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

Network Analysis to Identify Communities Among Multiple Exposure Biomarkers Measured at Birth in Three Flemish General Population Samples

Introduction: Humans are exposed to multiple environmental chemicals via different sources resulting in complex real-life exposure patterns. Insight into these patterns is important for applications such as linkage to health effects and (mixture) risk assessment. By providing internal exposure levels of (metabolites of) chemicals, biomonitoring studies can provide snapshots of exposure patterns and factors that drive them. Presentation of biomonitoring data in networks facilitates the detection of such exposure patterns and allows for the systematic comparison of observed exposure patterns between datasets and strata within datasets. Methods: We demonstrate the use of network techniques in human biomonitoring data from cord blood samples collected in three campaigns of the Flemish Environment and Health Studies (FLEHS) (sampling years resp. 2002-2004, 2008-2009, and 2013-2014). Measured biomarkers were multiple organochlorine compounds, PFAS and metals. Comparative network analysis (CNA) was conducted to systematically compare networks between sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Results: Network techniques offered an intuitive approach to visualize complex correlation structures within human biomonitoring data. The identification of groups of highly connected biomarkers, "communities," within these networks highlighted which biomarkers should be considered collectively in the analysis and interpretation of epidemiological studies or in the design of toxicological mixture studies. Network analyses demonstrated in our example to which extent biomarker networks and its communities changed across the sampling campaigns, smoking status during pregnancy, and maternal pre-pregnancy BMI. Conclusion: Network analysis is a data-driven and intuitive screening method when dealing with multiple exposure biomarkers, which can easily be upscaled to high dimensional HBM datasets, and can inform mixture risk assessment approaches.

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.

Potentiation of the apoptotic signaling pathway in both the striatum and hippocampus and neurobehavioral impairment in rats exposed chronically to a low-dose of cadmium

Cadmium (Cd) is a highly toxic heavy metal. It accumulates in biological tissues, especially in fish which constitutes a first rank food for humans, particularly in the coastal areas. This study investigates the effect of long-term exposure to low Cd concentration (17 μg/kg/day) in rat striatum and hippocampus. In this study, the neurobehavioral ability changes were assessed by applying cognitive standard testing at the end of the rats' exposure period. In addition, the examination of mitochondrial swelling was performed at the same time of evaluation of its redox status in the brain regions studied through stress parameters (GSH, MDA, GST, and CAT). This study examined also whether this long-term exposure can modify the apoptotic signaling pathway via assessment of apoptotic markers (caspase-8 and 9, Bax, Bcl-2, and Cyt-c) in cell lysates. The results of this study showed changes in neurobehavioral abilities of animals and a stronger mitochondrial swelling associated with a significant decrease in antioxidant systems (GSH, GST, and CAT) and conversely an increase in the lipoperoxidation end product (MDA) in both the striatal and hippocampal mitochondria. In addition, the results revealed a significant increase in pro-apoptotic intracellular components such as caspase-9, Cyt-c, and Bax, and showed also an evident decrease in Bcl-2 levels. In conclusion, our results reported that chronic exposure to Cd produces behavioral and cognitive perturbations, enhances oxidative stress associated with mitochondrial edema and Cyt-c leakage, and, ultimately, potentiates apoptosis signaling pathway in both brain regions in rats.

Metabolic Signatures of the Exposome-Quantifying the Impact of Exposure to Environmental Chemicals on Human Health

Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the “chemical exposome” (exposures to environmental chemicals), affect the host’s metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome.

Characterization of the Human Exposome by a Comprehensive and Quantitative Large-Scale Multianalyte Metabolomics Platform

The exposome, defined as the cumulative measure of external exposures and associated biological responses throughout the lifespan, has emerged in recent years as a cornerstone in biomedical sciences. Metabolomics stands out here as one of the most powerful tools for investigating the interplay between the genetic background, exogenous, and endogenous factors within human health. However, to address the complexity of the exposome, novel methods are needed to characterize the human metabolome. In this work, we have optimized and validated a multianalyte metabolomics platform for large-scale quantitative exposome research in plasma and urine samples, based on the use of simple extraction methods and high-throughput metabolomic fingerprinting. The methodology enables, for the first time, the simultaneous characterization of the endogenous metabolome, food-related metabolites, pharmaceuticals, household chemicals, environmental pollutants, and microbiota derivatives, comprising more than 1000 metabolites in total. This comprehensive and quantitative investigation of the exposome is achieved in short run times, through simple extraction methods requiring small-sample volumes, and using integrated quality control procedures for ensuring data quality. This metabolomics approach was satisfactorily validated in terms of linearity, recovery, matrix effects, specificity, limits of quantification, intraday and interday precision, and carryover. Furthermore, the clinical potential of the methodology was demonstrated in a dietary intervention trial as a case study. In summary, this study describes the optimization, validation, and application of a multimetabolite platform for comprehensive and quantitative metabolomics-based exposome research with great utility in large-scale epidemiological studies.

Expanded coverage of non-targeted LC-HRMS using atmospheric pressure chemical ionization: a case study with ENTACT mixtures

Non-targeted analysis (NTA) is a rapidly evolving analytical technique with numerous opportunities to improve and expand instrumental and data analysis methods. In this work, NTA was performed on eight synthetic mixtures containing 1264 unique chemical substances from the U.S. Environmental Protection Agency's Non-Targeted Analysis Collaborative Trial (ENTACT). These mixtures were analyzed by atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) using both positive and negative polarities for a total of four modes. Out of the 1264 ENTACT chemical substances, 1116 were detected in at least one ionization mode, 185 chemicals were detected using all four ionization modes, whereas 148 were not detected. Forty-four chemicals were detected only by APCI, and 181 were detected only by ESI. Molecular descriptors and physicochemical properties were used to assess which ionization type was preferred for a given compound. One ToxPrint substructure (naphthalene group) was found to be enriched in compounds only detected using APCI, and eight ToxPrints (e.g., several alcohol moieties) were enriched in compounds only detected using ESI. Examination of physicochemical parameters for ENTACT chemicals suggests that those with higher aqueous solubility preferentially ionized by ESI-. While ESI typically detects a larger number of compounds, APCI offers chromatograms with less background, fewer co-elutions, and additional chemical space coverage, suggesting both should be considered for broader coverage in future NTA research. Graphical abstract.

