Untargeted profiling of pesticide metabolites by LC-HRMS: an exposomics tool for human exposure evaluation

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

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

Meconium Concentrations of Pesticides and Risk of Hypospadias: A Case-Control Study in Brittany, France

BACKGROUND

Hypospadias is a male genital tract defect for which an increase in prevalence has been documented over the last few decades. A role for environmental risk factors is suspected, including prenatal exposure to pesticides.

OBJECTIVES

To study the risk of hypospadias in association with multiple pesticide measurements in meconium samples.

METHODS

The Brittany Registry of Congenital Anomalies (France) conducted a case-control study between 2012 and 2018. Cases were hypospadias, ascertained by a pediatrician and a pediatric surgeon, excluding genetic conditions, following European Surveillance of Congenital Anomalies guidelines (N = 69). Controls (N = 135) were two male infants without congenital anomaly born after each case in the same maternity unit. Mothers in the maternity units completed a self-administered questionnaire, we collected medical data from hospital records, and medical staff collected meconium samples. We performed chemical analysis of 38 pesticides (parent compound and/or metabolite) by UHPLC/MS/MS following strict quality assurance/quality control criteria and blind to case-control status. We carried out logistic regression accounting for frequency-matching variables and major risk factors.

RESULTS

Among the 38 pesticides measured, 16 (42%) were never detected in the meconium samples, 18 (47%) were in <5% of samples, and 4 (11%) in ≥5% of the samples. We observed an association between the detection of fenitrothion in meconium and the risk of hypospadias (OR = 2.6 [1.0-6.3] with n cases = 13, n controls = 21), but not the other pesticides.

CONCLUSIONS

Our small study provides a robust assessment of fetal exposure. Fenitrothion's established antiandrogenic activities provide biologic plausibility for our observations. Further studies are needed to confirm this hypothesis.

Comprehensive profiling and semi-quantification of exogenous chemicals in human urine using HRMS-based strategies

Chemicals infiltrate our daily experiences through multiple exposure pathways. Human biomonitoring (HBM) is routinely used to comprehensively understand these chemical interactions. Historically, HBM depended on targeted screening methods limited to a relatively small set of chemicals with triple quadrupole instruments typically. However, recent advances in high-resolution mass spectrometry (HRMS) have facilitated the use of broad-scope target, suspect, and non-target strategies, enhancing chemical exposome characterization within acceptable detection limits. Despite these advancements, establishing robust and efficient sample treatment protocols is still essential for trustworthy broad-range chemical analysis. This study sought to validate a methodology leveraging HRMS-based strategies for accurate profiling of exogenous chemicals and related metabolites in urine samples. We evaluated five extraction protocols, each encompassing various chemical classes, such as pharmaceuticals, plastic additives, personal care products, and pesticides, in terms of their extraction recoveries, linearity, matrix effect, sensitivity, and reproducibility. The most effective protocol was extensively validated and subsequently applied to 10 real human urine samples using wide-scope target analysis encompassing over 2000 chemicals. We successfully identified and semi-quantified a total of 36 chemicals using an ionization efficiency-based model, affirming the methodology's robust performance. Notably, our results dismissed the need for a deconjugation step, a typically labor-intensive and time-consuming process.

Development and Validation of a New UFLC-MS/MS Method for the Detection of Organophosphate Pesticide Metabolites in Urine

To monitor human exposure to pesticides, experts commonly measure their metabolites in urine, particularly dialkyl phosphates (DAPs), which include diethyl phosphate (DEP), Diethyl thiophosphate (DETP), diethyl dithiophosphate (DEDTP), dimethyl phosphate (DMP), dimethyl thiophosphate (DMTP) and dimethyl dithiophosphate (DMDTP)to monitor the metabolites of organophosphates. These DAP metabolites are a urinary biomarker for assessing pesticide exposure and potential health risks. This study presented a new screening method combining ultrafast liquid chromatography with tandem mass spectrometry (UFLC-MS/MS) to detect six DAP metabolites in human urine. The study also compared standard sample extraction methods, namely, liquid-liquid extraction (LLE); quick, easy, cheap, effective, ruggedand safe (QuEChERS); and lyophilization. After a comprehensive analysis of the methods used to extract the analytes, including recovery rate, repeatability and reproducibility, the liquid-liquid extraction (LLE) method was found to be the best. It had a high recovery rate, was easy to handle, required less sample volume and had a short extraction time. Therefore, the LLE method was chosen for further analysis. The results showed excellent performance with high recoveries between 93% and 102%, precise repeatability (RSD) between 0.62% and 5.46% and acceptable reproducibility values (RSD) between 0.80% and 11.33%. The method also had limits of detection (LOD) ranging from 0.0201 ng/mL to 0.0697 ng/mL and limits of quantification (LOQ) ranging from 0.0609 ng/mL to 0.2112 ng/mL. Furthermore, the UFLC-MS/MS method was validated based on the SANTE guidance and successfully analyzed 150 urine samples from farmers and non-farmers. This validated method proved useful for biomonitoring studies focusing on OP pesticide exposure. It offers several advantages, such as a reduced need for samples, chemicals and materials, and a shorter analysis time. The method is sensitive and selective in detecting metabolites in human urine, making it a valuable approach for the practical and efficient assessment of pesticide exposure.

