Biomonitoring in the Era of the Exposome

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.

Tear Fluid as a Matrix for Biomonitoring Environmental and Chemical Exposures

PURPOSE

Exposures to hazardous chemicals have been linked to many detrimental health effects and it is therefore critical to have effective biomonitoring methods to better evaluate key environmental exposures that increase the risk of chronic disease and death. Traditional biomonitoring utilizing blood and urine is limited due to the specialized skills and invasiveness of collecting these fluid samples. This systematic review focuses on tear fluid, which is largely under-researched, as a promising complementary matrix to the traditional fluids used for biomonitoring. The objective is to evaluate the practicability of using human tear fluid for biomonitoring environmental exposures, highlighting potential pitfalls and opportunities.

RECENT FINDING

Tear fluid biomonitoring represents a promising method for assessing exposures because it can be collected with minimal invasiveness and tears contain exposure markers from both the external and internal environments. Tear fluid uniquely interfaces with the external environment at the air-tear interface, providing a surface for airborne chemicals to diffuse into the ocular environment and interact with biomolecules. Tear fluid also contains molecules from the internal environment that have travelled from the blood to tears by crossing the blood-tear barrier. This review demonstrates that tear fluid can be used to identify hazardous chemicals from the external environment and differentiate exposure groups.

Handling of problematic ion chromatograms with the Automated Target Screening (ATS) workflow for unsupervised analysis of high-resolution mass spectrometry data

Liquid chromatography (LC) or gas chromatography (GC) coupled to high-resolution mass spectrometry (HRMS) is a versatile analytical method for the analysis of thousands of chemical pollutants that can be found in environmental and biological samples. While the tools for handling such complex datasets have improved, there are still no fully automated workflows for targeted screening analysis. Here we present an R-based workflow that is able to cope with challenging data like noisy ion chromatograms, retention time shifts, and multiple peak patterns. The workflow can be applied to batches of HRMS data recorded after GC with electron ionization (GC-EI) and LC coupled to electrospray ionization in both negative and positive mode (LC-ESIneg/LC-ESIpos) to perform peak annotation and quantitation fully unsupervised. We used Orbitrap HRMS data of surface water extracts to compare the Automated Target Screening (ATS) workflow with data evaluations performed with the vendor software TraceFinder and the established semi-automated analysis workflow in the MZmine software. The ATS approach increased the overall evaluation performance of the peak annotation compared to the established MZmine module without the need for any post-hoc corrections. The overall accuracy increased from 0.80 to 0.86 (LC-ESIpos), from 0.77 to 0.83 (LC-ESIneg), and from 0.67 to 0.76 (GC-EI). The mean average percentage errors for quantification of ATS were around 30% compared to the manual quantification with TraceFinder. The ATS workflow enables time-efficient analysis of GC- and LC-HRMS data and accelerates and improves the applicability of target screening in studies with a large number of analytes and sample sizes without the need for manual intervention.

Screening for contamination levels of select organic environmental chemicals in medical supplies used for human specimen collection

Trace-level analysis of environmental chemicals in human specimens can be compromised by contamination introduced during sample collection and storage. Sampling devices and tools can be a source of contamination by plasticizers, additives and antimicrobials, which warrants the need for pre-screening of these products prior to use. In this study, we determined leaching of 121 environmental chemicals in 10% and 100% methanol from 24 types of human specimen collection and storage devices. Cryovials, serum tubes, cups, syringes, transfer pipettes, and gloves -commonly used for the collection of blood, urine, breast milk and stools - were screened for the presence of plasticizers, environmental phenols, and pesticides. Measurable levels of mono-ethyl phthalate (mEP) and triethyl phosphate (TEP) were leached from vials, plastic storage bags, gloves, and diapers, and parabens were leached from collection bottles, at amounts exceeding 100 ng/device. The amount leached from the devices varied depending on the lot numbers of the same product type. Storage time and temperature were found to influence the leaching rate of chemicals, with increased levels observed following prolonged storage and at high temperatures. The study underscores the importance of pre-screening for contamination in devices used for collection and storage of human specimens for biomonitoring studies.

Assessing human exposure to pesticides and mycotoxins: optimization and validation of a method for multianalyte determination in urine samples

Humans are exposed to an increasing number of contaminants, with diet being one of the most important exposure routes. In this framework, human biomonitoring is considered the gold standard for evaluating human exposure to chemicals. Pesticides and mycotoxins are chemicals of special concern due to their health implications. They constitute the predominant border rejection notifications for food and feed in Europe and the USA. However, current biomonitoring studies are focused on a limited number of compounds and do not evaluate mycotoxins and pesticides together. In this study, an analytical method has been developed for the determination of 30 pesticides and 23 mycotoxins of concern in urine samples. A salting-out liquid-liquid extraction (SALLE) procedure was optimized achieving recoveries between 70 and 120% for almost all the compounds and limits as lower as when QuEChERS was applied. The compounds were then determined by liquid chromatography coupled to triple quadrupole mass spectrometry. Different chromatographic conditions and analytical columns were tested, selecting a Hypersild gold aQ column as the best option. Finally, the method was applied to the analysis of 45 urine samples, in which organophosphate and pyrethroid pesticides (detection rates (DR) of 82% and 42%, respectively) and ochratoxin A and deoxynivalenol (DR of 51% and 33%, respectively) were the most detected compounds. The proposed analytical method involves the simultaneous determination of a diverse set of pesticides and mycotoxins, including their most relevant metabolites, in human urine. It serves as an essential tool for biomonitoring the presence of highly prevalent contaminants in modern society.

Breast cancer risk for the joint exposure to metals and metalloids in women: Results from the EPIC-Spain cohort

Environmental factors play a role in breast cancer development. While metals and metalloids (MMs) include some carcinogens, their association with breast cancer depends on the element studied. Most studies focus on individual MMs, but the combined effects of metal mixtures remain unclear. The aim of this study was to analyze the relationship between the joint exposure to MMs and the risk of developing female breast cancer. We conducted a case-control study within the multicenter prospective EPIC-Spain cohort. Study population comprised 292 incident cases and 286 controls. Plasma concentrations of 16 MMs were quantified at recruitment. Potential confounders were collected using a questionnaire and anthropometric measurements. Mixed-effects logistic regression models were built to explore the effect of individual MMs. Quantile-based g computation models were applied to identify the main mixture components and to estimate the joint effect of the metal mixture. The geometric means were highest for Cu (845.6 ng/ml) and Zn (604.8 ng/ml). Cases had significantly higher Cu concentrations (p = 0.010) and significantly lower Zn concentrations (p < 0.001). Cu (+0.42) and Mn (+0.13) showed the highest positive weights, whereas Zn (-0.61) and W (-0.16) showed the highest negative weights. The joint effect of the metal mixture was estimated at an OR = 4.51 (95%CI = 2.32-8.79), suggesting a dose-response relationship. No evidence of non-linearity or non-additivity was found. An unfavorable exposure profile, primarily characterized by high Cu and low Zn levels, could lead to a significant increase in the risk of developing female breast cancer. Further studies are warranted to confirm these findings.

