Human urinary biomarkers of dioxin exposure: Analysis by metabolomics and biologically driven data dimensionality reduction

Metabolomics in Preclinical Drug Safety Assessment: Current Status and Future Trends

Metabolomics is emerging as a powerful systems biology approach for improving preclinical drug safety assessment. This review discusses current applications and future trends of metabolomics in toxicology and drug development. Metabolomics can elucidate adverse outcome pathways by detecting endogenous biochemical alterations underlying toxicity mechanisms. Furthermore, metabolomics enables better characterization of human environmental exposures and their influence on disease pathogenesis. Metabolomics approaches are being increasingly incorporated into toxicology studies and safety pharmacology evaluations to gain mechanistic insights and identify early biomarkers of toxicity. However, realizing the full potential of metabolomics in regulatory decision making requires a robust demonstration of reliability through quality assurance practices, reference materials, and interlaboratory studies. Overall, metabolomics shows great promise in strengthening the mechanistic understanding of toxicity, enhancing routine safety screening, and transforming exposure and risk assessment paradigms. Integration of metabolomics with computational, in vitro, and personalized medicine innovations will shape future applications in predictive toxicology.

Dioxin(-like)-Related Biological Effects through Integrated Chemical-wide and Metabolome-wide Analyses

Dioxin(-like) exposures are linked to adverse health effects, including cancer. However, metabolic alterations induced by these chemicals remain largely unknown. Beyond known dioxin(-like) compounds, we leveraged a chemical-wide approach to assess chlorinated co-exposures and parent compound products [termed dioxin(-like)-related compounds] among 137 occupational workers. Endogenous metabolites were profiled by untargeted metabolomics, namely, reversed-phase chromatography with negative electrospray ionization (C18-negative) and hydrophilic interaction liquid chromatography with positive electrospray ionization (HILIC-positive). We performed a metabolome-wide association study to select dioxin(-like) associated metabolic features using a 20% false discovery rate threshold. Metabolic features were then characterized by pathway enrichment analyses. There are no significant features associated with polychlorinated dibenzo-p-dioxins (PCDDs), a subgroup of known dioxin(-like) compounds. However, 3,110 C18-negative and 2,894 HILIC-positive features were associated with at least one of the PCDD-related compounds. Abundant metabolic changes were also observed for polychlorinated dibenzofuran-related and polychlorinated biphenyl-related compounds. These metabolic features were primarily enriched in pathways of amino acids, lipid and fatty acids, carbohydrates, cofactors, and nucleotides. Our study highlights the potential of chemical-wide analysis for comprehensive exposure assessment beyond targeted chemicals. Coupled with advanced endogenous metabolomics, this approach allows for an in-depth exploration of metabolic alterations induced by environmental chemicals.

Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives

INTRODUCTION

Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites.

OBJECTIVES

The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021.

RESULTS

Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures.

CONCLUSION

Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.

Metabolomics: A New Approach in the Evaluation of Effects in Human Beings and Wildlife Associated with Environmental Exposition to POPs

Human beings and wild organisms are exposed daily to a broad range of environmental stressors. Among them are the persistent organic pollutants that can trigger adverse effects on these organisms due to their toxicity properties. There is evidence that metabolomics can be used to identify biomarkers of effect by altering the profiles of endogenous metabolites in biological fluids or tissues. This approach is relatively new and has been used in vitro studies mainly. Therefore, this review addresses those that have used metabolomics as a key tool to identify metabolites associated with environmental exposure to POPs in wildlife and human populations and that can be used as biomarkers of effect. The published results suggest that the metabolic pathways that produce energy, fatty acids, and amino acids are commonly affected by POPs. Furthermore, these pathways can be promoters of additional effects. In the future, metabolomics combined with other omics will improve understanding of the origin, development, and progression of the effects caused by environmental exposure.

