The impact of ambient air pollution on the human blood metabolome

Prenatal and Early Life Exposure to Ambient Air Pollutants Is Associated with the Fecal Metabolome in the First Two Years of Life

Prenatal and early life air pollution exposure has been linked with several adverse health outcomes. However, the mechanisms underlying these relationships are not yet fully understood. Therefore, this study utilizes fecal metabolomics to determine if pre- and postnatal exposure to ambient air pollutants (i.e., PM10, PM2.5, and NO2) is associated with the fecal metabolome in the first 2 years of life in a Latino cohort from Southern California. The aims of this analysis were to estimate associations between (1) prenatal air pollution exposure with fecal metabolic features at 1-month of age, (2) prior month postnatal air pollution exposure with fecal metabolites from 1-month to 2 years of age, and (3) how postnatal air pollution exposure impacts the change over time of fecal metabolites in the first 2 years of life. Prenatal exposure to air pollutants was associated with several Level-1 metabolites, including those involved in vitamin B6 and tyrosine metabolism. Prior month air pollution exposure in the postnatal period was associated with Level-1 metabolites involved in histidine metabolism. Lastly, we found that pre- and postnatal ambient air pollution exposure was associated with changes in metabolic features involved in metabolic pathways including amino acid metabolism, histidine metabolism, and fatty acid metabolism.

Metabolic profiles associated with exposure to ambient particulate air pollution: findings from the Betula cohort

Introduction

Air pollution is a significant contributor to morbidity and mortality globally and has been linked to an increased risk of dementia. Previous studies within the Betula cohort in Northern Sweden have demonstrated associations between air pollution and dementia, as well as distinctive metabolomic profiles in dementia patients compared to controls. This study aimed to investigate whether air pollution is associated with quantitative changes in metabolite levels within this cohort, and whether future dementia status would modify this association.

Methods

Both short-term and long-term exposure to air pollution were evaluated using high spatial resolution models and measured data. Air pollution from vehicle exhaust and woodsmoke were analyzed separately. Metabolomic profiling was conducted on 321 participants, including 58 serum samples from dementia patients and a control group matched for age, sex, and education level, using nuclear magnetic resonance spectroscopy.

Results

No statistically significant associations were found between any metabolites and any measures of short-term or long-term exposure to air pollution. However, there were trends potentially suggesting associations between both long-term and short-term exposure to air pollution with lactate and glucose metabolites. Notably, these associations were observed despite the lack of correlation between long-term and short-term air pollution exposure in this cohort. There were also tendencies for associations between air pollution from woodsmoke to be more pronounced in participants that would later develop dementia, suggesting a potential effect depending on urban/rural factors.

Discussion

While no significant associations were found, the trends observed in the data suggest potential links between air pollution exposure and changes in lactate and glucose metabolites. These findings provide some new insights into the link between air pollution and metabolic markers in a low-exposure setting. However, addressing existing limitations is crucial to improve the robustness and applicability of future research in this area. The pronounced associations in participants who later developed dementia may indicate an influence of urban/rural factors, warranting further investigation.

A nested case-control study of untargeted plasma metabolomics and lung cancer among never-smoking women within the prospective Shanghai Women's Health Study

The etiology of lung cancer in never-smokers remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Here, we aimed to enhance our understanding of lung cancer pathogenesis among never-smokers using untargeted metabolomics. This nested case-control study included 395 never-smoking women who developed lung cancer and 395 matched never-smoking cancer-free women from the prospective Shanghai Women's Health Study with 15,353 metabolic features quantified in pre-diagnostic plasma using liquid chromatography high-resolution mass spectrometry. Recognizing that metabolites often correlate and seldom act independently in biological processes, we utilized a weighted correlation network analysis to agnostically construct 28 network modules of correlated metabolites. Using conditional logistic regression models, we assessed the associations for both metabolic network modules and individual metabolic features with lung cancer, accounting for multiple testing using a false discovery rate (FDR) < 0.20. We identified a network module of 121 features inversely associated with all lung cancer (p = .001, FDR = 0.028) and lung adenocarcinoma (p = .002, FDR = 0.056), where lyso-glycerophospholipids played a key role driving these associations. Another module of 440 features was inversely associated with lung adenocarcinoma (p = .014, FDR = 0.196). Individual metabolites within these network modules were enriched in biological pathways linked to oxidative stress, and energy metabolism. These pathways have been implicated in previous metabolomics studies involving populations exposed to known lung cancer risk factors such as traffic-related air pollution and polycyclic aromatic hydrocarbons. Our results suggest that untargeted plasma metabolomics could provide novel insights into the etiology and risk factors of lung cancer among never-smokers.

Air Pollution Metabolomic Signatures and Chronic Respiratory Diseases Risk: A Longitudinal Study

BACKGROUND

Although evidence has documented the associations of ambient air pollution with chronic respiratory diseases (CRDs) and lung function, the underlying metabolic mechanisms remain largely unclear.

RESEARCH QUESTION

How does the metabolomic signature for air pollution relate to CRD risk, respiratory symptoms, and lung function?

STUDY DESIGN AND METHODS

We retrieved 171,132 participants free of COPD and asthma at baseline from the UK Biobank, who had data on air pollution and metabolomics. Exposures to air pollutants (particulate matter with diameter ≤ 2.5 μm [PM2.5], particulate matter with a diameter ≤ 10 μm, nitrogen oxide [NOX], and NO2) were assessed for 4 years before baseline considering residential address histories. We used 10-fold cross-validation elastic net regression to identify air pollution-associated metabolites. Multivariable Cox models were used to assess the associations between metabolomic signatures and CRD risk. Mediation and pathway analysis were conducted to explore the metabolic mechanism underlying the associations.

RESULTS

During a median follow-up of 12.51 years, 8,951 and 5,980 incident COPD and asthma cases were recorded. In multivariable Cox regressions, air pollution was positively associated with CRD risk (eg, hazard ratio per interquartile range increment in PM2.5, 1.09; 95% CI, 1.06-1.13). We identified 103, 86, 85, and 90 metabolites in response to PM2.5, particulate matter with a diameter ≤ 10 μm, NOX, and NO2 exposure, respectively. The metabolomic signatures showed significant associations with CRD risk (hazard ratio per SD increment in PM2.5 metabolomic signature, 1.11; 95% CI, 1.09-1.14). Mediation analysis showed that peripheral inflammatory and erythrocyte-related markers mediated the effects of metabolomic signatures on CRD risk. We identified 14 and 12 perturbed metabolic pathways (energy metabolism and amino acid metabolism pathways, etc) for PM2.5 and NOX metabolomic signatures.

INTERPRETATION

Our study identifies metabolomic signatures for air pollution exposure. The metabolomic signatures showed significant associations with CRD risk, and inflammatory- and erythrocyte-related markers partly mediated the metabolomic signatures-CRD links.

3D printer emissions elicit filament-specific and dose-dependent metabolic and genotoxic effects in human airway epithelial cells

Three-dimensional (3D) printers have become popular educational tools in secondary and post-secondary STEM curriculum; however, concerns have emerged regarding inhalation exposures and associated health risks. Current evidence suggests that filament materials and site conditions may cause differences in the chemical profiles and toxicological properties of 3D printer emissions; however, few studies have evaluated exposures directly in the classroom. In this study, we monitored and sampled particulate matter (PM) emitted from acrylonitrile-butadiene-styrene (ABS) and polylactic acid (PLA) filaments during a 3-hour 3D printing session in a high school classroom using aerosol monitoring instrumentation and collection media. To evaluate potential inhalation risks, Multiple Path Particle Dosimetry (MPPD) modeling was used to estimate inhaled doses and calculate in vitro concentrations based on the observed aerosol data and specific lung and breathing characteristics. Dynamic light scattering was used to evaluate the hydrodynamic diameter, zeta potential, and polydispersity index (PDI) of extracted PM emissions dispersed in cell culture media. Small airway epithelial cells (SAEC) were employed to determine cellular viability, genotoxic, inflammatory, and metabolic responses to each emission exposure using MTS, ELISA, and high-performance liquid chromatography-mass spectrometry (HPLC-MS), respectively. Aerosol monitoring data revealed that emissions from ABS and PLA filaments generated similar PM concentrations within the ultrafine and fine ranges. However, DLS analysis showed differences in the physicochemical properties of ABS and PLA PM, where the hydrodynamic diameter of PLA PM was greater than ABS PM, which may have influenced particle deposition rates and cellular outcomes. While exposure to both ABS and PLA PM reduced cell viability and induced MDM2, an indicator of genomic instability, PLA PM alone increased gamma-H2AX, a marker of double-stranded DNA breaks. ABS and PLA emissions also increased the release of pro-inflammatory cytokines, although this did not reach significance. Furthermore, metabolic profiling via high performance liquid chromatography-mass spectrometry (HPLC-MS) and subsequent pathway analysis revealed filament and dose dependent cellular metabolic alterations. Notably, our metabolomic analysis also revealed key metabolites and pathways implicated in PM-induced oxidative stress, DNA damage, and respiratory disease that were perturbed across both tested doses for a given filament. Taken together, these findings suggest that use of ABS and PLA filaments in 3D printers within school settings may potentially contribute to adverse respiratory responses especially in vulnerable populations.