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

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

[Advances in the applications of exposomics in the identification of environmental pollutants and their health hazards]

Environmental pollution has become a prominent global problem, and the potential health hazards of pollutants have caused widespread concern. However, revealing the relationship between complex-pollutant exposure and disease development remains an immense challenge. The core of environmental-health research and risk assessment is the identification of contaminants and their effects. Exposomics provides a new approach in the study of the relationship between environmental factors and human health. Both "top-down" and "bottom-up" strategies are employed in exposomics research. The development of new technologies for chemical detection and "multi-omics" has greatly facilitated the implementation of these strategies. Exposomics focuses on the measurement of an individual's lifelong exposure and aims to identify the health effects of such exposure. It involves the dynamic monitoring of external and internal exposure levels at different stages of life through traditional biomonitoring and exposomic methods. It also includes the identification of biomarkers, which indicate specific environmental exposures and the adverse effects of these exposures on health. Compared with traditional environmental-health studies, exposomics can more accurately reflect the diversity of exposure factors such as pollutants, natural factors, and lifestyles in the real environment, as well as the complexity of their in vivo processes and the responses they trigger in an organism. Powerful chemical analytical tools such as high-resolution mass spectrometry (HRMS) are widely used in studies related to the field of exposomics. Liquid chromatography-mass spectrometry (LC-MS) has been applied in the detection and analysis of environmental pollutants. Proteomics and metabolomics, as two important tools for biomarker identification and effects analysis, are widely used to explore the relationship between environmental factors and diseases. Pollutants can lead to pathological changes and even toxic effects by interacting with proteins. In the case of mixed exposure, some contaminants may present joint toxicity. The interaction between contaminants may change their environmental behavior or the amount of each contaminant that enters the human body, which, in turn, affects their health effects.

Dummy molecularly imprinted polymer-based solid-phase extraction method for the determination of some phthalate monoesters in urine by gas chromatography-mass spectrometry analysis

A dummy molecularly imprinted polymer-based solid-phase extraction (SPE) sorbent was used for the selective extraction of some phthalate monoesters, monoethyl phthalate (MEP), monobutyl phthalate (MnBP) and mono-(2-ethylhexyl) phthalate (MEHP) in urine prior to gas-chromatography-mass spectrometry (GC-MS) analysis. Diethyl phthalate (DEP), a phthalate ester, was successfully used as a dummy template to prepare selective sorbent for MEP, MnBP, and MEHP extraction. DEP-imprinted poly(ethylene glycol dimethacrylate N-methacryloyl-l-tryptophan methyl ester) (DPEMT) microbeads were synthesized by suspension polymerization and characterized by Fourier Transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM) and Brunauer Emmet Teller (BET) analysis. The critical parameters (i.e., pH, sorbent amount, ionic strength, sample volume, elution solvent) affecting the extraction performance of the DPEMT-SPE sorbent were optimized. Under optimum conditions, good linearities were obtained in the concentration range of 4 to 60 ng/mL with determination coefficients (R2) of greater than 0.9959. The developed SPE method provided low limits of detection (LOD) of 0.05-1.20 ng/mL and limits of quantification (LOQ) of 0.18-4.01 ng/mL with relative standard deviations (RSDs) of less than 8.95 % for intra- and inter-day analyses. The proposed SPE method was used to analyze phthalate monoesters in spiked urine samples, and recoveries of 97.45-109.26 % were obtained. DPEMT-SPE sorbent was reused for 15 times without any losses of performance. Consequently, a highly selective and sensitive SPE method based on a dummy molecularly imprinted polymer combined with GC-MS was successfully developed to monitor human phthalate exposure via urine samples.

Exposure to per- and polyfluoroalkyl substances in early pregnancy and risk of cerebral palsy in children

BACKGROUND

Most cerebral palsy (CP) cases have an unexplained etiology, but a role for environmental exposures has been suggested. One purported environmental risk factor is exposure to endocrine-disrupting pollutants specifically per- and polyfluoroalkyl substances (PFAS).

OBJECTIVES

We investigated the association between prenatal PFAS exposures and CP in Swedish children.

METHODS

In this case-control study, 322 CP cases, 343 population controls, and 258 preterm controls were identified from a birth registry in combination with a CP follow-up program from 1995 to 2014 and linked to a biobank which contains serum samples from week 10-14 of pregnancy. Maternal serum concentrations of four PFAS compounds: perfluorohexane sulfonate (PFHxS), perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), and perfluorooctane sulfonate (PFOS) were analyzed using liquid chromatography-tandem-mass-spectrometry. We estimated odds ratios (ORs) and 95 % confidence intervals (CIs) for CP and each PFAS in quartiles and as continuous variables controlling for various sociodemographic and lifestyle factors.

RESULTS

In crude and adjusted analyses, we did not find consistent evidence of associations between serum PFHxS, PFOA, PFNA, PFOS and concentrations in early pregnancy and CP, except in preterm infants. The ORs comparing the highest PFAS quartiles to the lowest were 1.05 (95 % CI: 0.63-1.76), 0.96 (95 % CI: 0.55-1.68), 0.71 (95 % CI: 0.41-1.25), and 1.17 (95 % CI: 0.61-2.26), for PFHxS, PFOA, PFNA, and PFOS, respectively. Some positive associations were observed for preterm infants, but the results were imprecise. Similar patterns were observed in analyses treating PFAS as continuous variables.

CONCLUSIONS

In this study, we found little evidence that early pregnancy prenatal exposure to PFHxS, PFOA, PFNA, or PFOS increases the risk of CP. However, some positive associations were observed for preterm cases and warrant further investigation.

Comparing the sensitivity of a low- and a high-resolution mass spectrometry approach for xenobiotic trace analysis: An exposome-type case study

The chemical exposome consists of environmental exposures experienced throughout a lifetime but to date analytical approaches to investigate the plethora of low-abundance chemicals remain very limited. Liquid chromatography high-resolution mass spectrometry (HRMS) is commonly applied in untargeted exposome-wide analyses of xenobiotics in biological samples; however, human biomonitoring approaches usually utilize targeted low-resolution triple quadrupole (QQQ) mass spectrometry tailored to a small number of chemicals. HRMS can cover a broader chemical space but the detection of molecules from low-level exposure amidst a background of highly-abundant endogenous molecules has proven to be difficult. In this study, a triple quadrupole (QQQ) and a high-resolution mass spectrometer (HRMS) with identical chromatography were utilized to determine the limits of quantitation (LOQ) of >100 xenobiotics and estrogenic hormones in pure solvent and human urine. Both instrumental platforms are currently applied in exposure assessment studies and were operated in their most frequently used acquisition mode (full scan for HRMS and multiple reaction monitoring for QQQ) to mimic typical applications. For HRMS analyses, the median LOQ was 0.9 and 1.2 ng/mL in solvent and urine, respectively, while for low-resolution QQQ measurements, the median LOQ was 0.1 and 0.2 ng/mL in solvent and urine, respectively. To evaluate the calculated LOQs in complex biological samples, spot urine samples from 24 Nigerian female volunteers were investigated. The higher LOQ values for HRMS resulted in less quantified low-abundance analytes and decreased the number of compounds detected below the LOQ. Even at chronic low-dose exposure, such compounds might be relevant for human health because of high individual toxicity or potential mixture effects. Nevertheless, HRMS enabled the additional screening for exposure to unexpected/unknown analytes, including emerging compounds and biotransformation products. Therefore, a synergy between high- and low-resolution mass spectrometry may currently be the best option to elucidate and quantify xenobiotics in comprehensive exposome-wide association studies (ExWAS).