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.

Associations between persistent organic pollutants and endometriosis: A multipollutant assessment using machine learning algorithms

Endometriosis is a gynaecological disease characterised by the presence of endometriotic tissue outside of the uterus impacting a significant fraction of women of childbearing age. Evidence from epidemiological studies suggests a relationship between risk of endometriosis and exposure to some organochlorine persistent organic pollutants (POPs). However, these chemicals are numerous and occur in complex and highly correlated mixtures, and to date, most studies have not accounted for this simultaneous exposure. Linear and logistic regression models are constrained to adjusting for multiple exposures when variables are highly intercorrelated, resulting in unstable coefficients and arbitrary findings. Advanced machine learning models, of emerging use in epidemiology, today appear as a promising option to address these limitations. In this study, different machine learning techniques were compared on a dataset from a case-control study conducted in France to explore associations between mixtures of POPs and deep endometriosis. The battery of models encompassed regularised logistic regression, artificial neural network, support vector machine, adaptive boosting, and partial least-squares discriminant analysis with some additional sparsity constraints. These techniques were applied to identify the biomarkers of internal exposure in adipose tissue most associated with endometriosis and to compare model classification performance. The five tested models revealed a consistent selection of most associated POPs with deep endometriosis, including octachlorodibenzofuran, cis-heptachlor epoxide, polychlorinated biphenyl 77 or trans-nonachlor, among others. The high classification performance of all five models confirmed that machine learning may be a promising complementary approach in modelling highly correlated exposure biomarkers and their associations with health outcomes. Regularised logistic regression provided a good compromise between the interpretability of traditional statistical approaches and the classification capacity of machine learning approaches. Applying a battery of complementary algorithms may be a strategic approach to decipher complex exposome-health associations when the underlying structure is unknown.

Simultaneous exploration of nutrients and pollutants in human milk and their impact on preterm infant growth: An integrative cross-platform approach

Early nutritional management including fortified human breastmilk is currently recommended to fulfil the energy demands and counterbalance risks associated to preterm birth. However, little is known about the potential adverse effects of exposure to persistent organic pollutants (POPs) carried in human milk on preterm infant growth. We conducted a pilot study proving the application of an integrative analytical approach based on mass spectrometry (MS) coupled to advanced statistical models, favouring the comprehensive molecular profiling to support the identification of multiple biomarkers. We applied this workflow in the frame of a preterm infants' cohort to explore environmental determinants of growth. The combination of high resolution gas and liquid chromatography MS platforms generated a large molecular profile, including 102 pollutants and nutrients (targeted analysis) and 784 metabolites (non-targeted analysis). Data analysis consisted in a preliminary examination of associations between the signatures of POPs and the normalised growth of preterm infants, using multivariate linear regression adjusting for known confounding variables. A second analysis aimed to identify multidimensional biomarkers using a multiblock algorithm allowing the integration of multiple datasets in the growth model of preterm infants. The preliminary results did not suggest an impairment of preterm growth associated to the milk concentrations of POPs. The multiblock approach however revealed complex interrelated molecular networks of POPs, lipids, metabolites and amino acids in breastmilk associated to preterm infant growth, supporting the high potential of biomarkers exploration of this proposed workflow. Whereas the present study intended to identify simultaneously pollutant and nutrient exposure profiles associated to early preterm infant growth, this workflow may be easily adapted and applied to other matrices (e.g. serum) and research settings, favouring the functional exploration of environmental determinants of complex and multifactorial diseases.

Review of the environmental prenatal exposome and its relationship to maternal and fetal health

Environmental chemicals comprise a major portion of the human exposome, with some shown to impact the health of susceptible populations, including pregnant women and developing fetuses. The placenta and cord blood serve as important biological windows into the maternal and fetal environments. In this article we review how environmental chemicals (defined here to include man-made chemicals [e.g., flame retardants, pesticides/herbicides, per- and polyfluoroalkyl substances], toxins, metals, and other xenobiotic compounds) contribute to the prenatal exposome and highlight future directions to advance this research field. Our findings from a survey of recent literature indicate the need to better understand the breadth of environmental chemicals that reach the placenta and cord blood, as well as the linkages between prenatal exposures, mechanisms of toxicity, and subsequent health outcomes. Research efforts tailored towards addressing these needs will provide a more comprehensive understanding of how environmental chemicals impact maternal and fetal health.

Epigenetic Biomarkers for Environmental Exposures and Personalized Breast Cancer Prevention

Environmental and lifestyle factors are believed to account for >80% of breast cancers; however, it is not well understood how and when these factors affect risk and which exposed individuals will actually develop the disease. While alcohol consumption, obesity, and hormone therapy are some known risk factors for breast cancer, other exposures associated with breast cancer risk have not yet been identified or well characterized. In this paper, it is proposed that the identification of blood epigenetic markers for personal, in utero, and ancestral environmental exposures can help researchers better understand known and potential relationships between exposures and breast cancer risk and may enable personalized prevention strategies.