Multiomic Signatures of Traffic-Related Air Pollution in London Reveal Potential Short-Term Perturbations in Gut Microbiome-Related Pathways

This randomized crossover study investigated the metabolic and mRNA alterations associated with exposure to high and low traffic-related air pollution (TRAP) in 50 participants who were either healthy or were diagnosed with chronic pulmonary obstructive disease (COPD) or ischemic heart disease (IHD). For the first time, this study combined transcriptomics and serum metabolomics measured in the same participants over multiple time points (2 h before, and 2 and 24 h after exposure) and over two contrasted exposure regimes to identify potential multiomic modifications linked to TRAP exposure. With a multivariate normal model, we identified 78 metabolic features and 53 mRNA features associated with at least one TRAP exposure. Nitrogen dioxide (NO2) emerged as the dominant pollutant, with 67 unique associated metabolomic features. Pathway analysis and annotation of metabolic features consistently indicated perturbations in the tryptophan metabolism associated with NO2 exposure, particularly in the gut-microbiome-associated indole pathway. Conditional multiomics networks revealed complex and intricate mechanisms associated with TRAP exposure, with some effects persisting 24 h after exposure. Our findings indicate that exposure to TRAP can alter important physiological mechanisms even after a short-term exposure of a 2 h walk. We describe for the first time a potential link between NO2 exposure and perturbation of the microbiome-related pathways.

An untargeted metabolomics approach to study changes of the medium during human cornea culture

INTRODUCTION

Two main approaches (organ culture and hypothermia) for the preservation and storage of human donor corneas are globally adopted for corneal preservation before the transplant. Hypothermia is a hypothermic storage which slows down cellular metabolism while organ culture, a corneal culture performed at 28-37 °C, maintains an active corneal metabolism. Researchers, till now, have just studied the impact of organ culture on human cornea after manipulating and disrupting tissues.

OBJECTIVES

The aim of the current work was to optimize an analytical procedure which can be useful for discovering biomarkers capable of predicting tissue health status. For the first time, this research proposed a preliminary metabolomics study on medium for organ culture without manipulating and disrupting the valuable human tissues which could be still used for transplantation.

METHODS

In particular, the present research proposed a method for investigating changes in the medium, over a storage period of 20 days, in presence and absence of a human donor cornea. An untargeted metabolomics approach using UHPLC-QTOF was developed to deeply investigate the differences on metabolites and metabolic pathways and the influence of the presence of the cornea inside the medium.

RESULTS

Differences in the expression of some compounds emerged from this preliminary metabolomics approach, in particular in medium maintained for 10 and 20 days in presence but also in the absence of cornea. A total of 173 metabolites have been annotated and 36 pathways were enriched by pathway analysis.

CONCLUSION

The results revealed a valuable untargeted metabolomics approach which can be applied in organ culture metabolomics.

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

Evaluating changes in firefighter urinary metabolomes after structural fires: an untargeted, high resolution approach

Firefighters have elevated rates of urinary tract cancers and other adverse health outcomes, which may be attributable to environmental occupational exposures. Untargeted metabolomics was applied to characterize this suite of environmental exposures and biological changes in response to occupational firefighting. 200 urine samples from 100 firefighters collected at baseline and two to four hours post-fire were analyzed using untargeted liquid-chromatography and high-resolution mass spectrometry. Changes in metabolite abundance after a fire were estimated with fixed effects linear regression, with false discovery rate (FDR) adjustment. Partial least squares discriminant analysis (PLS-DA) was also used, and variable important projection (VIP) scores were extracted. Systemic changes were evaluated using pathway enrichment for highly discriminating metabolites. Metabolome-wide-association-study (MWAS) identified 268 metabolites associated with firefighting activity at FDR q < 0.05. Of these, 20 were annotated with high confidence, including the amino acids taurine, proline, and betaine; the indoles kynurenic acid and indole-3-acetic acid; the known uremic toxins trimethylamine n-oxide and hippuric acid; and the hormone 7a-hydroxytestosterone. Partial least squares discriminant analysis (PLS-DA) additionally implicated choline, cortisol, and other hormones. Significant pathways included metabolism of urea cycle/amino group, alanine and aspartate, aspartate and asparagine, vitamin b3 (nicotinate and nicotinamide), and arginine and proline. Firefighters show a broad metabolic response to fires, including altered excretion of indole compounds and uremic toxins. Implicated pathways and features, particularly uremic toxins, may be important regulators of firefighter's increased risk for urinary tract cancers.

Longitudinal associations between metabolites and immediate, short- and medium-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Short-term exposure to air pollution has been reported to be associated with cardiopulmonary diseases, but the underlying mechanisms remain unclear. This study aimed to investigate changes in serum metabolites associated with immediate, short- and medium-term exposures to ambient air pollution.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in this analysis. We collected daily averages of fine particles (PM2.5), coarse particles (PMcoarse), nitrogen dioxide (NO2), and ozone (O3) at urban background monitors located in Augsburg, Germany. Covariate-adjusted generalized additive mixed-effects models were used to examine the associations between immediate (2-day average of same day and previous day as individual's blood withdrawal), short- (2-week moving average), and medium-term exposures (8-week moving average) to air pollution and metabolites. We further performed pathway analysis for the metabolites significantly associated with air pollutants in each exposure window.

RESULTS

Of 9,620 observations from 4,261 study participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed quality control, multiple significant associations between metabolites and air pollutants with several exposure windows were identified at a Bonferroni corrected p-value threshold (p < 3.9 × 10-5). We found the highest number of associations for NO2, particularly at the medium-term exposure windows. Among the identified metabolic pathways based on the metabolites significantly associated with air pollutants, the glycerophospholipid metabolism was the most robust pathway in different air pollutants exposures.

CONCLUSIONS

Our study suggested that short- and medium-term exposure to air pollution might induce alterations of serum metabolites, particularly in metabolites involved in metabolic pathways related to inflammatory response and oxidative stress.

The mediating role of exhaled breath condensate metabolites in the effect of particulate matter on pulmonary function in schoolchildren: A crossover intervention study

The role played by metabolites in exhaled breath condensate (EBC) in the effect of PM on schoolchildren's pulmonary function has received little attention. Accordingly, we examined whether metabolites in EBC mediated the effect of PM10, PM2.5, and PM1 on the pulmonary function of schoolchildren at a residential primary school who had received an air-cleaner cross-over intervention. Samples of EBC were collected from a total of 60 schoolchildren and subjected to metabolomics analysis. We found that the effect of PM on six pulmonary function indicators was mediated by the following nine lipid peroxidation-related and energy metabolism-related metabolites present in EBC: 4-hydroxynonenal, arachidoyl ethanolamide, dl-pyroglutamic acid, 5-deoxy-d-glucose, myristic acid, lauric acid, linoleic acid, l-proline, and palmitic acid. However, while all nine of these metabolites mediated the effects of PM on boys' pulmonary function, only 4-hydroxynonenal, arachidoyl ethanolamide, and dl-pyroglutamic acid mediated the effects of PM on girls' pulmonary function. Overall, our results show that (1) short-term exposure to PM affected the schoolchildren's pulmonary function by causing an imbalance between lipid peroxidation and glutathione-based antioxidant activity and by perturbing energy metabolism in respiratory system and (2) there was a sex-dependent antioxidant response to PM exposure, with boys being less resistant than girls.

Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.

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.

Metabolomic Evaluation of Air Pollution-related Bone Damage and Potential Mediation

Ambient air pollution has been associated with bone damage. However, no studies have evaluated the metabolomic response to air pollutants and its potential influence on bone health in postmenopausal women. We analyzed data from WHI participants with plasma samples. Whole-body, total hip, femoral neck, and spine BMD at enrollment and follow-up (Y1, Y3, Y6). Daily particulate matter NO, NO2, PM10 and SO2 were averaged over 1-, 3-, and 5-year periods before metabolomic assessments. Statistical analyses included multivariable-adjusted linear mixed models, pathways analyses, and mediation modeling. NO, NO2, and SO2, but not PM10, were associated with taurine, inosine, and C38:4 phosphatidylethanolamine (PE), at all averaging periods. We found a partial mediation of C38:4 PE in the association between 1-year average NO and lumbar spine BMD (p-value: 0.032). This is the first study suggesting that a PE may partially mediate air pollution-related bone damage in postmenopausal women.

Study on metal elements in indoor particulate matter: a case study of rural residential environment in Northeast China

The use of solid fuels for heating and cooking in rural Northeast China has led to severe indoor metal element pollution in particulate matter (PM), posing a direct threat to human health and creating immense pressure on the sustainability of residential environments. To investigate the levels, sources, and potential health hazards of indoor metal element pollution in this region, we conducted a year-long sampling and monitoring campaign in actual residential settings and used ICP-OES to measure six metal elements (Mn, Cr, Zn, Cu, Pb, and Ni). This study's findings reveal that indoor metal element pollution levels in PM (33,513.65 mg/kg per year) are higher in rural Northeast China compared to other rural areas. Straw burning is the primary source of metal element pollution, followed by motor vehicle emissions and natural soil sources. It is crucial to note that our results indicate a total carcinogenic risk greater than 10^-4 according to the US EPA health risk model assessment, highlighting the high risk posed to human health by indoor metal elements in rural areas. By using a seriously polluted area in Northeast China as a case study, this research provides initial insights into the characteristics and sources of indoor metal pollution in rural areas, offering a reference for future prevention and control of indoor pollution in these regions. Ultimately, this work can help improve the rural habitat and enhance the health of the rural population.

Inulin and Chinese Gallotannin Affect Meat Quality and Lipid Metabolism on Hu Sheep

The aim of this study was to investigate the impacts of inulin and Chinese gallotannin on the meat fatty acids and urinary metabolites in sheep. Twenty-four healthy (25.80 ± 3.85 kg) weaned Hu lambs of approximately 4.5 months old were equally divided into four groups: control group (basal diet), treatment group I (basal diet + 0.1% inulin), treatment group II (basal diet + 0.1% inulin + 2% Chinese gallotannin), and treatment group III (basal diet + 0.1% inulin + 2% Chinese gallotannin + 4% PEG). The contents of myristic acid (C14:0) and palmitic acid (C16:0) were found to be lower in treatment group II than in the control group (p < 0.05). Moreover, the palmitoleic acid (C16:1) content in treatment group II was notably higher than that in the control group (p < 0.05), while the elaidic acid (C18:1n9t) content in treatment group II was higher than that in other groups (p < 0.05). Besides, the linoleic acid (C18:2n6c) content was higher in the treatment II and control groups than in the treatment I and III groups. Furthermore, compared with the control group, both 4-pyridoxic acid and creatinine in treatment groups I and II were upregulated (p < 0.05), while other metabolites, such as nicotinuric acid, l-threonine, palmitic acid, and oleic acid, were drastically downregulated (p < 0.05). These differential metabolites were found to be mainly involved in nicotinate and nicotinamide metabolism (ko00760), vitamin B6 metabolism (ko00750), and the fatty acid biosynthesis pathway (ko00061). It is concluded that the combination of inulin and Chinese gallotannin in the diet could improve the energy and lipid metabolism of sheep, which may improve both mutton quality and production performance.

Traffic-related air pollution and genome-wide DNA methylation: A randomized, crossover trial

BACKGROUND

Traffic-related air pollution (TRAP) has been associated with changes in gene-specific DNA methylation. However, few studies have investigated impact of TRAP exposure on genome-wide DNA methylation in circulating blood of human.

OBJECTIVE

To explore the association between TRAP exposure and genome-wide DNA methylation.

METHODS

We conducted a randomized, crossover exposure trial among 35 healthy adults in Shanghai, China. All subjects were randomly allocated to a traffic-free park or a main road for consecutive 4 h, respectively. Blood genome-wide DNA methylation after each exposure session was measured by the Infinium Methylation EPIC BeadChip (850K). The differentially methylated CpGs loci associated with TRAP exposure were identified using linear mixed-effect model.

RESULTS

The average concentrations of traffic-related air pollutants including black carbon, ultrafine particles, carbon dioxide, and nitrogen dioxide were 2-3 times higher in the road compared to those in the park. Methylation levels of 68 CpG loci were significantly changed (false discovery rate < 0.05) following TRAP exposure, among which 49 were hypermethylated and 19 were hypomethylated. The annotated genes based on the differential CpGs loci were related to pathways in cardiovascular signaling, cytokine signaling, immune response, nervous system signaling, and metabolism.

CONCLUSIONS

We found that TRAP exposure was associated with DNA methylation in dozens of genes concerning cardiometabolic health. This trial for the first-time profiled genome-wide methylation changes induced by TRAP exposure using the 850K assay, providing epigenetic insights in understanding the cardiometabolic effects of TRAP exposure.

Longitudinal associations between metabolites and long-term exposure to ambient air pollution: Results from the KORA cohort study

BACKGROUND

Long-term exposure to air pollution has been associated with cardiopulmonary diseases, while the underlying mechanisms remain unclear.

OBJECTIVES

To investigate changes in serum metabolites associated with long-term exposure to air pollution and explore the susceptibility characteristics.

METHODS

We used data from the German population-based Cooperative Health Research in the Region of Augsburg (KORA) S4 survey (1999-2001) and two follow-up examinations (F4: 2006-08 and FF4: 2013-14). Mass-spectrometry-based targeted metabolomics was used to quantify metabolites among serum samples. Only participants with repeated metabolites measurements were included in the current analysis. Land-use regression (LUR) models were used to estimate annual average concentrations of ultrafine particles, particulate matter (PM) with an aerodynamic diameter less than 10 μm (PM₁₀), coarse particles (PM_coarse), fine particles, PM_2.5 absorbance (a proxy of elemental carbon related to traffic exhaust, PM_2.5abs), nitrogen oxides (NO₂, NO_x), and ozone at individuals' residences. We applied confounder-adjusted mixed-effects regression models to examine the associations between long-term exposure to air pollution and metabolites.

RESULTS

Among 9,620 observations from 4,261 KORA participants, we included 5,772 (60.0%) observations from 2,583 (60.6%) participants in this analysis. Out of 108 metabolites that passed stringent quality control across three study points in time, we identified nine significant negative associations between phosphatidylcholines (PCs) and ambient pollutants at a Benjamini-Hochberg false discovery rate (FDR) corrected p-value < 0.05. The strongest association was seen for an increase of 0.27 μg/m³ (interquartile range) in PM_2.5abs and decreased phosphatidylcholine acyl-alkyl C36:3 (PC ae C36:3) concentrations [percent change in the geometric mean: -2.5% (95% confidence interval: -3.6%, -1.5%)].

CONCLUSIONS

Our study suggested that long-term exposure to air pollution is associated with metabolic alterations, particularly in PCs with unsaturated long-chain fatty acids. These findings might provide new insights into potential mechanisms for air pollution-related adverse outcomes.

Using follicular fluid metabolomics to investigate the association between air pollution and oocyte quality

BACKGROUND AND AIM

Our objective was to use metabolomics in a toxicological-relevant target tissue to gain insight into the biological processes that may underlie the negative association between air pollution exposure and oocyte quality.

