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

Dysregulated metabolic pathways associated with air pollution exposure and the risk of autism: Evidence from epidemiological studies

Autism spectrum disorder (ASD) is a developmental disorder with symptoms that range from social and communication impairments to restricted interests and repetitive behavior and is the 4th most disabling condition for children aged 5-14. Risk factors of ASD are not fully understood. Environmental risk factors are believed to play a significant role in the ASD epidemic. Research focusing on air pollution exposure as an early-life risk factor of autism is growing, with numerous studies finding associations of traffic and industrial emissions with an increased risk of ASD. One of the possible mechanisms linking autism and air pollution exposure is metabolic dysfunction. However, there were no consensus about the key metabolic pathways and corresponding metabolite signatures in mothers and children that are altered by air pollution exposure and cause the ASD. Therefore, we performed a review of published papers examining the metabolomic signatures and metabolic pathways that are associated with either air pollution exposure or ASD risk in human studies. In conclusion, we found that dysregulated lipid, fatty acid, amino acid, neurotransmitter, and microbiome metabolisms are associated with both short-term and long-term air pollution exposure and the risk of ASD. These dysregulated metabolisms may provide insights into ASD etiology related to air pollution exposure, particularly during the perinatal period in which neurodevelopment is highly susceptible to damage from oxidative stress and inflammation.

Development of a metabolomic risk score for exposure to traffic-related air pollution: A multi-cohort study

To synthesize vast amounts of high-throughput biological information, omics-fields like epigenetics have applied risk scores to develop biomarkers for environmental exposures. Extending the risk score analytic tool to the metabolomic data would be highly beneficial. This research aimed to develop and evaluate metabolomic risk score (metRS) approaches reflecting the biological response to traffic-related air pollution (TRAP) exposure (fine particulate matter, black carbon, and nitrogen dioxide). A simulation study compared three metRS methodologies: elastic net regression, which uses penalized regression to select metabolites, and two variations of thresholding, where a p-value cutoff is used to select metabolites. The methods performance was compared to assess 1) ability to correctly select metabolites associated with daily TRAP and 2) ability of the risk score to predict daily TRAP exposure. Power calculations and false discovery rates (FDR) were calculated for each approach. This metRS was applied to two real cohorts, the Center for Health Discovery and Wellbeing (CHDWB, n = 180) and Environment and Reproductive Health (EARTH, n = 200). In simulations, elastic net regression consistently presented inflated FDR for both high and low effect sizes and across all three sample sizes (n = 200; 500; 1000). Power to detect correct metabolites exceeded 0.8 for all three sample sizes in all three methods. In the real data application assessing associations of metabolomics risk scores and TRAP, associations were largely null. While we did not identify strong associations between the risk scores and TRAP in the real data application, metabolites selected by the risk score approaches were enriched in pathways that are well-known for their association with TRAP. These results demonstrate that certain methodologies to construct metabolomics risk scores are statistically robust and valid; however, standardized metabolic profiling and large sample sizes are required.

The chemical composition of secondary organic aerosols regulates transcriptomic and metabolomic signaling in an epithelial-endothelial in vitro coculture

BACKGROUND

The formation of secondary organic aerosols (SOA) by atmospheric oxidation reactions substantially contributes to the burden of fine particulate matter (PM2.5), which has been associated with adverse health effects (e.g., cardiovascular diseases). However, the molecular and cellular effects of atmospheric aging on aerosol toxicity have not been fully elucidated, especially in model systems that enable cell-to-cell signaling.

METHODS

In this study, we aimed to elucidate the complexity of atmospheric aerosol toxicology by exposing a coculture model system consisting of an alveolar (A549) and an endothelial (EA.hy926) cell line seeded in a 3D orientation at the air‒liquid interface for 4 h to model aerosols. Simulation of atmospheric aging was performed on volatile biogenic (β-pinene) or anthropogenic (naphthalene) precursors of SOA condensing on soot particles. The similar physical properties for both SOA, but distinct differences in chemical composition (e.g., aromatic compounds, oxidation state, unsaturated carbonyls) enabled to determine specifically induced toxic effects of SOA.

