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PURPOSE OF REVIEW: Review how to use metabolomic profiling in causal mediation analysis to assess epidemiological evidence for air pollution impacts on birth outcomes. RECENT FINDINGS: Maternal exposures to air pollutants have been associated with pregnancy complications and adverse pregnancy and birth outcomes. Causal mediation analysis enables us to estimate direct and indirect effects on outcomes (i.e., effect decomposition), elucidating causal mechanisms or effect pathways. Maternal metabolites and metabolic pathways are perturbed by air pollution exposures may lead to adverse pregnancy and birth outcomes, thus they can be considered mediators in the causal pathways. Metabolomic markers have been used to explain the biological mechanisms linking air pollution and respiratory function, and of arsenic exposure and birth weight. However, mediation analysis of metabolomic markers has not been used to assess air pollution effects on adverse birth outcomes. In this article, we describe the assumptions and applications of mediation analysis using metabolomic markers that elucidate the potential mechanisms of the effects of air pollution on adverse pregnancy and birth outcomes. SUMMARY: The hypothesis of mediation along specified pathways can be assessed within the structural causal modeling framework. For causal inferences, several assumptions that go beyond the data—including no uncontrolled confounding—need to be made to justify the effect decomposition. Nevertheless, studies that integrate metabolomic information in causal mediation analysis may greatly improve our understanding of the effects of ambient air pollution on adverse pregnancy and birth outcomes as they allow us to suggest and test hypotheses about underlying biological mechanisms in studies of pregnant women.

Discovering pathophysiologic networks in a blood-based approach may help to generate valuable tools for early treatment or preventive measures in autism. To date targeted or untargeted metabolomics approaches to identify metabolic features and pathways affecting fetal neurodevelopment have rarely been applied to pregnancy samples, that is, an early period potentially relevant for the development of autism spectrum disorders (ASD). We conducted a population-based study relying on autism diagnoses retrieved from California Department of Developmental Services record. After linking cases to and sampling controls from birth certificates, we retrieved stored maternal mid-pregnancy serum samples collected as part of the California Prenatal Screening Program from the California Biobank for children born 2004 to 2010 in the central valley of California. We retrieved serum for 52 mothers whose children developed autism and 62 population controls originally selected from all eligible children matched by birth year and child's sex. Also, we required that these mothers were relatively low or unexposed to air pollution and select pesticides during early pregnancy. We identified differences in metabolite levels in several metabolic pathways, including glycosphingolipid biosynthesis and metabolism, N-glycan and pyrimidine metabolism, bile acid pathways and, importantly, C21-steroid hormone biosynthesis and metabolism. Disturbances in these pathways have been shown to be relevant for neurodevelopment in rare genetic syndromes or implicated in previous studies of autism. This study provides new insight into maternal mid-pregnancy metabolic features possibly related to the development of autism and an incentive to explore whether these pathways and metabolites are useful for early diagnosis, treatment, or prevention. LAY SUMMARY: This study found that in mid-pregnancy the blood of mothers who give birth to a child that develops autism has some characteristic features that are different from those of blood samples taken from control mothers. These features are related to biologic mechanisms that can affect fetal brain development. In the future, these insights may help identify biomarkers for early autism diagnosis and treatment or preventive measures. Autism Res 2020, 13: 1258-1269. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.

Background Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates. Methods We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education. Results In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism. Conclusion The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

Background: Exposure to per- and polyfluoroalkyl substances (PFAS), a prevalent class of persistent pollutants, may increase the risk of type 2 diabetes. Objective: We examined associations between PFAS exposure and glucose metabolism in youth. Methods: Overweight/obese adolescents from the Study of Latino Adolescents at Risk of Type 2 Diabetes (SOLAR; n=310) participated in annual visits for an average of 3.3±2.9y. Generalizability of findings were tested in young adults from the Southern California Children’s Health Study (CHS; n=135) who participated in a clinical visit with a similar protocol. At each visit, oral glucose tolerance tests were performed to estimate glucose metabolism and β-cell function via the insulinogenic index. Four PFAS were measured at baseline using liquid chromatography–high-resolution mass spectrometry; high levels were defined as concentrations >66th percentile. Results: In females from the SOLAR, high perfluorohexane sulfonate (PFHxS) levels (≥2.0 ng/mL) were associated with the development of dysregulated glucose metabolism beginning in late puberty. The magnitude of these associations increased postpuberty and persisted through 18 years of age. For example, postpuberty, females with high PFHxS levels had 25-mg/dL higher 60-min glucose (95% CI: 12, 39mg/dL; p

BACKGROUND AND AIM: Perfluoroalkyl substances (PFAS), the “forever chemicals”, accumulate mainly in the liver and have various adverse health effects. Little is known about the mechanistic pathways...