Optimization of Parameters for ROI Data Compression for Nontargeted Analyses Using LC-HRMS

Nontargeted analyses of low-concentration analytes in the information-rich data collected by liquid chromatography with high-resolution mass spectrometry detection can be challenging to accomplish in an efficient and comprehensive manner. The aim of this study is to demonstrate a workflow involving targeted parameter optimization for entire chromatograms using region of interest (ROI) data compression uncoupled from a subsequent tile-based Fisher ratio (F-ratio) analysis, a supervised discovery-based method, for the discovery of low-concentration analytes. Soil samples spiked with 18 pesticides at nominal concentrations ranging from 0.1 to 50 ppb for a total of six sample classes served as challenging samples to demonstrate the overall workflow. Optimization of two parameters proved to be the most critical for ROI data compression: the signal threshold parameter and the admissible mass deviation parameter. The parameter optimization method workflow we introduce is based upon spiking known analytes into a representative sample and determining the number of detectable spikes and the Δppm for various combinations of the signal threshold and admissible mass deviation, where Δppm is the absolute value of the difference between the theoretical m/z and the ROI m/z. Once optimal parameters are determined providing the lowest average Δppm and the greatest number of detectable analytes, the optimized parameters can be utilized for the intended analysis. Herein, tile-based F-ratio analysis was performed on the ROI compressed data of all spiked soil samples first by applying ROI parameters recommended in the literature, referred to herein as the initial ROI parameters, and finally by the combination of the two optimized parameters. Using the initial ROI parameters, three pesticides were discovered, whereas all 18 spiked pesticides were discovered by optimizing both ROI parameters.

Characterization of multiple pesticide exposure in pregnant women in Brittany, France

BACKGROUND

France is one of the biggest users of pesticides in Europe and exposure to pesticides is a current concern, especially when it occurs early in life.

OBJECTIVE

The aim of this study was to assess the exposure of pregnant women in Brittany (western France) with high pesticide use.

METHODS

The pesticides were selected according to agricultural practices. Forty pesticides or metabolites were measured in urine samples collected in 2004 from 296 pregnant women in Brittany. The samples were analyzed by ultra-high performance liquid chromatography (UHPLC) coupled to high resolution mass spectrometry (HRMS) after a solid phase extraction (SPE) step.

RESULTS

Twenty seven pesticides were detected: the most frequently detected were the metabolites of organophosphate and pyrethroid insecticides (>89%) and several herbicides (phenoxypropionic acid derivatives and fluazifop >60%). Organophosphate and pyrethroid metabolites were also quantified in highest levels with maximum values of 590 μg/l for dimethylphosphate and 5.4 μg/l for 3- phenoxybenzoic acid. For the other parent compounds, such as prochloraz, bromoxynil and procymidone, they were also detected in 10-29% of the samples.

SIGNIFICANCE

Our results are consistent with pesticide use at the time of collection. The median concentrations of organophosphorus and pyrethroids were of the same order of magnitude as those reported in other countries. Herbicides and fungicides (fluazifop-p-butyl, bromoxynil, and prochloraz) were measured for the first time in this biomonitoring study, showing the usefulness of measuring widely used pesticides locally to improve knowledge of exposure.

IMPACT

The objective of this study is to assess the exposure of pregnant women in a region of Europe with high pesticide use.

