Deployment-Associated Exposure Surveillance With High-Resolution Metabolomics

Particulate matter exposure is associated with increased inflammatory cytokines and eosinophils in chronic rhinosinusitis

BACKGROUND

Chronic rhinosinusitis (CRS) is thought to result from complex interactions between the host immune system, microbiota, and environmental exposures. Currently, there is limited data regarding the impact of ambient particulate matter ≤2.5 μm in diameter (PM2.5) in the pathogenesis of CRS, despite evidence linking PM2.5 to other respiratory diseases. We hypothesized that PM2.5 may result in differential cytokine patterns that could inform our mechanistic understanding of the effect of environmental factors on CRS.

METHODS

We conducted an analysis of data prospectively collected from 308 CRS patients undergoing endoscopic sinus surgery. Cytokines were quantified in intraoperative mucus specimens using a multiplex flow cytometric bead assay. Clinical and demographic data including zip codes were extracted and used to obtain tract-level income and rurality measures. A spatiotemporal machine learning model was used to estimate daily PM2.5 levels for the year prior to each patient's surgery date. Spearman correlations and regression analysis were performed to characterize the relationship between mucus cytokines and PM2.5. RESULTS: Several inflammatory cytokines including IL-2, IL-5/IL-13, IL-12, and 21 were significantly correlated with estimated average 6, 9, and 12-month preoperative PM2.5 levels. These relationships were maintained for most cytokines after adjusting for age, income, body mass index, rurality, polyps, asthma, and allergic rhinitis (AR) (p < .05). There were also higher odds of asthma (OR = 1.5, p = .01) and AR (OR = 1.48, p = .03) with increasing 12-month PM2.5 exposure. Higher tissue eosinophil counts were associated with increasing PM2.5 levels across multiple timeframes (p < .05).

CONCLUSIONS

Chronic PM2.5 exposure may be an independent risk factor for development of a mixed, type-2 dominant CRS inflammatory response.

Implementation of multiomic mass spectrometry approaches for the evaluation of human health following environmental exposure

Omics analyses collectively refer to the possibility of profiling genetic variants, RNA, epigenetic markers, proteins, lipids, and metabolites. The most common analytical approaches used for detecting molecules present within biofluids related to metabolism are vibrational spectroscopy techniques, represented by infrared, Raman, and nuclear magnetic resonance (NMR) spectroscopies and mass spectrometry (MS). Omics-based assessments utilizing MS are rapidly expanding and being applied to various scientific disciplines and clinical settings. Most of the omics instruments are operated by specialists in dedicated laboratories; however, the development of miniature portable omics has made the technology more available to users for field applications. Variations in molecular information gained from omics approaches are useful for evaluating human health following environmental exposure and the development and progression of numerous diseases. As MS technology develops so do statistical and machine learning methods for the detection of molecular deviations from personalized metabolism, which are correlated to altered health conditions, and they are intended to provide a multi-disciplinary overview for researchers interested in adding multiomic analysis to their current efforts. This includes an introduction to mass spectrometry-based omics technologies, current state-of-the-art capabilities and their respective strengths and limitations for surveying molecular information. Furthermore, we describe how knowledge gained from these assessments can be applied to personalized medicine and diagnostic strategies.

[Application of multiomics mass spectrometry in the research of chemical exposome]

Environmental factors, such as environmental pollutants, behaviors, and lifestyles, are the leading causes of chronic noncommunicable diseases. Estimates indicate that approximately 50% of all deaths worldwide can be attributed to environmental factors. The exposome is defined as the totality of human environmental (i.e., all nongenetic) exposures from conception, including general external exposure (e.g., climate, education, and urban environment), specific external exposure (e.g., pollution, physical activity, and diet), and internal exposure (e.g., metabolic factors, oxidative stress, inflammation, and protein modification). As a new paradigm, this concept aims to comprehensively understand the link between human health and environmental factors. Therefore, a comprehensive measurement of the exposome, including accurate and reliable measurements of exposure to the external environment and a wide range of biological responses to the internal environment, is of great significance. The measurement of the general external exposome depends on advances in environmental sensors, personal-sensing technologies, and geographical information systems. The determination of exogenous chemicals to which individuals are exposed and endogenous chemicals that are produced or modified by external stressors relies on improvements in methodology and the development of instrumental approaches, including colorimetric, chromatographic, spectral, and mass-spectrometric methods. This article reviews the research strategies for chemical exposomes and summarizes existing exposome-measurement methods, focusing on mass spectrometry (MS)-based methods. The top-down and bottom-up approaches are commonly used in exposome studies. The bottom-up approach focuses on the identification of chemicals in the external environment (e.g., soil, water, diet, and air), whereas the top-down approach focuses on the evaluation of endogenous chemicals and biological processes in biological samples (e.g., blood, urine, and serum). Low- and high-resolution MS (LRMS and HRMS, respectively) have become the most popular methods for the direct measurement of exogenous and endogenous chemicals owing to their superior sensitivity, specificity, and dynamic range. LRMS has been widely applied in the targeted analysis of expected chemicals, whereas HRMS is a promising technique for the suspect and unknown screening of unexpected chemicals. The development of MS-based multiomics, including proteomics, metabolomics, epigenomics, and spatial omics, provides new opportunities to understand the effects of environmental exposure on human health. Metabolomics involves the sum of all low-molecular-weight metabolites in a living system. Nontargeted metabolomics can measure both endogenous and exogenous chemicals, which would directly link exposure to biological effects, internal dose, and disease pathobiology, whereas proteomics could play an important role in predicting potential adverse health outcomes and uncovering molecular mechanisms. MS imaging (MSI) is an emerging technique that provides unlabeled in-depth measurements of endogenous and exogenous molecules directly from tissue and cell sections without changing their spatial information. MSI-based spatial omics, which has been widely applied in biomarker discovery for clinical diagnosis, as well as drug and pollutant monitoring, is expected to become an effective method for exposome measurement. Integrating these response measurements from metabolomics, proteomics, spatial omics, and epigenomics will enable the generation of new hypotheses to discover the etiology of diseases caused by chemical exposure. Finally, we highlight the major challenges in achieving chemical exposome measurements.

