Global metabolomic profiling reveals an association of metal fume exposure and plasma unsaturated fatty acids

Air pollution exposure and plasma fatty acid profile in pregnant women: a cohort study

Air pollution exposure was known to result in body impairments by inducing inflammation and oxidation. But little is known about the associations of air pollutants with plasma fatty acid profile which may play important roles in the impairment of air pollutants based on the related mechanism, especially in pregnant women. This study aimed to explore the relationships of air pollution exposure with plasma fatty acid profile and the potential effect modification by pre-pregnancy body mass index (BMI). Based on a cohort in Wuhan, China, we measured concentrations of plasma fatty acids of 519 pregnant women enrolled from 2013 to 2016 by gas chromatography-mass spectrometry (GC-MS). Levels of exposure to air pollutants (fine particulate matter (PM2.5), inhalable particles (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and carbon monoxide (CO)) were estimated by using spatial-temporal land use regression models and calculated in three periods (average concentrations during 1 day, 1 week, and 1 month before the phlebotomizing day in the first trimester). Per interquartile range increment of the levels of air pollution exposure 1 day before phlebotomizing was related to 1.21-2.01% increment of omega-6 polyunsaturated fatty acids (n-6PUFA) and 0.63-1.74% decrement of omega-3 polyunsaturated fatty acids (n-3PUFA). Besides, relationships above were kept robust in the analysis during 1 week and 1 month before phlebotomizing. In women with normal BMI, plasma fatty acid profile was observed to be more sensitive to air pollutants. Our study demonstrated that increment of exposure to air pollutants was associated with higher plasma n-6PUFA known to be pro-inflammatory and lower plasma n-3PUFA known to be anti-inflammatory, which was more sensitive in pregnant women with normal BMI. Our findings suggested that changes in plasma fatty acid profile should cause concerns and may serve as biomarkers in the further studies. Future studies are needed to validate our findings and elucidate the underlying mechanisms.

Analysis of serum metabolome of laborers exposure to welding fume

OBJECTIVE

Welding fume exposure is inevitable of welding workers and poses a severe hazard to their health since welding is a necessary industrial process. Thus, preclinical diagnostic symptoms of worker exposure are of great importance. The aim of this study was to screen serum differential metabolites of welding fume exposure based on UPLC-QTOF-MS/MS.

METHODS

In 2019, 49 participants were recruited at a machinery manufacturing factory. The non-target metabolomics technique was used to clarify serum metabolic signatures in people exposed to welding fume. Differential metabolites were screened by OPLS-DA analysis and Student's t-test. The receiver operating characteristic curve evaluated the discriminatory power of differential metabolites. And the correlations between differential metabolites and metal concentrations in urine and whole blood were analyzed utilizing Pearson correlation analysis.

RESULTS

Thirty metabolites were increased significantly, and 5 metabolites were decreased. The differential metabolites are mainly enriched in the metabolism of arachidonic acid, glycero phospholipid, linoleic acid, and thiamine. These results observed that lysophosphatidylcholine (20:1/0:0) and phosphatidylglycerol(PGF1α/16:0) had a tremendous anticipating power with relatively increased AUC values (AUC > 0.9), and they also presented a significant correlation of Mo concentrations in whole blood and Cu concentrations in urine, respectively.

CONCLUSION

The serum metabolism was changed significantly after exposure to welding fume. Lysophosphatidylcholine (20:1/0:0) and phosphatidylglycerol (PGF1α/16:0) may be a potential biological mediator and biomarker for laborers exposure to welding fume.

A State-of-the-Science Review on High-Resolution Metabolomics Application in Air Pollution Health Research: Current Progress, Analytical Challenges, and Recommendations for Future Direction

BACKGROUND

Understanding the mechanistic basis of air pollution toxicity is dependent on accurately characterizing both exposure and biological responses. Untargeted metabolomics, an analysis of small-molecule metabolic phenotypes, may offer improved estimation of exposures and corresponding health responses to complex environmental mixtures such as air pollution. The field remains nascent, however, with questions concerning the coherence and generalizability of findings across studies, study designs and analytical platforms.

OBJECTIVES

We aimed to review the state of air pollution research from studies using untargeted high-resolution metabolomics (HRM), highlight the areas of concordance and dissimilarity in methodological approaches and reported findings, and discuss a path forward for future use of this analytical platform in air pollution research.