Synthesis and identification of deschloroketamine metabolites in rats' urine and a quantification method for deschloroketamine and metabolites in rats' serum and brain tissue using liquid chromatography tandem mass spectrometry

Deschloroketamine (2-(methylamino)-2-phenyl-cyclohexanone) is a ketamine analog belonging to a group of dissociative anesthetics, which have been distributed within the illicit market since 2015. However, it was also being sold as 'ketamine' misleading people to believe that they were getting genuine ketamine. Dissociative anesthetics have also come to the attention of the psychiatric field due to their potential properties in the treatment of depression. At present, there is a dearth of information on deschloroketamine related to its metabolism, biodistribution, and its mechanism of action. We have therefore carried out a metabolomics study for deschloroketamine via non-targeted screening of urine samples employing liquid chromatography combined with high-resolution mass spectrometry. We developed and validated a multiple reaction monitoring method using a triple quadrupole instrument to track metabolites of deschloroketamine. Furthermore, significant metabolites of deschloroketamine, (trans-dihydrodeschloroketamine, cis- and trans-dihydronordeschloroketamine, and nordeschloroketamine), were synthesized in-house. The prepared standards were utilized in the developed multiple reaction monitoring method. The quantification method for serum samples provided intra-day accuracy ranging from 86% to 112% with precision of 3% on average. The concentrations of cis/trans-dihydronordeschloroketamines and trans-dihydrodeschloroketamine were lower than 10 ng/mL, nordeschloroketamine and deschloroketamine ranged from 0.5 to 860 ng/mL in real samples. The quantification method for brain tissue provided intra-day accuracy ranging from 80% to 125% with precision of 7% on average. The concentrations of cis/trans-dihydronordeschloroketamines and trans-dihydrodeschloroketamine ranged from 0.5 to 70 ng/g, nordeschloroketamine and deschloroketamine varied from 0.5 to 4700 ng/g in real samples.

A Perspective and Framework for Developing Sample Type Specific Databases for LC/MS-Based Clinical Metabolomics

Metabolomics has the potential to greatly impact biomedical research in areas such as biomarker discovery and understanding molecular mechanisms of disease. However, compound identification (ID) remains a major challenge in liquid chromatography mass spectrometry-based metabolomics. This is partly due to a lack of specificity in metabolomics databases. Though impressive in depth and breadth, the sheer magnitude of currently available databases is in part what makes them ineffective for many metabolomics studies. While still in pilot phases, our experience suggests that custom-built databases, developed using empirical data from specific sample types, can significantly improve confidence in IDs. While the concept of sample type specific databases (STSDBs) and spectral libraries is not entirely new, inclusion of unique descriptors such as detection frequency and quality scores, can be used to increase confidence in results. These features can be used alone to judge the quality of a database entry, or together to provide filtering capabilities. STSDBs rely on and build upon several available tools for compound ID and are therefore compatible with current compound ID strategies. Overall, STSDBs can potentially result in a new paradigm for translational metabolomics, whereby investigators confidently know the identity of compounds following a simple, single STSDB search.

Streamlined MRM method transfer between instruments assisted with HRMS matching and retention-time prediction

Multiple reaction monitoring (MRM) mode using liquid-chromatography tandem mass spectrometry (e.g., LC-QqQ-MS/MS) has been extensively employed in the small molecule analysis with trace levels in complex samples owing to its high sensitivity. However, most of the reported MRM methods are developed using authentic standards, which are often costly yet not readily available. To address this question, a practical platform for the MRM method transfer between different LC-QqQ-MS/MS instruments, assisted by the high-resolution mass spectrometry (LC-HRMS) and retention time (RT) prediction, has been developed in this study. The reported platform can take advantage of both the high sensitivity of LC-MRM method and ion transition pairs from the previous publications. LC-HRMS can provide the accurate mass measurement of the compounds, though high-quality MS/MS fragments are usually difficult to obtain for chemicals at trace levels. Retention time matching and peaks matching between both instrumental platforms rule out isobaric candidates. With an additional retention time prediction filter from quantitative structure retention relationship (QSRR) model based on random forest feature selection (Pearson r² = 0.63), identification of small molecules is achieved at a high confidence level without using authentic standards. The developed platform has been validated with robustness by examining spiked environmental chemicals in sludge water samples, biological urine, and cell extracts.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

An overview of the current progress, challenges, and prospects of human biomonitoring and exposome studies

Human Biomonitoring (HB), the process for determining whether and to what extent chemical substances penetrated our bodies, serves as a useful tool to quantify human exposure to pollutants. In cases of nutrition and physiologic status, HB plays a critical role in the identification of excess or deficiency of essential nutrients. In pollutant HB studies, levels of substances measured in body fluids (blood, urine, and breast milk) or tissues (hair, nails or teeth) aid in the identification of potential health risks or associated adverse effects. However, even as a widespread practice in several countries, most HB studies reflect exposure to a single compound or mixtures which are measured at a single time point in lifecycle. On the other hand, throughout an individual's lifespan, the contact with different physical, chemical, and social stressors occurs at varying intensities, differing times and durations. Further, the interaction between stressors and body receptors leads to dynamic responses of the entire biological system including proteome, metabolome, transcriptome, and adductome. Bearing this in mind, a relatively new vision in exposure science, defined as the exposome, is postulated to expand the traditional practice of measuring a single exposure to one or few chemicals at one-time point to an approach that addresses measures of exposure to multiple stressors throughout the lifespan. With the exposome concept, the science of exposure advances to an Environment-Wide Association Perspective, which might exhibit a stronger relationship with good health or disease conditions for an individual (phenotype). Thus, this critical review focused on the current progress of HB and exposome investigations, anticipating some challenges, strategies, and future needs to be taken into account for designing future surveys.