Wearable Passive Samplers for Assessing Environmental Exposure to Organic Chemicals: Current Approaches and Future Directions

PURPOSE OF REVIEW

We are continuously exposed to dynamic mixtures of airborne contaminants that vary by location. Understanding the compositional diversity of these complex mixtures and the levels to which we are each exposed requires comprehensive exposure assessment. This comprehensive analysis is often lacking in population-based studies due to logistic and analytical challenges associated with traditional measurement approaches involving active air sampling and chemical-by-chemical analysis. The objective of this review is to provide an overview of wearable passive samplers as alternative tools to active samplers in environmental health research. The review highlights the advances and challenges in using wearable passive samplers for assessing personal exposure to organic chemicals and further presents a framework to enable quantitative measurements of exposure and expanded use of this monitoring approach to the population scale.

RECENT FINDINGS

Overall, wearable passive samplers are promising tools for assessing personal exposure to environmental contaminants, evident by the increased adoption and use of silicone-based devices in recent years. When combined with high throughput chemical analysis, these exposure assessment tools present opportunities for advancing our ability to assess personal exposures to complex mixtures. Most designs of wearable passive samplers used for assessing exposure to semi-volatile organic chemicals are currently uncalibrated, thus, are mostly used for qualitative research. The challenge with using wearable samplers for quantitative exposure assessment mostly lies with the inherent complexity in calibrating these wearable devices. Questions remain regarding how they perform under various conditions and the uncertainty of exposure estimates. As popularity of these samplers grows, it is critical to understand the uptake kinetics of chemicals and the different environmental and meteorological conditions that can introduce variability. Wearable passive samplers enable evaluation of exposure to hundreds of chemicals. The review presents the state-of-the-art of technology for assessing personal exposure to environmental chemicals. As more studies calibrate wearable samplers, these tools present promise for quantitatively assessing exposure at both the individual and population levels.

Large scale enzyme based xenobiotic identification for exposomics

Advances in genomics have revealed many of the genetic underpinnings of human disease, but exposomics methods are currently inadequate to obtain a similar level of understanding of environmental contributions to human disease. Exposomics methods are limited by low abundance of xenobiotic metabolites and lack of authentic standards, which precludes identification using solely mass spectrometry-based criteria. Here, we develop and validate a method for enzymatic generation of xenobiotic metabolites for use with high-resolution mass spectrometry (HRMS) for chemical identification. Generated xenobiotic metabolites were used to confirm identities of respective metabolites in mice and human samples based upon accurate mass, retention time and co-occurrence with related xenobiotic metabolites. The results establish a generally applicable enzyme-based identification (EBI) for mass spectrometry identification of xenobiotic metabolites and could complement existing criteria for chemical identification.

Occupational Exposures and Environmental Health Hazards of Military Personnel

BACKGROUND

Military personnel are frequently exposed to environmental pollutants that can cause a variety of diseases.

METHODS

This review analyzed publications regarding epidemiological and biomonitoring studies on occupationally-exposed military personnel.

RESULTS

The exposures include sulfur mustard, organ chlorines, combustion products, fuel vapors, and ionizing and exciting radiations. Important factors to be considered are the lengths and intensities of exposures, its proximity to the sources of environmental pollutants, as well as confounding factors (cigarette smoke, diet, photo-type, healthy warrior effect, etc.). Assessment of environmental and individual exposures to pollutants is crucial, although often omitted, because soldiers have often been evaluated based on reported health problems rather than on excessive exposure to pollutants. Biomarkers of exposures and effects are tools to explore relationships between exposures and diseases in military personnel. Another observation from this review is a major problem from the lack of suitable control groups.