Urinary mutagenicity reflects systemic exposure to complex mixtures of genotoxic/carcinogenic agents and is linked to tumor development. Coal combustion emissions (CCE) and diesel engine exhaust (DEE) are associated with cancers of the lung and other sites, but their influence on urinary mutagenicity is unclear. We investigated associations between exposure to CCE or DEE and urinary mutagenicity. In two separate cross-sectional studies of nonsmokers, organic extracts of urine were evaluated for mutagenicity levels using strain YG1041 in the Salmonella (Ames) mutagenicity assay. First, we compared levels among 10 female bituminous (smoky) coal users from Laibin, Xuanwei, China, and 10 female anthracite (smokeless) coal users. We estimated exposure-response relationships using indoor air concentrations of two carcinogens in CCE relevant to lung cancer, 5-methylchrysene (5MC), and benzo[a]pyrene (B[a]P). Second, we compared levels among 20 highly exposed male diesel factory workers and 15 unexposed male controls; we evaluated exposure-response relationships using elemental carbon (EC) as a DEE-surrogate. Age-adjusted linear regression was used to estimate associations. Laibin smoky coal users had significantly higher average urinary mutagenicity levels compared to smokeless coal users (28.4 ± 14.0 SD vs. 0.9 ± 2.8 SD rev/ml-eq, p = 2 × 10-5 ) and a significant exposure-response relationship with 5MC (p = 7 × 10-4 ). DEE-exposed workers had significantly higher urinary mutagenicity levels compared to unexposed controls (13.0 ± 10.1 SD vs. 5.6 ± 4.4 SD rev/ml-eq, p = .02) and a significant exposure-response relationship with EC (p-trend = 2 × 10-3 ). Exposure to CCE and DEE is associated with urinary mutagenicity, suggesting systemic exposure to mutagens, potentially contributing to cancer risk and development at various sites.

The concept of the exposome was introduced over 15 years ago to reflect the important role that the environment exerts on health and disease. While originally viewed as a call-to-arms to develop more comprehensive exposure assessment methods applicable at the individual level and throughout the life course, the scope of the exposome has now expanded to include the associated biological response. In order to explore these concepts, a workshop was hosted by the Gunma University Initiative for Advanced Research (GIAR, Japan) to discuss the scope of exposomics from an international and multidisciplinary perspective. This Global Perspective is a summary of the discussions with emphasis on (1) top-down, bottom-up, and functional approaches to exposomics, (2) the need for integration and standardization of LC- and GC-based high-resolution mass spectrometry methods for untargeted exposome analyses, (3) the design of an exposomics study, (4) the requirement for open science workflows including mass spectral libraries and public databases, (5) the necessity for large investments in mass spectrometry infrastructure in order to sequence the exposome, and (6) the role of the exposome in precision medicine and nutrition to create personalized environmental exposure profiles. Recommendations are made on key issues to encourage continued advancement and cooperation in exposomics.

Background Alzheimer’s disease (AD) is a complex neurological disorder with contributions from genetic and environmental factors. High‐resolution metabolomics (HRM) has the potential to identify novel endogenous and environmental factors involved in AD. Previous metabolomics studies have identified circulating metabolites linked to AD, but lack of replication and inconsistent diagnostic algorithms have hindered the generalizability of these findings. Here we applied HRM to identify plasma metabolic and environmental factors associated with AD in two study samples, with cerebrospinal fluid (CSF) biomarkers of AD incorporated to achieve high diagnostic accuracy. Methods Liquid chromatography‐mass spectrometry (LC–MS)‐based HRM was used to identify plasma and CSF metabolites associated with AD diagnosis and CSF AD biomarkers in two studies of prevalent AD (Study 1: 43 AD cases, 45 mild cognitive impairment [MCI] cases, 41 controls; Study 2: 50 AD cases, 18 controls). AD‐associated metabolites were identified using a metabolome‐wide association study (MWAS) framework. Results An MWAS meta‐analysis identified three non‐medication AD‐associated metabolites in plasma, including elevated levels of glutamine and an unknown halogenated compound and lower levels of piperine, a dietary alkaloid. The non‐medication metabolites were correlated with CSF AD biomarkers, and glutamine and the unknown halogenated compound were also detected in CSF. Furthermore, in Study 1, the unknown compound and piperine were altered in MCI patients in the same direction as AD dementia. Conclusions In plasma, AD was reproducibly associated with elevated levels of glutamine and a halogen‐containing compound and reduced levels of piperine. These findings provide further evidence that exposures and behavior may modify AD risks.

Objective This paper provides an overview of our Military Biomarkers Research Study (MBRS) designed to assess whether biomarkers can be used to retrospectively assess deployment exposures and health impacts related to deployment environmental exposures. Methods The MBRS consists of four phases. Phase I was a feasibility study of stored sera. Phase II looks at associations between exposures and biomarkers. Phase III examines relationships of biomarkers and health outcomes, and Phase IV investigates in vitro biomarker changes associated with exposures to chemicals of interest. This paper briefly summarizes work already published and introduces the new reports contained in this supplement. Results Novel biomarkers were identified. These were associated with deployment exposures. Conclusions Significant associations were noted between deployment exposures, microRNA biomarkers and metabolomic biomarkers, and deployment health outcomes.

