of odor on human breath, as described by Hippocrates in 400 BC, is considered the first analytical health assessment tool. Although less common in comparison to contemporary bio-fluids analyses, breath has become an attractive diagnostic medium as sampling is non-invasive, unlimited in timing and volume, and does not require clinical personnel. Exhaled breath, exhaled breath condensate (EBC), and exhaled breath aerosol (EBA) are different types of breath matrices used to assess human health and disease state. Over the past 20 years, breath research has made many advances in assessing health state, overcoming many of its initial challenges related to sampling and analysis. The wide variety of sampling techniques and collection devices that have been developed for these media are discussed herein. The different types of sensors and mass spectrometry instruments currently available for breath analysis are evaluated as well as emerging breath research topics, such as cytokines, security and airport surveillance, cellular respiration, and canine olfaction.

Cognitive impairments, uncontrolled drinking, and neuropathological cortical changes characterize alcohol use disorder. Dysfunction of the orbitofrontal cortex (OFC), a critical cortical subregion that controls learning, decision-making, and prediction of reward outcomes, contributes to executive cognitive function deficits in alcoholic individuals. Electrophysiological and quantitative synaptomics techniques were used to test the hypothesis that heavy drinking produces neuroadaptations in the macaque OFC. Integrative bioinformatics and reverse genetic approaches were used to identify and validate synaptic proteins with novel links to heavy drinking in BXD mice. In drinking monkeys, evoked firing of OFC pyramidal neurons was reduced, whereas the amplitude and frequency of postsynaptic currents were enhanced compared with controls. Bath application of alcohol reduced evoked firing in neurons from control monkeys, but not drinking monkeys. Profiling of the OFC synaptome identified alcohol-sensitive proteins that control glutamate release (e.g., SV2A, synaptogyrin-1) and postsynaptic signaling (e.g., GluA1, PRRT2) with no changes in synaptic GABAergic proteins. Western blot analysis confirmed the increase in GluA1 expression in drinking monkeys. An exploratory analysis of the OFC synaptome found cross-species genetic links to alcohol intake in discrete proteins (e.g., C2CD2L, DIRAS2) that discriminated between low- and heavy-drinking monkeys. Validation studies revealed that BXD mouse strains with theDallele at theC2cd2linterval drank less alcohol thanBallele strains. Thus, by profiling of the OFC synaptome, we identified changes in proteins controlling glutamate release and postsynaptic signaling and discovered several proteins related to heavy drinking that have potential as novel targets for treating alcohol use disorder.SIGNIFICANCE STATEMENTClinical research identified cognitive deficits in alcoholic individuals as a risk factor for relapse, and alcoholic individuals display deficits on cognitive tasks that are dependent upon the orbitofrontal cortex (OFC). To identify neurobiological mechanisms that underpin OFC dysfunction, this study used electrophysiology and integrative synaptomics in a translational nonhuman primate model of heavy alcohol consumption. We found adaptations in synaptic proteins that control glutamatergic signaling in chronically drinking monkeys. Our functional genomic exploratory analyses identified proteins with genetic links to alcohol and cocaine intake across mice, monkeys, and humans. Future work is necessary to determine whether targeting these novel targets reduces excessive and harmful levels of alcohol drinking.

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.

Exhaled breath has joined blood and urine as a valuable resource for sampling and analyzing biomarkers in human media for assessing exposure, uptake metabolism, and elimination of toxic chemicals. This article focuses current use of exhaled gas, aerosols, and vapor in human breath, the methods for collection, and ultimately the use of the resulting data. Some advantages of breath are the noninvasive and self-administered nature of collection, the essentially inexhaustible supply, and that breath sampling does not produce potentially infectious waste such as needles, wipes, bandages, and glassware. In contrast to blood and urine, breath samples can be collected on demand in rapid succession and so allow toxicokinetic observations of uptake and elimination in any time frame. Furthermore, new technologies now allow capturing condensed breath vapor directly, or just the aerosol fraction alone, to gain access to inorganic species, lung pH, proteins and protein fragments, cellular DNA, and whole microorganisms from the pulmonary microbiome. Future applications are discussed, especially the use of isotopically labeled probes, non-targeted (discovery) analysis, cellular level toxicity testing, and ultimately assessing "crowd breath" of groups of people and the relation to dose of airborne and other environmental chemicals at the population level.