RESULTS

In A549 cells, exposure to naphthalene-derived SOA induced stress-related airway remodeling and an early type I immune response to a greater extent. Transcriptomic analysis of EA.hy926 cells not directly exposed to aerosol and integration with metabolome data indicated generalized systemic effects resulting from the activation of early response genes and the involvement of cardiovascular disease (CVD) -related pathways, such as the intracellular signal transduction pathway (PI3K/AKT) and pathways associated with endothelial dysfunction (iNOS; PDGF). Greater induction following anthropogenic SOA exposure might be causative for the observed secondary genotoxicity.

CONCLUSION

Our findings revealed that the specific effects of SOA on directly exposed epithelial cells are highly dependent on the chemical identity, whereas non directly exposed endothelial cells exhibit more generalized systemic effects with the activation of early stress response genes and the involvement of CVD-related pathways. However, a greater correlation was made between the exposure to the anthropogenic SOA compared to the biogenic SOA. In summary, our study highlights the importance of chemical aerosol composition and the use of cell systems with cell-to-cell interplay on toxicological outcomes.

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.

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.

Human Milk Composition Is Associated with Maternal Body Mass Index in a Cross-Sectional, Untargeted Metabolomics Analysis of Human Milk from Guatemalan Mothers

Background

Maternal overweight and obesity has been associated with poor lactation performance including delayed lactogenesis and reduced duration. However, the effect on human milk composition is less well understood.

Objectives

We evaluated the relationship of maternal BMI on the human milk metabolome among Guatemalan mothers.

Methods

We used data from 75 Guatemalan mothers who participated in the Household Air Pollution Intervention Network trial. Maternal BMI was measured between 9 and <20 weeks of gestation. Milk samples were collected at a single time point using aseptic collection from one breast at 6 mo postpartum and analyzed using high-resolution mass spectrometry. A cross-sectional untargeted high-resolution metabolomics analysis was performed by coupling hydrophilic interaction liquid chromatography (HILIC) and reverse phase C18 chromatography with mass spectrometry. Metabolic features associated with maternal BMI were determined by a metabolome-wide association study (MWAS), adjusting for baseline maternal age, education, and dietary diversity, and perturbations in metabolic pathways were identified by pathway enrichment analysis.

Results

The mean age of participants at baseline was 23.62 ± 3.81 y, and mean BMI was 24.27 ± 4.22 kg/m2. Of the total metabolic features detected by HILIC column (19,199 features) and by C18 column (11,594 features), BMI was associated with 1026 HILIC and 500 C18 features. Enriched pathways represented amino acid metabolism, galactose metabolism, and xenobiotic metabolic metabolism. However, no significant features were identified after adjusting for multiple comparisons using the Benjamini-Hochberg false discovery rate procedure (FDRBH < 0.2).

Conclusions

Findings from this untargeted MWAS indicate that maternal BMI is associated with metabolic perturbations of galactose metabolism, xenobiotic metabolism, and xenobiotic metabolism by cytochrome p450 and biosynthesis of amino acid pathways. Significant metabolic pathway alterations detected in human milk were associated with energy metabolism-related pathways including carbohydrate and amino acid metabolism.This trial was registered at clinicaltrials.gov as NCT02944682.

Mechanistic insights into cardiovascular effects of ultrafine particle exposure: A longitudinal panel study

BACKGROUND

Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated.

OBJECTIVES

This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved.

METHODS

A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses.

RESULTS

Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0-3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7-12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism.

DISCUSSION

This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Mapping multi-omics characteristics related to short-term PM2.5 trajectory and their impact on type 2 diabetes in middle-aged and elderly adults in Southern China