Objective The potential health risks of deployment to sites with open burn pits remain poorly understood, in part, because personal exposure monitoring was not performed. Here, we investigated whether postdeployment serum samples contain biomarkers associated with exposure to burn pits. Methods A total of 237 biomarkers were measured in 800 serum samples from deployed and never-deployed subjects. We used a regression model and a supervised vector machine to identify serum biomarkers with significant associations with exposures and deployment. Results We identified 101 serum biomarkers associated with polycyclic aromatic hydrocarbons, dioxins or furans, and 54 biomarkers associated with deployment. Twenty-six of these biomarkers were shared in common by the exposure and deployment groups. Conclusions We identify a potential signature of exposure to open burn pits, and provide a framework for using postexposure sera to identify exposures when contemporaneous monitoring was inadequate.

Objective To develop a computational approach to link clinical outcomes with environmental exposures and molecular variations measured in Department of Defense (DOD) serum-repository samples. Methods International Classification of Diseases, Ninth Division codes which corresponded to cardiopulmonary symptoms for service personnel were selected to test for associations with deployment-related inhalation hazards and metabolomics, micro-RNA, cytokine, plasma markers, and environmental exposure analyses for corresponding samples. xMWAS and Mummichog were used for integrative network and pathway analysis. Results Comparison between 41 personnel exhibiting new cardio-pulmonary diagnoses after deployment start-date to 25 personnel exhibiting no symptoms identified biomarkers associated with cardiopulmonary conditions. Integrative network and pathway analysis showed communities of clinical, molecular, and environmental markers associated with fatty acid, lipid, nucleotide, and amino acid metabolism pathways. Conclusions The current proof of principle study establishes a computational framework for integrative analysis of deployment-related exposures, molecular responses, and health outcomes.

Objective To use high-resolution metabolomics (HRM) to identify metabolic changes in military personnel associated with deployment to Balad, Iraq, or Bagram, Afghanistan. Methods Pre- and post-deployment samples were obtained from the Department of Defense Serum Repository (DoDSR). HRM and bioinformatics were used to identify metabolic differences associated with deployment. Results Differences at baseline (pre-deployment) between personnel deployed to Bagram compared with Balad or Controls included sex hormone and keratan sulfate metabolism. Deployment to Balad was associated with alterations to amino acid and lipid metabolism, consistent with inflammation and oxidative stress, and pathways linked to metabolic adaptation and repair. Difference associated with deployment to Bagram included lipid pathways linked to cell signaling and inflammation. Conclusions Metabolic variations in pre- and post-deployment are consistent with deployment-associated responses to air pollution and other environmental stressors.

Background: Mechanisms underlying the effects of traffic-related air pollution on people with asthma remain largely unknown, despite the abundance of observational and controlled studies reporting associations between traffic sources and asthma exacerbation and hospitalizations. Objectives: To identify molecular pathways perturbed following traffic pollution exposures, we analyzed data as part of the Atlanta Commuters Exposure (ACE-2) study, a crossover panel of commuters with and without asthma. Methods: We measured 27 air pollutants and conducted high-resolution metabolomics profiling on blood samples from 45 commuters before and after each exposure session. We evaluated metabolite and metabolic pathway perturbations using an untargeted metabolome-wide association study framework with pathway analyses and chemical annotation. Results: Most of the measured pollutants were elevated in highway commutes (p

Objective: To examine the prospective associations between exposure to perfluoroalkyl substances (PFASs) and longitudinal measurements of glucose metabolism in high-risk overweight and obese Hispanic children. Methods: Forty overweight and obese Hispanic children (8–14 years) from urban Los Angeles underwent clinical measures and 2-hour oral glucose tolerance tests (OGTT) at baseline and a follow-up visit (range: 1–3 years after enrollment). Baseline plasma perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS), perfluorohexane sulfonic acid (PFHxS), and the plasma metabolome were measured by liquid-chromatography with high-resolution mass spectrometry. Multiple linear regression models were used to assess the association between baseline PFASs and changes in glucose homeostasis over follow-up. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with plasma PFASs concentrations. We performed a structural integrated analysis aiming to characterize the joint impact of all factors and to identify latent clusters of children with alterations in glucose homeostasis, based on their exposure and metabolomics profile. Results: Each ln (ng/ml) increase in PFOA and PFHxS concentrations was associated with a 30.6 mg/dL (95% CI: 8.8–52.4) and 10.2 mg/dL (95% CI: 2.7–17.7) increase in 2-hour glucose levels, respectively. A ln (ng/ml) increase in PFHxS concentrations was also associated with 17.8 mg/dL increase in the glucose area under the curve (95% CI: 1.5–34.1). Pathway enrichment analysis showed significant alterations of lipids (e.g., glycosphingolipids, linoleic acid, and de novo lipogenesis), and amino acids (e.g., aspartate and asparagine, tyrosine, arginine and proline) in association to PFASs exposure. The integrated analysis identified a cluster of children with increased 2-h glucose levels over follow up, characterized by increased PFAS levels and altered metabolite patterns. Conclusions: This proof-of-concept analysis shows that higher PFAS exposure was associated with dysregulation of several lipid and amino acid pathways and longitudinal alterations in glucose homeostasis in Hispanic youth. Larger studies are needed to confirm these findings and fully elucidate the underlying biological mechanisms. Keywords: Perfluoroalkyl substances, Type 2 diabetes, Glucose metabolism, Metabolomics, Children