A non-targeted analysis workflow was applied to analyze exhaled breath samples collected from firefighters pre- and post-structural fire suppression. Breath samples from firefighters functioning in attack and search positions were examined for target and non-target compounds in automated thermal desorption-GC/MS (ATD-GC/MS) selected ion monitoring (SIM)/scan mode and reviewed for prominent chemicals. Targeted chemicals included products of combustion such as benzene, toluene, xylenes, and polycyclic aromatic hydrocarbons (PAH) that serve as a standard assessment of exposure. Sixty unique chemical features representative of exogenous chemicals and endogenous compounds, including single-ring aromatics, polynuclear aromatic hydrocarbons, volatile sulfur-containing compounds, aldehydes, alkanes, and alkenes were identified using the non-targeted analysis workflow. Fifty-seven out of 60 non-targeted features changed by at least 50% from pre- to post-fire suppression activity in at least one subject, and 7 non-targeted features were found to exhibit significantly increased or decreased concentrations for all subjects as a group. This study is important for (1) alerting the firefighter community to potential new exposures, (2) expanding the current targeted list of toxicants, and (3) finding biomarkers of response to firefighting activity as reflected by changes in endogenous compounds. Data demonstrate that there are non-targeted compounds in firefighters' breath that are indicative of environmental exposure despite the use of protective gear, and this information may be further utilized to improve the effectiveness of personal protective equipment.

Biomarker measurements can provide unambiguous evidence of environmental exposures as well as the resultant biological responses. Firefighters have a high rate of occupational cancer incidence, which has been proposed to be linked in part to their increased environmental exposure to byproducts of combustion and contaminants produced during fire responses. In this article, the uptake and elimination of targeted volatile organic compounds were investigated by collecting the exhaled breath of firefighters on sorbent tubes before and after controlled structure burns and analyzing samples using automated thermal desorption-gas chromatography (ATD-GC/MS). Volatile organic compounds exposure was assessed by grouping the data according to firefighting job positions as well as visualizing the data at the level of the individual firefighter to determine which individuals had expected exposure responses. When data were assessed at the group level, benzene concentrations were found to be elevated post-exposure in both fire attack, victim search, and outside ventilation firefighting positions. However, the results of the data analysis at the individual level indicate that certain firefighters may be more susceptible to post-exposure volatile organic compounds increases than others, and this should be considered when assessing the effectiveness of firefighting protective gear. Although this work focuses on firefighting activity, the results can be translated to potential human health and ecological effects from building and forest fires.

Environmental exposure diagnostics use creatinine concentrations in urine aliquots as the internal standard for dilution normalization of all other excreted metabolites when urinary excretion rate data are not available. This is a reasonable approach for healthy adults as creatinine is a human metabolite that is continually produced in skeletal muscles and presumably excreted in the urine at a stable rate. However, creatinine also serves as a biomarker for glomerular filtration rate (efficiency) of the kidneys, so undiagnosed kidney function impairment could affect this commonly applied dilution calculation. The United States Environmental Protection Agency (US EPA) has recently conducted a study that collected approximately 2600 urine samples from 50 healthy adults, aged 19-50 years old, in North Carolina in 2009-2011. Urinary ancillary data (creatinine concentration, total void volume, elapsed time between voids), and participant demographic data (race, gender, height, and body weight) were collected. A representative subset of 280 urine samples from 29 participants was assayed using a new kidney injury panel (KIP). In this article, we investigated the relationships of KIP biomarkers within and between subjects and also calculated their interactions with measured creatinine levels. The aims of this work were to document the analytical methods (procedures, sensitivity, stability, etc.), provide summary statistics for the KIP biomarkers in "healthy" adults without diagnosed disease (distribution, fold range, central tendency, variance), and to develop an understanding as to how urinary creatinine level varies with respect to the individual KIP proteins. Results show that new instrumentation and data reduction methods have sufficient sensitivity to measure KIP levels in nominally healthy urine samples, that linear regression between creatinine concentration and urinary excretion explains only about 68% of variability, that KIP markers are poorly correlated with creatinine (r(2) ∼ 0.34), and that statistical outliers of KIP markers are not random, but are clustered within certain subjects. In addition, we interpret these new adverse outcome pathways based in vivo biomarkers for their potential use as intermediary chemicals that may be diagnostic of kidney adverse outcomes to environmental exposure.