METHODS

Our study included 125 women undergoing in vitro fertilization at an academic fertility center in Massachusetts, US (2005-2015). A follicular fluid sample was collected during oocyte retrieval and untargeted metabolic profiling was conducted using liquid chromatography with ultra-high-resolution mass spectrometry and two chromatography columns (C18 and HILIC). Daily exposure to nitrogen dioxide (NO2), ozone, fine particulate matter, and black carbon was estimated at the women's residence using spatiotemporal models and averaged over the period of ovarian stimulation (2-weeks). Multivariable linear regression models were used to evaluate the associations between the air pollutants, number of mature oocytes, and metabolic feature intensities. A meet-in-the-middle approach was used to identify overlapping features and metabolic pathways.

RESULTS

Of the air pollutants, NO2 exposure had the largest number of overlapping metabolites (C18: 105; HILIC: 91) and biological pathways (C18: 3; HILIC: 6) with number of mature oocytes. Key pathways of overlap included vitamin D3 metabolism (both columns), bile acid biosynthesis (both columns), C21-steroid hormone metabolism (HILIC), androgen and estrogen metabolism (HILIC), vitamin A metabolism (HILIC), carnitine shuttle (HILIC), and prostaglandin formation (C18). Three overlapping metabolites were confirmed with level-1 or level-2 evidence. For example, hypoxanthine, a metabolite that protects against oxidant-induced cell injury, was positively associated with NO2 exposure and negatively associated with number of mature oocytes. Minimal overlap was observed between the other pollutants and the number of mature oocytes.

CONCLUSIONS

Higher exposure to NO2 during ovarian stimulation was associated with many metabolites and biologic pathways involved in endogenous vitamin metabolism, hormone synthesis, and oxidative stress that may mediate the observed associations with lower oocyte quality.

Air pollution, metabolites and respiratory health across the life-course

Previous studies have explored the relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and the associated mechanisms have not been reviewed from a life-course perspective. Here, we provide a narrative review summarising recent evidence on the associations of metabolic profiles with air pollution exposure and lung function in children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analysing air pollution-related metabolic profiles and 16 studies analysing lung function-related metabolic profiles. A wide range of metabolites were associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general population and with respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers the potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many studies suffer from small sample sizes, cross-sectional designs, a preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools for healthy living in urbAN Settings (EXPANSE) project aims to address some of these shortcomings by combining biospecimens from large European cohorts and harmonised air pollution exposure and exposome data.

Length of PM2.5 exposure and alterations in the serum metabolome among women undergoing infertility treatment

Background:

Both acute and chronic exposure to fine particulate matter (PM_2.5) have been linked to negative health outcomes. Studies have used metabolomics to describe the biological pathways linking PM_2.5 with disease but have focused on a single exposure window. We compared alterations in the serum metabolome following various short- and long-term PM_2.5 exposures.

Methods:

Participants were women undergoing in vitro fertilization at a New England fertility clinic (n = 200). Women provided their residential address and provided a blood sample during controlled ovarian stimulation. PM_2.5 exposure was estimated in the 1, 2, and 3 days, 2 weeks, and 3 months prior to blood collection using a validated spatiotemporal model. We utilized liquid chromatography with high-resolution mass spectrometry. We used generalized linear models to test for associations between metabolomic features and PM_2.5 exposures after adjusting for potential confounders. Significant features (P < 0.005) were used for pathway analysis and metabolite identification.

Results:

We identified 17 pathways related to amino acid, lipid, energy, and nutrient metabolism that were solely associated with acute PM_2.5 exposure. Fifteen pathways, mostly, pro-inflammatory, anti-inflammatory, amino acid, and energy metabolism, were solely associated with long-term PM_2.5 exposure. Seven pathways were associated with the majority of exposure windows and were mostly related to anti-inflammatory and lipid metabolism. Among the significant features, we confirmed seven metabolites with level-1 evidence.

Conclusions:

We identified serum metabolites and metabolic pathways uniquely associated with acute versus chronic PM_2.5 exposure. These different biologic pathways may help explain differences in disease states when investigating different lengths of PM_2.5 exposure.

Source identification of pollution and health risks to metals in household indoor and outdoor dust: A cross-sectional study in a typical mining town, China

Dust is regarded as an important pathway of heavy metal(loid)s to the human body. Health risks posed by metal(loid)s from household dust are of particular concern. However, the contamination and sources of heavy metal(loid)s in household dust environments, as well as source identification of health risks related to heavy metal(loid)s from household dust for vulnerable populations such as children, have not been thoroughly studied in China, particularly for the areas involved with industrial activities such as ore mining. Thus, a cross-sectional study was conducted in a rural area famous for Pb/Zn ore mining, to assess the pollution sources and health risks of heavy metal(loid)s from household indoor and outdoor dust and to identify the contribution of household dust to the health risks for children. The results indicated that household environment was heavily contaminated by metal(loid)s, which were mainly attributed to mining activity. Meanwhile, the indoor/outdoor ratio and the redundancy analysis indicated that there were other pollution sources in indoor environments such as coal combustion, materials for interior building and decoration. Vapor inhalation was the main exposure pathway for Hg, while ingestion was the predominant pathway for other metal(loid)s. Although the cancer risks were relatively low, the HIt from household indoor and outdoor dust (2.19) was about twice the acceptable limit (1) and was primarily from Pb (64.52%) and As (23.42%). Outdoor dust was a larger contributor to the HI of Sb, As, Cr, Cd, Zn and Pb, which accounted for 51.37%, 58.63%, 52.14%, 59.66%, 52.87% and 64.47%, respectively, and the HIt was mainly from outdoor dust (60.76%). These results indicated that non-cancer health risks were largely from outdoor dust exposure, and strengthened the notion that concern should be given to the potential health risks from metal(loid)s in household dust both originating from mining activity and indoor environmental sources.

Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry

Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010, and analyzed using untargeted high-resolution metabolomics to characterize metabolite associations with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Metabolic associations with EC, OC and PM2.5 were evaluated for biochemical processes known to be associated with disease risk. Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and transcriptomic changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution.

Associations between time-weighted personal air pollution exposure and amino acid metabolism in healthy adults

The molecular mechanisms underlying the associations between air pollution exposure and adverse cardiopulmonary effects remain to be better understood. Altered amino acid metabolism may plays an important role in the development of cardiopulmonary diseases and may be perturbed by air pollution exposure. To test this hypothesized molecular mechanism, we conducted an association analysis from an existing intervention study to examine the relations of air pollution exposures with amino acids in 43 Chinese healthy adults. Plasma levels of amino acids were measured using a UPLC-QqQ-MS system. Time-weighted personal exposure to O₃, PM_2.5, NO₂, and SO₂ over four time windows, i.e., 12 h, 24 h, 1 week, and 2 weeks, were calculated using the measured indoor and outdoor concentrations coupled with the time-activity data for each participant. Linear mixed-effects models were used to estimate the associations between air pollutants at each exposure window and amino acids by controlling for potential confounders. We observed significant associations between exposures and plasma concentrations of amino acids, with the direction of associations varying by amino acid and air pollutant. While there is little evidence of associations for NO₂ and SO₂, the associations with amino acids were fairly pronounced for exposure to PM_2.5 and O₃. In particular, independent O₃ (12- and 24-hour) associations were observed with changes in the amino acids that were related to the urea cycle, including aspartate, asparagine, glutamate, arginine, citrulline, and ornithine. Our findings indicated that air pollution may cause acute perturbation of amino acid metabolism, and that O₃ and PM_2.5 may affect the metabolism of amino acids in different pathways. Main finding: Acute air pollution exposure might affect the perturbation of amino acid metabolism, and in particular, was associated with amino acids in relation to the urea cycle.

Perturbation of amino acid metabolism mediates air pollution associated vascular dysfunction in healthy adults

The molecular mechanisms of air pollution-associated adverse cardiovascular effects remain largely unknown. In the present study, we investigated the impacts of ambient air pollution on vascular function and the potential mediation effects of amino acids in a longitudinal follow-up of 73 healthy adults living in Beijing, China, between 2014 and 2016. We estimated associations between air pollutants and serum soluble intercellular adhesion molecule 1 (sICAM-1) and plasma levels of amino acids using linear mixed-effects models, and elucidated the biological pathways involved using mediation analyses. Higher air pollutant levels were significantly associated with increases in sICAM-1 levels. Metabolomics analysis showed that altered metabolites following short-term air pollution exposure were mainly involved in amino acid metabolism. Significant reductions in levels of plasma alanine, threonine and glutamic acid of 2.1 μM [95% confidence interval (CI): -3.8, -0.3] to 62.0 μM (95% CI: -76.1, -47.9) were associated with interquartile range increases in moving averages of PM_2.5, BC, CO and SO₂ in 1-7 days prior to clinical visits. Mediation analysis also showed that amino acids can mediate up to 48% of the changes in sICAM-1 associated with increased air pollution exposure. Our results indicated that air pollution may prompt vascular dysfunction through perturbing amino acid metabolism.