Although polychlorinated biphenyls and polybrominated biphenyls are no longer manufactured the United States, biomonitoring in human populations show that exposure to these pollutants persist in human tissues. The objective of this study was to identify metabolic variations associated with exposure to 2,2’4,4’,5,5’-hexabromobiphenyl (PBB-153) and 2,2’4,4’,5,5’-hexachlorobiphenyl (PCB-153) in two generations of participants enrolled in the Michigan PBB Registry (http://pbbregistry.emory.edu/). Untargeted, high-resolution metabolomic profiling of plasma collected from 156 individuals was completed using liquid chromatography with high-resolution mass spectrometry. PBB-153 and PCB-153 levels were measured in the same individuals using targeted gas chromatography-tandem mass spectrometry and tested for dose-dependent correlation with the metabolome. Biological response to these exposures were evaluated using identified endogenous metabolites and pathway enrichment. When compared to lipid-adjusted concentrations for adults in the National Health and Nutrition Examination Survey (NHANES) for years 2003–2004, PCB-153 levels were consistent with similarly aged individuals, whereas PBB-153 concentrations were elevated (p

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. 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. 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.

ObjectivesThe occupational exposure limit for trichloroethylene (TCE) in different countries varies from 1 to 100 ppm as an 8-hour time-weighted average (TWA). Many countries currently use 10 ppm as the regulatory standard for occupational exposures, but the biological effects in humans at this level of exposure remain unclear. The objective of our study was to evaluate alterations in immune and renal biomarkers among workers occupationally exposed to low levels of TCE below current regulatory standards.MethodsWe conducted a cross-sectional molecular epidemiology study of 80 healthy workers exposed to a wide range of TCE (ie, 0.4–229 ppm) and 96 comparable unexposed controls in China, and previously reported that TCE exposure was associated with multiple candidate biological markers related to immune function and kidney toxicity. Here, we conducted further analyses of all of the 31 biomarkers that we have measured to determine the magnitude and statistical significance of changes in the subgroup of workers (n=35) exposed to ResultsSix immune biomarkers (ie, CD4+ effector memory T cells, sCD27, sCD30, interleukin-10, IgG and IgM) were significantly decreased (% difference ranged from −16.0% to −72.1%) and one kidney toxicity marker (kidney injury molecule-1, KIM-1) was significantly increased (% difference: +52.5%) among workers exposed to ConclusionOur results suggest that occupational exposure to TCE below 10 ppm as an 8-hour TWA may alter levels of key markers of immune function and kidney toxicity.

Prevalence of autism spectrum disorder (ASD) has been increasing in the United States in the past decades. The exact mechanisms remain enigmatic, and diagnosis of the disease still relies primarily on assessment of behavior. We first used a case–control design (75 idiopathic cases and 29 controls, enrolled at Boston Children’s Hospital from 2007-2012) to identify plasma biomarkers of ASD through a metabolome-wide association study approach. Then we leveraged a family-based design (31 families) to investigate the influence of shared genetic and environmental components on the autism-associated features. Using untargeted high-resolution mass spectrometry metabolomics platforms, we detected 19 184 features. Of these, 191 were associated with ASD (false discovery rate < 0.05). We putatively annotated 30 features that had an odds ratio (OR) between

BACKGROUND: Previously, numerous epidemiologic studies reported an association between autism spectrum disorder (ASD) and exposure to air pollution during pregnancy. However, there have been no metabolomics studies investigating the impact of pregnancy pollution exposure to ASD risk in offspring. OBJECTIVES: To identify differences in maternal metabolism that may reflect a biological response to exposure to high air pollution in pregnancies of offspring who later did or did not develop ASD. METHODS: We obtained stored mid-pregnancy serum from 214 mothers who lived in California’s Central Valley and experienced the highest levels of air pollution during early pregnancy. We estimated each woman’s average traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter

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

Pregnant women with epilepsy (PWWE) require continuous anti-epileptic drug (AED) treatment to avoid risk to themselves and fetal risks secondary to maternal seizures, resulting in prolonged AED exposure to the developing embryo and fetus. The objectives of this study were to determine whether high-resolution metabolomics is able to link the metabolite profile of PWWE receiving lamotrigine or levetiracetam for seizure control to associated pharmacodynamic (PD) biological responses. Untargeted metabolomic analysis of plasma obtained from 82 PWWE was completed using high-resolution mass spectrometry. Biological alterations due to lamotrigine or levetiracetam monotherapy were determined by a metabolome-wide association study that compared patients taking either drug to those who did not require AED treatment. Metabolic changes associated with AED use were then evaluated by testing for drug-dose associated metabolic variations and pathway enrichment. AED therapy resulted in drug-associated metabolic profiles recognizable within maternal plasma. Both the parent compounds and major metabolites were detected, and each AED was correlated with other metabolic features and pathways. Changes in metabolites and metabolic pathways important to maternal health and linked to fetal neurodevelopment were detected for both drugs, including changes in one‑carbon metabolism, neurotransmitter biosynthesis and steroid metabolism. In addition, decreased levels of 5-methyltetrahydrofolate and tetrahydrofolate were detected in women taking lamotrigine, which is consistent with recent findings showing increased risk of autism spectrum disorder traits in PWWE using AED. These results represent a first step in development of pharmacometabolomic framework with potential to detect adverse AED-related metabolic changes during pregnancy.