CONCLUSIONS

This review indicates that only studies which analyzed epidemiological and molecular biomarkers in both exposed and control groups would provide evidence-based conclusions on exposure and disease risk in military personnel.

Metabolome-wide association study of flavorant vanillin exposure in bronchial epithelial cells reveals disease-related perturbations in metabolism

Electronic cigarettes (e-cig) are an increasingly popular alternative to traditional smoking but have been in use for too short of a period of time to fully understand health risks. Furthermore, associated health risks are difficult to evaluate because of a large range of flavoring agents and their combinations for use with e-cig. Many flavoring agents are generally regarded as safe but have limited studies for effects on lung. Vanillin, an aromatic aldehyde, is one of the most commonly used flavoring agents in e-cig. Vanillin is electrophilic and can be redox active, with chemical properties expected to interact within biologic systems. Because accumulating lung metabolomics studies have identified metabolic disruptions associated with idiopathic pulmonary fibrosis, asthma and acute respiratory distress syndrome, we used human bronchial epithelial cells (BEAS-2B) with high-resolution metabolomics analysis to determine whether these disease-associated pathways are impacted by vanillin over the range used in e-cig. A metabolome-wide association study showed that vanillin perturbed specific energy, amino acid, antioxidant and sphingolipid pathways previously associated with human disease. Analysis of a small publicly available human dataset showed associations with several of the same pathways. Because vanillin is a common and high-abundance flavorant in e-cig, these results show that vanillin has potential to be mechanistically important in lung diseases and warrants in vivo toxicity testing in the context of e-cig use.

Personalised Medicine: implication and perspectives in the field of occupational health

"Personalised medicine" relies on identifying and integrating individual variability in genomic, biological, and physiological parameters, as well as in environmental and lifestyle factors, to define "individually" targeted disease prevention and treatment. Although innovative "omic" technologies supported the application of personalised medicine in clinical, oncological, and pharmacological settings, its role in occupational health practice and research is still in a developing phase. Occupational personalised approaches have been currently applied in experimental settings and in conditions of unpredictable risks, e.g.. war missions and space flights, where it is essential to avoid disease manifestations and therapy failure. However, a debate is necessary as to whether personalized medicine may be even more important to support a redefinition of the risk assessment processes taking into consideration the complex interaction between occupational and individual factors. Indeed, "omic" techniques can be helpful to understand the hazardous properties of the xenobiotics, dose-response relationships through a deeper elucidation of the exposure-disease pathways and internal doses of exposure. Overall, this may guide the adoption/implementation of primary preventive measures protective for the vast majority of the population, including most susceptible subgroups. However, the application of personalised medicine into occupational health requires overcoming some practical, ethical, legal, economical, and socio-political issues, particularly concerning the protection of privacy, and the risk of discrimination that the workers may experience. In this scenario, the concerted action of academic, industry, governmental, and stakeholder representatives should be encouraged to improve research aimed to guide effective and sustainable implementation of personalised medicine in occupational health fields.

Respiratory Health after Military Service in Southwest Asia and Afghanistan. An Official American Thoracic Society Workshop Report

Since 2001, more than 2.7 million U.S. military personnel have been deployed in support of operations in Southwest Asia and Afghanistan. Land-based personnel experienced elevated exposures to particulate matter and other inhalational exposures from multiple sources, including desert dust, burn pit combustion, and other industrial, mobile, or military sources. A workshop conducted at the 2018 American Thoracic Society International Conference had the goals of: 1) identifying key studies assessing postdeployment respiratory health, 2) describing emerging research, and 3) highlighting knowledge gaps. The workshop reviewed epidemiologic studies that demonstrated more frequent encounters for respiratory symptoms postdeployment compared with nondeployers and for airway disease, predominantly asthma, as well as case series describing postdeployment dyspnea, asthma, and a range of other respiratory tract findings. On the basis of particulate matter effects in other populations, it also is possible that deployers experienced reductions in pulmonary function as a result of such exposure. The workshop also gave particular attention to constrictive bronchiolitis, which has been reported in lung biopsies of selected deployers. Workshop participants had heterogeneous views regarding the definition and frequency of constrictive bronchiolitis and other small airway pathologic findings in deployed populations. The workshop concluded that the relationship of airway disease, including constrictive bronchiolitis, to exposures experienced during deployment remains to be better defined. Future clinical and epidemiologic research efforts should address better characterization of deployment exposures; carry out longitudinal assessment of potentially related adverse health conditions, including lung function and other physiologic changes; and use rigorous histologic, exposure, and clinical characterization of patients with respiratory tract abnormalities.

Environmental Chemicals Altered in Association With Deployment for High Risk Areas

OBJECTIVE

A study was conducted using serum samples and high-resolution metabolomics (HRM) to test for changes in abundance of environmental chemicals in deployment in high-risk areas (Balad, Iraq; Bagram, Afghanistan).

METHODS

Pre and Post-deployment serum samples for deployment (cases) and matched controls stationed domestically were analyzed by HRM and bioinformatics for the relative abundance of 271 environmental chemicals.