The relationship between PM2.5 and metabolic diseases, including type 2 diabetes (T2D), has become increasingly prominent, but the molecular mechanism needs to be further clarified. To help understand the mechanistic association between PM2.5 exposure and human health, we investigated short-term PM2.5 exposure trajectory-related multi-omics characteristics from stool metagenome and metabolome and serum proteome and metabolome in a cohort of 3267 participants (age: 64.4 ± 5.8 years) living in Southern China. And then integrate these features to examine their relationship with T2D. We observed significant differences in overall structure in each omics and 193 individual biomarkers between the high- and low-PM2.5 groups. PM2.5-related features included the disturbance of microbes (carbohydrate metabolism-associated Bacteroides thetaiotaomicron), gut metabolites of amino acids and carbohydrates, serum biomarkers related to lipid metabolism and reducing n-3 fatty acids. The patterns of overall network relationships among the biomarkers differed between T2D and normal participants. The subnetwork membership centered on the hub nodes (fecal rhamnose and glycylproline, serum hippuric acid, and protein TB182) related to high-PM2.5, which well predicted higher T2D prevalence and incidence and a higher level of fasting blood glucose, HbA1C, insulin, and HOMA-IR. Our findings underline crucial PM2.5-related multi-omics biomarkers linking PM2.5 exposure and T2D in humans.

Combined exposure of MAHs and PAHs enhanced amino acid and lipid metabolism disruption in epithelium leading asthma risk

Monoaromatic hydrocarbons (MAHs) and polycyclic aromatic hydrocarbons (PAHs) are ubiquitous air pollutants from industry, with multiple adverse effects on respiratory system. However, the underlying mechanisms of their mixture to induce asthma is still unclear. Here, we examined mixture of 8 MAHs, mixture of 16 PAHs and a total mixture (MIX) on human bronchial epithelial (16-HBE) cells. Exposure to MIX resulted in increased expressions of asthma alarm cytokines (TSLP, IL-25 and IL-33), indicating potential asthma risk. Exposure to MIX led to significant upregulation of transcriptional level of oxidative stress and inflammation biomarkers through aryl hydrocarbon receptor activation, including SOD-2, NQO-1, IL-1β, IL-6 and IL-8 with 3.1, 19.9, 3.5, 23.4, 18.7, 28.1-fold change, indicated asthma related epithelial cell lesions. A total of 25, 49 and 59 differential metabolites were identified in cells response to MAH, PAH and MIX exposure, respectively, and enrichment analysis demonstrated MIX exposure disturbing alanine, aspartate and glutamate metabolism, glutathione metabolism, methionine metabolism and sphingolipid metabolism, involved in antioxidative defense and inflammation response. Combined exposure of MAHs and PAHs may result in increased toxic risks, and provide evidence to asthma onset and deterioration.

[New advances in exposomics-analysis methods and research paradigms based on chromatography-mass spectrometry]

The occurrence and development of human diseases are influenced by both genetic and environmental factors. Research models that describe disease occurrence only from the perspective of genetics present certain limitations. In recent years, effects of environment factors on the occurrence and development of diseases have attracted extensive attentions. Exposomics focuses on the measurement of all exposure factors in an individual's life and how these factors are related to disease development. Exposomics provides new ideas to promote studies on the relationship between human health and environmental factors. Environmental exposures are characterized with different physical and chemical properties, as well as very low concentrations in vivo, which contribute great challenges in the comprehensive measurement of chemical residues in the human body. Chromatography-mass spectrometry-based technologies combine the high-efficiency separation ability of chromatography with the high resolution and sensitive detection characteristics of mass spectrometry; the combination of these techniques can achieve the high-coverage, high-throughput, and sensitive detection of environmental exposures, thus providing a powerful tool for measuring chemical exposures. Exposomics-analysis methods based on chromatography-mass spectrometry mainly include targeted quantitative analysis, suspect screening, and non-targeted screening. To explore the relationship between environmental exposure and the occurrence and development of diseases, researchers have developed research paradigms, including exposome wide association study, mixed-exposure study, exposomics and multi-omics (genome, transcriptome, proteome, metabolome)-association study, and so on. The emergence of these methods has brought about unprecedented developments in exposomics studies. In this manuscript, analytical methods based on chromatography-mass spectrometry, exposomics research paradigms, and their relevant prospects are reviewed.