Generating the Blood Exposome Database Using a Comprehensive Text Mining and Database Fusion Approach

BACKGROUND

Blood chemicals are routinely measured in clinical or preclinical research studies to diagnose diseases, assess risks in epidemiological research, or use metabolomic phenotyping in response to treatments. A vast volume of blood-related literature is available via the PubMed database for data mining.

OBJECTIVES

We aimed to generate a comprehensive blood exposome database of endogenous and exogenous chemicals associated with the mammalian circulating system through text mining and database fusion.

METHODS

Using NCBI resources, we retrieved PubMed abstracts, PubChem chemical synonyms, and PMC supplementary tables. We then employed text mining and PubChem crowdsourcing to associate phrases relating to blood with PubChem chemicals. False positives were removed by a phrase pattern and a compound exclusion list.

RESULTS

A query to identify blood-related publications in the PubMed database yielded 1.1 million papers. Matching a total of 15 million synonyms from 6.5 million relevant PubChem chemicals against all blood-related publications yielded 37,514 chemicals and 851,999 publications records. Mapping PubChem compound identifiers to the PubMed database yielded 49,940 unique chemicals linked to 676,643 papers. Analysis of open-access metabolomics papers related to blood phrases in the PMC database yielded 4,039 unique compounds and 204 papers. Consolidating these three approaches summed up to a total of 41,474 achiral structures that were linked to 65,957 PubChem CIDs and to over 878,966 PubMed articles. We mapped these compounds to 50 databases such as those covering metabolites and pathways, governmental and toxicological databases, pharmacology resources, and bioassay repositories. In comparison, HMDB, the Human Metabolome Database, links 1,075 compounds to blood-related primary publications.

CONCLUSION

This new Blood Exposome Database can be used for prioritizing chemicals for systematic reviews, developing target assays in exposome research, identifying compounds in untargeted mass spectrometry, and biological interpretation in metabolomics data. The database is available at http://bloodexposome.org. https://doi.org/10.1289/EHP4713.

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

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

Non-targeted Screening in Environmental Monitoring Programs

Contaminant monitoring programs have been tasked with understanding the fate and transport of toxic chemicals in the environment. Mass spectrometry based methods have traditionally been developed to maximize sensitivity and accuracy of a select set of target compounds. As mass spectrometry methods have advanced, so has the breadth of questions proposed by environmental chemists. Incorporating these methods in chemical monitoring programs provides large data sets to explore the effects of complex mixtures on environmental systems.

Expanding phytoremediation to the realms of known and unknown organic chemicals of concern

Recent advancements in analytical chemistry and data analyses via high-resolution mass spectrometry (HRMS) are evolving scientific understanding of the potential totality of organic chemical exposure and pollutant risk. This review addresses the importance of HRMS approaches, namely suspect screening and nontarget chemical analyses, to the realm of phytoremediation. These analytical approaches are not without caveats and constraints, but they provide an opportunity to understand in greater totality how plant-based technologies contribute, mitigate, and reduce organic chemical exposure across scales of experimental and system-level studies. These analytical tools can enlighten the complexity and efficacy of plant-contaminant system design and expand our understanding of biogenic and anthropogenic chemicals at work in phytoremediation systems. Advances in data analytics from biological sciences, such as metabolomics, are crucial to HRMS analysis. This review provides an overview of targeted, suspect screening, and nontarget HRMS approaches, summarizes the expanding knowledge of regulated and unregulated organic chemicals in the environment, addresses requisite HRMS instrumentation, analysis cost, uncertainty, and data processing techniques, and offers potential bridges of HRMS analyses to phytoremediation research and application.

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.

Mass defect filtering for suspect screening of halogenated environmental chemicals: A case study of chlorinated organophosphate flame retardants

RATIONALE

Organophosphate flame retardants (OPFRs) are a class of flame retardants widely found in environmental and biological matrices that have been extensively studied due to their adverse health effects in humans. OPFRs are loosely bound chemicals that can detach from treated products and be released into indoor and outdoor environments, where they have the potential to further undergo transformation and degradation processes, in particular the chlorinated OPFRs (Cl-PFRs). Their detection remains a moving target for analysts, and traditional targeted mass spectrometry methods are suitable only for those compounds with authentic standards.

METHODS

Mass defect filter (MDF) is a strategy to filter molecular features using thresholds applied to the mass defect value of a target ion or molecular feature of interest. We have developed an MDF strategy for the detection and tentative identification of twelve potential Cl-PFR transformation products in a study mixture of six known Cl-PFRs using MS/MS data acquired on a high-resolution mass spectrometer. Most compounds in the Cl-PFRs family share a ClO₄ P group as a core structure, of which modification results in a significant shift in the exact masses of the resulting compounds but show only a minimal shift in their mass defects. Subsequently, the MDF strategy was employed to tentatively identify Cl-PFRs retrospectively in six human urine samples that had previously been analyzed.

RESULTS

MDF in combination with product ion filtering for the characteristic [H₂ O₃ P]⁺ and [H₄ O₄ P]⁺ ions and neutral loss filtering for the characteristic C_n H_2n-x Cl_x group resulted in revealing suspects and homologues in the Cl-PFRs family. Furthermore, the MDF of the product ions detected additional Cl-PFR-related compounds that differed significantly in the exact masses of both precursor and product ions but had minimal shift in the mass defects of product ions. The mass defect of one or more common product ions helped to detect a few Cl-PFR analogs that had not been identified by MDF of the core structure precursor ion.

CONCLUSIONS

MDF helped to detect some Cl-PFRs present in lower concentrations, which went undetected without data filters. MDF also helped to detect chromatographic peaks for Cl-PFR homologues that are likely structural analogs that resulted from impurities and/or derivatives and transformation products. The methodology was applied to demonstrate and tentatively detect known and suspect Cl-PFRs in human urine samples retrospectively.