RESULTS

Of the 271 chemicals, 153 were measurable in at least 80% of the samples in one of the pre- or post-deployment groups. Several pesticides and other chemicals were modestly elevated post-deployment in the Control as well as the Bagram and Balad samples. Similarly, small decreases were seen for some chemicals.

CONCLUSION

These results using serum samples show that for the 271 environmental chemicals studied, 56% were detected and small differences occurred with deployment to high-risk areas.

Benzo[a]pyrene Perturbs Mitochondrial and Amino Acid Metabolism in Lung Epithelial Cells and Has Similar Correlations With Metabolic Changes in Human Serum

OBJECTIVE

A study was conducted to identifymetabolic-related effects of benzo[a]pyrene (BaP) on human lung epithelial cells and validate these findings using human sera.

METHODS

Human lung epithelial cells were treated with BaP, and extracts were analyzed with a global metabolome-wide association study (MWAS) to test for pathways and metabolites altered relative to vehicle controls.

RESULTS

MWAS results showed that BaP metabolites were among the top metabolites differing between BaP-treated cells and controls. Pathway enrichment analysis further confirmed that fatty acid, lipid, and mitochondrial pathways were altered by BaP. Human sera analysis showed that lipids varied with BaP concentration. BaP associations with amino acid metabolism were found in both models.

CONCLUSIONS

These findings show that BaP has broad metabolic effects, and suggest that air pollution exacerbates disease processes by altered mitochondrial and amino acid metabolism.

Analysis of Postdeployment Serum Samples Identifies Potential Biomarkers of Exposure to Burn Pits and Other Environmental Hazards

OBJECTIVE

The potential health risks of deployment to sites with open burn pits remain poorly understood, in part, because personal exposure monitoring was not performed. Here, we investigated whether postdeployment serum samples contain biomarkers associated with exposure to burn pits.

METHODS

A total of 237 biomarkers were measured in 800 serum samples from deployed and never-deployed subjects. We used a regression model and a supervised vector machine to identify serum biomarkers with significant associations with exposures and deployment.

RESULTS

We identified 101 serum biomarkers associated with polycyclic aromatic hydrocarbons, dioxins or furans, and 54 biomarkers associated with deployment. Twenty-six of these biomarkers were shared in common by the exposure and deployment groups.

CONCLUSIONS

We identify a potential signature of exposure to open burn pits, and provide a framework for using postexposure sera to identify exposures when contemporaneous monitoring was inadequate.

Advances in Comprehensive Exposure Assessment: Opportunities for the US Military

OBJECTIVE

Review advances in exposure assessment offered by the exposome concept and new -omics and sensor technologies.

METHODS

Narrative review of advances, including current efforts and potential future applications by the US military.

RESULTS

Exposure assessment methods from both bottom-up and top-down exposomics approaches are advancing at a rapid pace, and the US military is engaged in developing both approaches. Top-down approaches employ various -omics technologies to identify biomarkers of internal exposure and biological effect. Bottom-up approaches use new sensor technology to better measure external dose. Key challenges of both approaches are largely centered around how to integrate, analyze, and interpret large datasets that are multidimensional and disparate.

CONCLUSIONS

Advances in -omics and sensor technologies may dramatically enhance exposure assessment and improve our ability to characterize health risks related to occupational and environmental exposures, including for the US military.

Metabolome-Wide Association Study of Deployment to Balad, Iraq or Bagram, Afghanistan

OBJECTIVE

To use high-resolution metabolomics (HRM) to identify metabolic changes in military personnel associated with deployment to Balad, Iraq, or Bagram, Afghanistan.

METHODS

Pre- and post-deployment samples were obtained from the Department of Defense Serum Repository (DoDSR). HRM and bioinformatics were used to identify metabolic differences associated with deployment.

RESULTS

Differences at baseline (pre-deployment) between personnel deployed to Bagram compared with Balad or Controls included sex hormone and keratan sulfate metabolism. Deployment to Balad was associated with alterations to amino acid and lipid metabolism, consistent with inflammation and oxidative stress, and pathways linked to metabolic adaptation and repair. Difference associated with deployment to Bagram included lipid pathways linked to cell signaling and inflammation.

CONCLUSIONS

Metabolic variations in pre- and post-deployment are consistent with deployment-associated responses to air pollution and other environmental stressors.

Integrative Network Analysis Linking Clinical Outcomes With Environmental Exposures and Molecular Variations in Service Personnel Deployed to Balad and Bagram

OBJECTIVE

To develop a computational approach to link clinical outcomes with environmental exposures and molecular variations measured in Department of Defense (DOD) serum-repository samples.

METHODS

International Classification of Diseases, Ninth Division codes which corresponded to cardiopulmonary symptoms for service personnel were selected to test for associations with deployment-related inhalation hazards and metabolomics, micro-RNA, cytokine, plasma markers, and environmental exposure analyses for corresponding samples. xMWAS and Mummichog were used for integrative network and pathway analysis.