A large scale multi-laboratory suspect screening of pesticide metabolites in human biomonitoring: From tentative annotations to verified occurrences

Within the Human Biomonitoring for Europe initiative (HBM4EU), a study to determine new biomarkers of exposure to pesticides and to assess exposure patterns was conducted. Human urine samples (N = 2,088) were collected from five European regions in two different seasons. The objective of the study was to identify pesticides and their metabolites in collected urine samples with a harmonized suspect screening approach based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) applied in five laboratories. A combined data processing workflow included comprehensive data reduction, correction of mass error and retention time (RT) drifts, isotopic pattern analysis, adduct and elemental composition annotation, finalized by a mining of the elemental compositions for possible annotations of pesticide metabolites. The obtained tentative annotations (n = 498) were used for acquiring representative data-dependent tandem mass spectra (MS2) and verified by spectral comparison to reference spectra generated from commercially available reference standards or produced through human liver S9 in vitro incubation experiments. 14 parent pesticides and 71 metabolites (including 16 glucuronide and 11 sulfate conjugates) were detected. Collectively these related to 46 unique pesticides. For the remaining tentative annotations either (i) no data-dependent MS2 spectra could be acquired, (ii) the spectral purity was too low for sufficient matching, or (iii) RTs indicated a wrong annotation, leaving potential for more pesticides and/or their metabolites being confirmed in further studies. Thus, the reported results are reflecting only a part of the possible pesticide exposure.

Metabolism of versicolorin A, a genotoxic precursor of aflatoxin B1: Characterization of metabolites using in vitro production of standards

The toxicity of mycotoxins containing bisfuranoid structures such as aflatoxin B1 (AFB1) depends largely on biotransformation processes. While the genotoxicity and mutagenicity of several bisfuranoid mycotoxins including AFB1 and sterigmatocystin have been linked to in vivo bioactivation of these molecules into reactive epoxide forms, the metabolites of genotoxic and mutagenic AFB1 precursor versicolorin A (VerA) have not yet been characterized. Because this molecule is not available commercially, our strategy was to produce a library of metabolites derived from the biotransformation of in-house purified VerA, following incubation with human liver S9 fractions, in presence of appropriate cofactors. The resulting chromatographic and mass-spectrometric data were used to identify VerA metabolites produced by intestinal cell lines as well as intestinal and liver tissues exposed ex vivo. In this way, we obtained a panel of metabolites suggesting the involvement of phase I (M + O) and phase II (glucuronide and sulfate metabolites) enzymes, the latter of which is implicated in the detoxification process. This first qualitative description of the metabolization products of VerA suggests bioactivation of the molecule into an epoxide form and provides qualitative analytic data to further conduct a precise metabolism study of VerA required for the risk assessment of this emerging mycotoxin.

Uncovering PFAS and Other Xenobiotics in the Dark Metabolome Using Ion Mobility Spectrometry, Mass Defect Analysis, and Machine Learning

The identification of xenobiotics in nontargeted metabolomic analyses is a vital step in understanding human exposure. Xenobiotic metabolism, transformation, excretion, and coexistence with other endogenous molecules, however, greatly complicate the interpretation of features detected in nontargeted studies. While mass spectrometry (MS)-based platforms are commonly used in metabolomic measurements, deconvoluting endogenous metabolites from xenobiotics is also often challenged by the lack of xenobiotic parent and metabolite standards as well as the numerous isomers possible for each small molecule m/z feature. Here, we evaluate a xenobiotic structural annotation workflow using ion mobility spectrometry coupled with MS (IMS-MS), mass defect filtering, and machine learning to uncover potential xenobiotic classes and species in large metabolomic feature lists. Xenobiotic classes examined included those of known high toxicities, including per- and polyfluoroalkyl substances (PFAS), polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and pesticides. Specifically, when the workflow was applied to identify PFAS in the NIST SRM 1957 and 909c human serum samples, it greatly reduced the hundreds of detected liquid chromatography (LC)-IMS-MS features by utilizing both mass defect filtering and m/z versus IMS collision cross sections relationships. These potential PFAS features were then compared to the EPA CompTox entries, and while some matched within specific m/z tolerances, there were still many unknowns illustrating the importance of nontargeted studies for detecting new molecules with known chemical characteristics. Additionally, this workflow can also be utilized to evaluate other xenobiotics and enable more confident annotations from nontargeted studies.

Comprehensive Peak Characterization (CPC) in Untargeted LC–MS Analysis

LC–MS-based untargeted metabolomics is heavily dependent on algorithms for automated peak detection and data preprocessing due to the complexity and size of the raw data generated. These algorithms are generally designed to be as inclusive as possible in order to minimize the number of missed peaks. This is known to result in an abundance of false positive peaks that further complicate downstream data processing and analysis. As a consequence, considerable effort is spent identifying features of interest that might represent peak detection artifacts. Here, we present the CPC algorithm, which allows automated characterization of detected peaks with subsequent filtering of low quality peaks using quality criteria familiar to analytical chemists. We provide a thorough description of the methods in addition to applying the algorithms to authentic metabolomics data. In the example presented, the algorithm removed about 35% of the peaks detected by XCMS, a majority of which exhibited a low signal-to-noise ratio. The algorithm is made available as an R-package and can be fully integrated into a standard XCMS workflow.