A Critical Review on the Opportunity to Use Placenta and Innovative Biomonitoring Methods to Characterize the Prenatal Chemical Exposome

Adverse effects associated with chemical exposures during pregnancy include several developmental and reproductive disorders. However, considering the tens of thousands of chemicals present on the market, the effects of chemical mixtures on the developing fetus is still likely underestimated. In this critical review, we discuss the potential to apply innovative biomonitoring methods using high-resolution mass spectrometry (HRMS) on placenta to improve the monitoring of chemical exposure during pregnancy. The physiology of the placenta and its relevance as a matrix for monitoring chemical exposures and their effects on fetal health is first outlined. We then identify several key parameters that require further investigations before placenta can be used for large-scale monitoring in a robust manner. Most critical is the need for standardization of placental sampling. Placenta is a highly heterogeneous organ, and knowledge of the intraplacenta variability of chemical composition is required to ensure unbiased and robust interindividual comparisons. Other important variables include the time of collection, the sex of the fetus, and mode of delivery. Finally, we discuss the first applications of HRMS methods on the placenta to decipher the chemical exposome and describe how the use of placenta can complement biofluids collected on the mother or the fetus.

The contribution of the exposome to the burden of cardiovascular disease

Large epidemiological and health impact assessment studies at the global scale, such as the Global Burden of Disease project, indicate that chronic non-communicable diseases, such as atherosclerosis and diabetes mellitus, caused almost two-thirds of the annual global deaths in 2020. By 2030, 77% of all deaths are expected to be caused by non-communicable diseases. Although this increase is mainly due to the ageing of the general population in Western societies, other reasons include the increasing effects of soil, water, air and noise pollution on health, together with the effects of other environmental risk factors such as climate change, unhealthy city designs (including lack of green spaces), unhealthy lifestyle habits and psychosocial stress. The exposome concept was established in 2005 as a new strategy to study the effect of the environment on health. The exposome describes the harmful biochemical and metabolic changes that occur in our body owing to the totality of different environmental exposures throughout the life course, which ultimately lead to adverse health effects and premature deaths. In this Review, we describe the exposome concept with a focus on environmental physical and chemical exposures and their effects on the burden of cardiovascular disease. We discuss selected exposome studies and highlight the relevance of the exposome concept for future health research as well as preventive medicine. We also discuss the challenges and limitations of exposome studies.

Target Exposome for Characterizing Early Gestational Exposure to Contaminants of Emerging Concern and Association with Gestational Diabetes Mellitus

Characterization of gestational exposure to complex contaminants of emerging concern (CECs) is critical to the identification of environmental risk factors for pregnancy complications. However, determination of various CECs with diverse physicochemical properties in biological fluids is technically challenging. In the present study, we developed a target exposome protocol, consisting of simple liquid-liquid extraction-based sample preparation and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis, to determine 325 CECs covering 11 subclasses, including poly- and perfluoroalkyl substances, organophosphate esters, ultraviolet (UV) stabilizers, synthetic antioxidants, phthalate esters, and several others. The protocol exhibits exceptional advantages over traditional approaches in the coverage of chemicals, sample volume demand, and time and financial cost. The protocol was applied in a prospective nested gestational diabetes mellitus (GDM) study including 120 cases and 240 matched healthy controls. Thirty-three CECs were detected in >70% of the samples, with a combined concentration of 17.0-484.7 ng/mL. Bayesian kernel machine regression analysis showed that exposure to the CEC mixture was significantly associated with a higher GDM risk. For example, when increasing all CECs in the mixture from 50th percentile to 75th percentile, the estimated probit of GDM incidence had an increase of 92% (95% CI: 56%, 127%). Meanwhile, perfluorohexanesulfonic acid, 1,3-diphenylguanidine, and dibutyl fumarate were identified as the key CECs driving the joint effect. This work demonstrates great potential of our target exposome protocol for environmental risk factor identification in large-scale epidemiology or biomonitoring studies.

Exploring Single-Cell Exposomics by Mass Spectrometry

Single-cell exposomics, a revolutionary approach that investigates cell-environment interactions at cellular and subcellular levels, stands distinct from conventional bulk exposomics. Leveraging advancements in mass spectrometry, it provides a detailed perspective on cellular dynamics, interactions, and responses to environmental stimuli and their impacts on human health. This work delves into this innovative realm, highlighting the nuanced interplay between environmental stressors and biological responses at cellular and subcellular levels. The application of spatial mass spectrometry in single-cell exposomics is discussed, revealing the intricate spatial organization and molecular composition within individual cells. Cell-type-specific exposomics, shedding light on distinct susceptibilities and adaptive strategies of various cell types to environmental exposures, is also examined. The Perspective further emphasizes the integration with molecular and cellular biology approaches to validate hypotheses derived from single-cell exposomics in a comprehensive biological context. Looking toward the future, we anticipate continued technological advancements and convergence with other -omics approaches and discuss implications for environmental health research, disease progression studies, and precision medicine. The final emphasis is on the need for robust computational tools and interdisciplinary collaboration to fully leverage the potential of single-cell exposomics, acknowledging the complexities inherent to this paradigm.

Investigating geographic differences in environmental chemical exposures in maternal and cord sera using non-targeted screening and silicone wristbands in California

BACKGROUND

Differential risks for adverse pregnancy outcomes may be influenced by prenatal chemical exposures, but current exposure methods may not fully capture data to identify harms and differences.

METHODS

We collected maternal and cord sera from pregnant people in Fresno and San Francisco, and screened for over 2420 chemicals using LC-QTOF/MS. We matched San Francisco participants to Fresno participants (N = 150) and compared detection frequencies. Twenty-six Fresno participants wore silicone wristbands evaluated for over 1500 chemicals using quantitative chemical analysis. We assessed whether living in tracts with higher levels of pollution according to CalEnviroScreen correlated with higher numbers of chemicals detected in sera.

RESULTS

We detected 2167 suspect chemical features across maternal and cord sera. The number of suspect chemical features was not different by city, but a higher number of suspect chemicals in cosmetics or fragrances was detected in the Fresno versus San Francisco participants' sera. We also found high levels of chemicals used in fragrances measured in the silicone wristbands. Fresno participants living in tracts with higher pesticide scores had higher numbers of suspect pesticides in their sera.

CONCLUSIONS

Multiple exposure-assessment approaches can identify exposure to many chemicals during pregnancy that have not been well-studied for health effects.