Metabolomic signatures of the short-term exposure to air pollution and temperature

BACKGROUND

Short-term exposures to air pollution and temperature have been reported to be associated with inflammation and oxidative stress. However, mechanistic understanding of the affected metabolic pathways is still lacking and literature on the short-term exposure of air-pollution on the metabolome is limited.

OBJECTIVES

We aimed to determine changes in the plasma metabolome and associated metabolic pathways related to short-term exposure to outdoor air pollution and temperature.

METHODS

We performed mass-spectrometry based untargeted metabolomic profiling of plasma samples from a large and well-characterized cohort of men (Normative Aging Study) to identify metabolic pathways associated with short-term exposure to PM2.5, NO2, O3, and temperature (one, seven-, and thirty-day average of address-specific predicted estimates). We used multivariable linear mixed-effect regression and independent component analysis (ICA) while simultaneously adjusting for all exposures and correcting for multiple testing.

RESULTS

Overall, 456 white men provided 648 blood samples, in which 1158 metabolites were quantified, between 2000 and 2016. Average age and body mass index were 75.0 years and 27.7 kg/m2, respectively. Only 3% were current smokers. In the adjusted models, NO2, and temperature showed statistically significant associations with several metabolites (19 metabolites for NO2 and 5 metabolites for temperature). We identified six metabolic pathways (sphingolipid, butanoate, pyrimidine, glycolysis/gluconeogenesis, propanoate, and pyruvate metabolisms) perturbed with short-term exposure to air pollution and temperature. These pathways were involved in inflammation and oxidative stress, immunity, and nucleic acid damage and repair.

CONCLUSIONS

This is the first study to report an untargeted metabolomic signature of temperature exposure, the largest to report an untargeted metabolomic signature of air pollution, and the first to use ICA. We identified several significant plasma metabolites and metabolic pathways associated with short-term exposure to air pollution and temperature; using an untargeted approach. Those pathways were involved in inflammation and oxidative stress, immunity, and nucleic acid damage and repair. These results need to be confirmed by future research.

Changes in arachidonic acid (AA)- and linoleic acid (LA)-derived hydroxy metabolites and their interplay with inflammatory biomarkers in response to drastic changes in air pollution exposure

BACKGROUND

Untargeted metabolomics analyses have indicated that fatty acids and their hydroxy derivatives may be important metabolites in the mechanism through which air pollution potentiates diseases. This study aimed to use targeted analysis to investigate how metabolites in arachidonic acid (AA) and linoleic acid (LA) pathways respond to short-term changes in air pollution exposure. We further explored how they might interact with markers of antioxidant enzymes and systemic inflammation.

METHODS

This study included a subset of participants (n = 53) from the Beijing Olympics Air Pollution (BoaP) study in which blood samples were collected before, during, and after the Beijing Olympics. Hydroxy fatty acids were measured by liquid chromatography/mass spectrometry (LC/MS). Native total fatty acids were measured as fatty acid methyl esters (FAMEs) using gas chromatography. A set of chemokines were measured by ELISA-based chemiluminescent assay and antioxidant enzyme activities were analyzed by kinetic enzyme assays. Changes in levels of metabolites over the three time points were examined using linear mixed-effects models, adjusting for age, sex, body mass index (BMI), and smoking status. Pearson correlation and repeated measures correlation coefficients were calculated to explore the relationships of metabolites with levels of serum chemokines and antioxidant enzymes.

RESULTS

12-hydroxyeicosatetraenoic acid (12-HETE) decreased by 50.5% (95% CI: -66.5, -34.5; p < 0.0001) when air pollution dropped during the Olympics and increased by 119.4% (95% CI: 36.4, 202.3; p < 0.0001) when air pollution returned to high levels after the Olympics. In contrast, 13-hydroxyoctadecadienoic acid (13-HODE) elevated significantly (p = 0.023) during the Olympics and decreased nonsignificantly after the games (p = 0.104). Interleukin 8 (IL-8) correlated with 12-HETE (r = 0.399, BH-adjusted p = 0.004) and 13-HODE (r = 0.342, BH-adjusted p = 0.014) over the three points; it presented a positive and moderate correlation with 12-HETE during the Olympics (r = 0.583, BH-adjusted p = 0.002) and with 13-HODE before the Olympics (r = 0.543, BH-adjusted p = 0.008).

CONCLUSION

AA- and LA-derived hydroxy metabolites are associated with air pollution and might interact with systemic inflammation in response to air pollution exposure.

MolDiscovery: learning mass spectrometry fragmentation of small molecules

Identification of small molecules is a critical task in various areas of life science. Recent advances in mass spectrometry have enabled the collection of tandem mass spectra of small molecules from hundreds of thousands of environments. To identify which molecules are present in a sample, one can search mass spectra collected from the sample against millions of molecular structures in small molecule databases. The existing approaches are based on chemistry domain knowledge, and they fail to explain many of the peaks in mass spectra of small molecules. Here, we present molDiscovery, a mass spectral database search method that improves both efficiency and accuracy of small molecule identification by learning a probabilistic model to match small molecules with their mass spectra. A search of over 8 million spectra from the Global Natural Product Social molecular networking infrastructure shows that molDiscovery correctly identify six times more unique small molecules than previous methods.

Data Processing Thresholds for Abundance and Sparsity and Missed Biological Insights in an Untargeted Chemical Analysis of Blood Specimens for Exposomics

Background: An untargeted chemical analysis of bio-fluids provides semi-quantitative data for thousands of chemicals for expanding our understanding about relationships among metabolic pathways, diseases, phenotypes and exposures. During the processing of mass spectral and chromatography data, various signal thresholds are used to control the number of peaks in the final data matrix that is used for statistical analyses. However, commonly used stringent thresholds generate constrained data matrices which may under-represent the detected chemical space, leading to missed biological insights in the exposome research. Methods: We have re-analyzed a liquid chromatography high resolution mass spectrometry data set for a publicly available epidemiology study (n = 499) of human cord blood samples using the MS-DIAL software with minimally possible thresholds during the data processing steps. Peak list for individual files and the data matrix after alignment and gap-filling steps were summarized for different peak height and detection frequency thresholds. Correlations between birth weight and LC/MS peaks in the newly generated data matrix were computed using the spearman correlation coefficient. Results: MS-DIAL software detected on average 23,156 peaks for individual LC/MS file and 63,393 peaks in the aligned peak table. A combination of peak height and detection frequency thresholds that was used in the original publication at the individual file and the peak alignment levels can reject 90% peaks from the untargeted chemical analysis dataset that was generated by MS-DIAL. Correlation analysis for birth weight data suggested that up to 80% of the significantly associated peaks were rejected by the data processing thresholds that were used in the original publication. The re-analysis with minimum possible thresholds recovered metabolic insights about C19 steroids and hydroxy-acyl-carnitines and their relationships with birth weight. Conclusions: Data processing thresholds for peak height and detection frequencies at individual data file and at the alignment level should be used at minimal possible level or completely avoided for mining untargeted chemical analysis data in the exposome research for discovering new biomarkers and mechanisms.

Ambient PM2.5 species and ultrafine particle exposure and their differential metabolomic signatures

BACKGROUND

The metabolomic signatures of short- and long-term exposure to PM_2.5 have been reported and linked to inflammation and oxidative stress. However, little is known about the relative contribution of the specific PM_2.5 species (hence sources) that drive these metabolomic signatures.

OBJECTIVES

We aimed to determine the relative contribution of the different species of PM_2.5 exposure to the perturbed metabolic pathways related to changes in the plasma metabolome.

METHODS

We performed mass-spectrometry based metabolomic profiling of plasma samples among men from the Normative Aging Study to identify metabolic pathways associated with PM_2.5 species. The exposure windows included short-term (one, seven-, and thirty-day moving average) and long-term (one year moving average). We used linear mixed-effect regression with subject-specific intercepts while simultaneously adjusting for PM_2.5, NO₂, O₃, temperature, relative humidity, and covariates and correcting for multiple testing. We also used independent component analysis (ICA) to examine the relative contribution of patterns of PM_2.5 species.