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.

Sample preparation techniques for suspect and non-target screening of emerging contaminants

The progress in sensitivity and resolution in mass spectrometers in recent years provides the possibility to detect a broad range of organic compounds in a single procedure. For this reason, suspect and non-target screening techniques are gaining attention since they enable the detection of hundreds of known and unknown emerging contaminants in various matrices of environmental, food and human sources. Sample preparation is a critical step before analysis as it can significantly affect selectivity, sensitivity and reproducibility. The lack of generic sample preparation protocols is obvious in this fast-growing analytical field, and most studies use those of traditional targeted analysis methods. Among them, solvent extraction and solid phase extraction (SPE) are widely used to extract emerging contaminants from solid and liquid sample types, respectively. Sequential solvent extraction and a combination of different SPE sorbents can cover a broad range of chemicals in the samples. Gel permeation chromatography (GPC) and adsorption chromatography, including acidification, are typically used to remove matrix components such as lipids from complex matrices, but usually at the expense of compound losses. Ideally, the purification of samples intended for non-target analysis should be selective of matrix interferences. Recent studies have suggested quality assurance/quality control measures for suspect and non-target screening, based on expansion and extrapolation of target compound lists, but method validations remain challenging in the absence of analytical standards and harmonized sample preparation approaches.

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.

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.

Multi-Target Analysis and Suspect Screening of Xenobiotics in Milk by UHPLC-HRMS/MS

The development of suspect or non-target screening methods to detect xenobiotics in biological fluids is essential to properly understand the exposome and assess its adverse health effects on humans. In order to fulfil that aim, the biomonitorization of human fluids is compulsory. However, these methods are not yet extensively developed, especially for polar organic xenobiotics in biofluids such as milk, as most works are only focused on certain analytes of interest. In this work, a multi-target analysis method to determine 245 diverse xenobiotics in milk by means of Ultra High Performance Liquid Chromatography (UHPLC)-qOrbitrap was developed. Under optimal conditions, liquid milk samples were extracted with acetonitrile in the presence of anhydrous Na2SO4 and NaCl, and the extracts were cleaned-up by protein precipitation at low temperature and Captiva Non-Drip (ND)—Lipids filters. The optimized method was validated at two concentration-levels (10 ng/g and 40 ng/g) obtaining satisfactory figures of merit for more than 200 compounds. The validated multi-target method was applied to several milk samples, including commercial and breast milk, provided by 4 healthy volunteers. Moreover, the method was extended to perform suspect analysis of more than 17,000 xenobiotics. All in all, several diverse xenobiotics were detected, highlighting food additives (benzothiazole) or phytoestrogens (genistein and genistin) in commercial milk samples, and stimulants (caffeine), plasticizers (phthalates), UV filters (benzophenone), or pharmaceuticals (orlistat) in breast milk samples.

Functional and Pharmacological Comparison of Human, Mouse, and Rat Organic Cation Transporter 1 toward Drug and Pesticide Interaction

Extrapolation from animal to human data is not always possible, because several essential factors, such as expression level, localization, as well as the substrate selectivity and affinity of relevant transport proteins, can differ between species. In this study, we examined the interactions of drugs and pesticides with the clinically relevant organic cation transporter hOCT1 (SLC22A1) in comparison to the orthologous transporters from mouse and rat. We determined K_m-values (73 ± 7, 36 ± 13, and 57 ± 5 µM) of human, mouse and rat OCT1 for the commonly used substrate 1-methyl-4-phenylpyridinium (MPP) and IC₅₀-values of decynium22 (12.1 ± 0.8, 5.3 ± 0.4, and 10.5 ± 0.4 µM). For the first time, we demonstrated the interaction of the cationic fungicides imazalil, azoxystrobin, prochloraz, and propamocarb with human and rodent OCT1. Drugs such as ketoconazole, clonidine, and verapamil showed substantial inhibitory potential to human, mouse, and rat OCT1 activity. A correlation analysis of hOCT1 versus mouse and rat orthologs revealed a strong functional correlation between the three species. In conclusion, this approach shows that transporter interaction data are in many cases transferable between rodents and humans, but potential species differences for other drugs and pesticides could not be excluded, though it is recommendable to perform functional comparisons of human and rodent transporters for new molecular entities.