Monitoring long-term chemical exposome by characterizing the hair metabolome using a high-resolution mass spectrometry-based suspect screening approach

Hair has recently emerged as a biospecimen for characterizing the long-term chemical exposome in biomonitoring investigations spanning several months, as chemical compounds circulating in the bloodstream accumulate in hair. Although there has been interest in using human hair as a biospecimen for exposome studies, it has yet to be widely adopted compared to blood and urine. Here, we applied a high-resolution mass spectrometry (HRMS)-based suspect screening strategy to characterize the long-term chemical exposome in human hair. Hair samples were collected from 70 subjects and cut into 3 cm segments, which were then mixed to prepare pooled samples. The pooled hair samples underwent a sample preparation procedure, and the hair extracts were further analyzed using an HRMS-based suspect screening approach. An in-house chemical suspect list containing 1227 chemical entries from National Report on Human Exposure to Environmental Chemicals (Report) published by the U.S. CDC and the Exposome-Explorer 3.0 database developed by the WHO was subsequently used to screen and filter the suspect features against the HRMS dataset. Overall, we matched 587 suspect features in the HRMS dataset to 246 unique chemical formulas in the suspect list, and the structures of 167 chemicals were further identified through a fragmentation analysis. Among these, chemicals such as mono-2-ethylhexyl phthalate, methyl paraben, and 1-naphthol, which have been detected in the urine or blood for exposure assessment, were also identified in human hair. This suggests that hair reflects the accumulation of environmental compounds to which an individual is exposed. Exposure to exogenous chemicals may exert adverse effects on cognitive function, and we discovered 15 chemicals in human hair that may contribute to the pathogenesis of Alzheimer's disease. This finding suggests that human hair may be a promising biospecimen for monitoring long-term exposure to multiple environmental chemicals and perturbations in endogenous chemicals in biomonitoring investigations.

Participatory environmental health research: A tool to explore the socio-exposome in a major european industrial zone

OBJECTIVES

We show that participatory research approaches can be a useful tool across disciplines and data collection methods to explore the socio-exposome near one of the largest industrial harbors in Europe. We analyzed resident involvement in each project and their capacity to affect structural changes.

METHODS

Longitudinal participatory environmental monitoring studies on lichens, petunias, aquatic systems and groundwater were conducted under the program VOCE (Volunteers for the Citizens' Observation of the Environment), which mobilized nearly 100 volunteers to collect and report data. A community-based participatory health survey, Fos EPSEAL was also carried out during the same period. We describe citizens' involvement in each study following Davis and Ramirez-Andreotta's (2021) 'best practice' grid. We also use residents' insights to refine understanding of the socio-exposome.

RESULTS

The region is significantly impacted by industrial pollution and fenceline communities are disproportionately exposed. The community-based participatory health survey documented negative health outcomes among the residents, including a higher prevalence of chronic symptoms and diabetes (e.g., 11.9%) in the Fos-Berre Lagoon region than in other communities. This methodology shows the benefits of the co-production of knowledge in environmental health: not only does it enable epistemological transformations favorable to the vulnerable population, but it also triggered public action (i.e., media and public authorities' attention leading to official expertise reports, filing of collective complaints before the courts).

CONCLUSION

This body of multiple participatory research studies over time is a useful approach to better understand the socio-exposome and health issues in an industrial zone.

Advancing Exposomic Research in Prenatal Respiratory Disease Programming

Disease programming reflects interactions between genes and the environment. Unlike the genome, environmental exposures and our response to exposures change over time. Starting in utero, the respiratory system and related processes develop sequentially in a carefully timed cascade, thus effects depend on both exposure dose and timing. A multitude of environmental and microbial exposures influence respiratory disease programming. Effects result from toxin-induced shifts in a host of molecular, cellular, and physiologic states and their interacting systems. Moreover, pregnant women and the developing child are not exposed to a single toxin, but to complex mixtures.

A geospatial modeling approach to quantifying the risk of exposure to environmental chemical mixtures via a common molecular target

In the real world, individuals are exposed to chemicals from sources that vary over space and time. However, traditional risk assessments based on in vivo animal studies typically use a chemical-by-chemical approach and apical disease endpoints. New approach methodologies (NAMs) in toxicology, such as in vitro high-throughput (HTS) assays generated in Tox21 and ToxCast, can more readily provide mechanistic chemical hazard information for chemicals with no existing data than in vivo methods. In this paper, we establish a workflow to assess the joint action of 41 modeled ambient chemical exposures in the air from the USA-wide National Air Toxics Assessment by integrating human exposures with hazard data from curated HTS (cHTS) assays to identify counties where exposure to the local chemical mixture may perturb a common biological target. We exemplify this proof-of-concept using CYP1A1 mRNA up-regulation. We first estimate internal exposure and then convert the inhaled concentration to a steady state plasma concentration using physiologically based toxicokinetic modeling parameterized with county-specific information on ages and body weights. We then use the estimated blood plasma concentration and the concentration-response curve from the in vitro cHTS assay to determine the chemical-specific effects of the mixture components. Three mixture modeling methods were used to estimate the joint effect from exposure to the chemical mixture on the activity levels, which were geospatially mapped. Finally, a Monte Carlo uncertainty analysis was performed to quantify the influence of each parameter on the combined effects. This workflow demonstrates how NAMs can be used to predict early-stage biological perturbations that can lead to adverse health outcomes that result from exposure to chemical mixtures. As a result, this work will advance mixture risk assessment and other early events in the effects of chemicals.

Developing human biomonitoring as a 21st century toolbox within the European exposure science strategy 2020-2030

Human biomonitoring (HBM) is a crucial approach for exposure assessment, as emphasised in the European Commission's Chemicals Strategy for Sustainability (CSS). HBM can help to improve chemical policies in five major key areas: (1) assessing internal and aggregate exposure in different target populations; 2) assessing exposure to chemicals across life stages; (3) assessing combined exposure to multiple chemicals (mixtures); (4) bridging regulatory silos on aggregate exposure; and (5) enhancing the effectiveness of risk management measures. In this strategy paper we propose a vision and a strategy for the use of HBM in chemical regulations and public health policy in Europe and beyond. We outline six strategic objectives and a roadmap to further strengthen HBM approaches and increase their implementation in the regulatory risk assessment of chemicals to enhance our understanding of exposure and health impacts, enabling timely and targeted policy interventions and risk management. These strategic objectives are: 1) further development of sampling strategies and sample preparation; 2) further development of chemical-analytical HBM methods; 3) improving harmonisation throughout the HBM research life cycle; 4) further development of quality control / quality assurance throughout the HBM research life cycle; 5) obtain sustained funding and reinforcement by legislation; and 6) extend target-specific communication with scientists, policymakers, citizens and other stakeholders. HBM approaches are essential in risk assessment to address scientific, regulatory and societal challenges. HBM requires full and strong support from the scientific and regulatory domain to reach its full potential in public and occupational health assessment and in regulatory decision-making.

