High-resolution metabolomics of occupational exposure to trichloroethylene

Integrating exposomics into biomedicine

Assessing a full range of environmental exposures will improve human health.

Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues

Non-communicable diseases (NCDs) such as cardiovascular diseases, chronic respiratory diseases, cancers, diabetes, and mental health disorders pose a significant global health challenge, accounting for the majority of fatalities and disability-adjusted life years worldwide. These diseases arise from the complex interactions between genetic, behavioral, and environmental factors, necessitating a thorough understanding of these dynamics to identify effective diagnostic strategies and interventions. Although recent advances in multi-omics technologies have greatly enhanced our ability to explore these interactions, several challenges remain. These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. This scoping review evaluates the global landscape of multi-omics data related to NCDs from 2000 to 2024, focusing on recent advancements in multi-omics data integration, translational applications, and equity considerations. We highlight the need for standardized protocols, harmonized data-sharing policies, and advanced approaches such as artificial intelligence/machine learning to integrate multi-omics data and study gene-environment interactions. We also explore challenges and opportunities in translating insights from gene-environment (GxE) research into precision medicine strategies. We underscore the potential of global multi-omics research in advancing our understanding of NCDs and enhancing patient outcomes across diverse and underserved populations, emphasizing the need for equity and fairness-centered research and strategic investments to build local capacities in underrepresented populations and regions.

Advancements in Assays for Micro- and Nanoplastic Detection: Paving the Way for Biomonitoring and Exposomics Studies

Although plastic pollution and exposure to plastic-related compounds have received worldwide attention, health risks associated with micro- and nanoplastics (MNPs) are largely unknown. Emerging evidence suggests MNPs are present in human biofluids and tissue, including blood, breast milk, stool, lung tissue, and placenta; however, exposure assessment is limited and the extent of human exposure to MNPs is not well known. While there is a critical need to establish robust and scalable biomonitoring strategies to assess human exposure to MNPs and plastic-related chemicals, over 10,000 chemicals have been linked to plastic manufacturing with no existing standardized approaches to account for even a fraction of these exposures. This review provides an overview of the status of methods for measuring MNPs and associated plastic-related chemicals in humans, with a focus on approaches that could be adapted for population-wide biomonitoring and integration with biological response measures to develop hypotheses on potential health effects of plastic exposures. We also examine the exposure risks associated with the widespread use of chemical additives in plastics. Despite advancements in analytical techniques, there remains a pressing need for standardized measurement protocols and untargeted, high-throughput analysis methods to enable comprehensive MNP biomonitoring to identify key MNP exposures in human populations. This review aims to merge insights into the toxicological effects of MNPs and plastic additives with an evaluation of analytical challenges, advocating for enhanced research methods to fully assess, understand, and mitigate the public health implications of MNPs.

Trichloroethylene: An Update on an Environmental Contaminant with Multiple Health Effects

The halogenated solvent trichloroethylene (TCE) has had many uses in medicine, construction, consumer products, and the military. Many of these uses have been discontinued or restricted due to its toxicity, which affects multiple target organs and includes both acute, high-dose toxicity and chronic, low-dose toxicity that also encompass several cancers. US and international agencies have conducted risk and hazard assessments for TCE, with comprehensive publications coming out in the last 10-15 years. Accordingly, the focus of this article is to review recently published data since that time (i.e., 2014) that clarify unsettled questions or provide additional insights into the metabolism and mechanisms of toxicity of TCE in several target organs. Besides metabolism, the review focuses on the kidneys, liver, immune system, nervous system, cardiovascular and pulmonary systems, the search for biomarkers, and recent analyses of human cancer risk and incidence from TCE exposure.

Effects of exposure to trihalomethanes in swimming pool waters on metabolomics profile: a randomized parallel design trial

Biological mechanisms of exposure to Trihalomethanes (THMs) in swimming pools remain unclear. Investigation of short-term changes in metabolomic profiles due to exposure to THMs during swimming can help to understand the health effects-related mechanisms. With this in view, we aimed to assess exposure of swimmers to THMs in chlorine and ozone-chlorine swimming pools using the metabolomics approach from September 2020 to January 2021 in Tehran. Two parallel panels of 29 healthy adult subjects swam over 60 min in either of swimming pools. Blood samples were collected before and 2 h after swimming to assess metabolomic profile using Hydrogen-Nuclear Magnetic Resonance Spectroscopy (H-NMR). Differential metabolites between the two groups were identified by multivariate analysis methods such as Orthogonal Partial Least-Squares Discriminant Analysis (OPLS-DA) and Random Forest (RF). The levels of THMs in exhaled air as a biomarker of exposure and the metabolic profile as a biomarker of the effect changed significantly between two participants of swimming pools. Based on the significant metabolites, the biochemical pathways were identified by the method of Metabolite Setts Enrichment Analysis (MSEA) and by using the Metaboanalyst platform. The pathways of tryptophan metabolism, galactose metabolism and fructose and mannose metabolism were the most important biochemically significant pathways in individuals after exposure to THMs. Finally, findings from metabolic changes in our study indicate that exposure to THMs in swimming pools can activate the mechanisms of central nervous system disorders, increased uric acid, increased risk of bladder cancer and oxidative stress.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40201-024-00912-2.

Volatile organic compounds (VOC) metabolites in urine are associated with increased systemic inflammation levels, and smokers are identified as a vulnerable population

BACKGROUND

Previous studies indicated that exposure to VOCs was linked to increased systemic inflammation levels. However, the dose-response relationships between urine VOCs metabolites and systemic inflammation have not been established, and the key metabolite of the toxic compounds has not been identified.

METHODS

We used data in 7007 US adults in the NHANES cycles (2011-2018) across 8 years. Urinary VOC metabolites were measured using ultra-performance liquid chromatography and electrospray tandem mass spectrometry (UPLC-ESI/MSMS). VOC metabolites were adjusted by urinary creatinine level before analysis. Systemic inflammation was assessed by systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) indices. Generalized linear models, restricted cubic splines (RCS), and weighted quantile sum (WQS) regression were applied to evaluate the associations, exposure-response (E-R) curve and identify the key contributor compound, adjusting for gender, age, race, BMI, marital condition, education level, smoking level, alcohol consumption and physical activity. Smoking status was assessed as an effect modifier.

RESULTS

Significant and robust positive correlations were found between 8 VOC metabolites and both SII and SIRI. They were N-Acetyl-S-(2-carboxyethyl)-L-cysteine (CEMA), N-Acetyl-S-(2-cyanoethyl)-L-cysteine (CYMA), N-Acetyl-S-(3,4-dihydroxybutyl)-L-cysteine (DHBMA), N-Acetyl-S-(3-hydroxypropyl)-L-cysteine (3HPMA), mandelic acid (MA), N-Acetyl-S-(4-hydroxy-2-butenyl)-L-cysteine (MHBMA3), phenylglyoxylic acid (PGA), and N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-cysteine (HPMMA). The RCS curves showed J-shaped or exponential shaped E-R relationships for most VOC metabolites. WQS regression found that exposure to the mixture of VOC metabolites was related to increased systemic inflammation, and MA was the key VOC metabolite contributing most to systemic inflammation levels. Smokers exhibited higher levels of urinary VOCs and larger susceptibility to VOC-related increases in SII and SIRI compared to non-smokers.