Air pollution and oxidative stress in adults suffering from airway diseases. Insights from the Gene Environment Interactions in Respiratory Diseases (GEIRD) multi-case control study

Air pollution is a leading risk factor for global mortality and morbidity. Oxidative stress is a key mechanism underlying air-pollution-mediated health effects, especially in the pathogenesis/exacerbation of airway impairments. However, evidence lacks on subgroups at higher risk of developing more severe outcomes in response to air pollution. This multi-centre study aims to evaluate the association between air pollution and oxidative stress in healthy adults and in patients affected by airway diseases from the Italian GEIRD (Gene Environment Interactions in Respiratory Diseases) multi-case control study. Overall, 1841 adults (49 % females, 20-83 years) were included from four Italian centres: Pavia, Sassari, Turin, and Verona. Following a 2-stage screening process, we identified 1273 cases of asthma, chronic bronchitis, rhinitis, or COPD and 568 controls. Systemic oxidative stress was quantified by urinary 8-isoprostane and 8-OH-dG. Individual residential exposures to NO2, PM10, PM2.5, and O3 were derived using an innovative five-stage machine-learning-based approach. Linear mixed regression models tested the association between oxidative stress biomarkers and air pollution tertiles, adjusting by age, sex, BMI, smoking, education and season, with recruiting centres as random intercept. Only cases exhibited higher levels of log-transformed 8-isoprostane and 8-OH-dG in association with NO2 (β: 0.30 95 % CI: 0.08-0.52 and 0.20 95 % CI: 0.03-0.37), PM10 (0.34 95 % CI: 0.12-0.55 and 0.21 95 % CI: 0.05-0.37) and PM2.5 (0.27 95 % CI: 0.09-0.49 and 0.18 95 % CI: 0.02-0.34) as compared to the first tertile of exposure. No significant associations were observed for summer O3. Our findings suggest that exposure to air pollution may increase systemic oxidative stress levels in people suffering from airway diseases. This introduces a potential novel approach available for future epidemiological studies and Public Health for effective prevention strategies oriented at the quantification of early biological effects in susceptible people, whose additional risk level might be currently underrated. Air-pollution-mediated exacerbations, driven by oxidative stress, still deserve our attention.

Traffic Density Exposure, Oxidative Stress Biomarkers and Plasma Metabolomics in a Population-Based Sample: The Hortega Study

Exposure to traffic-related air pollution (TRAP) generates oxidative stress, with downstream effects at the metabolic level. Human studies of traffic density and metabolomic markers, however, are rare. The main objective of this study was to evaluate the cross-sectional association between traffic density in the street of residence with oxidative stress and metabolomic profiles measured in a population-based sample from Spain. We also explored in silico the potential biological implications of the findings. Secondarily, we assessed the contribution of oxidative stress to the association between exposure to traffic density and variation in plasma metabolite levels. Traffic density was defined as the average daily traffic volume over an entire year within a buffer of 50 m around the participants' residence. Plasma metabolomic profiles and urine oxidative stress biomarkers were measured in samples from 1181 Hortega Study participants by nuclear magnetic resonance spectroscopy and high-performance liquid chromatography, respectively. Traffic density was associated with 7 (out of 49) plasma metabolites, including amino acids, fatty acids, products of bacterial and energy metabolism and fluid balance metabolites. Regarding urine oxidative stress biomarkers, traffic associations were positive for GSSG/GSH% and negative for MDA. A total of 12 KEGG pathways were linked to traffic-related metabolites. In a protein network from genes included in over-represented pathways and 63 redox-related candidate genes, we observed relevant proteins from the glutathione cycle. GSSG/GSH% and MDA accounted for 14.6% and 12.2% of changes in isobutyrate and the CH2CH2CO fatty acid moiety, respectively, which is attributable to traffic exposure. At the population level, exposure to traffic density was associated with specific urine oxidative stress and plasma metabolites. Although our results support a role of oxidative stress as a biological intermediary of traffic-related metabolic alterations, with potential implications for the co-bacterial and lipid metabolism, additional mechanistic and prospective studies are needed to confirm our findings.

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.

The neonatal blood spot metabolome in retinoblastoma

Background

Retinoblastoma is rare but nevertheless the most common pediatric eye cancer that occurs in children under age 5. High-resolution metabolomics (HRM) is a powerful analytical approach to profile metabolic features and pathways or identify metabolite biomarkers. To date, no studies have used pre-diagnosis blood samples from retinoblastoma cases and compared them to healthy controls to elucidate early perturbations in tumor pathways.