Climate change, human health, and the exposome: Utilizing OMIC technologies to navigate an era of uncertainty

Climate change is an anthropogenic phenomenon that is alarming scientists and non-scientists alike. The emission of greenhouse gases is causing the temperature of the earth to rise and this increase is accompanied by a multitude of climate change-induced environmental exposures with potential health impacts. Tracking human exposure has been a major research interest of scientists worldwide. This has led to the development of exposome studies that examine internal and external individual exposures over their lifetime and correlate them to health. The monitoring of health has also benefited from significant technological advances in the field of "omics" technologies that analyze physiological changes on the nucleic acid, protein, and metabolism levels, among others. In this review, we discuss various climate change-induced environmental exposures and their potential health implications. We also highlight the potential integration of the technological advancements in the fields of exposome tracking, climate monitoring, and omics technologies shedding light on important questions that need to be answered.

LC-HRMS based method for suspect/non-targeted screening for biomarkers of chemical exposure in human urine

Every day we are exposed to a cocktail of anthropogenic compounds many of which are biologically active and capable of inducing negative effects. The simplest way to monitor contaminants in a population is via human biomonitoring (HBM), however conventional targeted approaches require foreknowledge of chemicals of concern, often have compound specific extractions and provide information only for those compounds. This study developed an extraction process for human biomarkers of interest (BoE) in urine that is less compound specific. Combining this with an ultra-high resolution mass spectrometer capable of operating in full scan, and a suspect and non-targeted analysis (SS/NTA) approach, this method provides a more holistic characterization of human exposure. Sample preparation development was based on enzymatically hydrolysed urine spiked with 34 native standards and extracted by solid-phase extraction (SPE). HRMS data was processed by MzMine2 and 80% of standards were identified in the final data matrix using typical NTA data processing procedures.

Validated single urinary assay designed for exposomic multi-class biomarkers of common environmental exposures

Epidemiological studies often call for analytical methods that use a small biospecimen volume to quantify trace level exposures to environmental chemical mixtures. Currently, as many as 150 polar metabolites of environmental chemicals have been found in urine. Therefore, we developed a multi-class method for quantitation of biomarkers in urine. A single sample preparation followed by three LC injections was optimized in a proof-of-approach for a multi-class method. The assay was validated to quantify 50 biomarkers of exposure in urine, belonging to 7 chemical classes and 16 sub-classes. The classes represent metabolites of 12 personal care and consumer product chemicals (PCPs), 5 polycyclic aromatic hydrocarbons (PAHs), 5 organophosphate flame retardants (OPFRs), 18 pesticides, 5 volatile organic compounds (VOCs), 4 tobacco alkaloids, and 1 drug of abuse. Human urine (0.2 mL) was spiked with isotope-labeled internal standards, enzymatically deconjugated, extracted by solid-phase extraction, and analyzed using high-performance liquid chromatography-tandem mass spectrometry. The methanol eluate from the cleanup was split in half and the first half analyzed for PCPs, PAH, and OPFR on a Betasil C18 column; and pesticides and VOC on a Hypersil Gold AQ column. The second half was analyzed for tobacco smoke metabolites and a drug of abuse on a Synergi Polar RP column. Limits of detection ranged from 0.01 to 1.0 ng/mL of urine, with the majority ≤0.5 ng/mL (42/50). Analytical precision, estimated as relative standard deviation of intra- and inter-batch uncertainty, variabilities, was <20%. Extraction recoveries ranged from 83 to 109%. Results from the optimized multi-class method were qualified in formal international proficiency testing programs. Further method customization options were explored and method expansion was demonstrated by inclusion of up to 101 analytes of endo- and exogenous chemicals. This exposome-scale assay is being used for population studies with savings of assay costs and biospecimens, providing both quantitative results and the discovery of unexpected exposures.

Addressing Exposome: An Innovative Approach to Environmental Determinants in Pediatric Respiratory Health

Developmental age is particularly vulnerable to impacts of environmental exposures. Until recent years, the field of environment and child health has predominantly relied on the study of single exposure-health effect relationships. The exposome is an emerging concept in epidemiology, encompassing the totality of the exposures experienced by an individual throughout life and their changes over time. This innovative approach provides a risk profile instead of individual predictors. Exposome research may contribute to better understand the complex relationships between environmental exposures and childhood respiratory health, in order to implement prevention strategies and mitigate adverse health outcomes across the life span. Indeed, an accurate assessment of the exposome needs several measurements as well as different technologies. High-throughput "omics" technologies may be promising tools to integrate a wide range of exposures. However, analyzing large and complex datasets requires the development of advanced statistical tools. This narrative review summarizes the current knowledge on exposome-based approaches in pediatric respiratory health. Further, it explores practical implementation, associated evidence gaps, research limitations and future research perspectives.

Next-generation biomonitoring of the early-life chemical exposome in neonatal and infant development

Exposure to synthetic and natural chemicals is a major environmental risk factor in the etiology of many chronic diseases. Investigating complex co-exposures is necessary for a holistic assessment in exposome-wide association studies. In this work, a sensitive liquid chromatography-tandem mass spectrometry approach was developed and validated. The assay enables the analysis of more than 80 highly-diverse xenobiotics in urine, serum/plasma, and breast milk; with detection limits generally in the pg-ng mL-1 range. In plasma of extremely-premature infants, 27 xenobiotics are identified; including contamination with plasticizers, perfluorinated alkylated substances and parabens. In breast milk samples collected longitudinally over the first 211 days post-partum, 29 analytes are detected, including pyrrolizidine- and tropane alkaloids which have not been identified in this matrix before. A preliminary estimation of daily toxicant intake via breast milk is conducted. In conclusion, we observe significant early-life co-exposure to multiple toxicants, and demonstrate the method's applicability for large-scale exposomics-type cohort studies.

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

Let's Get Back to Normal? COVID-19 and the Logic of Cure

The COVID-19 pandemic has inversed certainties of absolutes of cure in everyday life but paradoxically this has occurred during a time when novel scientific advancements seem to herald a new frontier of cures for rare diseases, chronic conditions, disabilities and viruses that were previously incurable. In this paper, I illustrate the development of a logic of cure by first of all noting a lacuna in the medical sociological and anthropological literature, where although a lot of empirical research and theoretical work to understand cure has been undertaken, there has been no sociology or anthropology of cure. Using three case studies, I examine what they reveal about the logic of cure. Firstly, I argue that there is a development of a bioethics of cure in reactions of disability community and disabled people to care as cure during the COVID-19 pandemic. The second case-study focuses on understanding limitations of vaccines and how people react against such indeterminancies of loss of absolutes of cure. Lastly, the final case study describes how while there are cures, for example, for rare genetic conditions, they are often initially curated with long-term cost-benefit analysis for the Global North. In conclusion, it is found that many of the developments within sociology and anthropology are missing from a logic of cure and that a new theory of cure has to develop.

An exposomic framework to uncover environmental drivers of aging

The exposome, the environmental complement of the genome, is an omics level characterization of an individual’s exposures. There is growing interest in uncovering the role of the environment in human health using an exposomic framework that provides a systematic and unbiased analysis of the non-genetic drivers of health and disease. Many environmental toxicants are associated with molecular hallmarks of aging. An exposomic framework has potential to advance understanding of these associations and how modifications to the environment can promote healthy aging in the population. However, few studies have used this framework to study biological aging. We provide an overview of approaches and challenges in using an exposomic framework to investigate environmental drivers of aging. While capturing exposures over a life course is a daunting and expensive task, the use of historical data can be a practical way to approach this research.