RESULTS

Comparison between 41 personnel exhibiting new cardio-pulmonary diagnoses after deployment start-date to 25 personnel exhibiting no symptoms identified biomarkers associated with cardiopulmonary conditions. Integrative network and pathway analysis showed communities of clinical, molecular, and environmental markers associated with fatty acid, lipid, nucleotide, and amino acid metabolism pathways.

CONCLUSIONS

The current proof of principle study establishes a computational framework for integrative analysis of deployment-related exposures, molecular responses, and health outcomes.

Use of Biomarkers to Assess Environmental Exposures and Health Outcomes in Deployed Troops

OBJECTIVE

This paper provides an overview of our Military Biomarkers Research Study (MBRS) designed to assess whether biomarkers can be used to retrospectively assess deployment exposures and health impacts related to deployment environmental exposures.

METHODS

The MBRS consists of four phases. Phase I was a feasibility study of stored sera. Phase II looks at associations between exposures and biomarkers. Phase III examines relationships of biomarkers and health outcomes, and Phase IV investigates in vitro biomarker changes associated with exposures to chemicals of interest. This paper briefly summarizes work already published and introduces the new reports contained in this supplement.

RESULTS

Novel biomarkers were identified. These were associated with deployment exposures.

CONCLUSIONS

Significant associations were noted between deployment exposures, microRNA biomarkers and metabolomic biomarkers, and deployment health outcomes.

Phytochelatin database: a resource for phytochelatin complexes of nutritional and environmental metals

Phytochelatins (PyCs) are a diverse set of plant compounds that chelate metals, protect against metal toxicity and function in metal homeostasis. PyCs are present in plants consumed as food by humans and could, in principle, impact absorption and utilization of essential and toxic metals such as selenium and cadmium, respectively. PyCs vary in terminal amino acid composition and chain length, exist in multiple oxidation states and reversibly bind multiple metals; consequently, PyCs include a large set of possible structures. Although individual PyC-metal complexes have been studied, no resource exists to characterize the diversity of PyCs and PyC-metal complexes. We used the scientific literature to develop a database of elemental formulas for polymer forms varying in chain length from 2 to 11 glutamyl-cysteine repeats. Using elemental formulas, we calculated monoisotopic masses using the most abundant isotopes of each element and calculated masses for complexes with 13 metals of nutritional and toxicological significance. The resulting phytochelatin database (PyCDB) contains 46 260 unique elemental formulas for PyC and PyC-metal complexes. The database is available online for download as well as for direct mass queries for mass spectrometry using an accurate mass annotation tool for user-selected PyC types, metals and adducts of interest. We performed studies of a commonly consumed food—onion—to validate the database and test utility of the tool. Onion samples were analyzed using ultra-high resolution mass spectrometry-based metabolomics. Mass spectral features were annotated using the PyCDB web tool and the R package, xMSannotator; annotated features were further validated by collision-induced dissociation mass spectrometry. The results establish use and a workflow for PyCDB as a resource for characterization of PyCs and PyC-metal complexes.

Exposure to Heptachlorodibenzo-p-dioxin (HpCDD) Regulates microRNA Expression in Human Lung Fibroblasts

OBJECTIVE

Benzo(ghi)perylene (BghiP) and 1,2,3,4,6,7,8-Heptachlorodibenzo-p-dioxin (HpCDD) were elevated in serum from personnel deployed to sites with open burn pits. Here, we investigated the ability of BghiP and HpCDD to regulate microRNA (miRNA) expression through the aryl hydrocarbon receptor (AHR).

METHODS

Human lung fibroblasts (HLFs) were exposed to BghiP and HpCDD. AHR activity was measured by reporter assay and gene expression. Deployment related miRNA were measured by quantitative polymerase chain reaction. AHR expression was depleted using siRNA.

RESULTS

BghiP displayed weak AHR agonist activity. HpCDD induced AHR activity in a dose-dependent manner. Let-7d-5p, miR-103-3p, miR-107, and miR-144-3p levels were significantly altered by HpCDD. AHR knockdown attenuated these effects.

CONCLUSIONS

These studies reveal that miRNAs previously identified in sera from personnel deployed to sites with open burn pits are altered by HpCDD exposure in HLFs.