Suspect and non-targeted screening of chemicals of emerging concern for human biomonitoring, environmental health studies and support to risk assessment: From promises to challenges and harmonisation issues

Large-scale suspect and non-targeted screening approaches based on high-resolution mass spectrometry (HRMS) are today available for chemical profiling and holistic characterisation of biological samples. These advanced techniques allow the simultaneous detection of a large number of chemical features, including markers of human chemical exposure. Such markers are of interest for biomonitoring, environmental health studies and support to risk assessment. Furthermore, these screening approaches have the promising capability to detect chemicals of emerging concern (CECs), document the extent of human chemical exposure, generate new research hypotheses and provide early warning support to policy. Whilst of growing importance in the environment and food safety areas, respectively, CECs remain poorly addressed in the field of human biomonitoring. This shortfall is due to several scientific and methodological reasons, including a global lack of harmonisation. In this context, the main aim of this paper is to present an overview of the basic principles, promises and challenges of suspect and non-targeted screening approaches applied to human samples as this specific field introduce major specificities compared to other fields. Focused on liquid chromatography coupled to HRMS-based data acquisition methods, this overview addresses all steps of these new analytical workflows. Beyond this general picture, the main activities carried out on this topic within the particular framework of the European Human Biomonitoring initiative (project HBM4EU, 2017-2021) are described, with an emphasis on harmonisation measures.

Standard substances free quantification makes LC/ESI/MS non-targeted screening of pesticides in cereals comparable between labs

LC/ESI/MS is the technique of choice for qualitative and quantitative food monitoring; however, analysis of a large number of compounds is challenged by the availability of standard substances. The impediment of detection of food contaminants has been overcome by the suspect and non-targeted screening. Still, the results from one laboratory cannot be compared with the results of another laboratory as quantitative results are required for this purpose. Here we show that the results of the suspect and non-targeted screening for pesticides can be made quantitative with the aid of in silico predicted electrospray ionization efficiencies and this allows direct comparison of the results obtained in two different laboratories. For this purpose, six cereal matrices were spiked with 134 pesticides and analysed in two independent labs; a high correlation for the results with the R² of 0.85.

Global Profiling of Toxicologically Relevant Metabolites in Urine: Case Study of Reactive Aldehydes

Among the numerous unknown metabolites representative of our exposure, focusing on toxic compounds should provide more relevant data to link exposure and health. For that purpose, we developed and applied a global method using data independent acquisition (DIA) in mass spectrometry to profile specifically electrophilic compounds originating metabolites. These compounds are most of the time toxic, due to their chemical reactivity toward nucleophilic sites present in biomacromolecules. The main line of cellular defense against these electrophilic molecules is conjugation to glutathione, then metabolization into mercapturic acid conjugates (MACs). Interestingly, MACs display a characteristic neutral loss in MS/MS experiments that makes it possible to detect all the metabolites displaying this characteristic loss, thanks to the DIA mode, and therefore to highlight the corresponding reactive metabolites. As a proof of concept, our workflow was applied to the toxicological issue of the oxidation of dietary polyunsaturated fatty acids, leading in particular to the formation of toxic alkenals, which lead to MACs upon glutathione conjugation and metabolization. By this way, dozens of MACs were detected and identified. Interestingly, multivariate statistical analyses carried out only on extracted HRMS signals of MACs yield a better characterization of the studied groups compared to results obtained from a classic untargeted metabolomics approach.

Screening ToxCast™ for Chemicals That Affect Cholesterol Biosynthesis: Studies in Cell Culture and Human Induced Pluripotent Stem Cell-Derived Neuroprogenitors

BACKGROUND

Changes in cholesterol metabolism are common hallmarks of neurodevelopmental pathologies. A diverse array of genetic disorders of cholesterol metabolism support this claim as do multiple lines of research that demonstrate chemical inhibition of cholesterol biosynthesis compromises neurodevelopment. Recent work has revealed that a number of commonly used pharmaceuticals induce changes in cholesterol metabolism that are similar to changes induced by genetic disorders with devastating neurodevelopmental deficiencies.

OBJECTIVES

We tested the hypothesis that common environmental toxicants may also impair cholesterol metabolism and thereby possibly contribute to neurodevelopmental toxicity.