METHODS

We conducted a state-of-the-science review to a) summarize recent research of air pollution studies using untargeted metabolomics and b) identify gaps in the peer-reviewed literature and opportunities for addressing these gaps in future designs. We screened articles published within Pubmed and Web of Science between 1 January 2005 and 31 March 2022. Two reviewers independently screened 2,065 abstracts, with discrepancies resolved by a third reviewer.

RESULTS

We identified 47 articles that applied untargeted metabolomics on serum, plasma, whole blood, urine, saliva, or other biospecimens to investigate the impact of air pollution exposures on the human metabolome. Eight hundred sixteen unique features confirmed with level-1 or -2 evidence were reported to be associated with at least one or more air pollutants. Hypoxanthine, histidine, serine, aspartate, and glutamate were among the 35 metabolites consistently exhibiting associations with multiple air pollutants in at least 5 independent studies. Oxidative stress and inflammation-related pathways-including glycerophospholipid metabolism, pyrimidine metabolism, methionine and cysteine metabolism, tyrosine metabolism, and tryptophan metabolism-were the most commonly perturbed pathways reported in > 70 % of studies. More than 80% of the reported features were not chemically annotated, limiting the interpretability and generalizability of the findings.

CONCLUSIONS

Numerous investigations have demonstrated the feasibility of using untargeted metabolomics as a platform linking exposure to internal dose and biological response. Our review of the 47 existing untargeted HRM-air pollution studies points to an underlying coherence and consistency across a range of sample analytical quantitation methods, extraction algorithms, and statistical modeling approaches. Future directions should focus on validation of these findings via hypothesis-driven protocols and technical advances in metabolic annotation and quantification. https://doi.org/10.1289/EHP11851.

Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives

INTRODUCTION

Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites.

OBJECTIVES

The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021.

RESULTS

Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures.

CONCLUSION

Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.

Biomarkers for the adverse effects on respiratory system health associated with atmospheric particulate matter exposure

Large amounts of epidemiological evidence have confirmed the atmospheric particulate matter (PM_2.5) exposure was positively correlated with the morbidity and mortality of respiratory diseases. Nevertheless, its pathogenesis remains incompletely understood, probably resulting from the activation of oxidative stress, inflammation, altered genetic and epigenetic modifications in the lung upon PM_2.5 exposure. Currently, biomarker investigations have been widely used in epidemiological and toxicological studies, which may help in understanding the biologic mechanisms underlying PM_2.5-elicited adverse health outcomes. Here, the emerging biomarkers to indicate PM_2.5-respiratory system interactions were summarized, primarily related to oxidative stress (ROS, MDA, GSH, etc.), inflammation (Interleukins, FE_NO, CC16, etc.), DNA damage (8-OHdG, γH2AX, OGG1) and also epigenetic modulation (DNA methylation, histone modification, microRNAs). The identified biomarkers shed light on PM_2.5-elicited inflammation, fibrogenesis and carcinogenesis, thus may favor more precise interventions in public health. It is worth noting that some inconsistent findings may possibly relate to the inter-study differentials in the airborne PM_2.5 sample, exposure mode and targeted subjects, as well as methodological issues. Further research, particularly by -omics technique to identify novel, specific biomarkers, is warranted to illuminate the causal relationship between PM_2.5 pollution and deleterious lung outcomes.

Analysis of serum metabolome of workers occupationally exposed to hexavalent chromium: A preliminary study

Hexavalent chromium (Cr(VI)) compound is considered as a common environmental and occupational pollutant due to widespread application in industry and agriculture. Cr(VI) as a carcinogen poses a serious threat to human health and the underlying mechanisms need further investigation. Previous studies had demonstrated the characteristic expression profiling after Cr(VI) treatment in vitro and in vivo at the levels of gene and protein. The comprehensive metabolic signatures were also conducive to discover potential biomarkers for effects assessment of Cr(VI) toxicity. In the current study, Ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) non-targeted metabolomics was applied to analyze serum metabolic changes in 77 chromate exposure workers and 62 controls. Thirteen metabolites were found significantly decreased and 41 metabolites were increased, which were involved in arginine and proline metabolism, and glycerophospholipid metabolism by bioinformatic analysis. Furthermore, there were significant negative correlations between blood Cr level and Arginine, PC(18:2/24:4) and PC(14:0/16:0), subgroup analyses indicated that these correlations were observed in male-only subgroups, and were not found among chromate workers and controls separately. Diet could be a potential confounder which was not controlled rigorously in this study. These findings provided preliminary clues to investigate the underlying mechanisms of Cr(VI)-induced toxicity and were required to be further verified in future researches.