Objectives

Here, we report on metabolic profiles of neonatal blood comparing cases later in childhood diagnosed with retinoblastoma and controls.

Methods

We employed untargeted metabolomics analysis using neonatal dried blood spots for 1327 children (474 retinoblastoma cases and 853 healthy controls) born in California from 1983 to 2011. Cases were selected from the California Cancer Registry and controls, frequency matched to cases by birth year, from California birth rolls. We performed high-resolution metabolomics to extract metabolic features, partial least squares discriminant analysis (PLS-DA) and logistic regression to identify features associated with disease, and Mummichog pathway analysis to characterize enriched biological pathways.

Results

PLS-DA identified 1917 discriminative features associated with retinoblastoma and Mummichog identified 14 retinoblastoma-related enriched pathways including linoleate metabolism, pentose phosphate pathway, pyrimidine metabolism, fructose and mannose metabolism, vitamin A metabolism, as well as fatty acid and lipid metabolism.

Interpretation

Our findings linked a retinoblastoma diagnosis in early life to newborn blood metabolome perturbations indicating alterations in inflammatory pathways and energy metabolism. Neonatal blood spots may provide a venue for early detection for this or potentially other childhood 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.

Serum and follicular fluid metabolome and markers of ovarian stimulation

STUDY QUESTION

What metabolic pathways and metabolites in the serum and follicular fluid are associated with peak estradiol levels and the number of mature oocytes?

SUMMARY ANSWER

In the serum metabolome, mostly fatty acid and amino acid pathways were associated with estradiol levels and mature oocytes while in the follicular fluid metabolome, mostly lipid, vitamin, and hormone pathways were associated with peak estradiol levels and mature oocytes.

WHAT IS KNOWN ALREADY

Metabolomics has identified several metabolic pathways and metabolites associated with infertility but limited data are available for ovarian stimulation outcomes.

STUDY DESIGN, SIZE, DURATION

A prospective cohort study of women undergoing IVF from 2009 to 2015.

PARTICIPANTS/MATERIALS, SETTING, METHODS

A total of 125 women undergoing a fresh IVF cycle at a fertility clinic in the Northeast United States who provided a serum and follicular fluid sample. Untargeted metabolomics profiling was conducted using liquid chromatography with high-resolution mass spectrometry in two chromatography columns (C18 and hydrophilic interaction chromatography (HILIC)). The main ovarian stimulation outcomes were peak serum estradiol levels and number of mature oocytes. We utilized adjusted generalized linear regression models to identify significant metabolic features. Models were adjusted for age,BMI, initial infertility diagnosis, and ovarian stimulation protocol. We then conducted pathway analysis using mummichog and metabolite annotation using level-1 evidence.

MAIN RESULTS AND ROLE OF CHANCE

In the serum metabolome, 480 and 850 features were associated with peak estradiol levels in the C18 and HILIC columns, respectively. Additionally, 437 and 538 features were associated with mature oocytes in the C18 and HILIC columns, respectively. In the follicular fluid metabolome, 752 and 929 features were associated with peak estradiol levels in the C18 and HILIC columns, respectively, Additionally, 993 and 986 features were associated with mature oocytes in the C18 and HILIC columns, respectively. The most common pathways associated with peak estradiol included fatty acids (serum and follicular fluid), hormone (follicular fluid), and lipid pathways (follicular fluid). The most common pathways associated with the number of mature oocytes retrieved included amino acids (serum), fatty acids (serum and follicular fluid), hormone (follicular fluid), and vitamin pathways(follicular fluid). The vitamin D3 pathway had the strongest association with both ovarian stimulation outcomes in the follicularfluid. Four and nine metabolites were identified using level-1 evidence (validated identification) in the serum and follicular fluid metabolomes, respectively.

LIMITATIONS, REASONS FOR CAUTION

Our sample was majority White and highly educated and may not be generalizable to thewider population. Additionally, residual confounding is possible and the flushing medium used in the follicular fluid could have diluted our results.

WIDER IMPLICATIONS OF THE FINDINGS

The pathways and metabolites identified by our study provide novel insights into the biologicalmechanisms in the serum and follicular fluid that may underlie follicular and oocyte development, which could potentially be used to improve ovarian stimulation outcomes.