RESULTS

Between 2000 and 2016, 456 men provided 648 blood samples, in which 1158 metabolites were quantified. We chose 305 metabolites for the short-term and 288 metabolites for the long-term exposure in this analysis that were significantly associated (p-value < 0.01) with PM_2.5 to include in our PM_2.5 species analysis. On average, men were 75.0 years old and their body mass index was 27.7 kg/m². Only 3% were current smokers. In the adjusted models, ultrafine particles (UFPs) were the most significant species of short-term PM_2.5 exposure followed by nickel, vanadium, potassium, silicon, and aluminum. Black carbon, vanadium, zinc, nickel, iron, copper, and selenium were the significant species of long-term PM_2.5 exposure. We identified several metabolic pathways perturbed with PM_2.5 species including glycerophospholipid, sphingolipid, and glutathione. These pathways are involved in inflammation, oxidative stress, immunity, and nucleic acid damage and repair. Results were overlapped with the ICA.

CONCLUSIONS

We identified several significant perturbed plasma metabolites and metabolic pathways associated with exposure to PM_2.5 species. These species are associated with traffic, fuel oil, and wood smoke. This is the largest study to report a metabolomic signature of PM_2.5 species' exposure and the first to use ICA.

A feasibility study of metabolic phenotyping of dried blood spot specimens in rural Chinese women exposed to household air pollution

BACKGROUND

Exposure-response studies and policy evaluations of household air pollution (HAP) are limited by current methods of exposure assessment which are expensive and burdensome to participants.

METHODS

We collected 152 dried blood spot (DBS) specimens during the heating and non-heating seasons from 53 women who regularly used biomass-burning stoves for cooking and heating. Participants were enrolled in a longitudinal study in China. Untargeted metabolic phenotyping of DBS were generated using ultra-high performance liquid chromatography coupled with mass spectrometry to exemplify measurement precision and assessment for feasibility to detect exposure to HAP, evaluated by season (high pollution vs. low pollution) and measured personal exposure to fine particulate matter <2.5 μm diameters (PM2.5) and black carbon (BC) in the 48-h prior to collecting the DBS specimen.

RESULTS

Metabolites e.g., amino acids, acyl-carnitines, lyso-phosphorylcholines, sphinganine, and choline were detected in the DBS specimens. Our approach is capable of detecting the differences in personal exposure to HAP whilst showing high analytical reproducibility, coefficient of variance (CV) <15%, meeting the U.S. Food and Drug Administration criteria.

CONCLUSIONS

Our results provide a proof of principle that high-resolution metabolic phenotypic data can be generated using a simple DBS extraction method thus suitable for exposure studies in remote, low-resource settings where the collection of serum and plasma is logistically challenging or infeasible. The analytical run time (19 min/specimen) is similar to most global phenotyping methods and therefore suitable for large-scale application.

Air Pollution and Adverse Pregnancy and Birth Outcomes: Mediation Analysis Using Metabolomic Profiles

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. 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.

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.

Metabolomic signatures of the long-term exposure to air pollution and temperature

BACKGROUND

Long-term exposures to air pollution has been reported to be associated with inflammation and oxidative stress. However, the underlying metabolic mechanisms remain poorly understood.

OBJECTIVES

We aimed to determine the changes in the blood metabolome and thus the metabolic pathways associated with long-term exposure to outdoor air pollution and ambient temperature.

METHODS

We quantified metabolites using mass-spectrometry based global untargeted metabolomic profiling of plasma samples among men from the Normative Aging Study (NAS). We estimated the association between long-term exposure to PM2.5, NO2, O3, and temperature (annual average of central site monitors) with metabolites and their associated metabolic pathways. We used multivariable linear mixed-effect regression models (LMEM) while simultaneously adjusting for the four exposures and potential confounding and correcting for multiple testing. As a reduction method for the intercorrelated metabolites (outcome), we further used an independent component analysis (ICA) and conducted LMEM with the same exposures.

RESULTS

Men (N = 456) provided 648 blood samples between 2000 and 2016 in which 1158 metabolites were quantified. On average, men were 75.0 years and had an average body mass index of 27.7 kg/m2. Almost all men (97%) were not current smokers. The adjusted analysis showed statistically significant associations with several metabolites (58 metabolites with PM2.5, 15 metabolites with NO2, and 6 metabolites with temperature) while no metabolites were associated with O3. One out of five ICA factors (factor 2) was significantly associated with PM2.5. We identified eight perturbed metabolic pathways with long-term exposure to PM2.5 and temperature: glycerophospholipid, sphingolipid, glutathione, beta-alanine, propanoate, and purine metabolism, biosynthesis of unsaturated fatty acids, and taurine and hypotaurine metabolism. These pathways are related to inflammation, oxidative stress, immunity, and nucleic acid damage and repair.

CONCLUSIONS

Using a global untargeted metabolomic approach, we identified several significant metabolites and metabolic pathways associated with long-term exposure to PM2.5, NO2 and temperature. This study is the largest metabolomics study of long-term air pollution, to date, the first study to report a metabolomic signature of long-term temperature exposure, and the first to use ICA in the analysis of both.

Prenatal Exposure to Multiple Air Pollutants, Mediating Molecular Mechanisms, and Shifts in Birthweight

Mechanisms underlying adverse birth and later in life health effects from exposure to air pollution during the prenatal period have not been not fully elucidated, especially in the context of mixtures. We assessed the effects of prenatal exposure to mixtures of air pollutants of particulate matter (PM), PM2.5, PM10, nitrogen oxides, NO2, NOx, ultrafine particles (UFP), and oxidative potential (OP) of PM2.5 on infant birthweight in four European birth cohorts and the mechanistic underpinnings through cross-omics of metabolites and inflammatory proteins. The association between mixtures of air pollutants and birthweight z-scores (standardized for gestational age) was assessed for three different mixture models, using Bayesian machine kernel regression (BKMR). We determined the direct effect for PM2.5, PM10, NO2, and mediation by cross-omic signatures (identified using sparse partial least-squares regression) using causal mediation BKMR models. There was a negative association with birthweight z-scores and exposure to mixtures of air pollutants, where up to -0.21 or approximately a 96 g decrease in birthweight, comparing the 75th percentile to the median level of exposure to the air pollutant mixture could occur. Shifts in birthweight z-scores from prenatal exposure to PM2.5, PM10, and NO2 were mediated by molecular mechanisms, represented by cross-omics scores. Interleukin-17 and epidermal growth factor were identified as important inflammatory responses underlyingair pollution-associated shifts in birthweight. Our results signify that by identifying mechanisms through which mixtures of air pollutants operate, the causality of air pollution-associated shifts in birthweight is better supported, substantiating the need for reducing exposure in vulnerable populations.

Dynamic linkages among economic development, environmental pollution and human health in Chinese

Background

Research on the relationships between economic development, energy consumption, environmental pollution, and human health has tended to focus on the relationships between economic growth and air pollution, energy and air pollution, or the impact of air pollution on human health. However, there has been little past research focused on all the above associations.

Methods

The few studies that have examined the interconnections between the economy, energy consumption, environmental pollution and health have tended to employ regression analyses, DEA (Data Envelopment Analysis), or DEA efficiency analyses; however, as these are static analysis tools, the analyses did not fully reveal the sustainable economic, energy, environmental or health developments over time, did not consider the regional differences, and most often ignored community health factors. To go some way to filling this gap, this paper developed a modified two stage Undesirable Meta Dynamic Network model to jointly analyze energy consumption, economic growth, air pollution and health treatment data in 31 Chinese high-income and upper-middle income cities from 2013-2016, for which the overall efficiency, production efficiency, healthcare resource utilization efficiency and technology gap ratio (TGR) for all input and output variables were calculated.

Results

It was found that: (1) the annual average overall efficiency in China's eastern region was the highest; (2) the production stage efficiencies were higher than the healthcare resource utilization stage efficiencies in most cities; (3) the high-income cities had lower TGRs than the upper-middle income cities; (4) the high-income cities had higher average energy consumption efficiencies than the upper-middle income cities; (5) the health expenditure efficiencies were the lowest of all inputs; (6) the high-income cities' respiratory disease and mortality rate efficiencies were higher than in the upper-middle income cities, which had improving mortality rate efficiencies; and (7) there were significant regional differences in the annual average input and output indicator efficiencies.

