Plasma metabolomics profiles and breast cancer risk.

BACKGROUND: Breast cancer (BC) is the most common cancer in women and incidence rates are increasing; metabolomics may be a promising approach for identifying the drivers of the increasing trends that cannot be explained by changes in known BC risk factors. METHODS: We conducted a nested case-control study (median followup 6.3 years) within the New York site of the Breast Cancer Family Registry (BCFR) (n = 40 cases and 70 age-matched controls). We conducted a metabolome-wide association study using untargeted metabolomics coupling hydrophilic interaction liquid chromatography (HILIC) and C18 chromatography with high-resolution mass spectrometry (LC-HRMS) to identify BC-related metabolic features. RESULTS: We found eight metabolic features associated with BC risk. For the four metabolites negatively associated with risk, the adjusted odds ratios (ORs) ranged from 0.31 (95% confidence interval (CI): 0.14, 0.66) (L-Histidine) to 0.65 (95% CI: 0.43, 0.98) (N-Acetylgalactosamine), and for the four metabolites positively associated with risk, ORs ranged from 1.61 (95% CI: 1.04, 2.51, (m/z: 101.5813, RT: 90.4, 1,3-dibutyl-1-nitrosourea, a potential carcinogen)) to 2.20 (95% CI: 1.15, 4.23) (11-cis-Eicosenic acid). These results were no longer statistically significant after adjusting for multiple comparisons. Adding the BC-related metabolic features to a model, including age, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk score improved the accuracy of BC prediction from an area under the curve (AUC) of 66% to 83%. CONCLUSIONS: If replicated in larger prospective cohorts, these findings offer promising new ways to identify exposures related to BC and improve BC risk prediction.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage.

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

Protective and aggressive bacterial subsets and metabolites modify hepatobiliary inflammation and fibrosis in a murine model of PSC.

OBJECTIVE: Conflicting microbiota data exist for primary sclerosing cholangitis (PSC) and experimental models. GOAL: define the function of complex resident microbes and their association relevant to PSC patients by studying germ-free (GF) and antibiotic-treated specific pathogen-free (SPF) multidrug-resistant 2 deficient (mdr2-/- ) mice and microbial profiles in PSC patient cohorts. DESIGN: We measured weights, liver enzymes, RNA expression, histological, immunohistochemical and fibrotic biochemical parameters, faecal 16S rRNA gene profiling and metabolomic endpoints in gnotobiotic and antibiotic-treated SPF mdr2-/- mice and targeted metagenomic analysis in PSC patients. RESULTS: GF mdr2-/- mice had 100% mortality by 8 weeks with increasing hepatic bile acid (BA) accumulation and cholestasis. Early SPF autologous stool transplantation rescued liver-related mortality. Inhibition of ileal BA transport attenuated antibiotic-accelerated liver disease and decreased total serum and hepatic BAs. Depletion of vancomycin-sensitive microbiota exaggerated hepatobiliary disease. Vancomycin selectively decreased Lachnospiraceae and short-chain fatty acids (SCFAs) but expanded Enterococcus and Enterobacteriaceae. Antibiotics increased Enterococcus faecalis and Escherichia coli liver translocation. Colonisation of GF mdr2-/- mice with translocated E. faecalis and E. coli strains accelerated hepatobiliary inflammation and mortality. Lachnospiraceae colonisation of antibiotic pretreated mdr2-/- mice reduced liver fibrosis, inflammation and translocation of pathobionts, and SCFA-producing Lachnospiraceae and purified SCFA decreased fibrosis. Faecal Lachnospiraceae negatively associated, and E. faecalis/ Enterobacteriaceae positively associated, with PSC patients' clinical severity by Mayo risk scores. CONCLUSIONS: We identified novel functionally protective and detrimental resident bacterial species in mdr2-/- mice and PSC patients with associated clinical risk score. These insights may guide personalised targeted therapeutic interventions in PSC patients.

Toward Elucidating the Human Gut Microbiota-Brain Axis: Molecules, Biochemistry, and Implications for Health and Diseases.