HaloSeeker 1.0: A User-Friendly Software to Highlight Halogenated Chemicals in Nontargeted High-Resolution Mass Spectrometry Data Sets

In the present work, we address the issue of nontargeted screening of organohalogenated chemicals in complex matrixes. A global strategy aiming to seek halogenated signatures in full-scan high-resolution mass spectrometry (HRMS) fingerprints was developed. The resulting all-in-one user-friendly application, HaloSeeker 1.0, was developed to promote the accessibility of associated in-house bioinformatics tools to a large audience. The ergonomic web user interface avoids any interactions with the coding component while allowing interactions with the data, including peak detection (features), deconvolution, and comprehensive accompanying manual review for chemical formula assignment. HaloSeeker 1.0 was successfully applied to a marine sediment HRMS data set acquired on a liquid chromatography-heated electrospray ionization [LC-HESI(-)] Orbitrap instrument ( R = 140 000 at m/z 200). Among the 4532 detected features, 827 were paired and filtered in 165 polyhalogenated clusters. HaloSeeker was also compared to three similar tools and showed the best performances. HaloSeeker's ability to filter and investigate halogenated signals was demonstrated and illustrated by a potential homologue series with C₁₂H _xBr _yCl _zO₂ as a putative general formula.

Using prepared mixtures of ToxCast chemicals to evaluate non-targeted analysis (NTA) method performance

Non-targeted analysis (NTA) methods are increasingly used to discover contaminants of emerging concern (CECs), but the extent to which these methods can support exposure and health studies remains to be determined. EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) was launched in 2016 to address this need. As part of ENTACT, 1269 unique substances from EPA's ToxCast library were combined to make ten synthetic mixtures, with each mixture containing between 95 and 365 substances. As a participant in the trial, we first performed blinded NTA on each mixture using liquid chromatography (LC) coupled with high-resolution mass spectrometry (HRMS). We then performed an unblinded evaluation to identify limitations of our NTA method. Overall, at least 60% of spiked substances could be observed using selected methods. Discounting spiked isomers, true positive rates from the blinded and unblinded analyses reached a maximum of 46% and 65%, respectively. An overall reproducibility rate of 75% was observed for substances spiked into more than one mixture and observed at least once. Considerable discordance in substance identification was observed when comparing a subset of our results derived from two separate reversed-phase chromatography methods. We conclude that a single NTA method, even when optimized, can likely characterize only a subset of ToxCast substances (and, by extension, other CECs). Rigorous quality control and self-evaluation practices should be required of labs generating NTA data to support exposure and health studies. Accurate and transparent communication of performance results will best enable meaningful interpretations and defensible use of NTA data. Graphical abstract ᅟ.

Electrospray ionization-ion mobility spectrometry-high resolution tandem mass spectrometry with collision-induced charge stripping for the analysis of highly multiply charged intact polymers

Polymers with large molecular weight are difficult to interpret using electrospray ionization-mass spectrometry (ESI-MS) due to the generation of various highly multiply charged analytes. Although ESI-ion mobility spectrometry (IMS)-MS is effective in reducing the complexity of the mass spectrum, this approach is insufficient for analyzing highly multiply charged polymers. In this study, we propose a method combining tandem mass spectrometry (quadrupole and high-resolution time-of-flight MS, QMS/TOFMS), IMS, and collision-induced charge stripping (CICS) for analyzing large intact polymers (∼40 kDa), which are highly multiply charged. The number of charges can be estimated from a Fourier transform power spectrum of a mass spectrum when the charge number is less than approximately 20. Interpretations of the spectra of poly(ethylene oxide)s (PEOs) weighing 20 kDa, poly(methyl methacrylate)s weighing 22 kDa, and methoxy-PEO-maleimide weighing 40 kDa were successfully demonstrated with isotope level and polymerization degree level separations, respectively. In the proposed method, a mixture can be analyzed for relatively small (a few kDa) and large (a few tens of kDa) polymers simultaneously without any sample pretreatment.

Annotating Nontargeted LC-HRMS/MS Data with Two Complementary Tandem Mass Spectral Libraries

Tandem mass spectral databases are indispensable for fast and reliable compound identification in nontargeted analysis with liquid chromatography–high resolution tandem mass spectrometry (LC-HRMS/MS), which is applied to a wide range of scientific fields. While many articles now review and compare spectral libraries, in this manuscript we investigate two high-quality and specialized collections from our respective institutes, recorded on different instruments (quadrupole time-of-flight or QqTOF vs. Orbitrap). The optimal range of collision energies for spectral comparison was evaluated using 233 overlapping compounds between the two libraries, revealing that spectra in the range of CE 20–50 eV on the QqTOF and 30–60 nominal collision energy units on the Orbitrap provided optimal matching results for these libraries. Applications to complex samples from the respective institutes revealed that the libraries, combined with a simple data mining approach to retrieve all spectra with precursor and fragment information, could confirm many validated target identifications and yield several new Level 2a (spectral match) identifications. While the results presented are not surprising in many ways, this article adds new results to the debate on the comparability of Orbitrap and QqTOF data and the application of spectral libraries to yield rapid and high-confidence tentative identifications in complex human and environmental samples.