Defining the Scope of Exposome Studies and Research Needs from a Multidisciplinary Perspective

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Lipid metabolism disorders associated with dioxin exposure in a cohort of Chinese male workers revealed by a comprehensive lipidomics study

Dioxins, environmentally stable and ubiquitous, have been found to induce metabolic changes especially in lipids and be related to multiple diseases. However, limited study is available on lipid alternations related to human exposure to dioxins. This study aims to explore the serum lipidomic characterization and to understand the underlying mechanisms of adverse health risks associated with dioxin exposure. A lipidomic study integrating nontargeted lipidomics, and targeted free fatty acid (FFA) and acyl-coenzyme A (acyl-CoA) analyses were conducted to investigate the 94 serum samples from two groups of male workers with remarkably different dioxin concentrations. The obtained results exhibited distinct lipidomic signatures between the high and low exposed groups. A total of 37 lipids were identified with the significant changes. The results revealed that dioxin exposure caused accumulations of triglyceride (TG), ceramide (Cer) and sphingoid (So), remodeling of glycerophospholipid (GP), imbalanced FFA metabolism, as well as upregulation of platelet-activating factor (PAF). These findings implied the associations between dioxin exposure and potential adverse health risks including inflammation, apoptosis, cardiovascular diseases (CVDs), and liver diseases. This study is the first to explain the associations between dioxin exposure and health effects at the level of lipid metabolism.

Approaches in metabolomics for regulatory toxicology applications

Innovative methodological approaches are needed to conduct human health and environmental risk assessments on a growing number of marketed chemicals. Metabolomics is progressively proving its value as an efficient strategy to perform toxicological evaluations of new and existing substances, and it will likely become a key tool to accelerate chemical risk assessments. However, additional guidance with widely accepted and harmonized procedures is needed before metabolomics can be routinely incorporated in decision-making for regulatory purposes. The aim of this review is to provide an overview of metabolomic strategies that have been successfully employed in toxicity assessment as well as the most promising workflows in a regulatory context. First, we provide a general view of the different steps of regulatory toxicology-oriented metabolomics. Emphasis is put on three key elements: robustness of experimental design, choice of analytical platform, and use of adapted data treatment tools. Then, examples in which metabolomics supported regulatory toxicology outputs in different scenarios are reviewed, including chemical grouping, elucidation of mechanisms of toxicity, and determination of points of departure. The overall intention is to provide insights into why and how to plan and conduct metabolomic studies for regulatory toxicology purposes.

Serum metabolic changes associated with dioxin exposure in a Chinese male cohort

Dioxins, a group of persistent organic pollutants, have been proved to correlate with ranges of diseases by activating the aryl hydrocarbon receptor (AhR). However, previous dioxin toxicity studies primarily focused on the activation of AhR with signaling pathways at gene and protein levels. The investigation of underlying mechanisms at the metabolic level is still necessary. In this study, serum samples of 48 and 47 healthy participants with the highest and lowest dioxin levels based on quartile distribution of the serum dioxin concentrations of 215 male adults were selected for metabolomics analysis by using liquid chromatography coupled with orbitrap high-resolution mass spectrometry to investigate dioxin-related metabolic responses. The identified potential biomarkers included acylcarnitines, fatty acids and derivatives, glycerophospholipids, etc. suggested that metabolic pathways such as fatty acid β-oxidation, essential fatty acid metabolism, arachidonic acid metabolism, glycerophospholipid and sphingolipid metabolism and purine metabolism were disturbed by dioxin exposure. The results indicated that people with high dioxin exposure levels were at the potential health risks of inflammation, liver and cardiovascular diseases. The metabolic findings may help understand the link between dioxin exposure and the diseases.

Environmental lipidomics: understanding the response of organisms and ecosystems to a changing world

BACKGROUND

Understanding the interaction between organisms and the environment is important for predicting and mitigating the effects of global phenomena such as climate change, and the fate, transport, and health effects of anthropogenic pollutants. By understanding organism and ecosystem responses to environmental stressors at the molecular level, mechanisms of toxicity and adaptation can be determined. This information has important implications in human and environmental health, engineering biotechnologies, and understanding the interaction between anthropogenic induced changes and the biosphere. One class of molecules with unique promise for environmental science are lipids; lipids are highly abundant and ubiquitous across nearly all organisms, and lipid profiles often change drastically in response to external stimuli. These changes allow organisms to maintain essential biological functions, for example, membrane fluidity, as they adapt to a changing climate and chemical environment. Lipidomics can help scientists understand the historical and present biofeedback processes in climate change and the biogeochemical processes affecting nutrient cycles. Lipids can also be used to understand how ecosystems respond to historical environmental changes with lipid signatures dating back to hundreds of millions of years, which can help predict similar changes in the future. In addition, lipids are direct targets of environmental stressors, for example, lipids are easily prone to oxidative damage, which occurs during exposure to most toxins.