In recent years, a substantial amount of data have supported an active role of gut microbiota in mediating mammalian brain function and health. Mining gut microbiota and their metabolites for neuroprotection is enticing but requires that the fundamental biochemical details underlying such microbiota-brain crosstalk be deciphered. While a neuronal gut-brain axis (through the vagus nerve) is not disputable, accumulating studies also point to a humoral route (via blood/lymphatic circulation) by which innumerable microbial molecular cues translocate from local gut epithelia to circulation with potentials to further cross the blood-brain barrier and reach the brain. In this Perspective, we review a realm of gut microbial molecules to evaluate their fate, function, and neuroactivities in vivo as mediated by microbiota. We turn to seminal studies of neurophysiology and neurologic disease models for the elucidation of biochemical pathways that link microbiota to gut-brain signaling. In addition, we discuss opportunities and challenges for advancing the microbiota-brain axis field while calling for high-throughput discovery of microbial molecules and studies for resolving the interspecies, interorgan, and interclass interaction among these neuroactive microbial molecules.

Effects of Acute 2,3,7,8-Tetrachlorodibenzo-p-Dioxin Exposure on the Circulating and Cecal Metabolome Profile.

2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) is a polyhalogenated planar hydrocarbon belonging to a group of highly toxic and persistent environmental contaminants known as "dioxins". TCDD is an animal teratogen and carcinogen that is well characterized for causing immunosuppression through activation of aryl hydrocarbon receptor (AHR). In this study, we investigated the effect of exposure of mice to an acute dose of TCDD on the metabolic profile within the serum and cecal contents to better define the effects of TCDD on host physiology. Our findings demonstrated that within the circulating metabolome following acute TCDD exposure, there was significant dysregulation in the metabolism of bioactive lipids, amino acids, and carbohydrates when compared with the vehicle (VEH)-treated mice. These widespread changes in metabolite abundance were identified to regulate host immunity via modulating nuclear factor-kappa B (NF-κB) and extracellular signal-regulated protein kinase (ERK1/2) activity and work as biomarkers for a variety of organ injuries and dysfunctions that follow TCDD exposure. Within the cecal content of mice exposed to TCDD, we were able to detect changes in inflammatory markers that regulate NF-κB, markers of injury-related inflammation, and changes in lysine degradation, nicotinamide metabolism, and butanoate metabolism, which collectively suggested an immediate suppression of broad-scale metabolic processes in the gastrointestinal tract. Collectively, these results demonstrate that acute TCDD exposure results in immediate irregularities in the circulating and intestinal metabolome, which likely contribute to TCDD toxicity and can be used as biomarkers for the early detection of individual exposure.

Serum Metabolomics Reveals That Gut Microbiome Perturbation Mediates Metabolic Disruption Induced by Arsenic Exposure in Mice.

Arsenic contamination in drinking water has been a worldwide health concern for decades. In addition to being a well-recognized carcinogen, arsenic exposure has also been linked to diabetes, neurological effects, and cardiovascular diseases. Recently, increasing evidence has indicated that gut microbiome is an important risk factor in modulating the development of diseases. We aim to investigate the role of gut microbiome perturbation in arsenic-induced diseases by coupling a mass-spectrometry-based metabolomics approach and an animal model with altered gut microbiome induced by bacterial infection. Serum metabolic profiling has revealed that gut microbiome perturbation and arsenic exposure induced the dramatic changes of numerous metabolite pathways, including fatty acid metabolism, phospholipids, sphingolipids, cholesterols, and tryptophan metabolism, which were not or were less disrupted when the gut microbiome stayed normal. In summary, this study suggests that gut microbiome perturbation can exacerbate or cause metabolic disorders induced by arsenic exposure.

Chronic Arsenic Exposure Induces Oxidative Stress and Perturbs Serum Lysolipids and Fecal Unsaturated Fatty Acid Metabolism.