EPA's non-targeted analysis collaborative trial (ENTACT): genesis, design, and initial findings

In August 2015, the US Environmental Protection Agency (EPA) convened a workshop entitled "Advancing non-targeted analyses of xenobiotic chemicals in environmental and biological media." The purpose of the workshop was to bring together the foremost experts in non-targeted analysis (NTA) to discuss the state-of-the-science for generating, interpreting, and exchanging NTA measurement data. During the workshop, participants discussed potential designs for a collaborative project that would use EPA resources, including the ToxCast library of chemical substances, the DSSTox database, and the CompTox Chemicals Dashboard, to evaluate cutting-edge NTA methods. That discussion was the genesis of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT). Nearly 30 laboratories have enrolled in ENTACT and used a variety of chromatography, mass spectrometry, and data processing approaches to characterize ten synthetic chemical mixtures, three standardized media (human serum, house dust, and silicone band) extracts, and thousands of individual substances. Initial results show that nearly all participants have detected and reported more compounds in the mixtures than were intentionally added, with large inter-lab variability in the number of reported compounds. A comparison of gas and liquid chromatography results shows that the majority (45.3%) of correctly identified compounds were detected by only one method and 15.4% of compounds were not identified. Finally, a limited set of true positive identifications indicates substantial differences in observable chemical space when employing disparate separation and ionization techniques as part of NTA workflows. This article describes the genesis of ENTACT, all study methods and materials, and an analysis of results submitted to date. Graphical abstract ᅟ.

Beyond monoisotopic accurate mass spectrometry: ancillary techniques for identifying unknown features in non-targeted discovery analysis

High-resolution mass spectrometry (HR-MS) is an important tool for performing non-targeted analysis for investigating complex organic mixtures in human or environmental media. This perspective demonstrates HR-MS compound identification strategies using atom counting, isotope ratios, and fragmentation pattern analysis based on ‘exact’ or ‘accurate’ mass, which allows analytical distinction among mass fragments with the same integer mass, but with different atomic constituents of the original molecules. Herein, HR-MS technology is shown to narrow down the identity of unknown compounds for specific examples, and ultimately inform future analyses when these compounds reoccur. Although HR-MS is important for all biological media, this is particularly critical for new methods and instrumentation invoking exhaled breath condensate, particles, and aerosols. In contrast to standard breath gas-phase analyses where 1 mass unit (Da) resolution is generally sufficient, the condensed phase breath media are particularly vulnerable to errors in compound identification because the larger organic non-volatile molecules can form identical integer mass fragments from different atomic constituents which then require high-resolution mass analyses to tell them apart.

Integrating tools for non-targeted analysis research and chemical safety evaluations at the US EPA

Tens-of-thousands of chemicals are registered in the U.S. for use in countless processes and products. Recent evidence suggests that many of these chemicals are measureable in environmental and/or biological systems, indicating the potential for widespread exposures. Traditional public health research tools, including in vivo studies and targeted analytical chemistry methods, have been unable to meet the needs of screening programs designed to evaluate chemical safety. As such, new tools have been developed to enable rapid assessment of potentially harmful chemical exposures and their attendant biological responses. One group of tools, known as "non-targeted analysis" (NTA) methods, allows the rapid characterization of thousands of never-before-studied compounds in a wide variety of environmental, residential, and biological media. This article discusses current applications of NTA methods, challenges to their effective use in chemical screening studies, and ways in which shared resources (e.g., chemical standards, databases, model predictions, and media measurements) can advance their use in risk-based chemical prioritization. A brief review is provided of resources and projects within EPA's Office of Research and Development (ORD) that provide benefit to, and receive benefits from, NTA research endeavors. A summary of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) is also given, which makes direct use of ORD resources to benefit the global NTA research community. Finally, a research framework is described that shows how NTA methods will bridge chemical prioritization efforts within ORD. This framework exists as a guide for institutions seeking to understand the complexity of chemical exposures, and the impact of these exposures on living systems.

A Suspect Screening Method for Characterizing Multiple Chemical Exposures among a Demographically Diverse Population of Pregnant Women in San Francisco

BACKGROUND

In utero exposure to environmental chemicals can adversely impact pregnancy outcomes and childhood health, but minimal biomonitoring data exist on the majority of chemicals used in commerce.

OBJECTIVES

We aimed to profile exposure to multiple environmental organic acids (EOAs) and identify novel chemicals that have not been previously biomonitored in a diverse population of pregnant women.

METHODS

We used liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) to perform a suspect screen for 696 EOAs, (e.g., phenols and phthalate metabolites) on the maternal serum collected at delivery from 75 pregnant women delivering at two large San Francisco Hospitals. We examined demographic differences in peak areas and detection frequency (DF) of suspect EOAs using a Kruskal-Wallis Rank Sum test or Fisher's exact test. We confirmed selected suspects by comparison with their respective reference standards.

RESULTS

We detected, on average, 56 [standard deviation (SD)]: 8) suspect EOAs in each sample (range: 32-73). Twelve suspect EOAs with DF≥60 were matched to 21 candidate compounds in our EOA database, two-thirds of which are novel chemicals. We found demographic differences in DF for 13 suspect EOAs and confirmed the presence of 6 priority novel chemicals: 2,4-Di-tert-butylphenol, Pyrocatechol, 2,4-Dinitrophenol, 3,5-Di-tert-butylsalicylic acid, 4-Hydroxycoumarin, and 2'-Hydroxyacetophenone (or 3'-Hydroxyacetophenone). The first two are high-production-volume chemicals in the United States.

CONCLUSION

Suspect screening in human biomonitoring provides a viable method to characterize a broad spectrum of environmental chemicals to prioritize for targeted method development and quantification. https://doi.org/10.1289/EHP2920.