CONCLUSION

This study demonstrated a strong link between urinary VOC metabolites and increased systemic inflammation, and smokers were more susceptible. Our findings highlighted the significance of reducing VOC exposure to mitigate the inflammation levels, particularly for smokers.

Metabolomics and proteomics in occupational medicine: a comprehensive systematic review

BACKGROUND

Occupational biomonitoring is essential for assessing health risks linked to workplace exposures. The use of 'omics' technologies, such as metabolomics and proteomics, has become crucial in detecting subtle biological alterations induced by occupational hazards, thereby opening novel avenues for biomarker discovery.

AIMS

This systematic review aims to evaluate the application of metabolomics and proteomics in occupational health.

METHODS

Following the PRISMA guidelines, we conducted a comprehensive search on PubMed, Scopus, and Web of Science for original human studies that use metabolomics or proteomics to assess occupational exposure biomarkers. The risk of bias was assessed by adapting the Cochrane Collaboration tool and the Newcastle-Ottawa Quality Assessment Scale.

RESULTS

Of 2311 initially identified articles, 85 met the eligibility criteria. These studies were mainly conducted in China, Europe, and the United States of America, covering a wide range of occupational exposures. The findings revealed that metabolomics and proteomics approaches effectively identified biomarkers related to chemical, physical, biomechanical, and psychosocial hazards. Analytical methods varied, with mass spectrometry-based techniques emerging as the most prevalent. The risk of bias was generally low to moderate, with specific concerns about exposure measurement and confounding factors.

CONCLUSIONS

Integrating metabolomics and proteomics in occupational health biomonitoring significantly advances our understanding of exposure effects and facilitates the development of personalized preventive interventions. However, challenges remain regarding the complexity of data analysis, biomarker specificity, and the translation of findings into preventive measures. Future research should focus on longitudinal studies and biomarker validation across diverse populations to improve the reliability and applicability of occupational health interventions.

Gene-environment interactions within a precision environmental health framework

Understanding the complex interplay of genetic and environmental factors in disease etiology and the role of gene-environment interactions (GEIs) across human development stages is important. We review the state of GEI research, including challenges in measuring environmental factors and advantages of GEI analysis in understanding disease mechanisms. We discuss the evolution of GEI studies from candidate gene-environment studies to genome-wide interaction studies (GWISs) and the role of multi-omics in mediating GEI effects. We review advancements in GEI analysis methods and the importance of large-scale datasets. We also address the translation of GEI findings into precision environmental health (PEH), showcasing real-world applications in healthcare and disease prevention. Additionally, we highlight societal considerations in GEI research, including environmental justice, the return of results to participants, and data privacy. Overall, we underscore the significance of GEI for disease prediction and prevention and advocate for integrating the exposome into PEH omics studies.

Associations between metals and metabolomic profiles related to diabetes among adults in a rural region

INTRODUCTION

Exposure to metals is associated with increased risk of type 2 diabetes (T2D). Potential mechanisms for metals-T2D associations involve biological processes including oxidative stress and disruption of insulin-regulated glucose uptake. In this study, we assessed whether associations between metal exposure and metabolite profiles relate to biological pathways linked to T2D.

MATERIALS AND METHODS

We used data from 29 adults rural Colorado residents enrolled in the San Luis Valley Diabetes Study. Urinary concentrations of arsenic, cadmium, cobalt, lead, manganese, and tungsten were measured. Metabolic effects were evaluated using untargeted metabolic profiling, which included 61,851 metabolite signals detected in serum. We evaluated cross-sectional associations between metals and metabolites present in at least 50% of samples. Primary analyses adjusted urinary heavy metal concentrations for creatinine. Metabolite outcomes associated with each metal exposure were evaluated using pathway enrichment to investigate potential mechanisms underlying the relationship between metals and T2D.

RESULTS

Participants had a mean age of 58.5 years (standard deviation = 9.2), 48.3% were female, 48.3% identified as Hispanic/Latino, 13.8% were current smokers, and 65.5% had T2D. Of the detected metabolites, 455 were associated with at least one metal, including 42 associated with arsenic, 22 with cadmium, 10 with cobalt, 313 with lead, 66 with manganese, and two with tungsten. The metabolic features were linked to 24 pathways including linoleate metabolism, butanoate metabolism, and arginine and proline metabolism. Several of these pathways have been previously associated with T2D, and our results were similar when including only participants with T2D.

CONCLUSIONS

Our results support the hypothesis that metals exposure may be associated with biological processes related to T2D, including amino acid, co-enzyme, and sugar and fatty acid metabolism. Insight into biological pathways could influence interventions to prevent adverse health outcomes due to metal exposure.

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.

Exposome epidemiology for suspect environmental chemical exposures during pregnancy linked to subsequent breast cancer diagnosis

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry of pregnancy cohort biospecimens in the Child Health and Development Studies to test for associations with breast cancer identified via the California Cancer Registry. Second and third trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both second and third trimesters to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol, linked to variations in amino acid and nucleotide pathways in second trimester and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in third trimester. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

The role of Kupffer cell activation in immune liver damage induced by trichloroethylene associated with the IFN-γ/STAT1 signaling pathway

Trichloroethylene (TCE) is a metal detergent commonly used in industry that can enter the human body through the respiratory tract and skin, causing occupational medicamentosa-like dermatitis due to TCE (OMDT) and multiple organ damage, including liver failure. However, the pathogenesis of liver injury remains unclear. Kupffer cells (KCs) are important tissue macrophages in the body because the polarization of KCs plays a crucial role in immune-mediated liver injury. However, the mechanism of KCs polarization in TCE-induced immune liver injury has not been thoroughly elucidated. In this study, we investigated the effect of TCE-induced KCs polarization on liver function and signal transduction pathways using the TCE sensitization model developed by our group. BALB/c mouse skin was exposed to TCE for sensitization, and an increase in the expression of M1 macrophage-specific markers (CD16/CD32, iNOS), M1 macrophage-specific cytokines IL-1β, and IFN-γ, P-JAK-1 and P-STAT1 levels were also found to be dramatically increased. When using low doses of gadolinium trichloride (GdCl₃), the expression of these proteins and mRNA was significantly reduced. This phenomenon indicates that GdCl₃ blocks TCE-induced polarization of KCs and suggests that the IFN-γ/STAT1 signaling pathway may be involved in the polarization process of KCs. These findings clarify the relationship between the polarization of KCs and immune liver injury and highlight the importance of further study of immune-mediated liver injury in TCE-sensitized mice.

A global view of the genetic basis of Alzheimer disease

The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.