Background Each year, the U.S. NHANES measures hundreds of chemical biomarkers in samples from thousands of study participants. These biomarker measurements are used to establish population reference ranges, track exposure trends, identify population subsets with elevated exposures, and prioritize research needs. There is now interest in further utilizing the NHANES data to inform chemical risk assessments. Objectives This article highlights a) the extent to which U.S. NHANES chemical biomarker data have been evaluated, b) groups of chemicals that have been studied, c) data analysis approaches and challenges, and d) opportunities for using these data to inform risk assessments. Methods A literature search (1999–2013) was performed to identify publications in which U.S. NHANES data were reported. Manual curation identified only the subset of publications that clearly utilized chemical biomarker data. This subset was evaluated for chemical groupings, data analysis approaches, and overall trends. Results A small percentage of the sampled NHANES-related publications reported on chemical biomarkers (8% yearly average). Of 11 chemical groups, metals/metalloids were most frequently evaluated (49%), followed by pesticides (9%) and environmental phenols (7%). Studies of multiple chemical groups were also common (8%). Publications linking chemical biomarkers to health metrics have increased dramatically in recent years. New studies are addressing challenges related to NHANES data interpretation in health risk contexts. Conclusions This article demonstrates growing use of NHANES chemical biomarker data in studies that can impact risk assessments. Best practices for analysis and interpretation must be defined and adopted to allow the full potential of NHANES to be realized. Citation Sobus JR, DeWoskin RS, Tan YM, Pleil JD, Phillips MB, George BJ, Christensen K, Schreinemachers DM, Williams MA, Cohen Hubal EA, Edwards SW. 2015. Uses of NHANES biomarker data for chemical risk assessment: trends, challenges, and opportunities. Environ Health Perspect 123:919–927; http://dx.doi.org/10.1289/ehp.1409177

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.

Breath analysis is a young field of research with great clinical potential. As a result of this interest, researchers have developed new analytical techniques that permit real-time analysis of exhaled breath with breath-to-breath resolution in addition to the conventional central laboratory methods using gas chromatography–mass spectrometry. Breath tests are based on endogenously produced volatiles, metabolites of ingested precursors, metabolites produced by bacteria in the gut or the airways, or volatiles appearing after environmental exposure. The composition of exhaled breath may contain valuable information for patients presenting with asthma, renal and liver diseases, lung cancer, chronic obstructive pulmonary disease, inflammatory lung disease, or metabolic disorders. In addition, oxidative stress status may be monitored via volatile products of lipid peroxidation. Measurement of enzyme activity provides phenotypic information important in personalized medicine, whereas breath measurements provide insight into perturbations of the human exposome and can be interpreted as preclinical signals of adverse outcome pathways.

CD83 is a type-I membrane protein and an efficient marker for identifying mature dendritic cells. Whereas membrane-bound, full-length CD83 co-stimulates the immune system, a soluble variant (sCD83), consisting of the extracellular domain only, displays strong immune-suppressive activities. Besides a prediction that sCD83 adopts a V-set Ig-like fold, however, little is known about the molecular architecture of CD83 and the mechanism by which CD83 exerts its function on dendritic cells and additional immune cells. Here, we report the crystal structure of human sCD83 up to a resolution of 1.7A solved in three different crystal forms. Interestingly, β-strands C', C″, and D that are typical for V-set Ig-domains could not be traced in sCD83. Mass spectrometry analyses, limited proteolysis experiments, and bioinformatics studies show that the corresponding segment displays enhanced main-chain accessibility, extraordinary low sequence conservation, and a predicted high disorder propensity. Chimeric proteins with amino acid swaps in this segment show unaltered immune-suppressive activities in a TNF-α assay when compared to wild-type sCD83. This strongly indicates that this segment does not participate in the biological activity of CD83. The crystal structure of CD83 shows the recurrent formation of dimers and trimers in the various crystal forms and reveals strong structural similarities between sCD83 and B7 family members and CD48, a signaling lymphocyte activation molecule family member. This suggests that CD83 exerts its immunological activity by mixed homotypic and heterotypic interactions as typically observed for proteins present in the immunological synapse.