Exploring the Potential of a Global Emerging Contaminant Early Warning Network through the Use of Retrospective Suspect Screening with High-Resolution Mass Spectrometry

A key challenge in the environmental and exposure sciences is to establish experimental evidence of the role of chemical exposure in human and environmental systems. High resolution and accurate tandem mass spectrometry (HRMS) is increasingly being used for the analysis of environmental samples. One lauded benefit of HRMS is the possibility to retrospectively process data for (previously omitted) compounds that has led to the archiving of HRMS data. Archived HRMS data affords the possibility of exploiting historical data to rapidly and effectively establish the temporal and spatial occurrence of newly identified contaminants through retrospective suspect screening. We propose to establish a global emerging contaminant early warning network to rapidly assess the spatial and temporal distribution of contaminants of emerging concern in environmental samples through performing retrospective analysis on HRMS data. The effectiveness of such a network is demonstrated through a pilot study, where eight reference laboratories with available archived HRMS data retrospectively screened data acquired from aqueous environmental samples collected in 14 countries on 3 different continents. The widespread spatial occurrence of several surfactants (e.g., polyethylene glycols ( PEGs ) and C12AEO-PEGs ), transformation products of selected drugs (e.g., gabapentin-lactam, metoprolol-acid, carbamazepine-10-hydroxy, omeprazole-4-hydroxy-sulfide, and 2-benzothiazole-sulfonic-acid), and industrial chemicals (3-nitrobenzenesulfonate and bisphenol-S) was revealed. Obtaining identifications of increased reliability through retrospective suspect screening is challenging, and recommendations for dealing with issues such as broad chromatographic peaks, data acquisition, and sensitivity are provided.

Combining a Deconvolution and a Universal Library Search Algorithm for the Nontarget Analysis of Data-Independent Acquisition Mode Liquid Chromatography-High-Resolution Mass Spectrometry Results

Nontarget analysis is considered one of the most comprehensive tools for the identification of unknown compounds in a complex sample analyzed via liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Due to the complexity of the data generated via LC-HRMS, the data-dependent acquisition mode, which produces the MS² spectra of a limited number of the precursor ions, has been one of the most common approaches used during nontarget screening. However, data-independent acquisition mode produces highly complex spectra that require proper deconvolution and library search algorithms. We have developed a deconvolution algorithm and a universal library search algorithm (ULSA) for the analysis of complex spectra generated via data-independent acquisition. These algorithms were validated and tested using both semisynthetic and real environmental data. A total of 6000 randomly selected spectra from MassBank were introduced across the total ion chromatograms of 15 sludge extracts at three levels of background complexity for the validation of the algorithms via semisynthetic data. The deconvolution algorithm successfully extracted more than 60% of the added ions in the analytical signal for 95% of processed spectra (i.e., 3 complexity levels multiplied by 6000 spectra). The ULSA ranked the correct spectra among the top three for more than 95% of cases. We further tested the algorithms with 5 wastewater effluent extracts for 59 artificial unknown analytes (i.e., their presence or absence was confirmed via target analysis). These algorithms did not produce any cases of false identifications while correctly identifying ∼70% of the total inquiries. The implications, capabilities, and the limitations of both algorithms are further discussed.

Suspect Screening Analysis of Chemicals in Consumer Products

A two-dimensional gas chromatography-time-of-flight/mass spectrometry (GC×GC-TOF/MS) suspect screening analysis method was used to rapidly characterize chemicals in 100 consumer products-which included formulations (e.g., shampoos, paints), articles (e.g., upholsteries, shower curtains), and foods (cereals)-and therefore supports broader efforts to prioritize chemicals based on potential human health risks. Analyses yielded 4270 unique chemical signatures across the products, with 1602 signatures tentatively identified using the National Institute of Standards and Technology 2008 spectral database. Chemical standards confirmed the presence of 119 compounds. Of the 1602 tentatively identified chemicals, 1404 were not present in a public database of known consumer product chemicals. Reported data and model predictions of chemical functional use were applied to evaluate the tentative chemical identifications. Estimated chemical concentrations were compared to manufacturer-reported values and other measured data. Chemical presence and concentration data can now be used to improve estimates of chemical exposure, and refine estimates of risk posed to human health and the environment.

Suspect screening of maternal serum to identify new environmental chemical biomonitoring targets using liquid chromatography-quadrupole time-of-flight mass spectrometry

The use and advantages of high-resolution mass spectrometry (MS) as a discovery tool for environmental chemical monitoring has been demonstrated for environmental samples but not for biological samples. We developed a method using liquid chromatography-quadrupole time-of-flight MS (LC-QTOF/MS) for discovery of previously unmeasured environmental chemicals in human serum. Using non-targeted data acquisition (full scan MS analysis) we were able to screen for environmental organic acids (EOAs) in 20 serum samples from second trimester pregnant women. We define EOAs as environmental organic compounds with at least one dissociable proton which are utilized in commerce. EOAs include environmental phenols, phthalate metabolites, perfluorinated compounds, phenolic metabolites of polybrominated diphenyl ethers and polychlorinated biphenyls, and acidic pesticides and/or predicted acidic pesticide metabolites. Our validated method used solid phase extraction, reversed-phase chromatography in a C18 column with gradient elution, electrospray ionization in negative polarity and automated tandem MS (MS/MS) data acquisition to maximize true positive rates. We identified "suspect EOAs" using Agilent MassHunter Qualitative Analysis software, to match chemical formulas generated from each sample run with molecular formulas in our unique database of 693 EOAs assembled from multiple environmental literature sources. We found potential matches for 282 (41%) of the EOAs in our database. Sixty-five of these suspect EOAs were detected in at least 75% of the samples; only 19 of these compounds are currently biomonitored in National Health and Nutrition Examination Survey. We confirmed two of three suspect EOAs by LC-QTOF/MS using a targeted method developed through LC-MS/MS, reporting the first confirmation of benzophenone-1 and bisphenol S in pregnant women's sera. Our suspect screening workflow provides an approach to comprehensively scan environmental chemical exposures in humans. This can provide a better source of exposure information to help improve exposure and risk evaluation of industrial chemicals.