Chronic arsenic exposure from drinking water is a global public health issue, which is associated with numerous human diseases and influences millions of people worldwide. The effects of arsenic exposure to the metabolic networks remain elusive. Here, we exposed female C57BL/6J mice to 1 ppm inorganic arsenic in drinking water for 3 months to investigate how arsenic exposure perturbs serum and fecal metabolic profiles. We found decreased levels of serum compounds with antioxidative activities in arsenic-treated mice, in accordance with elevated oxidative stress indicated by higher urinary 8-oxo-2'-deoxyguanosine (8-oxo-dG) levels. Moreover, the levels of multiple lysophosphatidylcholines (lysoPCs) were significantly increased in the sera of arsenic-exposed mice, including lysoPC (O-18:0), lysoPC (20:3), lysoPC (18:1), and lysoPC (22:6). Arsenic exposure perturbed the levels of several key polyunsaturated fatty acids (PUFAs) in the fecal samples in concert with alterations in related microbial pathways. Additionally, changes in the abundances of many functional metabolites, together with decreased levels of amino acids, were found in the fecal samples of arsenic-treated mice. By delineating the impact of arsenic exposure on the metabolic profiles, the findings may provide new biomarkers and mechanistic insights into arsenic-associated diseases.

Gut microbiome disruption altered the biotransformation and liver toxicity of arsenic in mice.

The mammalian gut microbiome (GM) plays a critical role in xenobiotic biotransformation and can profoundly affect the toxic effects of xenobiotics. Previous in vitro studies have demonstrated that gut bacteria have the capability to metabolize arsenic (As); however, the specific roles of the gut microbiota in As metabolism in vivo and the toxic effects of As are largely unknown. Here, we administered sodium arsenite to conventionally raised mice (with normal microbiomes) and GM-disrupted mice with antibiotics to investigate the role of the gut microbiota in As biotransformation and its toxicity. We found that the urinary total As levels of GM-disrupted mice were much higher, but the fecal total As levels were lower, than the levels in the conventionally raised mice. In vitro experiments, in which the GM was incubated with As, also demonstrated that the gut bacteria could adsorb or take up As and thus reduce the free As levels in the culture medium. With the disruption of the gut microbiota, arsenic biotransformation was significantly perturbed. Of note, the urinary monomethylarsonic acid/dimethylarsinic acid ratio, a biomarker of arsenic metabolism and toxicity, was markedly increased. Meanwhile, the expression of genes of one-carbon metabolism, including folr2, bhmt, and mthfr, was downregulated, and the liver S-adenosylmethionine (SAM) levels were significantly decreased in the As-treated GM-disrupted mice only. Moreover, As exposure altered the expression of genes of the p53 signaling pathway, and the expression of multiple genes associated with hepatocellular carcinoma (HCC) was also changed in the As-treated GM-disrupted mice only. Collectively, disruption of the GM enhances the effect of As on one-carbon metabolism, which could in turn affect As biotransformation. GM disruption also increases the toxic effects of As and may increase the risk of As-induced HCC in mice.

Serum Metabolomics Identifies Altered Bioenergetics, Signaling Cascades in Parallel with Exposome Markers in Crohn's Disease.

: Inflammatory bowel disease (IBD) has stimulated much interest due to its surging incidences and health impacts in the U.S. and worldwide. However, the exact cause of IBD remains incompletely understood, and biomarker is lacking towards early diagnostics and effective therapy assessment. To tackle these, the emerging high-resolution mass spectrometry (HRMS)-based metabolomics shows promise. Here, we conducted a pilot untargeted LC/MS metabolomic profiling in Crohn's disease, for which serum samples of both active and inactive cases were collected, extracted, and profiled by a state-of-the-art compound identification workflow. Results show a distinct metabolic profile of Crohn's from control, with most metabolites downregulated. The identified compounds are structurally diverse, pointing to important pathway perturbations ranging from energy metabolism (e.g., ß-oxidation of fatty acids) to signaling cascades of lipids (e.g., DHA) and amino acid (e.g., L-tryptophan). Importantly, an integral role of gut microbiota in the pathogenesis of Crohn's disease is highlighted. Xenobiotics and their biotransformants were widely detected, calling for massive exposomic profiling for future cohort studies as such. This study endorses the analytical capacity of untargeted metabolomics for biomarker development, cohort stratification, and mechanistic interpretation; the findings might be valuable for advancing biomarker research and etiologic inquiry in IBD.

Individual susceptibility to arsenic-induced diseases: the role of host genetics, nutritional status, and the gut microbiome.