One of the main uses of biomarker measurements is to compare different populations to each other and to assess risk in comparison to established parameters. This is most often done using summary statistics such as central tendency, variance components, confidence intervals, exceedance levels and percentiles. Such comparisons are only valid if the underlying assumptions of distribution are correct. This article discusses methodology for interpreting and evaluating data distributions using quartile-quartile plots (QQ-plots) and making decisions as to how to treat outliers, interpreting effects of mixed distributions, and identifying left-censored data. The QQ-plot graph is shown to be a simple and elegant tool for visual inspection of complex data and deciding if summary statistics should be performed after log-transformation.

This commentary is the second of a series outlining one specific concept in interpreting biomarkers data. In the first, an observational method was presented for assessing the distribution of measurements before making parametric calculations. Here, the discussion revolves around the next step, the choice of using standard error of the mean or the calculated standard deviation to compare or predict measurement results.

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.

Exposure to diesel exhaust (DE) has been associated with acute cardiopulmonary and vascular responses, chronic noncancer health effects, and respiratory cancers in humans. To better understand DE exposures and eventually their related health effects, we established a controlled chamber experiment wherein human volunteer subjects were exposed to approximately 100 microg/m3 DE. In general, human exposure assessment for DE is based on ambient air measurements of surrogates such as elemental carbon (EC) or total organic carbon (OC) collected on filters. As specific health effect mechanisms and dose-response are obscured bythe complex composition of DE, the linkage from exposure to internal dose can presumably be improved by use of specific biomarkers and metabolites in blood, breath, or urine. Because EC and OC are not suitable as biomarkers, in this study, we focus on identifying compounds that are demonstrated indicators of DE and can also be found in biological fluids. We measured an assortment of volatile, semivolatile, and particle-bound aromatic compounds in the chamber air and report their airborne concentrations in DE and purified air, as well as the estimated values of the corresponding exposure ratios (mean DE air concentration:mean purified air concentration). These estimated exposure ratios were used to identify naphthalene (Nap) and phenanthrene (Phe) as potentially useful surrogates for DE exposure that could also serve as biomarkers. Estimated mean levels of Nap and Phe associated with the nominal 100 microg/m3 DE were 2600 and 765 ng/m3 with estimated exposure ratios of 252 and 92.4, respectively. Nap levels were significantly correlated with OC and total particle-bound polycyclic aromatic hydrocarbons (PAHs); Phe levels were significantly correlated with total volatile + semivolatile PAHs. These results suggest that Nap and Phe may be particularly useful surrogates for DE concentrations. While Nap and Phe are not validated here as internal biomarkers of DE exposure, we are currently assessing human biological specimens collected during this study and will discuss those results in ensuing papers.

Cytokines, low-molecular-weight messenger proteins that act as intercellular immunomodulatory signals, have become a mainstream preclinical marker for assessing the systemic inflammatory response to external stressors. The challenge is to quantitate from healthy subjects cytokine levels that are below or at baseline and relate those dynamic and complex cytokine signatures of exposures with the inflammatory and repair pathways. Thus, highly sensitive, specific, and precise analytical and statistical methods are critically important. Investigators at the U.S. Environmental Protection Agency (EPA) have implemented advanced technologies and developed statistics for evaluating panels of inflammatory cytokines in human blood, exhaled breath condensate, urine samples, and murine biological media. Advanced multiplex, bead-based, and automated analytical platforms provided sufficient sensitivity, precision, and accuracy over the traditional enzyme-linked immunosorbent assay (ELISA). Thus, baseline cytokine levels can be quantified from healthy human subjects and animals and compared to an in vivo exposure response from an environmental chemical. Specifically, patterns of cytokine responses in humans exposed to environmental levels of ozone and diesel exhaust, and in rodents exposed to selected pesticides (such as fipronil and carbaryl), were used as case studies to generally assess the taxonomic applicability of cytokine responses. The findings in this study may aid in the application of measureable cytokine markers in future adverse outcome pathway (AOP)-based toxicity testing. Data from human and animal studies were coalesced and the possibility of using cytokines as key events (KE) to bridge species responses to external stressors in an AOP-based framework was explored.