STUDY FUNDING/COMPETING INTEREST(S)

This work was supported by the following grants from the National Institute of Environmental Health Sciences (P30-ES019776, R01-ES009718, R01-ES022955, P30-ES000002, R00-ES026648, and T32-ES012870), and National Institute of Diabetes and Digestive and Kidney Diseases (P30DK046200). The authors have no competing interests to disclose.

TRIAL REGISTRATION NUMBER

N/A.

Metabolic Perturbations Associated with an Exposure Mixture of Per- and Polyfluoroalkyl Substances in the Atlanta African American Maternal-Child Cohort

Prenatal exposure to single chemicals belonging to the per- and polyfluoroalkyl substances (PFAS) family is associated with biological perturbations in the mother, fetus, and placenta, plus adverse health outcomes. Despite our knowledge that humans are exposed to multiple PFAS, the potential joint effects of PFAS on the metabolome remain largely unknown. Here, we leveraged high-resolution metabolomics to identify metabolites and metabolic pathways perturbed by exposure to a PFAS mixture during pregnancy. Targeted assessment of perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorooctanesulfonic acid (PFOS), and perfluorohexanesulfonic acid (PFHxS), along with untargeted metabolomics profiling, were conducted on nonfasting serum samples collected from pregnant African Americans at 6-17 weeks gestation. We estimated the overall mixture effect and partial effects using quantile g-computation and single-chemical effects using linear regression. All models were adjusted for maternal age, education, parity, early pregnancy body mass index, substance use, and gestational weeks at sample collection. Our analytic sample included 268 participants and was socioeconomically diverse, with the majority receiving public health insurance (78%). We observed 13.3% of the detected metabolic features were associated with the PFAS mixture (n = 1705, p < 0.05), which was more than any of the single PFAS chemicals. There was a consistent association with metabolic pathways indicative of systemic inflammation and oxidative stress (e.g., glutathione, histidine, leukotriene, linoleic acid, prostaglandins, and vitamins A, C, D, and E metabolism) across all metabolome-wide association studies. Twenty-six metabolites were validated against authenticated compounds and associated with the PFAS mixture (p < 0.05). Based on quantile g-computation weights, PFNA contributed the most to the overall mixture effect for γ-aminobutyric acid (GABA), tyrosine, and uracil. In one of the first studies of its kind, we demonstrate the feasibility and utility of using methods designed for exposure mixtures in conjunction with metabolomics to assess the potential joint effects of multiple PFAS chemicals on the human metabolome. We identified more pronounced metabolic perturbations associated with the PFAS mixture than for single PFAS chemicals. Taken together, our findings illustrate the potential for integrating environmental mixture analyses and high-throughput metabolomics to elucidate the molecular mechanisms underlying human health.

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.

Assessing Metabolic Differences Associated with Exposure to Polybrominated Biphenyl and Polychlorinated Biphenyls in the Michigan PBB Registry

BACKGROUND

Polybrominated biphenyls (PBB) and polychlorinated biphenyls (PCB) are persistent organic pollutants with potential endocrine-disrupting effects linked to adverse health outcomes.

OBJECTIVES

In this study, we utilize high-resolution metabolomics (HRM) to identify internal exposure and biological responses underlying PCB and multigenerational PBB exposure for participants enrolled in the Michigan PBB Registry.

METHODS

HRM profiling was conducted on plasma samples collected from 2013 to 2014 from a subset of participants enrolled in the Michigan PBB Registry, including 369 directly exposed individuals (F0) who were alive when PBB mixtures were accidentally introduced into the food chain and 129 participants exposed to PBB in utero or through breastfeeding, if applicable (F1). Metabolome-wide association studies were performed for PBB-153 separately for each generation and Σ PCB (PCB-118, PCB-138, PCB-153, and PCB-180) in the two generations combined, as both had direct PCB exposure. Metabolite and metabolic pathway alterations were evaluated following a well-established untargeted HRM workflow.