Use of Untargeted Metabolomics to Explore the Air Pollution-Related Disease Continuum

PURPOSE OF REVIEW

The purpose of this review is to summarize the application of untargeted metabolomics to identify the perturbation of metabolites or metabolic pathways associated with air pollutant exposures.

RECENT FINDINGS

Twenty-three studies were included in this review, in adults, children, or pregnant women. The most commonly measured air pollutant is particulate matter smaller than 2.5 μm. Size-fractioned particles, particle chemical species, gas pollutants, or organic compounds were also investigated. The reviewed studies used a wide range of air pollution measurement techniques and metabolomics analyses. Identified metabolites were primarily related to oxidative stress and inflammatory responses, and a few were related to the alterations of steroid metabolic pathways. The observed metabolic perturbations can differ by disease status, sex, and age. Air pollution-related metabolic changes were also associated with health outcomes in some studies. Our review shows that air pollutant exposures are associated with metabolic pathways primarily related to oxidative stress, inflammation, as assessed through untargeted metabolomics in 23 studies. More metabolomic studies with larger sample sizes are needed to identify air pollution components most responsible for adverse health effects, elaborate on mechanisms for subpopulation susceptibility, and link air pollution exposure to specific adverse health effects.

Setting up a collaborative European human biological monitoring study on occupational exposure to hexavalent chromium

The EU human biomonitoring initiative, HBM4EU, aims to co-ordinate and advance human biomonitoring (HBM) across Europe. Within its remit, the project is gathering new, policy relevant, EU-wide data on occupational exposure to relevant priority chemicals and developing new approaches for occupational biomonitoring. In this manuscript, the hexavalent chromium [Cr(VI)] study design is presented as the first example of this HBM4EU approach. This study involves eight European countries and plans to recruit 400 workers performing Cr(VI) surface treatment e.g. electroplating or stainless steel welding activities. The aim is to collect new data on current occupational exposure to Cr(VI) in Europe and to test new methods for Cr biomonitoring, specifically the analysis of Cr(VI) in exhaled breath condensate (EBC) and Cr in red blood cells (RBC) in addition to traditional urinary total Cr analyses. Furthermore, exposure data will be complemented with early biological effects data, including genetic and epigenetic effects. Personal air samples and wipe samples are collected in parallel to help informing the biomonitoring results. We present standard operational procedures (SOPs) to support the harmonized methodologies for the collection of occupational hygiene and HBM samples in different countries.

The modification of indoor PM2.5 exposure to chronic obstructive pulmonary disease in Chinese elderly people: A meet-in-metabolite analysis

BACKGROUND

Exposure to airborne fine particulate matter (PM_2.5) has been associated with a variety of adverse health outcomes including chronic obstructive pulmonary disease (COPD). However, the linkages between PM_2.5 exposure, PM_2.5-related biomarkers, COPD-related biomarkers and COPD remain poorly elucidated.

OBJECTIVES

To investigate the linkages between PM_2.5 exposure and COPD outcome by using the meet-in-middle strategy based on urinary metabolic biomarkers.

METHODS

A cross-sectional study was designed to illustrate the mentioned quadripartite linkages. Indoor PM_2.5 and its element components were assessed in 41 Chinese elderly participants including COPD patients and their healthy spouses. Metabolic biomarkers involved in PM_2.5 exposure and COPD were identified by using urinary metabolomics. The associations between PM_2.5- and COPD-related biomarkers were investigated by statistics and metabolic pathway analysis.