AIM OF REVIEW

This is the first review to summarize the current efforts to comprehensively measure lipids to better understand the interaction between organisms and their environment. This review focuses on lipidomic applications in the arenas of environmental toxicology and exposure assessment, xenobiotic exposures and health (e.g., obesity), global climate change, and nutrient cycles. Moreover, this review summarizes the use of and the potential for lipidomics in engineering biotechnologies for the remediation of persistent compounds and biofuel production.

KEY SCIENTIFIC CONCEPT

With the preservation of certain lipids across millions of years and our ever-increasing understanding of their diverse biological roles, lipidomic-based approaches provide a unique utility to increase our understanding of the contemporary and historical interactions between organisms, ecosystems, and anthropogenically-induced environmental changes.

Application of metabolomics to characterize environmental pollutant toxicity and disease risks

The increased incidence of non-communicable human diseases may be attributed, at least partially, to exposures to toxic chemicals such as persistent organic pollutants (POPs), air pollutants and heavy metals. Given the high mortality and morbidity of pollutant exposure associated diseases, a better understanding of the related mechanisms of toxicity and impacts on the endogenous host metabolism are needed. The metabolome represents the collection of the intermediates and end products of cellular processes, and is the most proximal reporter of the body's response to environmental exposures and pathological processes. Metabolomics is a powerful tool for studying how organisms interact with their environment and how these interactions shape diseases related to pollutant exposure. This mini review discusses potential biological mechanisms that link pollutant exposure to metabolic disturbances and chronic human diseases, with a focus on recent studies that demonstrate the application of metabolomics as a tool to elucidate biochemical modes of actions of various environmental pollutants. In addition, classes of metabolites that have been shown to be modulated by multiple environmental pollutants will be discussed with an emphasis on their use as potential early biomarkers of disease risks. Taken together, metabolomics is a useful and versatile tool for characterizing the disease risks and mechanisms associated with various environmental pollutants.

Potential of ion mobility-mass spectrometry for both targeted and non-targeted analysis of phase II steroid metabolites in urine

In recent years, the commercialization of hybrid ion mobility-mass spectrometers and their integration in traditional LC-MS workflows provide new opportunities to extend the current boundaries of targeted and non-targeted analyses. When coupled to LC-MS, ion mobility spectrometry (IMS) provides a novel characterization parameter, the so-called averaged collision cross section (CCS, Ω), as well as improves method selectivity and sensitivity by the separation of isobaric and isomeric molecules and the isolation of the analytes of interest from background noise. In this work, we have explored the potential and advantages of this technology for carrying out the determination of phase II steroid metabolites (i.e. androgen and estrogen conjugates, including glucuronide and sulfate compounds; n = 25) in urine samples. These molecules have been selected based on their relevance in the fields of chemical food safety and doping control, as well as in metabolomics studies. The influence of urine matrix on the CCS of steroid metabolites was evaluated in order to give more confidence to current CCS databases and support its use as complementary information to retention time (Rt) and mass spectra for compound identification. Samples were only diluted 10-fold with aqueous formic acid (0.1%, v/v) prior analysis. Only an almost insignificant effect of adult bovine urine matrix on the CCS of certain steroid metabolites was observed in comparison with calve urine matrix, which is a less complex sample. In addition, high accuracy was achieved for CCS measurements carried out over four months (ΔCCS < 1.3% for 99.8% of CCS measurements; n = 1806). Interestingly, it has been observed that signal-to-noise (S/N) ratio could be improved at least 2 or 7-fold when IMS is combined with LC-MS. In addition to the separation of isomeric steroid pairs (i.e. etiocholanolone glucuronide and epiandrosterone glucuronide, as well as 19-noretiocholanolone glucuronide and 19-norandrosterone glucuronide), steroid-based ions were also separated in the IMS dimension from co-eluting matrix compounds that presented similar mass-to-charge ratio (m/z). Finally, based on CCS measurements and as a proof of concept, 17α-boldenone glucuronide has been identified as one of the main metabolites resulted from boldione administration to calves.