Arsenic (As) contamination in water or food is a global issue affecting hundreds of millions of people. Although As is classified as a group 1 carcinogen and is associated with multiple diseases, the individual susceptibility to As-related diseases is highly variable, such that a proportion of people exposed to As have higher risks of developing related disorders. Many factors have been found to be associated with As susceptibility. One of the main sources of the variability found in As susceptibility is the variation in the host genome, namely, polymorphisms of many genes involved in As transportation, biotransformation, oxidative stress response, and DNA repair affect the susceptibility of an individual to As toxicity and then influence the disease outcomes. In addition, lifestyles and many nutritional factors, such as folate, vitamin C, and fruit, have been found to be associated with individual susceptibility to As-related diseases. Recently, the interactions between As exposure and the gut microbiome have been of particular concern. As exposure has been shown to perturb gut microbiome composition, and the gut microbiota has been shown to also influence As metabolism, which raises the question of whether the highly diverse gut microbiota contributes to As susceptibility. Here, we review the literature and summarize the factors, such as host genetics and nutritional status, that influence As susceptibility, and we also present potential mechanisms of how the gut microbiome may influence As metabolism and its toxic effects on the host to induce variations in As susceptibility. Challenges and future directions are also discussed to emphasize the importance of characterizing the specific role of these factors in interindividual susceptibility to As-related diseases.

Effects of the Artificial Sweetener Neotame on the Gut Microbiome and Fecal Metabolites in Mice.

Although artificial sweeteners are widely used in food industry, their effects on human health remain a controversy. It is known that the gut microbiota plays a key role in human metabolism and recent studies indicated that some artificial sweeteners such as saccharin could perturb gut microbiome and further affect host health, such as inducing glucose intolerance. Neotame is a relatively new low-caloric and high-intensity artificial sweetener, approved by FDA in 2002. However, the specific effects of neotame on gut bacteria are still unknown. In this study, we combined high-throughput sequencing and gas chromatography-mass spectrometry (GC-MS) metabolomics to investigate the effects of neotame on the gut microbiome and fecal metabolite profiles of CD-1 mice. We found that a four-week neotame consumption reduced the alpha-diversity and altered the beta-diversity of the gut microbiome. Firmicutes was largely decreased while Bacteroidetes was significantly increased. The Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis also indicated that the control mice and neotame-treated mice have different metabolic patterns and some key genes such as butyrate synthetic genes were decreased. Moreover, neotame consumption also changed the fecal metabolite profiles. Dramatically, the concentrations of multiple fatty acids, lipids as well as cholesterol in the feces of neotame-treated mice were consistently higher than controls. Other metabolites, such as malic acid and glyceric acid, however, were largely decreased. In conclusion, our study first explored the specific effects of neotame on mouse gut microbiota and the results may improve our understanding of the interaction between gut microbiome and neotame and how this interaction could influence the normal metabolism of host bodies.

Equilibrium State of PAHs in Bottom Sediment-Water-Suspended Sediment System of a Large River Considering Freely Dissolved Concentrations.

In natural waters, the equilibrium state of hydrophobic organic compounds among bottom sediment (BS), suspended sediment (SPS), and water is fundamental to infer their transfer flux and aqueous bioavailability. However, this type of information remains scarce and fragmented. This study systematically evaluated the equilibrium state of polycyclic aromatic hydrocarbons (PAHs) in the Yangtze River. Total and freely dissolved concentrations of the 16 priority PAHs in pore water and overlying water (including surface and near-bottom) of the Yangtze middle reaches were investigated, as were the concentrations of attached PAHs in SPS and BS. Results showed that concentrations of total/freely dissolved PAHs, dissolved organic carbon (DOC), and SPS in surface water were not statistically different from those in near-bottom water, and the DOC-water distribution coefficients of PAHs in pore water were not statistically different from overlying water. However, significant disequilibrium was found at the sediment-water interface; concentrations of total/freely dissolved PAHs in pore water were 1 to 2 orders of magnitude higher than those in overlying water. This study offers a complete analysis of the potential disequilibrium of PAHs in BS-water-SPS system of large rivers and suggests that distribution of hydrophobic organic compounds between BS and overlying water is essential in controlling their equilibrium state in the BS-water-SPS system of natural waters.