Background Near highway residents are exposed to elevated levels of traffic-related air pollution (TRAP), including ultrafine particles, which are associated with adverse health effects. The efficacy of using in-home air filtration units that reduce exposure and potentially yield health benefits has not been tested in a randomized controlled trial. Methods We will conduct a randomized double-blind crossover trial of portable air filtration units for 200 adults 30 years and older who live in near-highway homes in Somerville, MA, USA. We will recruit participants from 172 households. The intervention periods will be one month of true or sham filtration, followed by a one-month wash out period and then a month of the alternate intervention. The primary health outcome will be systolic blood pressure (BP); secondary outcome measures will include diastolic and central BP, C-Reactive Protein (CRP) and D-dimer. Reasons for success or failure of the intervention will be evaluated in a subset of homes using indoor/outdoor monitoring for particulate pollution, personal monitoring, size and composition of particulate pollution, tracking of time spent in the room with the filter, and interviews for qualitative feedback. Results This trial has begun recruitment and is expected to take 2–3 years to be completed. Recruitment has been particularly challenging because of additional precautions required by the COVID-19 pandemic. Discussion This study has the potential to shed light on the value of using portable air filtration in homes close to highways to reduce exposure to TRAP and whether doing so has benefits for cardiovascular health.

ADAP-GC is an automated computational workflow for extracting metabolite information from raw, untargeted gas chromatography-mass spectrometry metabolomics data. Deconvolution of coeluting analytes is a critical step in the workflow, and the underlying algorithm is able to extract fragmentation mass spectra of coeluting analytes with high accuracy. However, its latest version ADAP-GC 3.0 was not user-friendly. To make ADAP-GC easier to use, we have developed ADAP-GC 3.2 and describe here the improvements on three aspects. First, all of the algorithms in ADAP-GC 3.0 written in R have been replaced by their analogues in Java and incorporated into MZmine 2 to make the workflow user-friendly. Second, the clustering algorithm DBSCAN has replaced the original hierarchical clustering to allow faster spectral deconvolution. Finally, algorithms originally developed for constructing extracted ion chromatograms (EICs) and detecting EIC peaks from LC-MS data are incorporated into the ADAP-GC workflow, allowing the latter to process high mass resolution data. Performance of ADAP-GC 3.2 has been evaluated using unit mass resolution data from standard-mixture and urine samples. The identification and quantitation results were compared with those produced by ADAP-GC 3.0, AMDIS, AnalyzerPro, and ChromaTOF. Identification results for high mass resolution data derived from standard-mixture samples are presented as well.

Background Toxicant-associated steatohepatitis has been described in adults but less is known regarding the role of toxicants in liver disease of children. Perfluoroalkyl substances (PFAS) cause hepatic steatosis in rodents, but few previous studies have examined PFAS effects on severity of liver injury in children. Objectives We aimed to examine the relationship of PFAS to histologic severity of nonalcoholic fatty liver disease (NAFLD) in children. Methods Seventy-four children with physician-diagnosed NAFLD were recruited from Children’s Healthcare of Atlanta between 2007 and 2015. Biopsy-based liver histological features were scored for steatosis, lobular and portal inflammation, ballooning, and fibrosis. Plasma concentrations of perfluorooctanoic acid (PFOA), perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonic acid (PFHxS), and untargeted plasma metabolomic profiling, were determined using liquid chromatography with high-resolution mass spectrometry. A metabolome-wide association study coupled with pathway enrichment analysis was performed to evaluate metabolic dysregulation associated with PFAS. A structural integrated analysis was applied to identify latent clusters of children with more severe form of NAFLD based on their PFAS levels and metabolite pattern. Results Patients were 7–19 years old, mostly boys (71%), Hispanic (51%), and obese (85%). The odds of having nonalcoholic steatohepatitis (NASH), compared to children with steatosis alone, was significantly increased with each interquartile range (IQR) increase of PFOS (OR: 3.32, 95% CI: 1.40–7.87) and PFHxS (OR: 4.18, 95% CI: 1.64–10.7). Each IQR increase of PFHxS was associated with increased odds for liver fibrosis (OR: 4.44, 95% CI: 1.34–14.8), lobular inflammation (OR: 2.87, 95% CI: 1.12–7.31), and higher NAFLD activity score (β coefficient 0.46; 95% CI: 0.03, 0.89). A novel integrative analysis identified a cluster of children with NASH, characterized by increased PFAS levels and altered metabolite patterns including higher plasma levels of phosphoethanolamine, tyrosine, phenylalanine, aspartate and creatine, and decreased plasma levels of betaine. Conclusions Ηigher PFAS exposure was associated with more severe disease in children with NAFLD. PFAS may be an important toxicant contributing to NAFLD progression; however larger, longitudinal studies are warranted to confirm these findings.