Hydrophobic Organic Components of Ambient Fine Particulate Matter (PM2.5) Associated with Inflammatory Cellular Response

Nowadays, knowledge regarding component-specific inflammatory effect of fine particulate matter (PM_2.5) is limited. In this study, an omics approach based on time-of-flight mass spectrometry was established to identify the key hydrophobic components of PM_2.5 associated with pro-inflammatory cytokines released by macrophages after in vitro exposure. Of 764 compounds, 62 components were robustly screened with firmly identified 37 specific chemicals. In addition to polycyclic aromatic hydrocarbons (PAHs) and their methylated congeners, novel oxygen- and nitrogen-containing PAHs and, especially, oxygenated PAHs (Oxy-PAHs) were identified. Interleukin (IL)-6 was associated with Oxy-PAHs of 1,8-naphthalic anhydride, xanthone, and benzo[h]quinolone, especially, whereas IL-1β and tumor necrosis factor (TNF)-α were associated with most species. Most species were related to IL-1β, which was significantly higher in the heating season, with a monotonic dose-response pattern mainly for Oxy-PAHs and a U-shaped dose-response pattern for primary species. On the basis of the identified components, four sources of pollution (coal combustion, traffic emissions, biomass burning, and secondary formation, traced by Oxy-PAHs such as 1,8-naphthalic anhydride and quinones) were resolved by the positive matrix factorization model. TNF-α was associated with primary sources, whereas IL-1β and IL-6 were associated with both primary and secondary sources, suggesting different inflammatory effects between primary and secondary sources when assessing the toxicity-driven disparities of known and unknown PM_2.5 components.

Towards Mass Spectrometry-Based Chemical Exposome: Current Approaches, Challenges, and Future Directions

The proposal of the “exposome” concept represents a shift of the research paradigm in studying exposure-disease relationships from an isolated and partial way to a systematic and agnostic approach. Nevertheless, exposome implementation is facing a variety of challenges including measurement techniques and data analysis. Here we focus on the chemical exposome, which refers to the mixtures of chemical pollutants people are exposed to from embryo onwards. We review the current chemical exposome measurement approaches with a focus on those based on the mass spectrometry. We further explore the strategies in implementing the concept of chemical exposome and discuss the available chemical exposome studies. Early progresses in the chemical exposome research are outlined, and major challenges are highlighted. In conclusion, efforts towards chemical exposome have only uncovered the tip of the iceberg, and further advancement in measurement techniques, computational tools, high-throughput data analysis, and standardization may allow more exciting discoveries concerning the role of exposome in human health and disease.

The metabolome: A key measure for exposome research in epidemiology

PURPOSE OF REVIEW

Application of omics to study human health has created a new era of opportunities for epidemiology research. However, approaches to characterize exogenous health triggers have largely not leveraged advances in analytical platforms and big data. In this review, we highlight the exposome, which is defined as the cumulative measure of exposure and biological responses across a lifetime as a cornerstone for new epidemiology approaches to study complex and preventable human diseases.

RECENT FINDINGS

While no universal approach exists to measure the entirety of the exposome, use of high-resolution mass spectrometry methods provide distinct advantages over traditional biomonitoring and have provided key advances necessary for exposome research. Application to different study designs and recommendations for combining exposome data with novel data analytic frameworks to study complex interactions of multiple stressors are also discussed.

SUMMARY

Even though challenges still need to be addressed, advances in methods to characterize the exposome provide exciting new opportunities for epidemiology to support fundamental discoveries to improve public health.

Metabolome-wide association study of anti-epileptic drug treatment during pregnancy

Pregnant women with epilepsy (PWWE) require continuous anti-epileptic drug (AED) treatment to avoid risk to themselves and fetal risks secondary to maternal seizures, resulting in prolonged AED exposure to the developing embryo and fetus. The objectives of this study were to determine whether high-resolution metabolomics is able to link the metabolite profile of PWWE receiving lamotrigine or levetiracetam for seizure control to associated pharmacodynamic (PD) biological responses. Untargeted metabolomic analysis of plasma obtained from 82 PWWE was completed using high-resolution mass spectrometry. Biological alterations due to lamotrigine or levetiracetam monotherapy were determined by a metabolome-wide association study that compared patients taking either drug to those who did not require AED treatment. Metabolic changes associated with AED use were then evaluated by testing for drug-dose associated metabolic variations and pathway enrichment. AED therapy resulted in drug-associated metabolic profiles recognizable within maternal plasma. Both the parent compounds and major metabolites were detected, and each AED was correlated with other metabolic features and pathways. Changes in metabolites and metabolic pathways important to maternal health and linked to fetal neurodevelopment were detected for both drugs, including changes in one‑carbon metabolism, neurotransmitter biosynthesis and steroid metabolism. In addition, decreased levels of 5-methyltetrahydrofolate and tetrahydrofolate were detected in women taking lamotrigine, which is consistent with recent findings showing increased risk of autism spectrum disorder traits in PWWE using AED. These results represent a first step in development of pharmacometabolomic framework with potential to detect adverse AED-related metabolic changes during pregnancy.

The Exposome: Molecules to Populations

Derived from the term exposure, the exposome is an omic-scale characterization of the nongenetic drivers of health and disease. With the genome, it defines the phenome of an individual. The measurement of complex environmental factors that exert pressure on our health has not kept pace with genomics and historically has not provided a similar level of resolution. Emerging technologies make it possible to obtain detailed information on drugs, toxicants, pollutants, nutrients, and physical and psychological stressors on an omic scale. These forces can also be assessed at systems and network levels, providing a framework for advances in pharmacology and toxicology. The exposome paradigm can improve the analysis of drug interactions and detection of adverse effects of drugs and toxicants and provide data on biological responses to exposures. The comprehensive model can provide data at the individual level for precision medicine, group level for clinical trials, and population level for public health.