Methyl tertiary butyl ether (MTBE), a gasoline additive used to increase octane and reduce carbon monoxide emissions and ozone precursors, has contaminated drinking water and can lead to exposure by oral, inhalation, and dermal routes. To determine its dermal, oral, and inhalation kinetics, 14 volunteers were exposed to 51.3 microg/ml MTBE dermally in tap water for 1 h, drank 2.8 mg MTBE in 250 ml Gatorade(R), and inhaled 3.1 ppm. MTBE for 1 h. Blood and exhaled breath samples were then obtained. Blood MTBE peaked between 15 and 30 min following oral exposure, at the end of inhalation exposure, and ~5 min after dermal exposure. Elimination by each route was described well by a three-compartment model (Rsq >0.9). The Akaike Information Criterion for the three-compartment model was smaller than the two-compartment model, supporting it over the two-compartment model. One metabolite, tertiary butyl alcohol (TBA), measured in blood slowly increased and plateaued, but it did not return to the pre-exposure baseline at the 24-h follow-up. TBA is very water-soluble and has a blood:air partition ratio of 462, reducing elimination by exhalation. Oral exposure resulted in a significantly greater MTBE metabolism into TBA than by other routes based on a greater blood TBA:MTBE AUC ratio, implying significant first-pass metabolism. The slower TBA elimination may make it a better biomarker of MTBE exposure, though one must consider the exposure route when estimating MTBE exposure from TBA because of first-pass metabolism. Most subjects had a baseline blood TBA of 1-3 ppb. Because TBA is found in consumer products and can be used as a fuel additive, it is not a definitive marker of MTBE exposure. These data provide the risk assessment process of pharmacokinetic information relevant to the media through which most exposures occur-air and drinking water.

Exhaled breath condensate (EBC) and associated exhaled breath aerosols (EBA) are valuable non-invasive biological media used for the quantification of biomarkers. EBC contains exhaled water vapor, soluble gas-phase (polar) organic compounds, ionic species, plus other species including semi- and non-volatile organic compounds, proteins, cell fragments, DNA, dissolved inorganic compounds, ions, and micro-biota (bacteria and viruses) dissolved in the co-collected EBA. EBC is collected from subjects who breathe “normally” through a chilled tube assembly for approximately 10 minutes and is then harvested into small vials for analysis. Aerosol filters without the chilled tube assembly are also used to separately collect EBA. Unlike typical gas-phase breath samples used for environmental and clinical applications, the constituents of EBC and EBA are not easily characterized by total volume or carbon dioxide (CO2) concentration, because the gas-phase is vented. Furthermore, EBC and associated EBA are greatly affected by breathing protocol, more specifically, depth of inhalation and expelled breath velocity. We have tested a new instrument developed by Loccioni Gruppa Humancare (Ancona, Italy) for implementation of EBC collection from human subjects to assess EBC collection parameters. The instrument is the first EBC collection device that provides instantaneous visual feedback to the subjects to control breathing patterns. In this report we describe the operation of the instrument, and present an overview of performance and analytical applications.