METHODS

Using high-throughput screening with a targeted lipidomic analysis and the mouse neuroblastoma cell line, Neuro-2a, the ToxCast™ chemical library was screened for compounds that impact sterol metabolism. Validation of chemical effects was conducted by assessing cholesterol biosynthesis in human induced pluripotent stem cell (hiPSC)-derived neuroprogenitors using an isotopically labeled cholesterol precursor and by monitoring product formation with UPLC-MS/MS.

RESULTS

Twenty-nine compounds were identified as validated lead-hits, and four were prioritized for further study (endosulfan sulfate, tributyltin chloride, fenpropimorph, and spiroxamine). All four compounds were validated to cause hypocholesterolemia in Neuro-2a cells. The morpholine-like fungicides, fenpropimorph and spiroxamine, mirrored their Neuro-2a activity in four immortalized human cell lines and in a human neuroprogenitor model derived from hiPSCs, but endosulfan sulfate and tributyltin chloride did not.

CONCLUSIONS

These data reveal the existence of environmental compounds that interrupt cholesterol biosynthesis and that methodologically hiPSC neuroprogenitor cells provide a particularly sensitive system to monitor the effect of small molecules on de novo cholesterol formation. https://doi.org/10.1289/EHP5053.

The metabolome: A key measure for exposome research in epidemiology

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

The Exposome: Molecules to Populations

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

Metabolome disruption of pregnant rats and their offspring resulting from repeated exposure to a pesticide mixture representative of environmental contamination in Brittany

The use of pesticides exposes humans to numerous harmful molecules. Exposure in early-life may be responsible for adverse effects in later life. This study aimed to assess the metabolic modifications induced in pregnant rats and their offspring by a pesticide mixture representative of human exposure. Ten pregnant rats were exposed to a mixture of eight pesticides: acetochlor (246 μg/kg bw/d) + bromoxynil (12 μg/kg bw/d) + carbofuran (22.5 μg/kg bw/d) + chlormequat (35 μg/kg bw/d) + ethephon (22.5 μg/kg bw/d) + fenpropimorph (15.5 μg/kg bw/d) + glyphosate (12 μg/kg bw/d) + imidacloprid (12.5 μg/kg bw/d) representing the main environmental pesticide exposure in Brittany (France) in 2004. Another group of 10 pregnant rats served as controls. Females were fed ad libitum from early pregnancy, which is from gestational day (GD) 4 to GD 21. Urine samples were collected at GD 15. At the end of the exposure, mothers and pups were euthanized and blood, liver, and brain samples collected. 1H NMR-based metabolomics and GC-FID analyses were performed and PCA and PLS-DA used to discriminate between control and exposed groups. Metabolites for which the levels were significantly modified were then identified using the Kruskal-Wallis test, and p-values were adjusted for multiple testing correction using the False Discovery Rate. The metabolomics analysis revealed many differences between dams of the two groups, especially in the plasma, liver and brain. The modified metabolites are involved in TCA cycle, energy production and storage, lipid and carbohydrate metabolism, and amino-acid metabolism. These modifications suggest that the pesticide mixture may induce oxidative stress associated with mitochondrial dysfunction and the impairment of glucose and lipid metabolism. These observations may reflect liver dysfunction with increased relative liver weight and total lipid content. Similar findings were observed for glucose and energy metabolism in the liver of the offspring, and oxidative stress was also suggested in the brains of male offspring.

Metabolic Effects of a Chronic Dietary Exposure to a Low-Dose Pesticide Cocktail in Mice: Sexual Dimorphism and Role of the Constitutive Androstane Receptor

BACKGROUND

Epidemiological evidence suggests a link between pesticide exposure and the development of metabolic diseases. However, most experimental studies have evaluated the metabolic effects of pesticides using individual molecules, often at nonrelevant doses or in combination with other risk factors such as high-fat diets.

OBJECTIVES

We aimed to evaluate, in mice, the metabolic consequences of chronic dietary exposure to a pesticide mixture at nontoxic doses, relevant to consumers' risk assessment.

METHODS

A mixture of six pesticides commonly used in France, i.e., boscalid, captan, chlorpyrifos, thiofanate, thiacloprid, and ziram, was incorporated in a standard chow at doses exposing mice to the tolerable daily intake (TDI) of each pesticide. Wild-type (WT) and constitutive androstane receptor-deficient (CAR-/-) male and female mice were exposed for 52 wk. We assessed metabolic parameters [body weight (BW), food and water consumption, glucose tolerance, urinary metabolome] throughout the experiment. At the end of the experiment, we evaluated liver metabolism (histology, transcriptomics, metabolomics, lipidomics) and pesticide detoxification using liquid chromatography-mass spectrometry (LC-MS).