Seminar: Functional Exposomics and Mechanisms of Toxicity-Insights from Model Systems and NAMs.

BACKGROUND: Significant progress has been made over the past decade in measuring the chemical components of the exposome, providing transformative population-scale frameworks in probing the etiologic link between environmental factors and disease phenotypes. While the analytical technologies continue to evolve with reams of data being generated, there is an opportunity to complement exposome-wide association studies (ExWAS) with functional analyses to advance etiologic search at organismal, cellular, and molecular levels. OBJECTIVES: Exposomics is a transdisciplinary field aimed at enabling discovery-based analysis of the nongenetic factors that contribute to disease, including numerous environmental chemical stressors. While advances in exposure assessment are enhancing population-based discovery of exposome-wide effects and chemical exposure agents, functional screening and elucidation of biological effects of exposures represent the next logical step toward precision environmental health and medicine. In this work, we focus on the use, strategies, and prospects of alternative approaches and model systems to enhance the current human exposomics framework in biomarker search and causal understanding, spanning from bench-based nonmammalian organisms and cell culture to computational new approach methods (NAMs). DISCUSSION: We visit the definition of the functional exposome and exposomics and discuss a need to leverage alternative models as opposed to mammalian animals for delineating exposome-wide health effects. Under the "three Rs" principle of reduction, replacement, and refinement, model systems such as roundworms, fruit flies, zebrafish, and induced pluripotent stem cells (iPSCs) are advantageous over mammals (e.g., rodents or higher vertebrates). These models are cost-effective, and cell-specific genetic manipulations in these models are easier and faster, compared to mammalian models. Meanwhile, in silico NAMs enhance hazard identification and risk assessment in humans by bridging the translational gaps between toxicology data and etiologic inference, as represented by in vitro to in vivo extrapolation (IVIVE) and integrated approaches to testing and assessment (IATA) under the adverse outcome pathway (AOP) framework. Together, these alternatives offer a strong toolbox to support functional exposomics to study toxicity and causal mediators underpinning exposure-disease links. https://doi.org/10.1289/EHP13120.

Association of Coffee Consumption and Prediagnostic Caffeine Metabolites With Incident Parkinson Disease in a Population-Based Cohort.

BACKGROUND AND OBJECTIVES: Inverse associations between caffeine intake and Parkinson disease (PD) have been frequently implicated in human studies. However, no studies have quantified biomarkers of caffeine intake years before PD onset and investigated whether and which caffeine metabolites are related to PD. METHODS: Associations between self-reported total coffee consumption and future PD risk were examined in the EPIC4PD study, a prospective population-based cohort including 6 European countries. Cases with PD were identified through medical records and reviewed by expert neurologists. Hazard ratios (HRs) and 95% CIs for coffee consumption and PD incidence were estimated using Cox proportional hazards models. A case-control study nested within the EPIC4PD was conducted, recruiting cases with incident PD and matching each case with a control by age, sex, study center, and fasting status at blood collection. Caffeine metabolites were quantified by high-resolution mass spectrometry in baseline collected plasma samples. Using conditional logistic regression models, odds ratios (ORs) and 95% CIs were estimated for caffeine metabolites and PD risk. RESULTS: In the EPIC4PD cohort (comprising 184,024 individuals), the multivariable-adjusted HR comparing the highest coffee intake with nonconsumers was 0.63 (95% CI 0.46-0.88, p = 0.006). In the nested case-control study, which included 351 cases with incident PD and 351 matched controls, prediagnostic caffeine and its primary metabolites, paraxanthine and theophylline, were inversely associated with PD risk. The ORs were 0.80 (95% CI 0.67-0.95, p = 0.009), 0.82 (95% CI 0.69-0.96, p = 0.015), and 0.78 (95% CI 0.65-0.93, p = 0.005), respectively. Adjusting for smoking and alcohol consumption did not substantially change these results. DISCUSSION: This study demonstrates that the neuroprotection of coffee on PD is attributed to caffeine and its metabolites by detailed quantification of plasma caffeine and its metabolites years before diagnosis.

Biotin rescues manganese-induced Parkinson's disease phenotypes and neurotoxicity.