Associations between residential volatile organic compound exposures and liver injury markers: The role of biological sex and race

While occupational exposures to volatile organic compounds (VOCs) have been linked to steatohepatitis and liver cancer in industrial workers, recent findings have also positively correlated low-dose, residential VOC exposures with liver injury markers. VOC sources are numerous; factors including biological make up (sex), socio-cultural constructs (gender, race) and lifestyle (smoking) can influence both VOC exposure levels and disease outcomes. Therefore, the current study's objective is to investigate how sex and race influence associations between residential VOC exposures and liver injury markers particularly in smokers vs. nonsmokers. Subjects (n = 663) were recruited from residential neighborhoods; informed consent was obtained. Exposure biomarkers included 16 urinary VOC metabolites. Serological disease biomarkers included liver enzymes, direct bilirubin, and hepatocyte death markers (cytokeratin K18). Pearson correlations and generalized linear models were conducted. Models were adjusted for common liver-related confounders and interaction terms. The study population constituted approximately 60% females (n = 401) and 40% males (n = 262), and a higher percent of males were smokers and/or frequent drinkers. Both sexes had a higher percent of White (75% females, 82% males) vs. Black individuals. Positive associations were identified for metabolites of acrolein, acrylamide, acrylonitrile, butadiene, crotonaldehyde, and styrene with alkaline phosphatase (ALP), a biomarker for cholestatic injury; and for the benzene metabolite with bilirubin; only in females. These associations were retained in female smokers. Similar associations were also observed between these metabolites and ALP only in White individuals (n = 514). In Black individuals (n = 114), the styrene metabolite was positively associated with aspartate transaminase. Interaction models indicated that positive associations for acrylamide/crotonaldehyde metabolites with ALP in females were dose-dependent. Most VOC associations with K18 markers were negative in this residential population. Overall, the findings demonstrated that biological sex, race, and smoking status influence VOC effects on liver injury and underscored the role of biological-social-lifestyle factor(s) interactions when addressing air pollution-related health disparities.

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.

Using MetaboAnalyst 5.0 for LC-HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become a workhorse in global metabolomics studies with growing applications across biomedical and environmental sciences. However, outstanding bioinformatics challenges in terms of data processing, statistical analysis and functional interpretation remain critical barriers to the wider adoption of this technology. To help the user community overcome these barriers, we have made major updates to the well-established MetaboAnalyst platform ( www.metaboanalyst.ca ). This protocol extends the previous 2011 Nature Protocol by providing stepwise instructions on how to use MetaboAnalyst 5.0 to: optimize parameters for LC-HRMS spectra processing; obtain functional insights from peak list data; integrate metabolomics data with transcriptomics data or combine multiple metabolomics datasets; conduct exploratory statistical analysis with complex metadata. Parameter optimization may take ~2 h to complete depending on the server load, and the remaining three stages may be executed in ~60 min.

'Omics in environmental epidemiological studies of chemical exposures: A systematic evidence map

BACKGROUND

Systematic evidence maps are increasingly used to develop chemical risk assessments. These maps can provide an overview of available studies and relevant study information to be used for various research objectives and applications. Environmental epidemiological studies that examine the impact of chemical exposures on various 'omic profiles in human populations provide relevant mechanistic information and can be used for benchmark dose modeling to derive potential human health reference values.

OBJECTIVES

To create a systematic evidence map of environmental epidemiological studies examining environmental contaminant exposures with 'omics in order to characterize the extent of available studies for future research needs.

METHODS

Systematic review methods were used to search and screen the literature and included the use of machine learning methods to facilitate screening studies. The Populations, Exposures, Comparators and Outcomes (PECO) criteria were developed to identify and screen relevant studies. Studies that met the PECO criteria after full-text review were summarized with information such as study population, study design, sample size, exposure measurement, and 'omics analysis.

RESULTS

Over 10,000 studies were identified from scientific databases. Screening processes were used to identify 84 studies considered PECO-relevant after full-text review. Various contaminants (e.g. phthalate, benzene, arsenic, etc.) were investigated in epidemiological studies that used one or more of the four 'omics of interest: epigenomics, transcriptomics, proteomics, and metabolomics . The epidemiological study designs that were used to explore single or integrated 'omic research questions with contaminant exposures were cohort studies, controlled trials, cross-sectional, and case-control studies. An interactive web-based systematic evidence map was created to display more study-related information.

CONCLUSIONS

This systematic evidence map is a novel tool to visually characterize the available environmental epidemiological studies investigating contaminants and biological effects using 'omics technology and serves as a resource for investigators and allows for a range of applications in chemical research and risk assessment needs.

Multiomics to elucidate inflammatory bowel disease risk factors and pathways

Inflammatory bowel disease (IBD) is an immune-mediated disease of the intestinal tract, with complex pathophysiology involving genetic, environmental, microbiome, immunological and potentially other factors. Epidemiological data have provided important insights into risk factors associated with IBD, but are limited by confounding, biases and data quality, especially when pertaining to risk factors in early life. Multiomics platforms provide granular high-throughput data on numerous variables simultaneously and can be leveraged to characterize molecular pathways and risk factors for chronic diseases, such as IBD. Herein, we describe omics platforms that can advance our understanding of IBD risk factors and pathways, and available omics data on IBD and other relevant diseases. We highlight knowledge gaps and emphasize the importance of birth, at-risk and pre-diagnostic cohorts, and neonatal blood spots in omics analyses in IBD. Finally, we discuss network analysis, a powerful bioinformatics tool to assemble high-throughput data and derive clinical relevance.

Assessing Dietary Pesticide Intake and Potential Health Effects: The Application of Global Metabolomics Analysis

Scientific information is not yet available to provide insight into how individual metabolome might be affected by the presence of pesticides in regular diets. This study aimed to evaluate the perturbation of metabolomic pathways in children who switched their diets from conventional foods to mostly organic foods for five consecutive days. We selected 46 child-matched spot urine samples with distinct differences of urinary pesticide metabolite levels between the conventional and organic eating days and then analyzed those urine samples on three analytical platforms to perform global metabolomics analysis. We found statistically significant perturbations of metabolic pathways relevant to inflammation, oxidative stress, and the demands of xenobiotic detoxification when children switched their conventional diets to mostly organic foods. The outcomes of this study allow us to extend the current understanding beyond organophosphate pesticides' acute toxicity of cholinesterase inhibition to the perturbation of metabolic pathways at dietary intake levels.