RESULTS

Seven metabolites were screened and identified with significant correlations to PM_2.5 exposure, which were majorly involved in purine and amino acid metabolism as well as glycolysis. Ten COPD-related metabolic biomarkers were identified, which suggested that amino acid metabolism, lipid and fatty acid metabolism, and glucose metabolism were disturbed in the patients. Also, PM_2.5 and its many elemental components were significantly associated with COPD-related biomarkers. We observed that the two kinds of biomarkers (PM_2.5- and COPD-related) integrated in a locally connected network and the alterations of these metabolic biomarkers can biologically link PM_2.5 exposure to COPD outcome.

CONCLUSIONS

Our study indicated the modification of PM_2.5 to COPD via both modes of action of lowering participants' antioxidation capacity and decreasing their lung energy generation; this information would be valuable for the prevention strategy of COPD.

Nuclear magnetic resonance-based metabolomic investigation reveals metabolic perturbations in PM2.5-treated A549 cells

Exposure to PM_2.5 is associated with an increased risk of lung diseases, and oxidative damage is the main reason for PM_2.5-mediated lung injuries. However, little is known about the early molecular events in PM_2.5-induced lung toxicity. In the present study, the metabolites in PM_2.5-treated A549 cells were examined via a robust and nondestructive nuclear magnetic resonance (NMR)-based metabolic approach to clarify the molecular mechanism of PM_2.5-induced toxicity. NMR analysis revealed that 12 metabolites were significantly altered in PM_2.5-treated A549 cells, including up-regulation of alanine, valine, lactate, ω-6 fatty acids, and citrate and decreased levels of gamma-aminobutyric acid, acetate, leucine, isoleucine, D-glucose, lysine, and dimethylglycine. Pathway analysis demonstrated that seven metabolic pathways which included alanine, aspartate and glutamate metabolism, aminoacyl-tRNA biosynthesis, taurine and hypotaurine metabolism, arginine and proline metabolism, starch and sucrose metabolism, valine, leucine and isoleucine biosynthesis, and tricarboxylic acid cycle were mostly influenced. Our results indicate that NMR technique turns out to be a simple and reliable method for exploring the toxicity mechanism of air pollutant.

Metabolomics of World Trade Center-Lung Injury: a machine learning approach

Introduction

Biomarkers of metabolic syndrome expressed soon after World Trade Center (WTC) exposure predict development of WTC Lung Injury (WTC-LI). The metabolome remains an untapped resource with potential to comprehensively characterise many aspects of WTC-LI. This case–control study identified a clinically relevant, robust subset of metabolic contributors of WTC-LI through comprehensive high-dimensional metabolic profiling and integration of machine learning techniques.

Methods

Never-smoking, male, WTC-exposed firefighters with normal pre-9/11 lung function were segregated by post-9/11 lung function. Cases of WTC-LI (forced expiratory volume in 1s <lower limit of normal, n=15) and controls (n=15) were identified from previous cohorts. The metabolome of serum drawn within 6 months of 9/11 was quantified. Machine learning was used for dimension reduction to identify metabolites associated with WTC-LI.

Results

580 metabolites qualified for random forests (RF) analysis to identify a refined metabolite profile that yielded maximal class separation. RF of the refined profile correctly classified subjects with a 93.3% estimated success rate. 5 clusters of metabolites emerged within the refined profile. Prominent subpathways include known mediators of lung disease such as sphingolipids (elevated in cases of WTC-LI), and branched-chain amino acids (reduced in cases of WTC-LI). Principal component analysis of the refined profile explained 68.3% of variance in five components, demonstrating class separation.

Conclusion

Analysis of the metabolome of WTC-exposed 9/11 rescue workers has identified biologically plausible pathways associated with loss of lung function. Since metabolites are proximal markers of disease processes, metabolites could capture the complexity of past exposures and better inform treatment. These pathways warrant further mechanistic research.

Welding fume exposure is associated with inflammation: a global metabolomics profiling study

BACKGROUND

Increasing evidence suggests that welding fume exposure is associated with systemic inflammation. Although celluar metabolites may be associated with inflammation, there is limited information on metabolomic changes during welding fume exposure. Such changes may play an important role in the occurrence, development, and prevention of metal-associated diseases. We aim to investigate human metabolomics changes pre- and post-welding fume exposure.

METHODS

This study included 52 boilermakers totally. We collected plasma samples pre- and post-shift welding fume exposure and prepared samples using the automated MicroLab STAR® system. Metabolite concentrations were measured using ultra performance liquid chromatography - tandem mass spectrometer (UPLC-MS/MS) methods. Two-way analysis of variance was used to test the significance of metabolite changes with false discovery rate correction.