Effect-based approach for screening of chemical mixtures in whole blood of green turtles from the Great Barrier Reef

Organisms are exposed to mixtures of both known and unknown chemicals which are diverse and variable, and thus difficult and costly to characterise and monitor using traditional target analyses. The objective of this study was to validate and apply in vitro effect-based methods by which whole blood can be used to screen internal exposure to such complex chemical mixtures. For this study, we used whole blood of green sea turtles (Chelonia mydas). To ensure the chemical mixture in blood is transferred with minimal losses or bias, we tested a modified QuEChERS extraction method specifically developed for multi- and non-target instrument analysis. The extracts were dosed to a battery of in vitro bioassays (AhR-CAFLUX, AREc32, NFκB-bla, VM7Luc4E2, Microtox), each with a different mode of action (e.g., AhR receptor mediated xenobiotics, NrF2-mediated oxidative stress, NFκB mediated response to inflammation, estrogen activity and baseline toxicity oxidative stress, respectively) in order to cover a wide spectrum of chemicals. Results confirmed the absence of interferences of the blood extract with the responses of the different assays, thus indicating the methods' compatibility with effect-based screening approaches. To apply this approach, whole blood samples were collected from green turtles foraging in agricultural, urban and remote areas of the Australian Great Barrier Reef. The effect-based screening revealed significant differences in exposure, with higher induction of AhR-CAFLUX, AREc32 and Microtox assays in turtles from the agricultural foraging ground. Overall, these results corroborated with concurrent health, target and non-target analyses in the same animals performed as part of a larger program. This study provides evidence that the proposed effect-based approach is suitable for screening and evaluating internal exposure of organisms to chemical mixtures. The approach could be valuable for advancing understanding on multiple levels ranging from identification of priority chemicals in effect-directed investigations to exploring relationships between exposure and disease, not only in sea turtles, but in any organism.

Nontarget Screening with High Resolution Mass Spectrometry in the Environment: Ready to Go?

The vast, diverse universe of organic pollutants is a formidable challenge for environmental sciences, engineering, and regulation. Nontarget screening (NTS) based on high resolution mass spectrometry (HRMS) has enormous potential to help characterize this universe, but is it ready to go for real world applications? In this Feature article we argue that development of mass spectrometers with increasingly high resolution and novel couplings to both liquid and gas chromatography, combined with the integration of high performance computing, have significantly widened our analytical window and have enabled increasingly sophisticated data processing strategies, indicating a bright future for NTS. NTS has great potential for treatment assessment and pollutant prioritization within regulatory applications, as highlighted here by the case of real-time pollutant monitoring on the River Rhine. We discuss challenges for the future, including the transition from research toward solution-centered and robust, harmonized applications.

Rapid screening and identification of chemical hazards in surface and drinking water using high resolution mass spectrometry and a case-control filter

Access to clean, safe drinking water poses a serious challenge to regulators, and requires analytical strategies capable of rapid screening and identification of potentially hazardous chemicals, specifically in situations when threats to water quality or security require rapid investigations and potential response. This study describes a fast and efficient chemical hazard screening strategy for characterising trace levels of polar organic contaminants in water matrices, based on liquid chromatography high resolution mass spectrometry with post-acquisition 'case-control' data processing. This method allowed for a rapid response time of less than 24 h for the screening of target, suspect and non-target unknown chemicals via direct injection analysis, and a second, more sensitive analysis option requiring sample pre-concentration. The method was validated by fortifying samples with a range of pesticides, pharmaceuticals and personal care products (n = 46); with >90% of target compounds positively screened in samples at 1 ng mL^-1, and 46% at 0.1 ng mL^-1 when analysed via direct injection. To simulate a contamination event samples were fortified with compounds not present in the commercial library (designated 'non-target compounds'; fipronil and fenitrothion), tentatively identified at 0.2 and 1 ng mL^-1, respectively; and a compound not included in any known commercial library or public database (designated 'unknown' compounds; 8Cl^- perfluorooctanesulfonic acid), at 0.8 ng mL^-1. The method was applied to two 'real-case' scenarios: (1) the assessment of drinking water safety during a high-profile event in Brisbane, Australia; and (2) to screen treated, re-circulated drinking water and pre-treated (raw) water. The validated workflow was effective for rapid prioritisation and screening of suspect and non-target potential hazards at trace levels, and could be applied to a wide range of matrices and investigations where comparison of organic contaminants between an affected and control site and or timeframe is warranted.

Redox theory of aging: implications for health and disease

Genetics ultimately defines an individual, yet the phenotype of an adult is extensively determined by the sequence of lifelong exposures, termed the exposome. The redox theory of aging recognizes that animals evolved within an oxygen-rich environment, which created a critical redox interface between an organism and its environment. Advances in redox biology show that redox elements are present throughout metabolic and structural systems and operate as functional networks to support the genome in adaptation to environmental resources and challenges during lifespan. These principles emphasize that physical and functional phenotypes of an adult are determined by gene-environment interactions from early life onward. The principles highlight the critical nature of cumulative exposure memories in defining changes in resilience progressively during life. Both plasma glutathione and cysteine systems become oxidized with aging, and the recent finding that cystine to glutathione ratio in human plasma predicts death in coronary artery disease (CAD) patients suggests this could provide a way to measure resilience of redox networks in aging and disease. The emerging concepts of cumulative gene-environment interactions warrant focused efforts to elucidate central mechanisms by which exposure memory governs health and etiology, onset and progression of disease.