A scoring approach for multi-platform acquisition in metabolomics

Since the ultimate goal of untargeted metabolomics is the analysis of the broadest possible range of metabolites, some new metrics have to be used by researchers to evaluate and select different analytical strategies when multi-platform analyses are considered. In this context, we aimed at developing a scoring approach allowing to compare the performance of different LC-MS conditions for metabolomics studies. By taking into account both chromatographic and MS attributes of the analytes' peaks (i.e. retention, signal-to-noise ratio, peak intensity and shape), the newly proposed score reflects the potential of a set of LC-MS operating conditions to provide useful analytical information for a given compound. A chemical library containing 597 metabolites was used as a benchmark to apply this approach on two RPLC and three HILIC methods hyphenated to high resolution mass spectrometry (HRMS) in positive and negative ionization modes. The scores not only allowed to evaluate each analytical platform, but also to optimize the number of analytical methods needed for the analysis of metabolomics samples. As a result, the most informative combination of three LC methods and ionization modes was found, leading to a coverage of nearly 95% of the detected compounds. It was therefore demonstrated that the overall performance reached with three selected methods was almost equivalent to the performance reached when five LC-MS conditions were used.

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.

Hepatic metabolite profiling of polychlorinated biphenyl (PCB)-resistant and sensitive populations of Atlantic killifish (Fundulus heteroclitus)

Atlantic killifish inhabiting polluted sites along the east coast of the U.S. have evolved resistance to toxic effects of contaminants. One such contaminated site is the Acushnet River estuary, near New Bedford Harbor (NBH), Massachusetts, which is characterized by very high PCB concentrations in the sediments and in the tissues of resident killifish. Though killifish at this site appear to be thriving, the metabolic costs of survival in a highly contaminated environment are not well understood. In this study we compared the hepatic metabolite profiles of resistant (NBH) and sensitive populations (Scorton Creek (SC), Sandwich, MA) using a targeted metabolomics approach in which polar metabolites were extracted from adult fish livers and quantified. Our results revealed differences in the levels of several metabolites between fish from the two sites. The majority of these metabolites are associated with one-carbon metabolism, an important pathway that supports multiple physiological processes including DNA and protein methylation, nucleic acid biosynthesis and amino acid metabolism. We measured the gene expression of DNA methylation (DNA methyltransferase 1, dnmt1) and demethylation genes (Ten-Eleven Translocation (TET) genes) in the two populations, and observed lower levels of dnmt1 and higher levels of TET gene expression in the NBH livers, suggesting possible differences in DNA methylation profiles. Consistent with this, the two populations differed significantly in the levels of 5-methylcytosine and 5-hydroxymethylcytosine nucleotides. Overall, our results suggest that the unique hepatic metabolite signatures observed in NBH and SC reflect the adaptive mechanisms for survival in their respective habitats.

Comprehensive steroid profiling by liquid chromatography coupled to high resolution mass spectrometry

A steroidomics workflow has been developed in the objective of monitoring a wide range (n >150) of steroids in urine. The proposed workflow relies on the optimization of an adequate SPE extraction step followed by an UHPLC-HRMS/MS simultaneous analysis of both free and conjugated forms of C18, C19 and C21 steroid hormones. On the basis of 44 selected steroids, representative of main classes of steroids constituting the steroidome, the performances of the developed workflow were evaluated in terms of selectivity, repeatability (< 13%) and linearity (R2> 0.985 in the concentration range [0.01-10 ng/mL]). As metabolites identification and characterization constitute the bottleneck of such profiling approaches, a homemade database was created encompassing a large number of characterized free and conjugated steroids (n> 150) for putative steroid-like biomarkers identification purposes. The efficiency of the workflow in highlighting fine modifications within the urinary steroidome was assessed in the frame of an anabolic treatment involving an intra-muscular administration of boldenone undecylenate (2 mg/kg) to veals (n=6) and the investigation of potential steroid biomarkers. Besides monitoring known phase II metabolites of boldenone in the bovine specie, namely, boldenone glucuronide and sulfate, the applied strategy also permitted to observe, upon boldenone administration, a modified profile of epiboldenone glucuronide. Furthermore, 31 signals corresponding to non-identified steroid species could also be highlighted as impacted upon the exogenous steroid treatment. This study is the first to simultaneously investigate both free and conjugated C18, C19 and C21 steroid hormones in their native form using UHPLC-HRMS/MS and allowing their comprehensive profiling. This strategy was probed in-vivo.