Urinary concentrations of bisphenol analogues in the south of China population and their contribution to the per capital mass loads in wastewater

Bisphenol analogues (BPs) are heavily used and negatively affect the health of human beings, however, there is little knowledge regarding human exposure to BPs other than BPA. This study aims to assess human exposure to BPs through investigating pooled urine and wastewater samples. Twenty-four pooled urine samples were prepared from 960 specimens (classified by age and gender). Wastewater samples were collected from six major wastewater treatment plants (WWTPs) in Guangzhou, South of China. BPA, BPS, and BPAF were widely detected in urine samples, with a median concentration of 0.96, 0.42, and 0.15 μg/L, respectively. Median urinary levels of BPA and BPS were higher in males than females (p > 0.05). In addition, BPA and BPS urinary levels in young adults (15-30 years old) were greater than those in children (0-15 years old) (p > 0.05). Nevertheless, most of the BPs were detected in wastewater samples, of which BPA and BPS were predominant BPs, with a median concentration of 1.0 and 0.29 μg/L. The average per capital mass loads of ΣBPs on the weekdays of mix typed WWTP was much higher than those of the weekends. Nonetheless, the average loads of ΣBPs on the weekdays of domestic WWTP was slightly lower than those of the weekends. This indicated that important sources of BPs might include industrial wastewater and household cleaning products. Urinary BPA, BPS, and BPAF accounted for less than 5% per capital mass loads in wastewater, suggesting that much of the BPA, BPS, and BPAF in municipal wastewater originate non-human excretion. Hence, the wastewater-based epidemiology (WBE) approach based on parent compounds is not available for assessing human exposure to BPs, neither for other industrial chemicals with diverse sources in municipal wastewater. These results contributes to the development of an efficient surveillance system which can provide insight in the trends of human exposure of BPs.

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.

Exposure study on susceptible people - SPES: An integrative biomonitoring approach

BACKGROUND

The evaluation of environmental exposure risk requires a global analysis of pollution phenomena, including biological effects and potentially correlated clinical outcomes in susceptible populations. Although human biomonitoring plays a fundamental role in assessing the degree of contamination, it is not effective alone in identifying a direct link between exposure, biomolecular effects and outcomes on target organisms. While toxicogenomics and epidemiology are mainly focused on the investigation of molecular reactions and clinical outcomes, the monitoring of environmental matrices works independently to characterize the territorial distribution of toxic compounds, without proving any correlated health risk for residents.

OBJECTIVES

We propose a new biomonitoring model based on a whole systemic analytical evaluation of environmental context. The paradigm of the method consists of identifying the sources of pollution, the migration pathways of those pollutants and their effects on target organisms. By means of this innovative, holistic epidemiological approach, we included healthy human subjects in a cohort to identify potential risks of exposure and predict possible correlated clinical outcomes. 4205 residents of the Campania region were enrolled in the "SPES" biomonitoring study, which especially focused on the areas dubbed "Land of Fires" in the recent decades.

DISCUSSION

The analysis of environmental exposure risk suffers the lack of data integration from various science fields, and this comes down to a limited point of view and a limited knowledge of phenomena. In implementing our model, we first constructed an analytical picture of the Real-world situation. We next conducted a comparative risk assessment, in order to identify possible correlations between pollution and health within a holistic view.

CONCLUSION

This type of research activities aims to support the implementation of public health interventions and to become a reference model in the evaluation of the risk of exposure to environmental pollutants.

FLEXiGUT: Rationale for exposomics associations with chronic low-grade gut inflammation

FLEXiGUT is the first large-scale exposomics study focused on chronic low-grade inflammation. It aims to characterize human life course environmental exposure to assess and validate its impact on gut inflammation and related biological processes and diseases. The cumulative influences of environmental and food contaminants throughout the lifespan on certain biological responses related to chronic gut inflammation will be investigated in two Flemish prospective cohorts, namely the "ENVIRONAGE birth cohort", which provides follow-up from gestation to early childhood, and the "Flemish Gut Flora Project longitudinal cohort", a cohort of adults. The exposome will be characterised through biomonitoring of legacy and emerging contaminants, mycotoxins and markers of air pollution, by analysing the available metadata on nutrition, location and activity, and by applying state-of-the-art -omics techniques, including metagenomics, metabolomics and DNA adductomics, as well as the assessment of telomere length and measurement of inflammatory markers, to encompass both exposure and effect. Associations between exposures and health outcomes will be uncovered using an integrated -omics data analysis framework comprising data exploration, pre-processing, dimensionality reduction and data mining, combined with machine learning-based pathway analysis approaches. This is expected to lead to a more profound insight in mechanisms underlying disease progression (e.g. metabolic disorders, food allergies, gastrointestinal cancers) and/or accelerated biological ageing.

Implementing in vitro bioactivity data to modernize priority setting of chemical inventories

Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioac­tivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioac­tivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.

Emerging investigator series: the role of chemical properties in human exposure to environmental chemicals

One of the ultimate goals of environmental exposure science is to mechanistically understand how chemical properties and human behavior interactively determine human exposure to the wide spectrum of chemicals present in the environment. This comprehensive review assembles state-of-the-art knowledge of the role of partitioning, dissociation, mass transfer, and reactive properties in human contact with and absorption of organic chemicals via oral, dermal, and respiratory routes. Existing studies have revealed that chemicals with different properties vary greatly in mass distribution and occurrence among multiple exposure media, resulting in distinct patterns of human intake from the environment. On the other hand, these chemicals encounter different levels of resistance in the passage of intestinal, dermal, and pulmonary absorption barriers and demonstrate different levels of bioavailability, due to the selectivity of biochemical, anatomical and physiological structures of these absorption barriers. Moving forward, the research community needs to gain more in-depth mechanistic insights into the complex processes in human exposure, advance the technique to better characterize and predict chemical properties, generate and leverage experimental data for a more diverse range of chemicals, and describe better the interactions between chemical properties and human behavior.

The exposome in practice: an exploratory panel study of biomarkers of air pollutant exposure in Chinese people aged 60-69 years (China BAPE Study)

The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60-69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques.

Network biology approach to human tissue-specific chemical exposome

Human exposure to environmental chemicals is a major contributor to the global disease burden. To characterize the external exposome it is important to assess its chemical components and to study their impact on human health. Biomonitoring studies measure the body burden of environmental chemicals detected in biospecimens from a wide range of the population. The detection of these chemicals in biospecimens (and, hence, human tissues) is considered an important biomarker of human exposure. However, there is no readily available resource that compiles such exposure data for human tissues from published literature, and no studies that explore the patterns in the associations between tissue-specific exposures and human diseases. We present Human Tissue-specific Exposome Atlas (TExAs), a compilation of 380 environmental chemicals detected across 27 human tissues. TExAs is accessible via a user friendly webserver: https://cb.imsc.res.in/texas. We compare the chemicals in TExAs with 55 global chemical regulations, guidelines, and inventories, which represent several categories of the external exposome of humans. Further to understand the potential implications on human health of chemicals detected across human tissues, we employ a network biology approach and explore possible chemical exposure-disease associations. Ensuing analyses reveal the possibilities of disease comorbidities and demonstrate the application of network biology in unraveling complex disease associations due to chemical exposure.