Molecular signatures associated with diuron exposure on rat urothelial mitochondria

Diuron, 3- (3,4-dichlorophenyl)-1,1-dimethylurea, is a worldwide used herbicide whose biotransformation gives rise to the metabolites, 3-(3,4-dichlorophenyl)-1-methylurea (DCPMU) and 3,4-dichloroaniline (DCA). Previous studies indicate that diuron and/or its metabolites are toxic to the bladder urothelium of the Wistar rats where, under certain conditions of exposure, they may induce successively urothelial cell degeneration, necrosis, hyperplasia and eventually tumors. The hypothesis was raised that the molecular initiating event (MIE) of this Adverse Outcome Pathway (AOP) is the mitochondrial toxicity of those compounds. Therefore, this study aimed to investigate in vitro the metabolic alterations resulting from urothelial mitochondria isolated from male Wistar rats exposure to diuron, DCPMU and DCA at 10 and 100 µM. A non-targeted metabolomic analysis using mass spectrometry showed discriminative clustering among groups and alterations in the intensity abundance of membrane-associated molecules phosphatidylcholine (PC), phosphatidylinositol (PI) and phosphatidylserine (PS), in addition to methylhexanoyl-CoA and, particularly for diuron 100 µM, dehydro-L-gulonate, all of them involved in critical mitochondrial metabolism. Collectively, these data indicate the mitochondrial dysfunction as a MIE that triggers cellular damage and death observed in previous studies.

Toxicity assessments of selected trichloroethylene and perchloroethylene metabolites in three in vitro human placental models

Residential and occupational exposures to the industrial solvents perchloroethylene (PERC) and trichloroethylene (TCE) present public health concerns. In humans, maternal PERC and TCE exposures can be associated with adverse birth outcomes. Because PERC and TCE are biotransformed to toxic metabolites and placental dysfunction can contribute to adverse birth outcomes, the present study compared the toxicity of key PERC and TCE metabolites in three in vitro human placenta models. We measured cell viability and caspase 3 + 7 activity in the HTR-8/SVneo and BeWo cell lines, and caspase 3 + 7 activity in first trimester villous explant cultures. Cultures were exposed for 24 h to 5-100 µM S-(1,2-dichlorovinyl)-L-cysteine (DCVC) and S-(1,2,2-trichlorovinyl)-L-cysteine (TCVC), or 5-200 µM trichloroacetate (TCA) and dichloroacetate (DCA). DCVC significantly reduced cell viability and increased caspase 3 + 7 activity in HTR-8/SVneo cells at a lower concentration (20 µM) compared with concentrations toxic to BeWo cells and villous explants. Similarly, TCVC reduced cell viability and increased caspase 3 + 7 activity in HTR-8/SVneo cells but not in BeWo cells. TCA and DCA had only negligible effects on HTR-8/SVneo or BeWo cells. This study advances understanding of potential risks of PERC and TCE exposure during pregnancy by identifying metabolites toxic in placental cells and tissues.

Operationalizing the Exposome Using Passive Silicone Samplers

The exposome, which is defined as the cumulative effect of environmental exposures and corresponding biological responses, aims to provide a comprehensive measure for evaluating non-genetic causes of disease. Operationalization of the exposome for environmental health and precision medicine has been limited by the lack of a universal approach for characterizing complex exposures, particularly as they vary temporally and geographically. To overcome these challenges, passive sampling devices (PSDs) provide a key measurement strategy for deep exposome phenotyping, which aims to provide comprehensive chemical assessment using untargeted high-resolution mass spectrometry for exposome-wide association studies. To highlight the advantages of silicone PSDs, we review their use in population studies and evaluate the broad range of applications and chemical classes characterized using these samplers. We assess key aspects of incorporating PSDs within observational studies, including the need to preclean samplers prior to use to remove impurities that interfere with compound detection, analytical considerations, and cost. We close with strategies on how to incorporate measures of the external exposome using PSDs, and their advantages for reducing variability in exposure measures and providing a more thorough accounting of the exposome. Continued development and application of silicone PSDs will facilitate greater understanding of how environmental exposures drive disease risk, while providing a feasible strategy for incorporating untargeted, high-resolution characterization of the external exposome in human studies.

A review of environmental metabolism disrupting chemicals and effect biomarkers associating disease risks: Where exposomics meets metabolomics

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been elucidated to be important risk factors for metabolic diseases, such as diabetes and obesity. These metabolism-sensitive diseases typically occur when key metabolic and signaling pathways were disrupted, which can be influenced by the exposure to contaminants such as endocrine disrupting chemicals (EDCs), along with genetic and lifestyle factors. This promotes the concept and research on environmental metabolism disrupting chemicals (MDCs). In addition, identifying endogenous biochemical markers of effect linked to disease states is becoming an important tool to screen the biological targets following environmental contaminant exposure, as well as to provide an overview of toxicity risk assessment. As such, the current review aims to contribute to the further understanding of exposome and human health and disease by characterizing environmental exposure and effect metabolic biomarkers. We summarized MDC-associated metabolic biomarkers in laboratory animal and human cohort studies using high throughput targeted and nontargeted metabolomics techniques. Contaminants including heavy metals and organohalogen compounds, especially EDCs, have been repetitively associated with metabolic disorders, whereas emerging contaminants such as perfluoroalkyl substances and microplastics have also been found to disrupt metabolism. In addition, we found major limitations in the effective identification of metabolic biomarkers especially in human studies, toxicological research on the mixed effect of environmental exposure has also been insufficient compared to the research on single chemicals. Thus, it is timely to call for research efforts dedicated to the study of combined effect and metabolic alterations for the better assessment of exposomic toxicology and health risks. Moreover, advanced computational and prediction tools, further validation of metabolic biomarkers, as well as systematic and integrative investigations are also needed in order to reliably identify novel biomarkers and elucidate toxicity mechanisms, and to further utilize exposome and metabolome profiling in public health and safety management.

Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry

Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010, and analyzed using untargeted high-resolution metabolomics to characterize metabolite associations with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Metabolic associations with EC, OC and PM2.5 were evaluated for biochemical processes known to be associated with disease risk. Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and transcriptomic changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution.

Associations Between Residential Exposure to Volatile Organic Compounds and Liver Injury Markers

Occupational exposures to volatile organic compounds (VOCs) have been associated with numerous health complications including steatohepatitis and liver cancer. However, the potential impact of environmental/residential VOC exposures on liver health and function is largely unknown. To address this knowledge gap, the objective of this cross-sectional study is to investigate associations between VOCs and liver injury biomarkers in community residents. Subjects were recruited from six Louisville neighborhoods, and informed consent was obtained. Exposure biomarkers included 16 creatinine-adjusted urinary metabolites corresponding to 12 parent VOCs. Serological disease biomarkers measured included cytokertain-18 (K18 M65 and M30), liver enzymes, and direct bilirubin. Associations between exposure and disease biomarkers were assessed using generalized linear models. Smoking status was confirmed through urinary cotinine levels. The population comprised of approximately 60% females and 40% males; White persons accounted 78% of the population; with more nonsmokers (n = 413) than smokers (n = 250). When compared with nonsmokers, males (45%) and Black persons (26%) were more likely to be smokers. In the overall population, metabolites of acrolein, acrylonitrile, acrylamide, 1,3-butadiene, crotonaldehyde, styrene, and xylene were positively associated with alkaline phosphatase. These associations persisted in smokers, with the exception of crotonaldehyde, and addition of N,N-dimethylformamide and propylene oxide metabolites. Although no positive associations were observed for K18 M30, the benzene metabolite was positively associated with bilirubin, irrespective of smoking status. Taken together, the results demonstrated that selected VOCs were positively associated with liver injury biomarkers. These findings will enable better risk assessment and identification of populations vulnerable to liver disease.