Highly sensitive fluorescent bioassay of 2,3,7,8-tetrachloro-dibenzo-p-dioxin based on abnormal expression of cytochrome P450 1A2 in human cells

Current in vitro bioassays of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD, a major threat carcinogen) are relied on murine cells and fluorescent probe 7-ethoxyresorufin (7-ER), in which TCDD mostly causes abnormal expression of cytochrome P450 1A1 (CYP1A1). However, for human cells, TCDD mainly leads to a distinct abnormal expression of cytochrome P450 1A2 (CYP1A2). The poor response of 7-ER to CYP1A2 limits the traditional bioassay for human cells. Herein, we report a fluorescent probe N-(3-hydroxybutyl)-4-methoxy-1,8-naphthalimide (HBMN) for in vitro bioassay of TCDD with human cells. HBMN had ca. 60 times higher affinity to CYP1A2 than 7-ER. As such, the sensing sensitivity increased by 10 times, and different expression of CYP1A2 by TCDD induction in different human cells was found. Besides, HBMN was also feasible in rapid screening of TCDD concentration by naked eye. It would open a new way to highly sensitive detect TCDD and understand the pathogenesis of TCDD in different human organs.

Biomarkers of exposure in environment-wide association studies - Opportunities to decode the exposome using human biomonitoring data

BACKGROUND

The European Union's 7th Framework Programme (EU's FP7) project HEALS - Health and Environment-wide Associations based on Large Population Surveys - aims a refinement of the methodology to elucidate the human exposome. Human biomonitoring (HBM) provides a valuable tool for understanding the magnitude of human exposure from all pathways and sources. However, availability of specific biomarkers of exposure (BoE) is limited.

OBJECTIVES

The objective was to summarize the availability of BoEs for a broad range of environmental stressors and exposure determinants and corresponding reference and exposure limit values and biomonitoring equivalents useful for unraveling the exposome using the framework of environment-wide association studies (EWAS).

METHODS

In a face-to-face group discussion, scope, content, and structure of the HEALS deliverable "Guidelines for appropriate BoE selection for EWAS studies" were determined. An expert-driven, distributed, narrative review process involving around 30 individuals of the HEALS consortium made it possible to include extensive information targeted towards the specific characteristics of various environmental stressors and exposure determinants. From the resulting 265 page report, targeted information about BoE, corresponding reference values (e.g., 95th percentile or measures of central tendency), exposure limit values (e.g., the German HBM I and II values) and biomonitoring equivalents (BEs) were summarized and updated.

RESULTS

64 individual biological, chemical, physical, psychological and social environmental stressors or exposure determinants were included to fulfil the requirements of EWAS. The list of available BoEs is extensive with a number of 135; however, 12 of the stressors and exposure determinants considered do not leave any measurable specific substance in accessible body specimens. Opportunities to estimate the internal exposure stressors not (yet) detectable in human specimens were discussed.

CONCLUSIONS

Data about internal exposures are useful to decode the exposome. The paper provides extensive information for EWAS. Information included serves as a guideline - snapshot in time without any claim to comprehensiveness - to interpret HBM data and offers opportunities to collect information about the internal exposure of stressors if no specific BoE is available.

Targeting human urinary metabolome by LC-MS/MS: a review

Urine is a biological matrix that contains hundreds of metabolic end products which constitute the urinary metabolome. The development and advances on LC-MS/MS have revolutionized the analytical study of biomolecules by enabling their accurate identification and quantification in an unprecedented manner. Nowadays, LC-MS/MS is helping to unveil the complexity of urine metabolome, and the results obtained have multiple biomedical applications. This review focuses on the targeted LC-MS/MS analysis of the urine metabolome. In the first part, we describe general considerations (from sample collection to quantitation) required for a proper targeted metabolic analysis. In the second part, we address the urinary analysis and recent applications of four relevant families: amino acids, catecholamines, lipids and steroids.

Extracting Knowledge from MS Clinical Metabolomic Data: Processing and Analysis Strategies

Assessing potential alterations of metabolic pathways using large-scale approaches today plays a central role in clinical research. Because several thousands of mass features can be measured for each sample with separation techniques hyphenated to mass spectrometry (MS) detection, adapted strategies should be implemented to detect altered pathways and help to elucidate the mechanisms of pathologies. These procedures include peak detection, sample alignment, normalization, statistical analysis, and metabolite annotation. Interestingly, considerable advances have been made over the last years in terms of analytics, bioinformatics, and chemometrics to help massive and complex metabolomic data to be more adequately handled with automated processing and data analysis workflows. Recent developments and remaining challenges related to MS signal processing, metabolite annotation, and biomarker discovery based on statistical models are illustrated in this chapter considering their application to clinical research.