Turnout gear provides protection against dermal exposure to contaminants during firefighting; however, the level of protection is unknown. We explored the dermal contribution to the systemic dose of polycyclic aromatic hydrocarbons (PAHs) and other aromatic hydrocarbons in firefighters during suppression and overhaul of controlled structure burns. The study was organized into two rounds, three controlled burns per round, and five firefighters per burn. The firefighters wore new or laundered turnout gear tested before each burn to ensure lack of PAH contamination. To ensure that any increase in systemic PAH levels after the burn was the result of dermal rather than inhalation exposure, the firefighters did not remove their self-contained breathing apparatus until overhaul was completed and they were >30 m upwind from the burn structure. Specimens were collected before and at intervals after the burn for biomarker analysis. Urine was analyzed for phenanthrene equivalents using enzyme-linked immunosorbent assay and a benzene metabolite (s-phenylmercapturic acid) using liquid chromatography/tandem mass spectrometry; both were adjusted by creatinine. Exhaled breath collected on thermal desorption tubes was analyzed for PAHs and other aromatic hydrocarbons using gas chromatography/mass spectrometry. We collected personal air samples during the burn and skin wipe samples (corn oil medium) on several body sites before and after the burn. The air and wipe samples were analyzed for PAHs using a liquid chromatography with photodiode array detection. We explored possible changes in external exposures or biomarkers over time and the relationships between these variables using non-parametric sign tests and Spearman tests, respectively. We found significantly elevated (P < 0.05) post-exposure breath concentrations of benzene compared with pre-exposure concentrations for both rounds. We also found significantly elevated post-exposure levels of PAHs on the neck compared with pre-exposure levels for round 1. We found statistically significant positive correlations between external exposures (i.e. personal air concentrations of PAHs) and biomarkers (i.e. change in urinary PAH metabolite levels in round 1 and change in breath concentrations of benzene in round 2). The results suggest that firefighters wearing full protective ensembles absorbed combustion products into their bodies. The PAHs most likely entered firefighters’ bodies through their skin, with the neck being the primary site of exposure and absorption due to the lower level of dermal protection afforded by hoods. Aromatic hydrocarbons could have been absorbed dermally during firefighting or inhaled during the doffing of gear that was off-gassing contaminants.

Biomonitoring is the process by which biomarkers are measured in human tissues and specimens to evaluate exposures. Given the growing number of population-based biomonitoring surveys, there is now an escalated interest in using biomarker data to reconstruct exposures for supporting risk assessment and risk management. While detection of biomarkers is de facto evidence of exposure and absorption, biomarker data cannot be used to reconstruct exposure unless other information is available to establish the external exposure-biomarker concentration relationship. In this review, the process of using biomarker data and other information to reconstruct human exposures is examined. Information that is essential to the exposure reconstruction process includes (1) the type of biomarker based on its origin (e.g., endogenous vs. exogenous), (2) the purpose/design of the biomonitoring study (e.g., occupational monitoring), (3) exposure information (including product/chemical use scenarios and reasons for expected contact, the physicochemical properties of the chemical and nature of the residues, and likely exposure scenarios), and (4) an understanding of the biological system and mechanisms of clearance. This review also presents the use of exposure modeling, pharmacokinetic modeling, and molecular modeling to assist in integrating these various types of information.

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.

Biomarkers are useful exposure surrogates given their ability to integrate exposures through all routes and to reflect interindividual differences in toxicokinetic processes. Also, biomarker concentrations tend to vary less than corresponding environmental measurements, making them less-biasing surrogates for exposure. In this article, urinary PAH biomarkers (namely, urinary naphthalene [U-Nap]; urinary phenenthrene [U-Phe]; 1-hydroxypyrene [1-OH-Pyr]; and 1-, (2+3)-, 4-, and 9-hydroxyphenenthrene [1-, (2+3)-, 4-, and 9-OH-Phe]) were evaluated as surrogates for exposure to hot asphalt emissions using data from 20 road-paving workers. Linear mixed-effects models were used to estimate the within- and between-person components of variance for each urinary biomarker. The ratio of within- to between-person variance was then used to estimate the biasing effects of each biomarker on a theoretical exposure-response relationship. Mixed models were also used to estimate the amounts of variation in Phe metabolism to individual OH-Phe isomers that could be attributed to Phe exposure (as represented by U-Phe concentrations) and covariates representing time, hydration level, smoking status, age, and body mass index. Results showed that 1-OH-Phe, (2+3)-OH-Phe, and 1-OH-Pyr were the least-biasing surrogates for exposure to hot asphalt emissions, and that effects of hydration level and sample collection time substantially inflated bias estimates for the urinary biomarkers. Mixed-model results for the individual OH-Phe isomers showed that between 63% and 82% of the observed biomarker variance was collectively explained by Phe exposure, the time and day of sample collection, and the hydration level, smoking status, body mass index, and age of each worker. By difference, the model results also showed that, depending on the OH-Phe isomer, a maximum of 6% to 23% of the total biomarker variance was attributable to differences in unobserved toxicokinetic processes between the workers. Therefore, toxicokinetic processes are probably less influential on urinary biomarker variance than are exposures and observable covariate effects. The methods described in this analysis should be considered for the selection and interpretation of biomarkers as exposure surrogates in future exposure investigations.