RESULTS

Analysis detected several metabolic changes after welding fume exposure, mainly involved in the lipid pathway [glucocorticoid class (cortisol, corticosterone, and cortisone), acylcarnitine class, and DiHOME species (9,10-DiHOME and 12,13-DiHOME)], amino acid utilization (isoleucine, proline and phenylalanine), and S-(3-hydroxypropyl) mercapturic acid (3-HPMA). These compounds are all associated with inflammation according to previous studies. Further, additive interaction effects linked smoking and 3-HPMA levels. In the metabolite set enrichment analysis for diseases, the top two disease-associated metabolite pathways were systemic inflammation-related diseases including rheumatoid arthritis and systemic lupus erythematosus.

CONCLUSIONS

This global metabolomics study shows evidence that metabolite changes during welding fume exposure are closely associated with systemic inflammation. The altered metabolites detected may be potential health monitoring biomarkers for boilermakers, especially for inflammation-related disease prevention.

Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study

Introduction

The Dorm Room Inhalation to Vehicle Emissions (DRIVE2) study was conducted to measure traditional single-pollutant and novel multipollutant traffic indicators along a complete emission-to-exposure pathway. The overarching goal of the study was to evaluate the suitability of these indicators for use as primary traffic exposure metrics in panel-based and small-cohort epidemiological studies.

Methods

Intensive field sampling was conducted on the campus of the Georgia Institute of Technology (GIT) between September 2014 and January 2015 at 8 monitoring sites (2 indoors and 6 outdoors) ranging from 5 m to 2.3 km from the busiest and most congested highway artery in Atlanta. In addition, 54 GIT students living in one of two dormitories either near (20 m) or far (1.4 km) from the highway were recruited to conduct personal exposure sampling and weekly biomonitoring. The pollutants measured were selected to provide information about the heterogeneous particulate and gaseous composition of primary traffic emissions, including the traditional traffic-related species (e.g., carbon monoxide [CO], nitrogen dioxide [NO2], nitric oxide [NO], fine particulate matter [PM2.5], and black carbon [BC]), and of secondary species (e.g., ozone [O3] and sulfate as well as organic carbon [OC], which is both primary and secondary) from traffic and other sources. Along with these pollutants, we also measured two multipollutant traffic indicators: integrated mobile source indicators (IMSIs) and fine particulate matter oxidative potential (FPMOP). IMSIs are derived from elemental carbon (EC), CO, and nitrogen oxide (NOx) concentrations, along with the fractions of these species emitted by gasoline and diesel vehicles, to construct integrated estimates of gasoline and diesel vehicle impacts. Our FPMOP indicator was based on an acellular assay involving the depletion of dithiothreitol (DTT), considering both water-soluble and insoluble components (referred to as FPMOPtotal-DTT). In addition, a limited assessment of 18 low-cost sensors was added to the study to supplement the four original aims.