Particulate metal exposures induce plasma metabolome changes in a commuter panel study

INTRODUCTION

Advances in liquid chromatography-mass spectrometry (LC-MS) have enabled high-resolution metabolomics (HRM) to emerge as a sensitive tool for measuring environmental exposures and corresponding biological response. Using measurements collected as part of a large, panel-based study of car commuters, the current analysis examines in-vehicle air pollution concentrations, targeted inflammatory biomarker levels, and metabolomic profiles to trace potential metabolic perturbations associated with on-road traffic exposures.

METHODS

A 60-person panel of adults participated in a crossover study, where each participant conducted a highway commute and randomized to either a side-street commute or clinic exposure session. In addition to in-vehicle exposure characterizations, participants contributed pre- and post-exposure dried blood spots for 2-hr changes in targeted proinflammatory and vascular injury biomarkers and 10-hr changes in the plasma metabolome. Samples were analyzed on a Thermo QExactive MS system in positive and negative electrospray ionization (ESI) mode. Data were processed and analyzed in R using apLCMS, xMSanalyzer, and limma. Features associated with environmental exposures or biological endpoints were identified with a linear mixed effects model and annotated through human metabolic pathway analysis in mummichog.

RESULTS

HRM detected 10-hr perturbations in 110 features associated with in-vehicle, particulate metal exposures (Al, Pb, and Fe) which reflect changes in arachidonic acid, leukotriene, and tryptophan metabolism. Two-hour changes in proinflammatory biomarkers hs-CRP, IL-6, IL-8, and IL-1β were also associated with 10-hr changes in the plasma metabolome, suggesting diverse amino acid, leukotriene, and antioxidant metabolism effects. A putatively identified metabolite, 20-OH-LTB4, decreased after in-vehicle exposure to particulate metals, suggesting a subclinical immune response.

CONCLUSIONS

Acute exposures to traffic-related air pollutants are associated with broad inflammatory response, including several traditional markers of inflammation.

Putrescine as indicator of manganese neurotoxicity: Dose-response study in human SH-SY5Y cells

Disrupted polyamine metabolism with elevated putrescine is associated with neuronal dysfunction. Manganese (Mn) is an essential nutrient that causes neurotoxicity in excess, but methods to evaluate biochemical responses to high Mn are limited. No information is available on dose-response effects of Mn on putrescine abundance and related polyamine metabolism. The present research was to test the hypothesis that Mn causes putrescine accumulation over a physiologically adequate to toxic concentration range in a neuronal cell line. We used human SH-SY5Y neuroblastoma cells treated with MnCl2 under conditions that resulted in cell death or no cell death after 48 h. Putrescine and other metabolites were analyzed by liquid chromatography-ultra high-resolution mass spectrometry. Putrescine-related pathway changes were identified with metabolome-wide association study (MWAS). Results show that Mn caused a dose-dependent increase in putrescine over a non-toxic to toxic concentration range. MWAS of putrescine showed positive correlations with the polyamine metabolite N8-acetylspermidine, methionine-related precursors, and arginine-associated urea cycle metabolites, while putrescine was negatively correlated with γ-aminobutyric acid (GABA)-related and succinate-related metabolites (P < 0.001, FDR < 0.01). These data suggest that measurement of putrescine and correlated metabolites may be useful to study effects of Mn intake in the high adequate to UL range.

Introduction to Department of Defense Research on Burn Pits, Biomarkers, and Health Outcomes Related to Deployment in Iraq and Afghanistan

OBJECTIVE

This paper provides an overview of our study that was designed to assess the health impact of environmental exposures to open pit burning in deployed troops.

METHODS

The rationale for the study and the structure of the research plan was laid out. An overview of each article in the supplement was provided. The cohort of deployed Service members was assessed for airborne exposure, relevant biomarkers, and health outcomes following deployment to Balad, Iraq, and/or Bagram, Afghanistan.

RESULTS

Polycyclic aromatic hydrocarbon (PAH) exposures were elevated, and serum biomarkers were statistically different postdeployment. Associations were noted between PAHs and dioxins and microRNAs. Some health outcomes were evident in deployers compared with nondeployers.

CONCLUSIONS

Future research will examine the associations between demographic variables, smoking status, biomarker levels, and related health outcomes.