[Chemical exposome and non-targeted approaches]

The technological advances in high-resolution mass spectrometry (HRMS), associated with the development of bioinformatics tools, allows the simultaneous detection of tens of thousands of chemical signals in biological matrices, including exogenous (i.e. xenobiotics) and endogenous molecules. These novel approaches based on HRMS, called "non-targeted" approaches, provide a unique opportunity to capture exposures to a wide range of chemicals (i.e. the internal chemical exposome) in populations, and to better understand the links between chemical exposures and the occurrence of chronic diseases.

Software Application Profile: exposomeShiny—a toolbox for exposome data analysis

Motivation

Studying the role of the exposome in human health and its impact on different omic layers requires advanced statistical methods. Many of these methods are implemented in different R and Bioconductor packages, but their use may require strong expertise in R, in writing pipelines and in using new R classes which may not be familiar to non-advanced users. ExposomeShiny provides a bridge between researchers and most of the state-of-the-art exposome analysis methodologies, without the need of advanced programming skills.

Implementation

ExposomeShiny is a standalone web application implemented in R. It is available as source files and can be installed in any server or computer avoiding problems with data confidentiality. It is executed in RStudio which opens a browser window with the web application.

General features

The presented implementation allows the conduct of: (i) data pre-processing: normalization and missing imputation (including limit of detection); (ii) descriptive analysis; (iii) exposome principal component analysis (PCA) and hierarchical clustering; (iv) exposome-wide association studies (ExWAS) and variable selection ExWAS; (v) omic data integration by single association and multi-omic analyses; and (vi) post-exposome data analyses to gain biological insight for the exposures, genes or using the Comparative Toxicogenomics Database (CTD) and pathway analysis.

Availability

The exposomeShiny source code is freely available on Github at [https://github.com/isglobal-brge/exposomeShiny], Git tag v1.4. The software is also available as a Docker image [https://hub.docker.com/r/brgelab/exposome-shiny], tag v1.4. A user guide with information about the analysis methodologies as well as information on how to use exposomeShiny is freely hosted at [https://isglobal-brge.github.io/exposome_bookdown/].

Identification of chemicals of emerging concern in urine of Flemish adolescents using a new suspect screening workflow for LC-QTOF-MS

An essential step in human biomonitoring or molecular epidemiology programs is to estimate human exposure to environmental chemicals. Despite significant progress in the capabilities of analytical methods, the number of pollutants and their metabolites keeps increasing continuously. Some of these relatively unknown chemicals of emerging concern (CECs) may pose significant health risks to humans and biota, but remain virtually undetected in traditional HBM-studies. Non-target and suspect screening techniques based on high-resolution mass spectrometry (HRMS) perform the detection and identification of compounds without any a priori compound selection or chemical information and provide a more holistic overview of human exposure. In this study, 50 urine samples (25 female and 25 male) from a larger cohort of the Flemish Environment and Health Study (FLEHS IV, 2016-2020) have been submitted to suspect screening analysis, with the aim of detecting and identifying new CECs. For this purpose, an analytical method has been developed, optimised and evaluated in terms of analytical performance. Satisfactory results were obtained in terms of reproducibility, sensitivity and quality control. Data-mining was performed through the combination of two different workflows. The use of two complementary workflows enhanced the number of identified compounds. As a result, 45 CECs have been identified with a level of confidence ranged between 3 and 1. Most of the identified compounds were metabolisation products, many of which were currently not included in the targeted measurements of FLEHS IV. The identified chemicals and metabolites could be used as candidate biomarkers of exposure in future studies. Overall, the newly developed suspect screening workflow of this pilot study provided complementary and promising results for future HBM-programs.

Advancing tools for human early lifecourse exposome research and translation (ATHLETE): Project overview

Early life stages are vulnerable to environmental hazards and present important windows of opportunity for lifelong disease prevention. This makes early life a relevant starting point for exposome studies. The Advancing Tools for Human Early Lifecourse Exposome Research and Translation (ATHLETE) project aims to develop a toolbox of exposome tools and a Europe-wide exposome cohort that will be used to systematically quantify the effects of a wide range of community- and individual-level environmental risk factors on mental, cardiometabolic, and respiratory health outcomes and associated biological pathways, longitudinally from early pregnancy through to adolescence. Exposome tool and data development include as follows: (1) a findable, accessible, interoperable, reusable (FAIR) data infrastructure for early life exposome cohort data, including 16 prospective birth cohorts in 11 European countries; (2) targeted and nontargeted approaches to measure a wide range of environmental exposures (urban, chemical, physical, behavioral, social); (3) advanced statistical and toxicological strategies to analyze complex multidimensional exposome data; (4) estimation of associations between the exposome and early organ development, health trajectories, and biological (metagenomic, metabolomic, epigenetic, aging, and stress) pathways; (5) intervention strategies to improve early life urban and chemical exposomes, co-produced with local communities; and (6) child health impacts and associated costs related to the exposome. Data, tools, and results will be assembled in an openly accessible toolbox, which will provide great opportunities for researchers, policymakers, and other stakeholders, beyond the duration of the project. ATHLETE's results will help to better understand and prevent health damage from environmental exposures and their mixtures from the earliest parts of the life course onward.

Lead uptake into calcified and keratinized compartments of horns from a convenience sample of lead-dosed goats

Hair and/or nail analyses are sometimes used in biomonitoring studies due to the convenience of sample collection, storage, and transport, as well as the potential to assess past exposures to toxic metals, such as lead (Pb). However, the validity of Pb measurements in these keratinized matrices as biomarkers of absorbed dose remains unclear. The aim of this study was to examine the uptake of Pb into horns harvested postmortem from 11 goats that received a cumulative oral dose of up to 151 g Pb acetate over a period of 1-11 years as part of a long-term blood Pb proficiency testing program. Uptake of Pb into keratinized horn was compared to the corresponding underlying bony horn core, which, as part of the bone compartment, provided a measure of absorbed Pb dose. Two complementary analytical techniques were used to assess Pb: X-Ray Fluorescence (XRF) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Detectable amounts of Pb were found in all keratinized horn samples (0.45-6.6 µg/g) and in all but one bony core sample (1.4-68 µg/g). In both bony core and keratinized horn samples, Pb accumulation increased with dose over a low-to-moderate cumulative-dose interval, consistent with previous observations, but plateaued at higher doses. Significant associations were observed between Pb in keratinized horn and bony core samples particularly with XRF measurements, which represent the surface bone compartment. These findings provide evidence that Pb is excreted in keratinized tissues but reflects only a small fraction of the absorbed Pb dose, likely transferred from underlying bone tissue.