BackgroundInsulin impairment and inflammation are two features common to type 2 diabetes and Alzheimer’s disease; however, the molecular and signaling interactions underlying this relationship are not well understood. Mounting evidence point to the associations between the disruption of metabolite processing in insulin impairment and neurodegenerative conditions such as Alzheimer’s. Although the brain depends partially on metabolites processed in the periphery, to date, little is known about how soluble tumor necrosis factor signaling (solTNF) impacts integrated peripheral immune and metabolic feedback signals in states of energy overload and insulin insensitivity.MethodsC57Bl/6J mice were fed a high-fat high-carbohydrate diet (HFHC) for 14 weeks. The brain-permeant biologic XPro1595® was used to block solTNF-dependent pathways. Metabolic and immune alterations were evaluated in the gut, liver, and brain. Behavioral tests were performed. Untargeted metabolomics was carried out in the plasma and liver.ResultsHFHC diet promotes central insulin impairment and dysregulation of immune-modulatory gene expressed in the brain. Alteration of metabolites associated with type 2 diabetes and Alzheimer’s such as butanoate, glutamate, biopterin, branched-chain amino acids, purines, and proteoglycan metabolism was observed in HFHC-fed mice. solTNF inhibition ameliorates hepatic metabolic disturbances and hepatic and intestinal lipocalin-2 levels, and decreases insulin impairment in the brain and behavioral deficits associated with HFHC diet.ConclusionsOur novel findings suggest that HFHC diet impacts central insulin signaling and immune-metabolic interactions in a solTNF-dependent manner to increase the risk for neurodegenerative conditions. Our novel findings indicate that selective solTNF neutralization can ameliorate peripheral and central diet-induced insulin impairment and identify lipocalin-2 as a potential target for therapeutic intervention to target inflammation and insulin disturbances in obesogenic environments. Collectively, our findings identify solTNF as a potential target for therapeutic intervention in inflammatory states and insulin disturbances in obesogenic environments to lower risk for AD.

Background: Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and neurodevelopmental disorders. By utilizing high-resolution metabolomics (HRM), we investigated perturbations of the maternal serum metabolome in response to traffic-related air pollution to identify biological mechanisms. Methods: We retrieved stored mid-pregnancy serum samples from 160 mothers who lived in the Central Valley of California known for high air particulate levels. We estimated prenatal traffic-related air pollution exposure (carbon monoxide, nitric oxides, and particulate matter

Key Points Question What is the association of metabolomic biomarkers with lung cancer in women who have never smoked? Findings In this case-control study of 275 never-smoking women with lung cancer and 289 never-smoking cancer-free women in China, the metabolite 5-methyl-2-furoic acid was correlated with dietary soy consumption and pathways including 1-carbon metabolism, oxidative stress, nucleotide metabolism, and inflammation and was significantly associated with lower lung cancer risk. Meaning These findings suggest that certain metabolites and pathways are associated with lower lung cancer risk in never-smoking women and biological processes linked to air pollution may be associated with higher lung cancer risk in this population., This case-control study investigates the association between urinary metabolomic biomarkers and lung cancer risk among never-smoking women in China., Importance Chinese women have the highest rate of lung cancer among female never-smokers in the world, and the etiology is poorly understood. Objective To assess the association between metabolomics and lung cancer risk among never-smoking women. Design, Setting, and Participants This nested case-control study included 275 never-smoking female patients with lung cancer and 289 never-smoking cancer-free control participants from the prospective Shanghai Women’s Health Study recruited from December 28, 1996, to May 23, 2000. Validated food frequency questionnaires were used for the collection of dietary information. Metabolomic analysis was conducted from November 13, 2015, to January 6, 2016. Data analysis was conducted from January 6, 2016, to November 29, 2018. Exposures Untargeted ultra-high-performance liquid chromatography–tandem mass spectrometry and nuclear magnetic resonance metabolomic profiles were characterized using prediagnosis urine samples. A total of 39 416 metabolites were measured. Main Outcomes and Measures Incident lung cancer. Results Among the 564 women, those who developed lung cancer (275 participants; median [interquartile range] age, 61.0 [52-65] years) and those who did not develop lung cancer (289 participants; median [interquartile range] age, 62.0 [53-66] years) at follow-up (median [interquartile range] follow-up, 10.9 [9.0-11.7] years) were similar in terms of their secondhand smoke exposure, history of respiratory diseases, and body mass index. A peak metabolite, identified as 5-methyl-2-furoic acid, was significantly associated with lower lung cancer risk (odds ratio, 0.57 [95% CI, 0.46-0.72]; P