Yale school of public health symposium on lifetime exposures and human health: the exposome; summary and future reflections

The exposome is defined as "the totality of environmental exposures encountered from birth to death" and was developed to address the need for comprehensive environmental exposure assessment to better understand disease etiology. Due to the complexity of the exposome, significant efforts have been made to develop technologies for longitudinal, internal and external exposure monitoring, and bioinformatics to integrate and analyze datasets generated. Our objectives were to bring together leaders in the field of exposomics, at a recent Symposium on "Lifetime Exposures and Human Health: The Exposome," held at Yale School of Public Health. Our aim was to highlight the most recent technological advancements for measurement of the exposome, bioinformatics development, current limitations, and future needs in environmental health. In the discussions, an emphasis was placed on moving away from a one-chemical one-health outcome model toward a new paradigm of monitoring the totality of exposures that individuals may experience over their lifetime. This is critical to better understand the underlying biological impact on human health, particularly during windows of susceptibility. Recent advancements in metabolomics and bioinformatics are driving the field forward in biomonitoring and understanding the biological impact, and the technological and logistical challenges involved in the analyses were highlighted. In conclusion, further developments and support are needed for large-scale biomonitoring and management of big data, standardization for exposure and data analyses, bioinformatics tools for co-exposure or mixture analyses, and methods for data sharing.

Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome

Global profiling of xenobiotics in human matrices in an untargeted mode is gaining attention for studying the environmental chemical space of the human exposome. Defined as the study of a comprehensive inclusion of environmental influences and associated biological responses, human exposome science is currently evolving out of the metabolomics science. In analogy to the latter, the development and applications of high resolution mass spectrometry (HRMS) has shown potential and promise to greatly expand our ability to capture the broad spectrum of environmental chemicals in exposome studies. HRMS can perform both untargeted and targeted analysis because of its capability of full- and/or tandem-mass spectrum acquisition at high mass accuracy with good sensitivity. The collected data from target, suspect and non-target screening can be used not only for the identification of environmental chemical contaminants in human matrices prospectively but also retrospectively. This review covers recent trends and advances in this field. We focus on advances and applications of HRMS in human biomonitoring studies, and data acquisition and mining. The acquired insights provide stepping stones to improve understanding of the human exposome by applying HRMS, and the challenges and prospects for future research.

Computational Metabolomics: A Framework for the Million Metabolome

"Sola dosis facit venenum." These words of Paracelsus, "the dose makes the poison", can lead to a cavalier attitude concerning potential toxicities of the vast array of low abundance environmental chemicals to which humans are exposed. Exposome research teaches that 80-85% of human disease is linked to environmental exposures. The human exposome is estimated to include >400,000 environmental chemicals, most of which are uncharacterized with regard to human health. In fact, mass spectrometry measures >200,000 m/z features (ions) in microliter volumes derived from human samples; most are unidentified. This crystallizes a grand challenge for chemical research in toxicology: to develop reliable and affordable analytical methods to understand health impacts of the extensive human chemical experience. To this end, there appears to be no choice but to abandon the limitations of measuring one chemical at a time. The present review looks at progress in computational metabolomics to provide probability-based annotation linking ions to known chemicals and serve as a foundation for unambiguous designation of unidentified ions for toxicologic study. We review methods to characterize ions in terms of accurate mass m/z, chromatographic retention time, correlation of adduct, isotopic and fragment forms, association with metabolic pathways and measurement of collision-induced dissociation products, collision cross section, and chirality. Such information can support a largely unambiguous system for documenting unidentified ions in environmental surveillance and human biomonitoring. Assembly of this data would provide a resource to characterize and understand health risks of the array of low-abundance chemicals to which humans are exposed.

Metabolic pathways of lung inflammation revealed by high-resolution metabolomics (HRM) of H1N1 influenza virus infection in mice

Influenza is a significant health concern worldwide. Viral infection induces local and systemic activation of the immune system causing attendant changes in metabolism. High-resolution metabolomics (HRM) uses advanced mass spectrometry and computational methods to measure thousands of metabolites inclusive of most metabolic pathways. We used HRM to identify metabolic pathways and clusters of association related to inflammatory cytokines in lungs of mice with H1N1 influenza virus infection. Infected mice showed progressive weight loss, decreased lung function, and severe lung inflammation with elevated cytokines [interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, and interferon (IFN)-γ] and increased oxidative stress via cysteine oxidation. HRM showed prominent effects of influenza virus infection on tryptophan and other amino acids, and widespread effects on pathways including purines, pyrimidines, fatty acids, and glycerophospholipids. A metabolome-wide association study (MWAS) of the aforementioned inflammatory cytokines was used to determine the relationship of metabolic responses to inflammation during infection. This cytokine-MWAS (cMWAS) showed that metabolic associations consisted of distinct and shared clusters of 396 metabolites highly correlated with inflammatory cytokines. Strong negative associations of selected glycosphingolipid, linoleate, and tryptophan metabolites with IFN-γ contrasted strong positive associations of glycosphingolipid and bile acid metabolites with IL-1β, TNF-α, and IL-10. Anti-inflammatory cytokine IL-10 had strong positive associations with vitamin D, purine, and vitamin E metabolism. The detailed metabolic interactions with cytokines indicate that targeted metabolic interventions may be useful during life-threatening crises related to severe acute infection and inflammation.