Occupational exposure to manganese (Mn) induces manganism and has been widely linked as a contributing environmental factor to Parkinson's disease (PD), featuring dramatic signature overlaps between the two in motor symptoms and clinical hallmarks. However, the molecular mechanism underlying such link remains elusive, and for combating PD, effective mechanism-based therapies are lacking. Here, we developed an adult Drosophila model of Mn toxicity to recapitulate key parkinsonian features, spanning behavioral deficits, neuronal loss, and dysfunctions in lysosome and mitochondria. We performed global metabolomics on flies at an early stage of toxicity and identified metabolism of the B vitamin, biotin (vitamin B 7 ), as a master pathway underpinning Mn toxicity with systemic, body-brain increases in Mn-treated groups compared to the controls. Using Btnd RNAi mutant flies, we show that biotin depletion exacerbates Mn-induced neurotoxicity, parkinsonism, and mitochondrial dysfunction; while in Mn-exposed wild-type flies, biotin feeding dramatically ameliorates these pathophenotypes. We further show in human induced stem cells (iPSCs)- differentiated midbrain dopaminergic neurons that the supplemented biotin protects against Mn-induced neuronal loss, cytotoxicity, and mitochondrial dysregulation. Finally, human data profiling biotin-related proteins show for PD cases elevated circulating levels of biotin transporters but not of metabolic enzymes compared to healthy controls, suggesting humoral biotin transport as a key event involved in PD. Taken together, our findings identified compensatory biotin pathway as a convergent, systemic driver of Mn toxicity and parkinsonian pathology, providing new basis for devising effective countermeasures against manganism and PD. Significance Statement: Environmental exposure to manganese (Mn) may increase the risk for Parkinson's disease (PD); however, the mechanistic basis linking the two remains unclear. Our adult fruit fly ( Drosophila ) model of Mn toxicity recapitulated key Parkinson's hallmarks in vivo spanning behavioral deficits, neuronal loss, and mitochondrial dysfunction. Metabolomics identified the biotin (vitamin B 7 ) pathway as a key mediator, featuring systemic biotin increases in the flies. Rescue trials leveraging biotin-deficient flies, wild-type flies, and human iPSC-derived dopaminergic neurons determined biotin as a driver of manganism, with the parkinsonian phenotypes dramatically reversed through biotin supplementation. Our findings, in line with overexpressed circulating biotin transporters observed in PD patients, suggest compensatory biotin pathway as a key to untangle the Mn-PD link for combating neurodegenerative disease.

Exposomics as a tool to investigate differences in health and disease by sex and gender.

The health and disease of an individual is mediated by their genetics, a lifetime of environmental exposures, and interactions between the two. Genetic or biological sex, including chromosome composition and hormone expression, may influence both the types and frequency of environmental exposures an individual experiences, as well as the biological responses an individual has to those exposures. Gender identity, which can be associated with social behaviors such as expressions of self, may also mediate the types and frequency of exposures an individual experiences. Recent advances in exposome-level analysis have progressed our understanding of how environmental factors affect health outcomes; however, the relationship between environmental exposures and sex- and gender-specific health remains underexplored. The comprehensive, non-targeted, and unbiased nature of exposomic research provides a unique opportunity to systematically evaluate how environmental exposures interact with biological sex and gender identity to influence health. In this forward-looking narrative review, we provide examples of how biological sex and gender identity influence environmental exposures, discuss how environmental factors may interact with biological processes, and highlight how an intersectional approach to exposomics can provide critical insights for sex- and gender-specific health sciences.

Integrative exposomic, transcriptomic, epigenomic analyses of human placental samples links understudied chemicals to preeclampsia.