The Role of Gut Microbiota and Microbiota-Related Serum Metabolites in the Progression of Diabetic Kidney Disease

Objective: Diabetic kidney disease (DKD) has become the major cause of end-stage renal disease (ESRD) associated with the progression of renal fibrosis. As gut microbiota dysbiosis is closely related to renal damage and fibrosis, we investigated the role of gut microbiota and microbiota-related serum metabolites in DKD progression in this study.

Methods: Fecal and serum samples obtained from predialysis DKD patients from January 2017 to December 2019 were detected using 16S rRNA gene sequencing and liquid chromatography-mass spectrometry, respectively. Forty-one predialysis patients were divided into two groups according to their estimated glomerular filtration rate (eGFR): the DKD non-ESRD group (eGFR ≥ 15 ml/min/1.73 m²) (n = 22), and the DKD ESRD group (eGFR < 15 ml/min/1.73 m²) (n = 19). The metabolic pathways related to differential serum metabolites were obtained by the KEGG pathway analysis. Differences between the two groups relative to gut microbiota profiles and serum metabolites were investigated, and associations between gut microbiota and metabolite concentrations were assessed. Correlations between clinical indicators and both microbiota-related metabolites and gut microbiota were calculated by Spearman rank correlation coefficient and visualized by heatmap.

Results: Eleven different intestinal floras and 239 different serum metabolites were identified between the two groups. Of 239 serum metabolites, 192 related to the 11 different intestinal flora were mainly enriched in six metabolic pathways, among which, phenylalanine and tryptophan metabolic pathways were most associated with DKD progression. Four microbiota-related metabolites in the phenylalanine metabolic pathway [hippuric acid (HA), L-(−)-3-phenylactic acid, trans-3-hydroxy-cinnamate, and dihydro-3-coumaric acid] and indole-3 acetic acid (IAA) in the tryptophan metabolic pathway positively correlated with DKD progression, whereas L-tryptophan in the tryptophan metabolic pathway had a negative correlation. Intestinal flora g_Abiotrophia and g_norank_f_Peptococcaceae were positively correlated with the increase in renal function indicators and serum metabolite HA. G_Lachnospiraceae_NC2004_Group was negatively correlated with the increase in renal function indicators and serum metabolites [L-(−)-3-phenyllactic acid and IAA].

Conclusions: This study highlights the interaction among gut microbiota, serum metabolites, and clinical indicators in predialysis DKD patients, and provides new insights into the role of gut microbiota and microbiota-related serum metabolites that were enriched in the phenylalanine and tryptophan metabolic pathways, which correlated with the progression of DKD.

Metabolome-wide association study of occupational exposure to benzene

Benzene is a recognized hematotoxin and leukemogen; however, its mechanism of action in humans remain unclear. To provide insight into the processes underlying benzene hematotoxicity, we performed high-resolution metabolomic profiling of plasma collected from a cross-sectional study of 33 healthy workers exposed to benzene (median 8-h time-weighted average exposure; 20 ppma), and 25 unexposed controls in Shanghai, China. Metabolic features associated with benzene were identified using a metabolome-wide association study (MWAS) that tested for the relationship between feature intensity and benzene exposure. MWAS identified 478 mass spectral features associated with benzene exposure at false discovery rate < 20%. Comparison to a list of 13 known benzene metabolites and metabolites predicted using a multi-component biotransformation algorithm showed five metabolites were detected, which included the known metabolites phenol and benzene diolepoxide. Metabolic pathway enrichment identified 41 pathways associated with benzene exposure, with altered pathways including carnitine shuttle, fatty acid metabolism, sulfur amino acid metabolism, glycolysis, gluconeogenesis and branched chain amino acid metabolism. These results suggest disruption to fatty acid uptake, energy metabolism and increased oxidative stress, and point towards pathways related to mitochondrial dysfunction, which has previously been linked to benzene exposure in animal models and human studies. Taken together, these results suggest benzene exposure is associated with disruption of mitochondrial pathways, and provide promising, systems biology biomarkers for risk assessment of benzene-induced hematotoxicity in humans.

A Scoping Review of Technologies and Their Applicability for Exposome-Based Risk Assessment in the Oil and Gas Industry

INTRODUCTION

Oil and gas workers have been shown to be at increased risk of chronic diseases including cancer, asthma, chronic obstructive pulmonary disease, and hearing loss, among others. Technological advances may be used to assess the external (e.g. personal sensors, smartphone apps and online platforms, exposure models) and internal exposome (e.g. physiologically based kinetic modeling (PBK), biomonitoring, omics), offering numerous possibilities for chronic disease prevention strategies and risk management measures. The objective of this study was to review the literature on these technologies, by focusing on: (i) evaluating their applicability for exposome research in the oil and gas industry, and (ii) identifying key challenges that may hamper the successful application of such technologies in the oil and gas industry.

METHOD

A scoping review was conducted by identifying peer-reviewed literature with searches in MEDLINE/PubMed and SciVerse Scopus. Two assessors trained on the search strategy screened retrieved articles on title and abstract. The inclusion criteria used for this review were: application of the aforementioned technologies at a workplace in the oil and gas industry or, application of these technologies for an exposure relevant to the oil and gas industry but in another occupational sector, English language and publication period 2005-end of 2019.

RESULTS

In total, 72 articles were included in this scoping review with most articles focused on omics and bioinformatics (N = 22), followed by biomonitoring and biomarkers (N = 20), external exposure modeling (N = 11), PBK modeling (N = 10), and personal sensors (N = 9). Several studies were identified in the oil and gas industry on the application of PBK models and biomarkers, mainly focusing on workers exposed to benzene. The application of personal sensors, new types of exposure models, and omics technology are still in their infancy with respect to the oil and gas industry. Nevertheless, applications of these technologies in other occupational sectors showed the potential for application in this sector.

DISCUSSION AND CONCLUSION

New exposome technologies offer great promise for personal monitoring of workers in the oil and gas industry, but more applied research is needed in collaboration with the industry. Current challenges hindering a successful application of such technologies include (i) the technological readiness of sensors, (ii) the availability of data, (iii) the absence of standardized and validated methods, and (iv) the need for new study designs to study the development of disease during working life.

Preventing Parkinson's Disease: An Environmental Agenda

Fueled by aging populations and continued environmental contamination, the global burden of Parkinson's disease (PD) is increasing. The disease, or more appropriately diseases, have multiple environmental and genetic influences but no approved disease modifying therapy. Additionally, efforts to prevent this debilitating disease have been limited. As numerous environmental contaminants (e.g., pesticides, metals, industrial chemicals) are implicated in PD, disease prevention is possible. To reduce the burden of PD, we have compiled preclinical and clinical research priorities that highlight both disease prediction and primary prevention. Though not exhaustive, the "PD prevention agenda" builds upon many years of research by our colleagues and proposes next steps through the lens of modifiable risk factors. The agenda identifies ten specific areas of further inquiry and considers the funding and policy changes that will be necessary to help prevent the world's fastest growing brain disease.