Assessing the impact of hazardous waste on children's health: The exposome paradigm

Assessment of the health impacts related to hazardous waste is a major scientific challenge with multiple societal implications. Most studies related to associations between hazardous waste and public health do not provide established of mechanistic links between environmental exposure and disease burden, resulting in ineffective waste management options. The exposome concept comes to overhaul the nature vs. nurture paradigm and embraces a world of dynamic interactions between environmental exposures, endogenous exposures and genetic expression in humans. In this context, the exposome paradigm provides a novel tool for holistic hazardous waste management. Waste streams and the related contamination of environmental media are not viewed in isolation, but rather as components of the expotype, the vector of exposures an individual is exposed to over time. Thus, a multi-route and multi-pathway exposure estimation can be performed setting a realistic basis for integrated health risk assessment. Waste management practices are thus assessed not only regarding their technological edge and efficacy but also their effects on human health at the individual and community level, considering intra-subject variability in the affected population. The effectiveness of the exposome approach is demonstrated in the case of Athens, the capital of Greece, where the health effects associated to long term and short term exposure to two major waste management facilities (landfill and plastic recycling) are presented. Using the exposome analysis tools, we confirmed that proximity to a landfill is critical for children neurodevelopment. However, this effect is significantly modified by parameters such as parental education level, socioeconomic status and nutrition. Proximity to a plastics recycling plant does not pose significant threats under normal operating conditions; yet, in the case of an accidental fire, release of persistent carcinogenic compounds (dioxins and furans) even for a short period results in increased lifelong risk, especially for breast feeding neonates.

The aryl hydrocarbon receptor as a moderator of host-microbiota communication

The aryl hydrocarbon receptor (AHR) is an important component of the host-microbiota communication network. Comparisons of wild-type and Ahr-null mice as well as from exposure studies with potent AHR ligands (e.g., 2,3,7,8-tetrachlorodibenzo-p-dioxin) have provided compelling evidence that the AHR may be a master regulator of the host-microbiota interaction thus helping to shape the immune system and impact host metabolism. Metabolomics and sequenced-based microbial community profiling, two recent technological advances, have helped to solidify this host-microbiota signaling concept and identified not only how specific ligands generated by the host and by the microbiota can activate the AHR, but also how activation/disruption of the AHR can influence and shape the microbiota. We are just beginning to understand how the temporal nature and tissue- and microbiota-specific generation of AHR ligands contribute to many AHR-dependent processes. In this review, we focus on several recent advances where metabolomics and characterization of the microbiota structure and function have generated new perspectives by which to evaluate AHR activity.

Deployment-Associated Exposure Surveillance With High-Resolution Metabolomics

OBJECTIVE

The aim of this study was to assess the suitability of high-resolution metabolomics (HRM) for measure of internal exposure and effect biomarkers from deployment-related environmental hazards.

METHODS

HRM provides extensive coverage of metabolism and data relevant to a broad spectrum of environmental exposures. This review briefly describes the analytic platform, workflow, and recent applications of HRM as a prototype environmental exposure surveillance system.

RESULTS

Building upon techniques available for contemporary occupational medicine and exposure sciences, HRM methods are able to integrate external exposures, internal body burden of environmental agents, and relevant biological responses with health outcomes.

CONCLUSIONS

Systematic analysis of existing Department of Defense Serum Repository samples will provide a high-quality, cross-sectional reference dataset for deployment-associated exposures while at the same time establishing a foundation for precision medicine.

Metabolomics and Its Application to Acute Lung Diseases

Metabolomics is a rapidly expanding field of systems biology that is gaining significant attention in many areas of biomedical research. Also known as metabonomics, it comprises the analysis of all small molecules or metabolites that are present within an organism or a specific compartment of the body. Metabolite detection and quantification provide a valuable addition to genomics and proteomics and give unique insights into metabolic changes that occur in tangent to alterations in gene and protein activity that are associated with disease. As a novel approach to understanding disease, metabolomics provides a "snapshot" in time of all metabolites present in a biological sample such as whole blood, plasma, serum, urine, and many other specimens that may be obtained from either patients or experimental models. In this article, we review the burgeoning field of metabolomics in its application to acute lung diseases, specifically pneumonia and acute respiratory disease syndrome (ARDS). We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized environmental toxins. Recent reports have suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe disease, such as sepsis, which kills many patients each year. In addition, metabolomics may provide more detailed phenotyping of patient heterogeneity, which is needed to achieve the goal of precision medicine. However, although several experimental and clinical metabolomics studies have been conducted assessing the application of the science to acute lung diseases, only incremental progress has been made. Specifically, little is known about the metabolic phenotypes of these illnesses. These data are needed to substantiate metabolomics biomarker credentials so that clinicians can employ them for clinical decision-making and investigators can use them to design clinical trials.