Results

Pollutant levels measured during the study showed a low impact by this highway hotspot source on its surrounding vicinity. These findings are broadly consistent with results from other studies throughout North America showing decreased relative contributions to urban air pollution from primary traffic emissions. We view these reductions as an indication of a changing near-road environment, facilitated by the effectiveness of mobile source emission controls. Many of the primary pollutant species, including NO, CO, and BC, decreased to near background levels by 20 to 30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO2 exhibited spatial trends that differed from those of the other single-pollutant primary traffic indicators. We believe this was caused by kinetic limitations in the photochemical chemistry, associated with primary emission reductions, required to convert the NO-dominant primary NOx, emitted from automobiles, to NO2. This finding provides some indication of limitations in the use of NO2 as a primary traffic exposure indicator in panel-based health effect studies. Roadside monitoring of NO, CO, and BC tended to be more strongly correlated with sites, both near and far from the road, during morning rush hour periods and often weakly to moderately correlated during other time periods of the day. This pattern was likely associated with diurnal changes in mixing and chemistry and their impact on spatial heterogeneity across the campus. Among our candidate multipollutant primary traffic indicators, we report several key findings related to the use of oxidative potential (OP)-based indicators. Although earlier studies have reported elevated levels of FPMOP in direct exhaust emissions, we found that atmospheric processing further enhanced FPMOPtotal-DTT, likely associated with the oxidation of primary polycyclic aromatic hydrocarbons (PAHs) to quinones and hydroxyquinones and with the oxidization and water solubility of metals. This has important implications in terms both of the utility of FPMOPtotal-DTT as a marker for exhaust emissions and of the importance of atmospheric processing of particulate matter (PM) being tied to potential health outcomes. The results from the personal exposure monitoring also point to the complexity and diversity of the spatiotemporal variability patterns among the study monitoring sites and the importance of accounting for location and spatial mobility when estimating exposures in panel-based and small-cohort studies. This was most clearly demonstrated with the personal BC measurements, where ambient roadside monitoring was shown to be a poor surrogate for exposures to BC. Alternative surrogates, including ambient and indoor BC at the participants' respective dorms, were more strongly associated with personal BC, and knowledge of the participants' mean proximity to the highway was also shown to explain a substantial level of the variability in corresponding personal exposures to both BC and NO2. In addition, untargeted metabolomic indicators measured in plasma and saliva, which represent emerging methods for measuring exposure, were used to extract approximately 20,000 and 30,000 features from plasma and saliva, respectively. Using hydrophilic interaction liquid chromatography (HILIC) in the positive ion mode, we identified 221 plasma features that differed significantly between the two dorm cohorts. The bimodal distribution of these features in the HILIC column was highly idiosyncratic; one peak consisted of features with elevated intensities for participants living in the near dorm; the other consisted of features with elevated intensities for participants in the far dorm. Both peaks were characterized by relatively short retention times, indicative of the hydrophobicity of the identified features. The results from the metabolomics analyses provide a strong basis for continuing this work toward specific chemical validation of putative biomarkers of traffic-related pollution. Finally, the study had a supplemental aim of examining the performance of 18 low-cost CO, NO, NO2, O3, and PM2.5 pollutant sensors. These were colocated alongside the other study monitors and assessed for their ability to capture temporal trends observed by the reference monitoring instrumentation. Generally, we found the performance of the low-cost gas-phase sensors to be promising after extensive calibration; the uncalibrated measurements alone, however, would likely not have led to reliable results. The low-cost PM sensors we evaluated had poor accuracy, although PM sensor technology is evolving quickly and warrants future attention.

Conclusions

An immediate implication of the changing near-road environment is that future studies aimed at characterizing hotspots related to mobile sources and their impacts on health will need to consider multiple approaches for characterizing spatial gradients and exposures. Specifically and most directly, the mobile source contributions to ambient concentrations of single-pollutant indicators of traffic exposure are not as distinguishable to the degree that they have been in the past. Collectively, the study suggests that characterizing exposures to traffic-related pollutants, which is already difficult, will become more difficult because of the reduction in traffic-related emissions. Additional multi-tiered approaches should be considered along with traditional measurements, including the use of alternative OP measures beyond those based on DTT assays, metabolomics, low-cost sensors, and air quality modeling.

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

INTRODUCTION

Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explores their potential for measuring mobile-source air toxics.

METHODS

Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2 h road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization mode and resolution of 70 000 full-width at half-maximum with C18 chromatography. Data were processed using an apLCMS and xMSanalyzer on the R statistical platform.

RESULTS

The analysis yielded 7110, 6019, and 7747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41-0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics.

CONCLUSIONS

Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile-source air toxics, though further, targeted study is needed.

Metabolomics analysis reveals that benzo[a]pyrene, a component of PM2.5, promotes pulmonary injury by modifying lipid metabolism in a phospholipase A2-dependent manner in vivo and in vitro