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.

Utilizing a Biology-Driven Approach to Map the Exposome in Health and Disease: An Essential Investment to Drive the Next Generation of Environmental Discovery

BACKGROUND

Recent developments in technologies have offered opportunities to measure the exposome with unprecedented accuracy and scale. However, because most investigations have targeted only a few exposures at a time, it is hypothesized that the majority of the environmental determinants of chronic diseases remain unknown.

OBJECTIVES

We describe a functional exposome concept and explain how it can leverage existing bioassays and high-resolution mass spectrometry for exploratory study. We discuss how such an approach can address well-known barriers to interpret exposures and present a vision of next-generation exposomics.

DISCUSSION

The exposome is vast. Instead of trying to capture all exposures, we can reduce the complexity by measuring the functional exposome-the totality of the biologically active exposures relevant to disease development-through coupling biochemical receptor-binding assays with affinity purification-mass spectrometry. We claim the idea of capturing exposures with functional biomolecules opens new opportunities to solve critical problems in exposomics, including low-dose detection, unknown annotations, and complex mixtures of exposures. Although novel, biology-based measurement can make use of the existing data processing and bioinformatics pipelines. The functional exposome concept also complements conventional targeted and untargeted approaches for understanding exposure-disease relationships.

CONCLUSIONS

Although measurement technology has advanced, critical technological, analytical, and inferential barriers impede the detection of many environmental exposures relevant to chronic-disease etiology. Through biology-driven exposomics, it is possible to simultaneously scale up discovery of these causal environmental factors. https://doi.org/10.1289/EHP8327.

Data Processing Thresholds for Abundance and Sparsity and Missed Biological Insights in an Untargeted Chemical Analysis of Blood Specimens for Exposomics

Background: An untargeted chemical analysis of bio-fluids provides semi-quantitative data for thousands of chemicals for expanding our understanding about relationships among metabolic pathways, diseases, phenotypes and exposures. During the processing of mass spectral and chromatography data, various signal thresholds are used to control the number of peaks in the final data matrix that is used for statistical analyses. However, commonly used stringent thresholds generate constrained data matrices which may under-represent the detected chemical space, leading to missed biological insights in the exposome research. Methods: We have re-analyzed a liquid chromatography high resolution mass spectrometry data set for a publicly available epidemiology study (n = 499) of human cord blood samples using the MS-DIAL software with minimally possible thresholds during the data processing steps. Peak list for individual files and the data matrix after alignment and gap-filling steps were summarized for different peak height and detection frequency thresholds. Correlations between birth weight and LC/MS peaks in the newly generated data matrix were computed using the spearman correlation coefficient. Results: MS-DIAL software detected on average 23,156 peaks for individual LC/MS file and 63,393 peaks in the aligned peak table. A combination of peak height and detection frequency thresholds that was used in the original publication at the individual file and the peak alignment levels can reject 90% peaks from the untargeted chemical analysis dataset that was generated by MS-DIAL. Correlation analysis for birth weight data suggested that up to 80% of the significantly associated peaks were rejected by the data processing thresholds that were used in the original publication. The re-analysis with minimum possible thresholds recovered metabolic insights about C19 steroids and hydroxy-acyl-carnitines and their relationships with birth weight. Conclusions: Data processing thresholds for peak height and detection frequencies at individual data file and at the alignment level should be used at minimal possible level or completely avoided for mining untargeted chemical analysis data in the exposome research for discovering new biomarkers and mechanisms.

Transcriptional profiling of the response to the trichloroethylene metabolite S-(1,2-dichlorovinyl)-L-cysteine revealed activation of the eIF2α/ATF4 integrated stress response in two in vitro placental models

Trichloroethylene (TCE) is an industrial solvent and widespread environmental contaminant. Although TCE exposure is prevalent, epidemiological studies of TCE exposure associations with adverse birth outcomes are inconclusive. Prior studies show that the TCE metabolite S-(1,2-dichlorovinyl)-L-cysteine (DCVC) exhibits toxicity in a placental cell line. In the current study, genome-wide gene expression and gene set enrichment analyses were used to identify novel genes and pathway alterations in the HTR-8/SVneo human trophoblast cell line and human placental villous explants treated with DCVC at concentrations relevant to human exposures. In the cells, concentration- and time-dependent effects were observed, as evidenced by the magnitude of altered gene expression after treatment with 20 µM DCVC versus 10 µM, and 12-h versus 6-h of treatment. Comparing the two models for the transcriptional response to 12-h 20 µM DCVC treatment, no differentially expressed genes reached significance in villous explants, whereas 301 differentially expressed genes were detected in HTR-8/SVneo cells compared with non-treated controls (FDR < 0.05 + LogFC > 0.35 [FC > 1.3]). GSEA revealed five upregulated enriched pathways in common between explants and cells (FDR < 0.05). Moreover, all 12-h DCVC treatment groups from both models contained upregulated pathways enriched for genes regulated by the ATF4 transcription factor. The overrepresentation of ATF4 regulation of differentially expressed genes indicated activation of the integrated stress response (ISR), a condition triggered by multiple stress stimuli, including the unfolded protein response. DCVC-induced ISR activation was confirmed by elevated eIF2α phosphorylation, ATF4 protein concentrations, and decreased global protein synthesis in HTR-8/SVneo cells. This study identifies a mechanism of DCVC-induced cytotoxicity by revealing the involvement of a specific stress signaling pathway.

High-Resolution Metabolomic Assessment of Pesticide Exposure in Central Valley, California

Pesticides are widely used in the agricultural Central Valley region of California. Historically, this has included organophosphates (OPs), organochlorines (OCs), and pyrethroids (PYRs). This study aimed to identify perturbations of the serum metabolome in response to each class of pesticide and mutual associations between groups of metabolites and multiple pesticides. We conducted high-resolution metabolomic profiling of serum samples from 176 older adults living in the California Central Valley using liquid chromatography with high-resolution mass spectrometry. We estimated chronic pesticide exposure (from 1974 to year of blood draw) to OPs, OCs, and PYRs from ambient sources at homes and workplaces with a geographic information system (GIS)-based model. Based on partial least-squares regression and pathway enrichment analysis, we identified metabolites and metabolic pathways associated with one or multiple pesticide classes, including mitochondrial energy metabolism, fatty acid and lipid metabolism, and amino acid metabolism. Utilizing an integrative network approach, we found that the fatty acid β-oxidation pathway is a common pathway shared across all three pesticide classes. The disruptions of the serum metabolome suggested that chronic pesticide exposure might result in oxidative stress, inflammatory reactions, and mitochondrial dysfunction, all of which have been previously implicated in a wide variety of diseases. Overall, our findings provided a comprehensive view of the molecular mechanisms of chronic pesticide toxicity, and, for the first time, our approach informs exposome research by moving from macrolevel population exposures to microlevel biologic responses.