An overview of detection techniques for monitoring dioxin-like compounds: latest technique trends and their applications

Dioxin-like compounds (DLCs) are considered as persistent bioaccumulative toxicants with a number of continuing issues in the fields of ecotoxicology and bioassay.

Metabolome analyses in exposome studies: Profiling methods for a vast chemical space

Metabolic profiling (metabonomics/metabolomics) is now used routinely as a tool to provide information-rich datasets for biomarker discovery, prompting and augmenting detailed mechanistic studies. The experimental design and focus of any individual study will be reflected in the types of biomarkers that can be detected; toxicological studies will likely focus on markers of response to insult, whereas clinical case-control studies may yield diagnostic markers of disease. Population studies can make use of omics analyses, including metabonomics, to provide mechanistically-relevant markers that link environmental exposures to chronic disease endpoints. In this article, examples of how metabolic profiling has played a key role in molecular epidemiological analyses of chronic disease are presented, and how these reflect different aspects of the causal pathway. A commentary on the nature of metabolome analysis as a complex mixture problem as opposed to a coded, sequence or template problem is provided, alongside an overview of current and future analytical platforms that are being applied to meet this analytical challenge. Epidemiological studies are an important nexus for integrating various measures of the human exposome, and the ubiquity, diversity and functions of small molecule metabolites, represent an important way to link individual exposures, genetics and phenotype.

Evaluation of steroidomics by liquid chromatography hyphenated to mass spectrometry as a powerful analytical strategy for measuring human steroid perturbations

This review presents the evolution of steroid analytical techniques, including gas chromatography coupled to mass spectrometry (GC-MS), immunoassay (IA) and targeted liquid chromatography coupled to mass spectrometry (LC-MS), and it evaluates the potential of extended steroid profiles by a metabolomics-based approach, namely steroidomics. Steroids regulate essential biological functions including growth and reproduction, and perturbations of the steroid homeostasis can generate serious physiological issues; therefore, specific and sensitive methods have been developed to measure steroid concentrations. GC-MS measuring several steroids simultaneously was considered the first historical standard method for analysis. Steroids were then quantified by immunoassay, allowing a higher throughput; however, major drawbacks included the measurement of a single compound instead of a panel and cross-reactivity reactions. Targeted LC-MS methods with selected reaction monitoring (SRM) were then introduced for quantifying a small steroid subset without the problems of cross-reactivity. The next step was the integration of metabolomic approaches in the context of steroid analyses. As metabolomics tends to identify and quantify all the metabolites (i.e., the metabolome) in a specific system, appropriate strategies were proposed for discovering new biomarkers. Steroidomics, defined as the untargeted analysis of the steroid content in a sample, was implemented in several fields, including doping analysis, clinical studies, in vivo or in vitro toxicology assays, and more. This review discusses the current analytical methods for assessing steroid changes and compares them to steroidomics. Steroids, their pathways, their implications in diseases and the biological matrices in which they are analysed will first be described. Then, the different analytical strategies will be presented with a focus on their ability to obtain relevant information on the steroid pattern. The future technical requirements for improving steroid analysis will also be presented.

Metabonomics in the preclinical and environmental toxicity field

Preclinical studies assess both efficacy and safety of new drugs through a series of assays used to identify potential target organs and determine safety thresholds. However, despite these efforts, too many drugs prove toxic to humans during clinical phases or later on the market. This paper reviews how metabonomics, one of the key players in systems biology, should be able to assist toxicologists in better predicting the adverse effects of xenobiotics.

Potential of mass spectrometry metabolomics for chemical food safety

This review aims to describe the most significant applications of mass spectrometry-based metabolomics in the field of chemical food safety. A particular discussion of all the different analytical steps involved in the metabolomics workflow (sample preparation, mass spectrometry analytical platform and data processing) will be addressed.

A short review of applications of liquid chromatography mass spectrometry based metabolomics techniques to the analysis of human urine

Mass spectrometry based metabolomics profiling.