RESULTS

Compared to those fed control chow, WT male mice fed pesticide chow had greater BW gain and more adiposity. Moreover, these WT males fed pesticide chow exhibited characteristics of hepatic steatosis and glucose intolerance, which were not observed in those fed control chow. WT exposed female mice exhibited fasting hyperglycemia, higher reduced glutathione (GSH):oxidized glutathione (GSSG) liver ratio and perturbations of gut microbiota-related urinary metabolites compared to WT mice fed control chow. When we performed these experiments on CAR-/- mice, pesticide-exposed CAR-/- males did not exhibit BW gain or changes in glucose metabolism compared to the CAR-/- males fed control chow. Moreover, CAR-/- females fed pesticide chow exhibited pesticide toxicity with higher BWs and mortality rate compared to the CAR-/- females fed control chow.

CONCLUSIONS

To our knowledge, we are the first to demonstrate a sexually dimorphic obesogenic and diabetogenic effect of chronic dietary exposure to a common mixture of pesticides at TDI levels, and to provide evidence for a partial role for CAR in an in vivo mouse model. This raises questions about the relevance of TDI for individual pesticides when present in a mixture. https://doi.org/10.1289/EHP2877.

A review of nanoscale LC-ESI for metabolomics and its potential to enhance the metabolome coverage

Liquid chromatography-electrospray ionisation-mass spectrometry (LC-ESI-MS) platforms are widely used to perform high throughput untargeted profiling of biological samples for metabolomics-based approaches. However, these LC-ESI platforms usually favour the detection of metabolites present at relatively high concentrations because of analytical limitations such as ion suppression, thus reducing overall sensitivity. To counter this issue of sensitivity, the latest in terms of analytical platforms can be adopted to enable a greater portion of the metabolome to be analysed in a single analytical run. Here, nanoflow liquid chromatography-nanoelectrospray ionisation (nLC-nESI), which has previously been utilised successfully in proteomics, is explored for use in metabolomic and exposomic research. As a discovery based field, the markedly increased sensitivity of these nLC-nESI platforms offer the potential to uncover the roles played by low abundant signalling metabolites (e.g. steroids, eicosanoids) in health and disease studies, and would also enable an improvement in the detection of xenobiotics present at trace levels in biological matrices to better characterise the chemical exposome. This review aims to give an insight into the advantages associated with nLC-nESI for metabolomics-based approaches. Initially we detail the source of improved sensitivity prior to reviewing the available approaches to achieving nanoflow rates and nanospray ionisation for metabolomics. The robustness of nLC-nESI platforms was then assessed using the literature available from a metabolomic viewpoint. We also discuss the challenging point of sample preparation which needs to be addressed to fully enjoy the benefits of these nLC-nESI platforms. Finally, we assess metabolomic analysis utilising nano scale platforms and look ahead to the future of metabolomics using these new highly sensitive platforms.

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

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

Identifying Chemical Groups for Biomonitoring

Regulatory agencies face daunting challenges identifying emerging chemical hazards because of the large number of chemicals in commerce and limited data on exposure and toxicology. Evaluating one chemical at a time is inefficient and can lead to replacement with uncharacterized chemicals or chemicals with structural features already linked to toxicity. The Office of Environmental Health Hazard Assessment (OEHHA) has developed a process for constructing and assessing chemical groups for potential biomonitoring in California. We screen for chemicals with significant exposure potential and propose possible chemical groups, based on structure and function. To support formal consideration of these groups by Biomonitoring California’s Scientific Guidance Panel, we conduct a detailed review of exposure and toxicity data and examine the likelihood of detection in biological samples. To date, 12 chemical groups have been constructed and added to the pool of chemicals that can be selected for Biomonitoring California studies, including p,p´-bisphenols, brominated and chlorinated organic compounds used as flame retardants, non-halogenated aromatic phosphates, and synthetic polycyclic musks. Evaluating chemical groups, rather than individual chemicals, is an efficient way to respond to shifts in chemical use and the emergence of new chemicals. This strategy can enable earlier identification of important chemicals for monitoring and intervention.

Computational Metabolomics: A Framework for the Million Metabolome

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

Deployment-Associated Exposure Surveillance With High-Resolution Metabolomics

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The tooth exposome in children's health research

PURPOSE OF REVIEW

The exposome concept proposes a comprehensive assessment of environmental exposures from the prenatal period onwards. However, determining exposure timing, especially over the prenatal period, is a major challenge in environmental epidemiologic studies.