Gaussian graphical modeling of the serum exposome and metabolome reveals interactions between environmental chemicals and endogenous metabolites

Given the complex exposures from both exogenous and endogenous sources that an individual experiences during life, exposome-wide association studies that interrogate levels of small molecules in biospecimens have been proposed for discovering causes of chronic diseases. We conducted a study to explore associations between environmental chemicals and endogenous molecules using Gaussian graphical models (GGMs) of non-targeted metabolomics data measured in a cohort of California women firefighters and office workers. GGMs revealed many exposure-metabolite associations, including that exposures to mono-hydroxyisononyl phthalate, ethyl paraben and 4-ethylbenzoic acid were associated with metabolites involved in steroid hormone biosynthesis, and perfluoroalkyl substances were linked to bile acids-hormones that regulate cholesterol and glucose metabolism-and inflammatory signaling molecules. Some hypotheses generated from these findings were confirmed by analysis of data from the National Health and Nutrition Examination Survey. Taken together, our findings demonstrate a novel approach to discovering associations between chemical exposures and biological processes of potential relevance for disease causation.

Use of Exposomic Methods Incorporating Sensors in Environmental Epidemiology

PURPOSE OF REVIEW

The exposome is a recently coined concept that comprises the totality of nongenetic factors that affect human health. It is recognized as a major conceptual advancement in environmental epidemiology, and there is increased demand for technologies that capture the spatial, temporal, and chemical variability of exposures across individuals (i.e., "exposomic sensors"). We review a selection of these tools, highlighting their strengths and limitations with regard to epidemiological research.

RECENT FINDINGS

Wearable passive samplers are emerging as promising exposomic sensors for individuals. In conjunction with targeted and untargeted assays, these sensors enable the measurement of complex multipollutant mixtures, which can include both known and previously unknown environmental contaminants. Because of their minimally burdensome and noninvasive nature, they are deployable among sensitive populations, such as seniors, pregnant women, and children. The integration of exposomic data captured by these sensors with other omic data (e.g., transcriptomic and metabolomic) presents exciting opportunities for investigating disease risk factors. For example, the linkage of exposomic sensor data with other omic data may indicate perturbation by multipollutant mixtures at multiple physiological levels, which would strengthen evidence of their effects and potentially indicate targets for interventions. However, there remain considerable theoretical and methodological challenges that must be overcome to realize the potential promise of omic integration. Through continued investment and improvement in exposomic sensor technologies, it may be possible to refine their application and reduce their outstanding limitations to advance the fields of exposure science and epidemiology.

What is new in the exposome?

The exposome concept refers to the totality of exposures from a variety of external and internal sources including chemical agents, biological agents, or radiation, from conception onward, over a complete lifetime. It encompasses also "psychosocial components" including the impact of social relations and socio-economic position on health. In this review we provide examples of recent contributions from exposome research, where we believe their application will be of the greatest value for moving forward. So far, environmental epidemiology has mainly focused on hard outcomes, such as mortality, disease exacerbation and hospitalizations. However, there are many subtle outcomes that can be related to environmental exposures, and investigations can be facilitated by an improved understanding of internal biomarkers of exposure and response, through the application of omic technologies. Second, though we have a wealth of studies on environmental pollutants, the assessment of causality is often difficult because of confounding, reverse causation and other uncertainties. Biomarkers and omic technologies may allow better causal attribution, for example using instrumental variables in triangulation, as we discuss here. Even more complex is the understanding of how social relationships (in particular socio-economic differences) influence health and imprint on the fundamental biology of the individual. The identification of molecular changes that are intermediate between social determinants and disease status is a way to fill the gap. Another field in which biomarkers and omics are relevant is the study of mixtures. Epidemiology often deals with complex mixtures (e.g. ambient air pollution, food, smoking) without fully disentangling the compositional complexity of the mixture, or with rudimentary approaches to reflect the overall effect of multiple exposures or components. From the point of view of disease mechanisms, most models hypothesize that several stages need to be transitioned through health to the induction of disease, but very little is known about the characteristics and temporal sequence of such stages. Exposome models reinforce the idea of a biography-to-biology transition, in that everyone's disease is the product of the individual history of exposures, superimposed on their underlying genetic susceptibilities. Finally, exposome research is facilitated by technological developments that complement traditional epidemiological study designs. We describe in depth one such new tools, adductomics. In general, the development of high-resolution and high-throughput technologies interrogating multiple -omics (such as epigenomics, transcriptomics, proteomics, adductomics and metabolomics) yields an unprecedented perspective into the impact of the environment in its widest sense on disease. The world of the exposome is rapidly evolving, though a huge gap still needs to be filled between the original expectations and the concrete achievements. Perhaps the most urgent need is for the establishment of a new generation of cohort studies with appropriately specified biosample collection, improved questionnaire data (including social variables), and the deployment of novel technologies that allow better characterization of individual environmental exposures, ranging from personal monitoring to satellite based observations.

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.

Unsupervised dimensionality reduction for exposome research

Understanding the effect of the environment on human health has benefited from progress made in measuring the exposome. High resolution mass spectrometry (HRMS) has made it possible to measure small molecules across a large dynamic range, allowing researchers to study the role of low abundance environmental toxicants in causing human disease. HRMS data have a high dimensional structure (number of predictors >> number of observations), generating information on the abundance of many chemical features (predictors) which may be highly correlated. Unsupervised dimension reduction techniques can allow dimensionality reduction of the various features into components that capture the essence of the variability in the exposome dataset. We illustrate and discuss the relevance of three different unsupervised dimension reduction techniques: principal component analysis, factor analysis, and non-negative matrix factorization. We focus on the utility of each method in understanding the relationship between the exposome and a disease outcome and describe their strengths and limitations. While the utility of these methods is context specific, it remains important to focus on the interpretability of results from each method.

The exposome and health: Where chemistry meets biology

Despite extensive evidence showing that exposure to specific chemicals can lead to disease, current research approaches and regulatory policies fail to address the chemical complexity of our world. To safeguard current and future generations from the increasing number of chemicals polluting our environment, a systematic and agnostic approach is needed. The "exposome" concept strives to capture the diversity and range of exposures to synthetic chemicals, dietary constituents, psychosocial stressors, and physical factors, as well as their corresponding biological responses. Technological advances such as high-resolution mass spectrometry and network science have allowed us to take the first steps toward a comprehensive assessment of the exposome. Given the increased recognition of the dominant role that nongenetic factors play in disease, an effort to characterize the exposome at a scale comparable to that of the human genome is warranted.