Particulate matter with an aerodynamic diameter less than 2.5μM (PM2.5) is one of the major environmental pollutants in China. In this study, we carried out a metabolomics profile study on PM2.5-induced inflammation. PM2.5 from Beijing, China, was collected and given to rats through intra-tracheal instillation in vivo. Acute pulmonary injury were observed by pulmonary function assessment and H.E. staining. The lipid metabolic profile was also altered with increased phospholipid and sphingolipid metabolites in broncho-alveolar lavage fluid (BALF) after PM2.5 instillation. Organic component analysis revealed that benzo[a]pyrene (BaP) is one of the most abundant and toxic components in the PM2.5 collected on the fiber filter. In vitro, BaP was used to treat A549 cells, an alveolar type II cell line. BaP (4μM, 24h) induced inflammation in the cells. Metabolomics analysis revealed that BaP (4μM, 6h) treatment altered the cellular lipid metabolic profile with increased phospholipid metabolites and reduced sphingolipid metabolites and free fatty acids (FFAs). The proportion of ω-3 polyunsaturated fatty acid (PUFA) was also decreased. Mechanically, BaP (4μM) increased the phospholipase A2 (PLA2) activity at 4h as well as the mRNA level of Pla2g2a at 12h. The pro-inflammatory effect of BaP was reversed by the cytosolic PLA2 (cPLA2) inhibitor and chelator of intracellular Ca2+. This study revealed that BaP, as a component of PM2.5, induces pulmonary injury by activating PLA2 and elevating lysophosphatidylcholine (LPC) in a Ca2+-dependent manner in the alveolar type II cells.

Metabolomics analysis of serum from subjects after occupational exposure to acrylamide using UPLC-MS

Since occupational exposure to acrylamide (ACR) may cause nerve damage, sensitive biomarkers to evaluate the early effects of ACR on human health are needed. In the present study, we have compared a group of individuals with occupational exposure to ACR (contact group, n = 65) with a group of individuals with no exposure (non-contact group, n = 60). Serum metabolomics analysis of the contact and non-contact groups was carried out using ultra performance liquid chromatograph/time of flight mass spectrometry, combined with multivariate analysis, to identify potential metabolites. Serum biochemical indexes of the contact and non-contact groups were also determined using an automatic biochemistry analyzer. There was a clear separation between the contact group and the non-contact group; receiver operator characteristic curve analysis suggested that phytosphingosine, 4E,15Z-bilirubin IXa and tryptophan were the best metabolites to use as biomarkers. Liver function was also found to be abnormal in the contact group. Important, ACR-related, metabolic changes were seen in the contact group and new biomarkers for assessing the toxicity of ACR on the central nervous system have been proposed. This study will provide a sound basis for exploring the toxic mechanisms and metabolic pathways of ACR.

Global metabolic profiling for the study of Rhizoma Paridis saponins-induced hepatotoxicity in rats

Rhizoma Paridis saponins (RPS) is a traditional Chinese medicine (TCM) from the plant Paris polyphylla var. yunnanensis (Fr.) Hand.-Mazz. Despite its potentially clinical utility such as anticancer and anti-inflammation, it has slight side effects and toxicity as previous report. In this work, 90-day administration of RPS induced liver injury. ¹ H-NMR- and GC/MS-based metabonomic analyses in conjunction with histopathological examinations, blood biochemistry and hepatic phase I and II enzymes assays were performed to evaluate the toxic mechanisms of RPS induced in rats. As a result, oral administration of RPS possessed certain liver toxicity in SD rats. ¹ H-NMR and GC/MS data indicated that RPS inhibited the oxidation of fatty acids, glycolysis, and TCA cycle pathway, and disturbed glycine, serine, and threonine metabolism. Low expression of TG, T-CHO, and LDL-C and high levels of ALT and AST indicated that chronic exposure to RPS caused hepatocyte damage, synthesis dysfunction, and transportation failure of lipoproteins. In addition, RPS downregulated the mRNA levels of CYP1A2, CYP2E1, and UGTs. In conclusion, we used metabonomics approach to study the toxicity of RPS for the first time. This research demonstrated that metabonomics method was a promising tool to study and diagnose TCM-induced toxicity. © 2015 Wiley Periodicals, Inc. Environ Toxicol 32: 99-108, 2017.

Associations among plasma metabolite levels and short-term exposure to PM2.5 and ozone in a cardiac catheterization cohort

RATIONALE

Exposure to ambient particulate matter (PM) and ozone has been associated with cardiovascular disease (CVD). However, the mechanisms linking PM and ozone exposure to CVD remain poorly understood.

OBJECTIVE

This study explored associations between short-term exposures to PM with a diameter <2.5μm (PM_2.5) and ozone with plasma metabolite concentrations.