BACKGROUND: Environmental health research has recently undergone a dramatic shift, with ongoing technological advancements allowing for broader coverage of exposure and molecular biology signatures. Approaches to integrate such measures are still needed to increase understanding between systems-level exposure and biology. OBJECTIVES: We address this gap by evaluating placental tissues to identify novel chemical-biological interactions associated with preeclampsia. This study tests the hypothesis that understudied chemicals are present in the human placenta and associated with preeclampsia-relevant disruptions, including overall case status (preeclamptic vs. normotensive patients) and underlying transcriptomic/epigenomic signatures. METHODS: A non-targeted analysis based on high-resolution mass spectrometry was used to analyze placental tissues from a cohort of 35 patients with preeclampsia (n = 18) and normotensive (n = 17) pregnancies. Molecular feature data were prioritized for confirmation based on association with preeclampsia case status and confidence of chemical identification. All molecular features were evaluated for relationships to mRNA, microRNA, and CpG methylation (i.e., multi-omic) signature alterations involved in preeclampsia. RESULTS: A total of 183 molecular features were identified with significantly differentiated abundance in placental extracts of preeclamptic patients; these features clustered into distinct chemical groupings using unsupervised methods. Of these features, 53 were identified (mapping to 40 distinct chemicals) using chemical standards, fragmentation spectra, and chemical metadata. In general, human metabolites had the largest feature intensities and strongest associations with preeclampsia-relevant multi-omic changes. Exogenous drugs were second most abundant and had fewer associations with multi-omic changes. Other exogenous chemicals (non-drugs) were least abundant and had the fewest associations with multi-omic changes. CONCLUSIONS: These global data trends suggest that human metabolites are heavily intertwined with biological processes involved in preeclampsia etiology, while exogenous chemicals may still impact select transcriptomic/epigenomic processes. This study serves as a demonstration of merging systems exposures with systems biology to better understand chemical-disease relationships.

An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry.

Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.

High-Resolution Metabolomics of 50 Neurotransmitters and Tryptophan Metabolites in Feces, Serum, and Brain Tissues Using UHPLC-ESI-Q Exactive Mass Spectrometry.

Recent evidence indicates that tryptophan metabolites and neurotransmitters are potential mediators of the microbiome-gut-brain interaction. Here, a high-resolution ultra-high performance liquid chromatography-electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) assay was developed and validated for quantifying 50 neurotransmitters, tryptophan metabolites, and bacterial indole derivatives in mouse serum, feces, and brain. The lower limit of quantitation for the 50 compounds ranged from 0.5 to 100 nmol/L, and sample preparation procedures were adapted for individual compounds to allow quantitation within linearity of the assay with a correlation coefficient >0.99. Reproducibility was tested by intra- and interday precision and accuracy of analysis: intra- and interday precision at the lower limit of quantitation was less than 20% for all compounds, with over two-thirds of the compounds achieving an interday precision below 10%, while the interday accuracy at the lower limit of quantitation ranged from 82.3 to 128.0% for all compounds. The analyte recovery was assessed based on sample-spiked stable-isotope-labeling standards, illustrating a need to consider matrix-specific recovery discrepancies when performing interorgan comparison. Carryover was evaluated by intermittent solvent blank injection. The assay was successfully applied to determining the concentration profiles of neurotransmitter and tryptophan metabolites in serum, feces, and brain of conventionally raised specific pathogen-free (SPF) C57BL/6 mice. Our method may serve as a useful analytical resource for investigating the roles of tryptophan metabolism and neurotransmitter signaling in host-microbiota interaction.

The gut microbiome and arsenic-induced disease-iAs metabolism in mice.

PURPOSE OF REVIEW: This review summarizes inorganic arsenic (iAs) metabolism and toxicity in mice and the gut microbiome and how iAs and the gut microbiome interact to induce diseases. RECENT FINDINGS: Recently, a variety of studies have started to reveal the interactions between iAs and the gut microbiome. Evidence shows that gut bacteria can influence iAs biotransformation and disease risks. The gut microbiome can directly metabolize iAs, and it can also indirectly be involved in iAs metabolism through the host, such as altering iAs absorption, cofactors, and genes related to iAs metabolism. Many factors, such as iAs metabolism influenced by the gut microbiome, and microbiome metabolites perturbed by iAs can lead to different disease risks. iAs is a widespread toxic metalloid in environment, and iAs toxicity has become a global health issue. iAs is subject to metabolic reactions after entering the host body, including methylation, demethylation, oxidation, reduction, and thiolation. Different arsenic species, including trivalent and pentavalent forms and inorganic and organic forms, determine their toxicity. iAs poisoning is predominately caused by contaminated drinking water and food, and chronic arsenic toxicity can cause various diseases. Therefore, studies of iAs metabolism are important for understanding iAs associated disease risks.