Background Advances in untargeted metabolomic technologies have great potential for insight into adverse metabolic effects underlying exposure to environmental chemicals. However, important challenges need to be addressed, including how biological response corresponds to the environmental chemical burden in different target tissues. Aim We performed a pilot study using state-of-the-art ultra-high-resolution mass spectrometry (UHRMS) to characterize the burden of lipophilic persistent organic pollutants (POPs) in metabolic tissues and associated alterations in the plasma metabolome. Methods We studied 11 adolescents with severe obesity at the time of bariatric surgery. We measured 18 POPs that can act as endocrine and metabolic disruptors (i.e. 2 dioxins, 11 organochlorine compounds [OCs] and 5 polybrominated diphenyl ethers [PBDEs]) in visceral and subcutaneous abdominal adipose tissue (vAT and sAT), and liver samples using gas chromatography with UHRMS. Biological pathways were evaluated by measuring the plasma metabolome using high-resolution metabolomics. Network and pathway enrichment analysis assessed correlations between the tissue-specific burden of three frequently detected POPs (i.e. p,p’-dichlorodiphenyldichloroethene [DDE], hexachlorobenzene [HCB] and PBDE-47) and plasma metabolic pathways. Results Concentrations of 4 OCs and 3 PBDEs were quantifiable in at least one metabolic tissue for > 80% of participants. All POPs had the highest median concentrations in adipose tissue, especially sAT, except for PBDE-154, which had comparable average concentrations across all tissues. Pathway analysis showed high correlations between tissue-specific POPs and metabolic alterations in pathways of amino acid metabolism, lipid and fatty acid metabolism, and carbohydrate metabolism. Conclusions Most of the measured POPs appear to accumulate preferentially in adipose tissue compared to liver. Findings of plasma metabolic pathways potentially associated with tissue-specific POPs concentrations merit further investigation in larger populations.

INTRODUCTION: Exposure to perfluoroalkyl substances (PFAS), synthetic and persistent chemicals used in commercial and industrial processes, are associated with cardiometabolic dysfunction and related risk factors including reduced birth weight, excess adiposity, dyslipidemia, and insulin resistance. Identifying the metabolic changes induced by PFAS exposure could enhance our understanding of biological pathways underlying PFAS toxicity. OBJECTIVE: To identify metabolic alterations associated with serum concentrations of four PFAS in children using a metabolome-wide association study. METHODS: We performed untargeted metabolomic profiling by liquid chromatography with ultra-high-resolution mass spectrometry, and separately quantified serum concentrations of perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), perfluorononanoic acid (PFNA), and perfluorohexanesulphonic acid (PFHxS) for 114 8-year old children from Cincinnati, OH. We evaluated associations between each serum PFAS concentration and 16,097 metabolic features using linear regression adjusted for child age, sex, and race with a false discovery rate

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Tissue interstitial fluid (ISF) surrounds cells and is an underutilized source of biomarkers that complements conventional sources such as blood and urine. However, ISF has received limited attention due largely to lack of simple collection methods. Here, we developed a minimally invasive, microneedle-based method to sample ISF from human skin that was well tolerated by participants. Using a microneedle patch to create an array of micropores in skin coupled with mild suction, we sampled ISF from 21 human participants and identified clinically relevant and sometimes distinct biomarkers in ISF when compared to companion plasma samples based on mass spectrometry analysis. Many biomarkers used in research and current clinical practice were common to ISF and plasma. Because ISF does not clot, these biomarkers could be continuously monitored in ISF similar to current continuous glucose monitors but without requiring an indwelling subcutaneous sensor. Biomarkers distinct to ISF included molecules associated with systemic and dermatological physiology, as well as exogenous compounds from environmental exposures. We also determined that pharmacokinetics of caffeine in healthy adults and pharmacodynamics of glucose in children and young adults with diabetes were similar in ISF and plasma. Overall, these studies provide a minimally invasive method to sample dermal ISF using microneedles and demonstrate human ISF as a source of biomarkers that may enable research and translation for future clinical applications.

Background: Never-smoking Chinese women have a high rate of lung cancer but the etiology is poorly understood. This study is the first to evaluate the untargeted urinary metabolome and risk of lung...

Parkinson’s disease (PD) is a progressive neurological disorder caused by a combination of genetic and environmental factors. Metabolomics is a powerful tool that can be used to screen for potential biomarkers, exogenous toxicants, and metabolic network changes associated with disease states. Here, we used high-resolution metabolomics to compare over 10,000 plasma metabolic features from older adults with and without PD in an untargeted approach. We performed a network analysis that demonstrates that the presence of the PD drug levodopa influences variation observed between PD and control patients. Metabolome wide association studies and discrimination analysis identified significant differentiation in the metabolomics profile of older adults with and without PD. Notably, 15 metabolic features (ten of which we putatively identified) differed between PD and control adults with p < 0.05 and a corrected false discovery rate less than 20%. Furthermore, 13 metabolic networks were identified to be functionally different between PD and non-PD patients. Lastly, the dopaminergic toxic intermediate DOPAL differed between PD and non-PD populations, which supports the dopaminergic sequestration model of PD. These individual metabolites and metabolic networks have been implicated in past PD pathogenesis models, including the beta-carboline harmalol and the glycosphingolipid metabolism pathway including the ganglioside GM2. We recommend that future studies take into account the confounding effects of levodopa in metabolomic analyses of disease versus control patients, and encourage validation of several promising metabolic markers of PD.