METHODS AND RESULTS

We used cross-sectional data from a cardiac catheterization cohort at Duke University, North Carolina (NC), USA, accumulated between 2001 and 2007. Amino acids, acylcarnitines, ketones and total non-esterified fatty acid plasma concentrations were determined in fasting samples. Daily concentrations of PM_2.5 and ozone were obtained from a Bayesian space-time hierarchical model, matched to each patient's residential address. Ten metabolites were selected for the analysis based on quality criteria and cluster analysis. Associations between metabolites and PM_2.5 or ozone were analyzed using linear regression models adjusting for long-term trend and seasonality, calendar effects, meteorological parameters, and participant characteristics. We found delayed associations between PM_2.5 or ozone and changes in metabolite levels of the glycine-ornithine-arginine metabolic axis and incomplete fatty acid oxidation associated with mitochondrial dysfunction. The strongest association was seen for an increase of 8.1μg/m³ in PM_2.5 with a lag of one day and decreased mean glycine concentrations (-2.5% [95% confidence interval: -3.8%; -1.2%]).

CONCLUSIONS

Short-term exposures to ambient PM_2.5 and ozone is associated with changes in plasma concentrations of metabolites in a cohort of cardiac catheterization patients. Our findings might help to understand the link between air pollution and cardiovascular disease.

Deployment-Associated Exposure Surveillance With High-Resolution Metabolomics

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Potential Harmful Effects of PM2.5 on Occurrence and Progression of Acute Coronary Syndrome: Epidemiology, Mechanisms, and Prevention Measures

The harmful effects of particulate matter with an aerodynamic diameter of <2.5 µm (PM_2.5) and its association with acute coronary syndrome (ACS) has gained increased attention in recent years. Significant associations between PM_2.5 and ACS have been found in most studies, although sometimes only observed in specific subgroups. PM_2.5-induced detrimental effects and ACS arise through multiple mechanisms, including endothelial injury, an enhanced inflammatory response, oxidative stress, autonomic dysfunction, and mitochondria damage as well as genotoxic effects. These effects can lead to a series of physiopathological changes including coronary artery atherosclerosis, hypertension, an imbalance between energy supply and demand to heart tissue, and a systemic hypercoagulable state. Effective strategies to prevent the harmful effects of PM_2.5 include reducing pollution sources of PM_2.5 and population exposure to PM_2.5, and governments and organizations publicizing the harmful effects of PM_2.5 and establishing air quality standards for PM_2.5. PM_2.5 exposure is a significant risk factor for ACS, and effective strategies with which to prevent both susceptible and healthy populations from an increased risk for ACS have important clinical significance in the prevention and treatment of ACS.

Metabolomics and Its Application to Acute Lung Diseases

Metabolomics is a rapidly expanding field of systems biology that is gaining significant attention in many areas of biomedical research. Also known as metabonomics, it comprises the analysis of all small molecules or metabolites that are present within an organism or a specific compartment of the body. Metabolite detection and quantification provide a valuable addition to genomics and proteomics and give unique insights into metabolic changes that occur in tangent to alterations in gene and protein activity that are associated with disease. As a novel approach to understanding disease, metabolomics provides a "snapshot" in time of all metabolites present in a biological sample such as whole blood, plasma, serum, urine, and many other specimens that may be obtained from either patients or experimental models. In this article, we review the burgeoning field of metabolomics in its application to acute lung diseases, specifically pneumonia and acute respiratory disease syndrome (ARDS). We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized environmental toxins. Recent reports have suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe disease, such as sepsis, which kills many patients each year. In addition, metabolomics may provide more detailed phenotyping of patient heterogeneity, which is needed to achieve the goal of precision medicine. However, although several experimental and clinical metabolomics studies have been conducted assessing the application of the science to acute lung diseases, only incremental progress has been made. Specifically, little is known about the metabolic phenotypes of these illnesses. These data are needed to substantiate metabolomics biomarker credentials so that clinicians can employ them for clinical decision-making and investigators can use them to design clinical trials.

Metabolomics reveals disturbed metabolic pathways in human lung epithelial cells exposed to airborne fine particulate matter

Airborne PM2.5 exposure disturbs citrate cycle, amino acid biosynthesis and metabolism, and glutathione metabolism in A549 cells.