Monitoring Human Exposure to Organophosphate Esters: Comparing Silicone Wristbands with Spot Urine Samples as Predictors of Internal Dose

Silicone wristbands present a noninvasive exposure assessment tool and an alternative to traditional biomonitoring; however, questions about their utility remain as validation studies are limited. We sought to determine if wristbands provide quantitative estimates of internal organophosphate ester (OPE) exposure. We evaluated internal dose by measuring metabolite masses excreted in 24-hour urine samples collected over five days among ten adults. We compared internal dose to OPE concentrations in paired wristbands worn during collection and, as a comparison, evaluated metabolite levels in spot urine samples. Three of six OPE metabolites evaluated were detected in >98% of urine samples, and 24 of 34 assessed OPEs were detected in at least one wristband. OPE uptake in wristbands was linear over time (range=0.54-61.8 ng/g/day). OPE concentrations in spot urine and wristbands were not correlated with total diphenyl phosphate (DPHP) excreted in urine, which may be due to the range of possible DPHP parent compounds or dietary exposure. However, for tris-(1,3-dichloro-2-propyl)phosphate (TDCIPP) and tris-(2-chloroisopropyl)phosphate (TCIPP), wristbands and spot urine samples were both moderately to strongly correlated with internal dose (all r_s>0.56 and p<0.1), suggesting both perform well as integrated exposure estimates. Given the potential advantages of silicone wristbands, further studies investigating additional compounds are warranted.

Three genetic-environmental networks for human personality

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.

[Recent advances in chemical derivatization-based chromatography-mass spectrometry methods for analysis of aldehyde biomarkers]

Human exposure to chemical pollutants in the environment can cause a variety of diseases, including cancer, diabetes, cardiovascular disease, and neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, etc.). Exogenous and environmental pollutant exposure-induced endogenous aldehydes are highly reactive electrophilic compounds that can form covalently modified products with a variety of important biological molecules in the human body, thus inducing toxic effects. Exposome research has become a hotspot since it was first proposed in 2005. Exposure studies can map the complex relationships between biomarkers and disease risk. Therefore, the measurable and characteristic changes of all biomarkers together constitute a key basis for exposome research. Aldehydes are among the main components of chemical exposure. Because of the physical and chemical properties of aldehydes and the existence of multiple matrix interferences in the samples, it is particularly difficult to analyze and characterize them. The analysis and detection methods for aldehydes mainly include sensing analysis, electrochemical methods, fluorescence imaging, chromatography, mass spectrometry (MS), and chromatography-MS. Analytical techniques based on gas chromatography-MS (GC-MS) and liquid chromatography-MS (LC-MS) have emerged as the main methods for chemical exposome research. Chemical derivatization, especially stable isotope labeling derivatization (also known as chemical isotope labeling) combined with LC-MS analytical techniques, can help circumvent the problems encountered in targeted and non-targeted metabolome and exposome analysis. The combination of chemical derivatization with chromatography-MS is one of the most important solutions for the accurate analysis of aldehydes in complex samples. Over the past five years, the development and application of chromatography-MS analytical methods based on chemical derivatization have become key topics in aldehyde analysis. This paper summarizes and reviews the latest progress in GC-MS and LC-MS methods based on chemical derivatization (2015-2020). The review focuses on analytical method development for aldehyde exposure biomarkers in bio-matrices (blood, urine, saliva, biological tissue, etc.). Various derivatization reagents for labeling small-molecule aldehydes, qualitative/quantitative analytical methods and their application value, advantages/disadvantages of different analytical methods for aldehyde exposure biomarkers, and future development trends are also included. The manuscript contents may aid the integrated development of exposome, metabolomics, and lipidomics, as well as research on the environment, ecology, and health. To clarify the complex actions of exogenous and endogenous aldehydes in physiological and pathological events, it is necessary to improve the analysis and characterization techniques and tools for studying the "aldehydome." With the development and application of sophisticated mass spectrometers, advances in high-performance chromatographic separation and bioinformatics, and advent of single-cell analysis and MS imaging, future aldehyde exposome analytical methods will have higher sensitivity and throughput. This in turn would be more useful for screening and identifying unknown aldehyde compounds and discovering new exposome biomarkers.

Development of a strategic approach for comprehensive detection of organophosphate pesticide metabolites in urine: Extrapolation of cadusafos and prothiofos metabolomics data of mice to humans

Objectives

The comprehensive detection of environmental chemicals in biospecimens, an indispensable task in exposome research, is advancing. This study aimed to develop an exposomic approach to identify urinary metabolites of organophosphate (OP) pesticides, specifically cadusafos and prothiofos metabolites, as an example chemical group, using an original metabolome dataset generated from animal experiments.

Methods

Urine samples from 73 university students were analyzed using liquid chromatography–high‐resolution mass spectrometry. The metabolome data, including the exact masses, retention time (t_R), and tandem mass spectra obtained from the human samples, were compared with the existing reference databases and with our original metabolome dataset for cadusafos and prothiofos, which was produced from mice to whom two doses of these OPs were orally administered.

Results

Using the existing databases, one chromatographic peak was annotated as 2,4‐dichlorophenol, which could be a prothiofos metabolite. Using our original dataset, one peak was annotated as a putative cadusafos metabolite and three peaks as putative prothiofos metabolites. Of these, all three peaks suggestive of prothiofos metabolites, 2,4‐dichlorophenol, 3,4,5‐trihydroxy‐6‐(2,4‐dichlorophenoxy) oxane‐2‐carboxylic acid, and (2,4‐dichlorophenyl) hydrogen sulfate were confirmed as authentic compounds by comparing their peak data with both the original dataset and peak data of the standard reagents. The putative cadusafos metabolite was identified as a level C compound (metabolite candidate with limited plausibility).

Conclusions

Our developed method successfully identified prothiofos metabolites that are usually not a target of biomonitoring studies. Our approach is extensively applicable to various environmental contaminants beyond OP pesticides.

Analytical aspects of meet-in-metabolite analysis for molecular pathway reconstitution from exposure to adverse outcome

To explore the etiology of diseases is one of the major goals in epidemiological study. Meet-in-metabolite analysis reconstitutes biomonitoring-based adverse outcome (AO) pathways from environmental exposure to a disease, in which the chemical exposome-related metabolism responses are transmitted to incur the AO-related metabolism phenotypes. However, the ongoing data-dependent acquisition of non-targeted biomonitoring by high-resolution mass spectrometry (HRMS) is biased against the low abundance molecules, which forms the major of molecular internal exposome, i.e., the totality of trace levels of environmental pollutants and/or their metabolites in human samples. The recent development of data-independent acquisition protocols for HRMS screening has opened new opportunities to enhance unbiased measurement of the extremely low abundance molecules, which can encompass a wide range of analytes and has been applied in metabolomics, DNA, and protein adductomics. In addition, computational MS for small molecules is urgently required for the top-down exposome databases. Although a holistic analysis of the exposome and endogenous metabolites is plausible, multiple and flexible strategies, instead of "putting one thing above all" are proposed.