Reduction in the deposition of amyloid β (Aβ) has been the primary target for Alzheimer's disease (AD) therapeutics recently, but in clinical trials this approach has generally been unsuccessful. A common feature of AD pathology is a complex inflammatory component that could be a target for treatment. One feature of this inflammation has been the involvement of the receptor for advanced glycation endproducts (RAGE), whose ligands include advanced glycation-endproduct-modified proteins as well as lipids and Aβ, which are found at elevated levels in AD brains.In this article, the authors describe the key features of RAGE and how it could have a role in AD pathogenesis. They also summarize experimental animal and clinical data that demonstrate the therapeutic effect of RAGE inhibition and consider what these findings mean for human disease.RAGE has multiple ligands, including Aβ, that are increased in AD brains. Inhibiting RAGE-ligand interactions without activating receptor signaling can reduce multiple pathological pathways relevant for AD. Several RAGE inhibitors and modulators are now being tested as therapeutics for AD. Recent Phase II studies have established the good safety and tolerability of TTP448 with some evidence of positive benefit at lower dose. This suggests that further studies are required.

Background Cystic fibrosis (CF) is a chronic catabolic disease often requiring hospitalization for acute episodes of worsening pulmonary exacerbations. Limited data suggest that vitamin D may have beneficial clinical effects, but the impact of vitamin D on systemic metabolism in this setting is unknown. Objective We used high-resolution metabolomics (HRM) to assess the impact of baseline vitamin D status and high-dose vitamin D3 administration on systemic metabolism in adults with CF with an acute pulmonary exacerbation. Design Twenty-five hospitalized adults with CF were enrolled in a randomized trial of high-dose vitamin D3 (250,000 IU vitamin D3 bolus) versus placebo. Age-matched healthy subjects served as a reference group for baseline comparisons. Plasma was analyzed with liquid chromatography/ultra-high resolution mass spectrometry. Using recent HRM bioinformatics and metabolic pathway enrichment methods, we examined associations with baseline vitamin D status (sufficient vs. deficient per serum 25-hydroxyvitamin D concentrations) and the 7-day response to vitamin D3 supplementation. Results Several amino acids and lipid metabolites differed between CF and healthy control subjects, indicative of an overall catabolic state. In CF subjects, 343 metabolites differed (P Conclusions Numerous metabolic pathways detected by HRM varied in association with vitamin D status and high-dose vitamin D3 supplementation in adults with CF experiencing a pulmonary exacerbation. Overall, these pilot data suggest an anti-catabolic effect of high-dose vitamin D3 in this clinical setting.

OBJECTIVE The aim of this study was to test the utility of high-resolution metabolomics (HRM) for analysis of nutritional status and health indicators in military personnel. METHODS Serum samples from 400 military personnel were obtained from the Department of Defense Serum Repository (DoDSR) and analyzed for metabolites related to nutrition and health status. Metabolic profile organization was studied using modulated modularity clustering (MMC). RESULTS HRM provided quantitative measures of 61 metabolites across chemical classes for use as nutritional and clinical biomarkers. Levels were comparable to reported values except for arginine and glutamine, which were above and below reference ranges, respectively. MMC generated five clusters, three of which were associated and contained amino acids. The others contained lipids and mitochondria-related metabolites. CONCLUSIONS HRM analysis of serum is suitable for real-time and/or retrospective evaluation of nutrition and health status of specific military cohorts.

Objective This paper provides an overview of our study that was designed to assess the health impact of environmental exposures to open pit burning in deployed troops. Methods The rationale for the study and the structure of the research plan was laid out. An overview of each article in the supplement was provided. The cohort of deployed Service members was assessed for airborne exposure, relevant biomarkers, and health outcomes following deployment to Balad, Iraq, and/or Bagram, Afghanistan. Results Polycyclic aromatic hydrocarbon (PAH) exposures were elevated, and serum biomarkers were statistically different postdeployment. Associations were noted between PAHs and dioxins and microRNAs. Some health outcomes were evident in deployers compared with nondeployers. Conclusions Future research will examine the associations between demographic variables, smoking status, biomarker levels, and related health outcomes.

The aim of this study is to use high-resolution metabolomics (HRM) to identify metabolic pathways and networks associated with tobacco use in military personnel.Four hundred deidentified samples obtained from the Department of Defense Serum Repository were classified as tobacco users or nonusers according to cotinine content. HRM and bioinformatic methods were used to determine pathways and networks associated with classification.Eighty individuals were classified as tobacco users compared with 320 nonusers on the basis of cotinine levels at least 10 ng/mL. Alterations in lipid and xenobiotic metabolism, and diverse effects on amino acid, sialic acid, and purine and pyrimidine metabolism were observed. Importantly, network analysis showed broad effects on metabolic associations not simply linked to well-defined pathways.Tobacco use has complex metabolic effects that must be considered in evaluation of deployment-associated environmental exposures in military personnel.