RECENT FINDINGS

For decades, teeth have been used to estimate long-term cumulative exposure to metals. Recently developed high-dimensional analytical methods, which combine sophisticated histological and chemical analysis to precisely sample tooth layers that correspond to specific life stages, have the potential to reconstruct the exposome in the second and third trimesters of prenatal development and during early childhood.

SUMMARY

A retrospective temporal exposomic approach that precisely measures exposure intensity 'and timing' during prenatal and early childhood development would substantially aid epidemiologic investigations, particularly case-control studies of rare health outcomes.

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

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

Multiresidue analysis of pesticides in urine of healthy adult companion dogs

The objective of this study was to determine the background exposures to pesticides as detected in urine from 21 healthy companion dogs in Northern Colorado. A panel of 301 pesticides was used to screen urine samples collected from dogs using an established ultraperformance liquid chromatography-mass spectrometry (UPLC-MS/MS) platform. Canine food intakes were controlled for one month on diets that were also screened for pesticide contents. Fifteen distinct pesticides were detected in urine. The most frequently detected compounds in canine urine samples collected over a 1 month period were atrazine, fuberidazole, imidacloprid, terbumeton, and clopyralid. Fuberidazole was the only pesticide detected in both the diets and urine. Companion dogs develop many similar chronic diseases as humans and represent a relevant model for biomonitoring combinations of environmental pesticide exposures, as well as for evaluating the potential relationships between environmental exposures and disease risk.

Hair-based rapid analyses for multiple drugs in forensics and doping: application of dynamic multiple reaction monitoring with LC-MS/MS

Background

Considerable efforts are being extended to develop more effective methods to detect drugs in forensic science for applications such as preventing doping in sport. The aim of this study was to develop a sensitive and accurate method for analytes of forensic and toxicological nature in human hair at sub-pg levels.

Results

The hair test covers a range of different classes of drugs and metabolites of forensic and toxicological nature including selected anabolic steroids, cocaine, amphetamines, cannabinoids, opiates, bronchodilators, phencyclidine and ketamine. For extraction purposes, the hair samples were decontaminated using dichloromethane, ground and treated with 1 M sodium hydroxide and neutralised with hydrochloric acid and phosphate buffer and the homogenate was later extracted with hexane using liquid-liquid extraction (LLE). Following extraction from hair samples, drug-screening employed liquid chromatography coupled to tandem mass spectrometric (LC-MS/MS) analysis using dynamic multiple reaction monitoring (DYN-MRM) method using proprietary software. The screening method (for > 200 drugs/metabolites) was calibrated with a tailored drug mixture and was validated for 20 selected drugs for this study. Using standard additions to hair sample extracts, validation was in line with FDA guidance. A Zorbax Eclipse plus C18 (2.1 mm internal diameter × 100 mm length × 1.8 μm particle size) column was used for analysis. Total instrument run time was 8 minutes with no noted matrix interferences. The LOD of compounds ranged between 0.05-0.5 pg/mg of hair. 233 human hair samples were screened using this new method and samples were confirmed positive for 20 different drugs, mainly steroids and drugs of abuse.

Conclusions

This is the first report of the application of this proprietary system to investigate the presence of drugs in human hair samples. The method is selective, sensitive and robust for the screening and confirmation of multiple drugs in a single analysis and has potential as a very useful tool for the analysis of large array of controlled substances and drugs of abuse.

Potential input from metabolomics for exploring and understanding the links between environment and health

Humans may be exposed via their environment to multiple chemicals as a consequence of human activities and use of synthetic products. Little knowledge is routinely generated on the hazards of these chemical mixtures. The metabolomic approach is widely used to identify metabolic pathways modified by diseases, drugs, or exposures to toxicants. This review, based on the state of the art of the current applications of metabolomics in environmental health, attempts to determine whether metabolomics might constitute an original approach to the study of associations between multiple, low-dose environmental exposures in humans. Studying the biochemical consequences of complex environmental exposures is a challenge demanding the development of careful experimental and epidemiological designs, in order to take into account possible confounders associated with the high level of interindividual variability induced by different lifestyles. The choices of populations studied, sampling and storage procedures, statistical tools used, and system biology need to be considered. Suggestions for improved experimental and epidemiological designs are described. Evidence indicates that metabolomics may be a powerful tool in environmental health in the identification of both complex exposure biomarkers directly in human populations and modified metabolic pathways, in an attempt to improve understanding the underlying environmental causes of diseases. Nevertheless, the validity of biomarkers and relevancy of animal-to-human extrapolation remain key challenges that need to be properly explored.