We have investigated the mechanism of the changes in the profile of metabolic enzyme expression that occur in association with fast-to-slow transformation of rabbit skeletal muscle. The hypotheses assessed are: do 1) lowered intracellular ATP concentration or 2) reduction of the muscular glycogen stores act as triggers of metabolic transformation? We find that 3 days of decreased cytosolic ATP content have no impact on the investigated metabolic markers, whereas incubation of the cells with little or no glucose leads to decreases in glycogen in conjunction with decreases in glyceraldehyde-3-phosphate dehydrogenase (GAPDH) promoter activity, GAPDH mRNA and specific GAPDH enzyme activity (indicators of the anaerobic glycolytic pathway), and furthermore to increases in mitochondrial acetoacetyl-CoA thiolase (MAT, also known as ACAT) promoter activity, peroxisome proliferator-activated receptor gamma coactivator 1alpha (PGC-1alpha) expression and citrate synthase (CS) specific enzyme activity (all indicators of oxidative metabolic pathways). The AMP-activated protein kinase (AMPK) activity under these conditions is reduced compared to controls. In experiments with two inhibitors of glycogen degradation we show that the observed metabolic transformation caused by low glucose takes place even if intracellular glycogen content is high. These findings for the first time provide evidence that metabolic adaptation of skeletal muscle cells from rabbit in primary culture can be induced not only by elevation of intracellular calcium concentration or by a rise of AMPK activity, but also by reduction of glucose supply. Contrary to expectations, neither an increase in phospho-AMPK nor a reduction of muscular glycogen content are crucial events in the glucose-dependent induction of metabolic transformation in the muscle cell culture system studied.

Adverse health risks from environmental agents are generally related to average (long-term) exposures. Because a given individual's contact with a pollutant is highly variable and dependent on activity patterns, local sources and exposure pathways, simple 'snapshot' measurements of surrounding environmental media may not accurately assign the exposure level. Furthermore, susceptibility to adverse effects from contaminants is considered highly variable in the population so that even similar environmental exposure levels may result in differential health outcomes in different individuals. The use of biomarker measurements coupled to knowledge of rates of uptake, metabolism and elimination has been suggested as a remedy for reducing this type of uncertainty. To demonstrate the utility of such an approach, we invoke results from a series of controlled human exposure tests and classical first-order rate kinetic calculations to estimate how well spot measurements of methyl tertiary butyl ether and the primary metabolite, tertiary butyl alcohol, can be expected to predict different hypothetical scenarios of previous exposures. We found that blood and breath biomarker measurements give similar results and that the biological damping effect of the metabolite production gives more stable estimates of previous exposure. We also explore the value of a potential urinary biomarker, 2-hydroxyisobutyrate suggested in the literature. We find that individual biomarker measurements are a valuable tool in reconstruction of previous exposures and that a simple pharmacokinetic model can identify the time frames over which an exogenous chemical and the related chemical biomarker are useful. These techniques could be applied to broader ranges of environmental contaminants to assess cumulative exposure risks if ADME (Absorption, Distribution, Metabolization and Excretion) is understood and systemic biomarkers can be measured.

Exhaled alveolar breath can provide a great deal of information about an individual's health and previous exposure to potentially harmful xenobiotic materials. Because breath can be obtained non-invasively and its constituents directly reflect concentrations in the blood, its use has many potential applications in the field of biomarker research. This paper reviews the utility and application of the single breath canister (SBC) method of alveolar breath collection and analysis first developed by the US Environmental Protection Agency (USEPA) in the 1990s. This review covers the development of the SBC technique in the laboratory and its application in a range of field studies. Together these studies specifically show how the SBC method (and exhaled breath analysis in general) can be used to clearly demonstrate recent exposure to volatile organic compounds, to link particular activities to specific exposures, to determine compound-specific uptake and elimination kinetics, and to assess the relative importance of various routes of exposure (i.e. dermal, ingestion, inhalation) in multi-pathway scenarios. Specific investigations covered in this overview include an assessment of exposures related to the residential use of contaminated groundwater, exposures to gasoline and fuel additives at self-service gas stations, swimmers' exposures to trihalomethanes, and occupational exposures to jet fuel.