Conclusions

First, the high-income cities had higher average efficiencies than the upper-middle income cities. Of the ten eastern region high-income cities, Guangzhou and Shanghai had average efficiencies of 1, with the least efficient being Shijiazhuang. In the other regions, the upper-middle income cities required greater technology and health treatment investments. Second, Guangzhou, Lhasa, Nanning, and Shanghai had production efficiencies of 1, and Guangzhou, Lhasa, Nanning, Shanghai and Fuzhou had healthcare resource utilization efficiencies of 1. As the average production stage efficiencies in most cities were higher than the healthcare resource utilization stage efficiencies, greater efforts are needed to improve the healthcare resource utilization. Third, the technology gap ratios (TGRs) in the high-income cities were slightly higher than in the upper-middle income cities. Therefore, the upper-middle income cities need to learn from the high-income cities to improve their general health treatment TGRs. Fourth, while the high-income cities had higher energy consumption efficiencies than the upper-middle income cities, these were decreasing in most cities. There were few respiratory disease efficiency differences between the high-income and upper-middle income cities, the high-income cities had falling mortality rate efficiencies, and the upper-middle income cities had increasing mortality rate efficiencies. Overall, therefore, most cities needed to strengthen their health governance to balance economic growth and urban expansion. Fifth, the average AQI efficiencies in both the high-income and upper-middle income cities were higher than the average CO₂ efficiencies. However, the high-income cities had lower average CO₂ emissions and AQI efficiencies than the upper-middle income cities, with the AQI efficiency differences between the two city groups expanding. As most cities were focusing more on air pollution controls than carbon dioxide emissions, greater efforts were needed in coordinating the air pollution and carbon dioxide emissions treatments. Therefore, the following suggestions are given. (1) The government should reform the hospital and medical systems. (2) Local governments need to strengthen their air pollution and disease education. (3) High-income cities need to improve their healthcare governance to reduce the incidence of respiratory diseases and the associated mortality. (4) Healthcare governance efficiency needs to be prioritized in 17 upper-middle income cities, such as Hangzhou, Changchun, Harbin, Chengdu, Guiyang, Kunming and Xi'an, by establishing sound medical management systems and emergency environmental pollution treatments, and by increasing capital asset medical investments. (5) Upper-middle income cities need to adapt their treatment controls to local conditions and design medium to long-term development strategies. (6) Upper-middle income cities need to actively learn from the technological and governance experiences in the more efficient higher-income cities.

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry

BACKGROUND

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR.

AIM OF REVIEW

This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

Prospective Investigation of Serum Metabolites, Coffee Drinking, Liver Cancer Incidence, and Liver Disease Mortality

BACKGROUND

Coffee has been consistently associated with lower risk of liver cancer and chronic liver disease, suggesting that coffee affects mechanisms underlying disease development.

METHODS

We measured serum metabolites using untargeted metabolomics in 1:1 matched nested case-control studies of liver cancer (n = 221 cases) and fatal liver disease (n = 242 cases) in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention cohort (n = 29 133). Associations between baseline coffee drinking and metabolites were identified using linear regression; conditional logistic regression models were used to identify associations with subsequent outcomes.

RESULTS

Overall, 21 metabolites were associated with coffee drinking and also each subsequent endpoint; nine metabolites and trigonelline, a known coffee biomarker, were identified. Tyrosine and two bile acids, glycochenodeoxycholic acid (GCDCA) and glycocholic acid (GCA), were inversely associated with coffee but positively associated with both outcomes; odds ratios (ORs) comparing the 90th to 10th percentile (modeled on a continuous basis) ranged from 3.93 (95% confidence interval [CI] = 2.00 to 7.74) for tyrosine to 4.95 (95% CI = 2.64 to 9.29) for GCA and from 4.00 (95% CI = 2.42 to 6.62) for GCA to 6.77 (95% CI = 3.62 to 12.65) for GCDCA for liver cancer and fatal liver disease, respectively. The remaining six metabolites and trigonelline were positively associated with coffee drinking but inversely associated with both outcomes; odds ratio ranged from 0.16 to 0.37. Associations persisted following diet adjustment and for outcomes occurring greater than 10 years after blood collection.

CONCLUSIONS

A broad range of compounds were associated with coffee drinking, incident liver cancer, and liver disease death over 27 years of follow-up. These associations provide novel insight into chronic liver disease and liver cancer etiology and support a possible hepatoprotective effect of coffee.

The Energy Efficiency and the Impact of Air Pollution on Health in China

The rapid growth of China's economy in recent years has greatly improved its citizens' living standards, but economic growth consumes many various energy sources as well as produces harmful air pollution. Nitrogen oxides, SO₂ (sulfur dioxide), and other polluting gases are damaging the environment and people's health, with a particular spike in incidences of many air pollution-related diseases in recent years. While there have been many documents discussing China's energy and environmental issues in the past, few of them analyze economic development, air pollution, and residents' health together. Therefore, this study uses the modified undesirable dynamic two-stage DEA (data envelopment analysis) model to explore the economic, environmental, and health efficiencies of 30 provinces in China. The empirical results show the following: (1) Most provinces have lower efficiency values in the health stage than in the production stage. (2) Among the provinces with annual efficiency values below 1, their energy consumption, CO₂ (carbon dioxide), and NOx (nitrogen oxide) efficiency values have mostly declined from 2013 to 2016, while their SO₂ efficiency values have increased (less SO₂ emissions). (3) The growth rate of SO₂ efficiency in 2016 for 10 provinces is much higher than in previous years. (4) The health expenditure efficiencies of most provinces are at a lower level and show room for improvement. (5) In most provinces, the mortality rate is higher, but on a decreasing trend. (6) Finally, as representative for a typical respiratory infection, most provinces have a high level of tuberculosis efficiency, indicating that most areas of China are highly effective at respiratory disease governance.

Identification of Potential Biomarkers of Radiation Exposure in Blood Cells by Capillary Electrophoresis Time-of-Flight Mass Spectrometry

Biodosimetry is a useful method for estimating personal exposure doses to ionizing radiation. Studies have identified metabolites in non-cellular biofluids that can be used as markers in biodosimetry. Levels of metabolites in blood cells may reflect health status or environmental stresses differentially. Here, we report changes in the levels of murine blood cell metabolites following exposure to X-rays in vivo. Levels of blood cell metabolites were measured by capillary electrophoresis time-of-flight mass spectrometry. The levels of 100 metabolites were altered substantially following exposure. We identified 2-aminobutyric acid, 2'-deoxycytidine, and choline as potentially useful markers of radiation exposure and established a potential prediction panel of the exposure dose using stepwise regression. Levels of blood cell metabolites may be useful biomarkers in estimating exposure doses during unexpected radiation incidents.

Pollution evaluation and health risk assessment of airborne toxic metals in both indoors and outdoors of the Pearl River Delta, China

BACKGROUND

Industries deveploped cities in the Pearl River Delta (PRD) are suffering serious atmospheric metals pollution, in which, people's health risks after inhaling particulate matter (PM) with airborne toxic metals might be rising. This study provides the latest and comprehensive pollution profiles of toxic metals both from indoors and outdoors in PRD.

METHOD

Total 22 pairs of indoor and outdoor total suspended particulates (TSP), PM₁₀ and PM_2.5 samples in residential area were synchronously sampled and investigated in detail within 9 main cities of the PRD, China. The concentrations of the Zn, Pb, Mn, Ni, As, V, Sb and Cd in the samples were measured by inductively coupled plasma mass spectrometry (ICP-MS). Health risk assessment via inhalation of residents was estimated by EPA recommended model with exposure parameters of Chinese population indoor and outdoor activity pattern.

RESULTS

The trends followed as Zn > Pb ≈ Mn > Ni > As > V > Sb ≈ Cd for both indoors and outdoors. Investigated metals were found to be dominantly distributed in PM_2.5 for both indoors and outdoors. The concentrations of outdoor PM and the most of metals were significantly higher than those of indoors. The results concluded that toxic metals might be from regional emission, such as Pb from ceramic factory, Ni from motor factory and V from oil combustion of ship. In health risk assessments, LCR is higher than 1.00E-06 for adults, while contrary to children in the PRD. Among four carcinogenic metals, LCR of As and Cd are higher than 1.00E-06 in some cities. In addition, HI below one for both adults and children in the PRD.