Association of occupational exposures with ex vivo functional immune response in workers handling carbon nanotubes and nanofibers

The objective of this study was to evaluate the association between carbon nanotube and nanofiber (CNT/F) exposure and ex vivo responses of whole blood challenged with secondary stimulants, adjusting for potential confounders, in a cross-sectional study of 102 workers. Multi-day exposure was measured by CNT/F structure count (SC) and elemental carbon (EC) air concentrations. Demographic, lifestyle and other occupational covariate data were obtained via questionnaire. Whole blood collected from each participant was incubated for 18 hours with and without two microbial stimulants (lipopolysaccharide/LPS and staphylococcal enterotoxin type B/SEB) using TruCulture technology to evaluate immune cell activity. Following incubation, supernatants were preserved and analyzed for protein concentrations. The stimulant:null response ratio for each individual protein was analyzed using multiple linear regression, followed by principal component (PC) analysis to determine whether patterns of protein response were related to CNT/F exposure. Adjusting for confounders, CNT/F metrics (most strongly, the SC-based) were significantly (p < 0.05) inversely associated with stimulant:null ratios of several individual biomarkers: GM-CSF, IFN-γ, interleukin (IL)-2, IL-4, IL-5, IL-10, IL-17, and IL-23. CNT/F metrics were significantly inversely associated with PC1 (a weighted mean of most biomarkers, explaining 25% of the variance in the protein ratios) and PC2 (a biomarker contrast, explaining 14%). Among other occupational exposures, only solvent exposure was significant (inversely related to PC2). CNT/F exposure metrics were uniquely related to stimulant responses in challenged whole blood, illustrating reduced responsiveness to a secondary stimulus. This approach, if replicated in other exposed populations, may present a relatively sensitive method to evaluate human response to CNT/F or other occupational exposures.

Metabolome Wide Association Study of serum DDT and DDE in Pregnancy and Early Postpartum

The advancement of high-resolution metabolomics (HRM) and metabolome-wide-association study (MWAS) enables the readout of environmental effects in human specimens. We used HRM to understand DDT-induced alterations of in utero environment and potential health effects. Endogenous metabolites were measured in 397 maternal perinatal serum samples collected during 1959-1967 in the Child Health and Development Studies (CHDS) and in 16 maternal postnatal serum samples of mice treated with or without DDT. MWAS was performed to assess associations between metabolites and p,p'-DDT, o,p'-DDT and p,p'-DDE levels, followed by pathway analysis. Distinct metabolic profiles were found with p,p'-DDT and p,p'-DDE. Amino acids such arginine had a strong association with p,p'-DDT and o,p'-DDT in both women and mice, whereas lipids and acyl-carnitine intermediates were found exclusively associated with p,p'-DDE in CHDS women indicating mitochondrial impairment. It suggests that the role of serine and fatty acid metabolism on the causal disease pathway should be examined.

Trichloroethylene, a ubiquitous environmental contaminant in the risk for Parkinson's disease

Organic solvents are common chemicals used in industry throughout the world, however, there is evidence for adverse health effects from exposure to these compounds. Trichloroethylene (TCE) is a halogenated solvent that has been used as a degreasing agent since the early 20th century. Due to its widespread use, TCE remains one of the most significant environmental contaminants in the US, and extensive research suggests TCE is a causative factor in a number of diseases, including cancer, fetal cardiac development, and neurotoxicity. TCE has also been implicated as a possible risk factor in the development of the most common neurodegenerative movement disorder, Parkinson's disease (PD). However, there is variable concordance across multiple occupational epidemiological studies assessing TCE (or solvent) exposure and risk for PD. In addition, there remains a degree of uncertainty about how TCE elicits toxicity to the dopaminergic system. To this end, we review the specific neurotoxic mechanisms of TCE in the context of selective vulnerability of dopaminergic neurons. In addition, we consider the complexity of combined risk factors that ultimately contribute to neurodegeneration and discuss the limitations of single-factor exposure assessments.

A vision for exposome epidemiology: The pregnancy exposome in relation to breast cancer in the Child Health and Development Studies

Etiology of complex diseases, such as breast cancer, involves multiple genetic, behavioral and environmental factors. Gene sequencing enabled detection of genetic risks with relatively small effect size, and high-resolution metabolomics (HRM) to provide omics level data for exposures is poised to do the same for environmental epidemiology. Coupling HRM to the Child Health and Development Studies (CHDS) cohort combines two unique resources to create a prototype for exposome epidemiology, in which omics scale measures of exposure are used for study of distribution and determinants of health and disease. Using this approach, exposures and biologic responses during pregnancy have been linked to breast cancer in the CHDS. With improved chemical coverage and extension to larger populations and other disease processes, development of exposome epidemiology portends discovery of new disease-associated environment factors with small effect size as well as new capabilities to disentangle these from behavioral and other risk factors.

Exposure to Trichloroethylene Metabolite S-(1,2-Dichlorovinyl)-L-cysteine Causes Compensatory Changes to Macronutrient Utilization and Energy Metabolism in Placental HTR-8/SVneo Cells

Trichloroethylene (TCE) is a widespread environmental contaminant following decades of use as an industrial solvent, improper disposal, and remediation challenges. Consequently, TCE exposure continues to constitute a risk to human health. Despite epidemiological evidence associating exposure with adverse birth outcomes, the effects of TCE and its metabolite S-(1, 2-dichlorovinyl)-L-cysteine (DCVC) on the placenta remain undetermined. Flexible and efficient macronutrient and energy metabolism pathway utilization is essential for placental cell physiological adaptability. Because DCVC is known to compromise cellular energy status and disrupt energy metabolism in renal proximal tubular cells, this study investigated the effects of DCVC on cellular energy status and energy metabolism pathways in placental cells. Human extravillous trophoblast cells, HTR-8/SVneo, were exposed to 5–20 μM DCVC for 6 or 12 h. After establishing concentration and exposure duration thresholds for DCVC-induced cytotoxicity, targeted metabolomics was used to evaluate overall energy status and metabolite concentrations from energy metabolism pathways. The data revealed glucose metabolism perturbations including a time-dependent accumulation of glucose-6-phosphate+frutose-6-phosphate (G6P+F6P) as well as independent shunting of glucose intermediates that diminished with time, with modest energy status decline but in the absence of significant changes in ATP concentrations. Furthermore, metabolic profiling suggested that DCVC stimulated compensatory utilization of glycerol, lipid, and amino acid metabolism to provide intermediate substrates entering downstream in the glycolytic pathway or the tricarboxylic acid cycle. Lastly, amino acid deprivation increased susceptibility to DCVC-induced cytotoxicity. Taken together, these results suggest that DCVC caused metabolic perturbations necessitating adaptations in macronutrient and energy metabolism pathway utilization to maintain adequate ATP levels.

The exposome and health: Where chemistry meets biology

Despite extensive evidence showing that exposure to specific chemicals can lead to disease, current research approaches and regulatory policies fail to address the chemical complexity of our world. To safeguard current and future generations from the increasing number of chemicals polluting our environment, a systematic and agnostic approach is needed. The "exposome" concept strives to capture the diversity and range of exposures to synthetic chemicals, dietary constituents, psychosocial stressors, and physical factors, as well as their corresponding biological responses. Technological advances such as high-resolution mass spectrometry and network science have allowed us to take the first steps toward a comprehensive assessment of the exposome. Given the increased recognition of the dominant role that nongenetic factors play in disease, an effort to characterize the exposome at a scale comparable to that of the human genome is warranted.