CONCLUSIONS

Outdoor metals concentrations are related to local industry types, while indoor metals are mainly from outdoor. Health risk assessments indicated that adults suffered unsafe cancer risk from metals, especially As and Cd in some cities, while both adults and children did not suffer non-carcinogenic risks.

Maternal serum metabolome and traffic-related air pollution exposure in pregnancy

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 <2.5 μm) during first-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We used liquid chromatography-high resolution mass spectrometry to obtain untargeted metabolic profiles and partial least squares discriminant analysis (PLS-DA) to select metabolic features associated with air pollution exposure. Pathway analyses were employed to identify biologic pathways related to air pollution exposure. As potential confounders we included maternal age, maternal race/ethnicity, and maternal education.

RESULTS

In total we extracted 4038 and 4957 metabolic features from maternal serum samples in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 (negative ion mode) columns, respectively. After controlling for confounding factors, PLS-DA (Variable Importance in Projection (VIP) ≥2) yielded 181 and 251 metabolic features (HILIC and C18, respectively) that discriminated between the high (n = 98) and low exposed (n = 62). Pathway enrichment analysis for discriminatory features associated with air pollution indicated that in maternal serum oxidative stress and inflammation related pathways were altered, including linoleate, leukotriene, and prostaglandin pathways.

CONCLUSION

The metabolomic features and pathways we found to be associated with air pollution exposure suggest that maternal exposure during pregnancy induces oxidative stress and inflammation pathways previously implicated in pregnancy complications and adverse outcomes.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSION

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

Perturbations of the arginine metabolome following exposures to traffic-related air pollution in a panel of commuters with and without asthma

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 < 0.05). From both negative and positive ionization modes, 17,586 and 9087 metabolic features were extracted from plasma, respectively. 494 and 220 unique features were associated with at least 3 of the 27 exposures, respectively (p < 0.05), after controlling confounders and false discovery rates. Pathway analysis indicated alteration of several inflammatory and oxidative stress related metabolic pathways, including leukotriene, vitamin E, cytochrome P450, and tryptophan metabolism. We identified and annotated 45 unique metabolites enriched in these pathways, including arginine, histidine, and methionine. Most of these metabolites were not only associated with multiple pollutants, but also differentially expressed between participants with and without asthma. The analysis indicated that these metabolites collectively participated in an interrelated molecular network centering on arginine metabolism, underlying the impact of traffic-related pollutants on individuals with asthma.

CONCLUSIONS

We detected numerous significant metabolic perturbations associated with in-vehicle exposures during commuting and validated metabolites that were closely linked to several inflammatory and redox pathways, elucidating the potential molecular mechanisms of traffic-related air pollution toxicity. These results support future studies of metabolic markers of traffic exposures and the corresponding molecular mechanisms.

Metabolomic assessment of exposure to near-highway ultrafine particles

Exposure to traffic-related air pollutants has been associated with increased risk of adverse cardiopulmonary outcomes and mortality; however, the biochemical pathways linking exposure to disease are not known. To delineate biological response mechanisms associated with exposure to near-highway ultrafine particles (UFP), we used untargeted high-resolution metabolomics to profile plasma from 59 participants enrolled in the Community Assessment of Freeway Exposure and Health (CAFEH) study. Metabolic variations associated with UFP exposure were assessed using a cross-sectional study design based upon low (mean 16,000 particles/cm3) and high (mean 24,000 particles/cm3) annual average UFP exposures. In comparing quantified metabolites, we identified five metabolites that were differentially expressed between low and high exposures, including arginine, aspartic acid, glutamine, cystine and methionine sulfoxide. Analysis of the metabolome identified 316 m/z features associated with UFP, which were consistent with increased lipid peroxidation, endogenous inhibitors of nitric oxide and vehicle exhaust exposure biomarkers. Network correlation analysis and metabolic pathway enrichment identified 38 pathways and included variations related to inflammation, endothelial function and mitochondrial bioenergetics. Taken together, these results suggest UFP exposure is associated with a complex series of metabolic variations related to antioxidant pathways, in vivo generation of reactive oxygen species and processes critical to endothelial function.

Metabolomics Profiling before, during, and after the Beijing Olympics: A Panel Study of Within-Individual Differences during Periods of High and Low Air Pollution

BACKGROUND

The metabolome is a collection of exogenous chemicals and metabolites from cellular processes that may reflect the body's response to environmental exposures. Studies of air pollution and metabolomics are limited.

OBJECTIVES

To explore changes in the human metabolome before, during, and after the 2008 Beijing Olympics Games, when air pollution was high, low, and high, respectively.

METHODS

Serum samples were collected before, during, and after the Olympics from 26 participants in an existing panel study. Gas and ultra-high performance liquid chromatography/mass spectrometry were used in metabolomics analysis. Repeated measures ANOVA, network analysis, and enrichment analysis methods were employed to identify metabolites and classes associated with air pollution changes.

RESULTS

A total of 886 molecules were measured in our metabolomics analysis. Network partitioning identified four modules with 65 known metabolites that significantly changed across the three time points. All known molecules in the first module ([Formula: see text]) were lipids (e.g., eicosapentaenoic acid, stearic acid). The second module consisted primarily of dipeptides ([Formula: see text], e.g., isoleucylglycine) plus 8 metabolites from four other classes (e.g., hypoxanthine, 12-hydroxyeicosatetraenoic acid). Most of the metabolites in Modules 3 (19 of 23) and 4 (5 of 5) were unknown. Enrichment analysis of module-identified metabolites indicted significantly overrepresented pathways, including long- and medium-chain fatty acids, polyunsaturated fatty acids (n3 and n6), eicosanoids, lysolipid, dipeptides, fatty acid metabolism, and purine metabolism [(hypo) xanthine/inosine-containing pathways].

CONCLUSIONS

We identified two major metabolic signatures: one consisting of lipids, and a second that included dipeptides, polyunsaturated fatty acids, taurine, and xanthine. Metabolites in both groups decreased during the 2008 Beijing Olympics, when air pollution was low, and increased after the Olympics, when air pollution returned to normal (high) levels. https://doi.org/10.1289/EHP3705.

The metabolome: A key measure for exposome research in epidemiology

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

SUMMARY

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

Emerging concepts and challenges in implementing the exposome paradigm in allergic diseases and asthma: a Practall document

Exposome research can improve the understanding of the mechanistic connections between exposures and health to help mitigate adverse health outcomes across the life span. The exposomic approach provides a risk profile instead of single predictors and thus is particularly applicable to allergic diseases and asthma. Under the PRACTALL collaboration between the European Academy of Allergy and Clinical Immunology (EAACI) and the American Academy of Allergy, Asthma, and Immunology (AAAAI), we evaluated the current concepts and the unmet needs on the role of the exposome in allergic diseases and asthma.

Impact of short-term traffic-related air pollution on the metabolome - Results from two metabolome-wide experimental studies

Exposure to traffic-related air pollution (TRAP) has been associated with adverse health outcomes but underlying biological mechanisms remain poorly understood. Two randomized crossover trials were used here, the Oxford Street II (London) and the TAPAS II (Barcelona) studies, where volunteers were allocated to high or low air pollution exposures. The two locations represent different exposure scenarios, with Oxford Street characterized by diesel vehicles and Barcelona by normal mixed urban traffic. Levels of five and four pollutants were measured, respectively, using personal exposure monitoring devices. Serum samples were used for metabolomic profiling. The association between TRAP and levels of each metabolic feature was assessed. All pollutant levels were significantly higher at the high pollution sites. 29 and 77 metabolic features were associated with at least one pollutant in the Oxford Street II and TAPAS II studies, respectively, which related to 17 and 30 metabolic compounds. Little overlap was observed across pollutants for metabolic features, suggesting that different pollutants may affect levels of different metabolic features. After observing the annotated compounds, the main pathway suggested in Oxford Street II in association with NO2 was the acyl-carnitine pathway, previously found to be associated with cardio-respiratory disease. No overlap was found between the metabolic features identified in the two studies.