RESULTS

Mean levels were 1.75  ng / mL [standard deviation (SD): 13.9] for PBB-153 and 1.04  ng / mL (SD: 0.788) for Σ PCB . Sixty-two and 26 metabolic features were significantly associated with PBB-153 in F0 and F1 [false discovery rate (FDR) p < 0.2 ], respectively. There were 2,861 features associated with Σ PCB (FDR p < 0.2 ). Metabolic pathway enrichment analysis using a bioinformatics tool revealed perturbations associated with Σ PCB in numerous oxidative stress and inflammation pathways (e.g., carnitine shuttle, glycosphingolipid, and vitamin B9 metabolism). Metabolic perturbations associated with PBB-153 in F0 were related to oxidative stress (e.g., pentose phosphate and vitamin C metabolism) and in F1 were related to energy production (e.g., pyrimidine, amino sugars, and lysine metabolism). Using authentic chemical standards, we confirmed the chemical identity of 29 metabolites associated with Σ PCB levels (level 1 evidence).

CONCLUSIONS

Our results demonstrate that serum PBB-153 is associated with alterations in inflammation and oxidative stress-related pathways, which differed when stratified by generation. We also found that Σ PCB was associated with the downregulation of important neurotransmitters, serotonin, and 4-aminobutanoate. These findings provide novel insights for future investigations of molecular mechanisms underlying PBB and PCB exposure on health. https://doi.org/10.1289/EHP12657.

The impact of heat exposures on biomarkers of AKI and plasma metabolome among agricultural and non-agricultural workers

BACKGROUND

Agricultural workers are consistently exposed to elevated heat exposures and vulnerable to acute kidney injury. The underlying pathophysiology and detailed molecular mechanisms of AKI among agricultural workers, and the disproportionate burden of HRI and heat stress exposure are not well understood, especially at the level of cellular metabolism.

OBJECTIVE

The aim of this study was to examine the impact of heat exposures on renal biomarkers and on the human metabolome via untargeted high-resolution metabolomics among agricultural and non-agricultural workers.

METHODS

Blood and urine samples were collected pre- and post-work shift from 63 agricultural workers and 27 non- agricultural workers. We evaluated pre- and post-work shift renal biomarkers and completed untargeted metabolomics using high-resolution mass spectrometry with liquid chromatography. Metabolome-wide association studies (MWAS) models identified the metabolic features differentially expressed between agricultural workers and non-agricultural workers.

RESULTS

Median values of pre-shift creatinine and osteopontin (p < 0.05) were higher for agricultural workers than non-agricultural workers. Metabolic pathway enrichment analyses revealed 27 diverse pathways differed between agricultural workers and non-agricultural workers (p < 0.05) including TCA cycle and urea cycle, carbohydrate metabolism, histidine metabolism and evidence for altered microbiome shikimate pathway.

CONCLUSION

This is the first investigation on the metabolic pathways that are affected among agricultural workers who are exposed to heat compared to non-heat exposed workers. This study shows extensive responses of central metabolic systems to heat exposures that impact human health.

PM2.5 and its respiratory tract depositions on blood pressure, anxiety, depression and health risk assessment: A mechanistic study based on urinary metabolome

Effects of fine particulate matter (PM2.5) and regional respiratory tract depositions on blood pressure (BP), anxiety, depression, health risk and the underlying mechanisms need further investigations. A repeated-measures panel investigation among 40 healthy young adults in Hefei, China was performed to explore the acute impacts of PM2.5 exposure and its deposition doses in 3 regions of respiratory tract over diverse lag times on BP, anxiety, depression, health risk, and the potential mechanisms. We collected PM2.5 concentrations, its deposition doses, BP, the Self-Rating Anxiety Scale (SAS) score and the Self-Rating Depression Scale (SDS) score. An untargeted metabolomics approach was used to detect significant urine metabolites, and the health risk assessment model was used to evaluate the non-carcinogenic risks associated with PM2.5. We applied linear mixed-effects models to assess the relationships of PM2.5 with the aforementioned health indicators We further evaluate the non-carcinogenic risks associated with PM2.5. We found deposited PM2.5 dose in the head accounted for a large proportion. PM2.5 and its three depositions exposures at a specific lag day was significantly related to increased BP levels and higher SAS and SDS scores. Metabolomics analysis showed significant alterations in urinary metabolites (i.e., glucoses, lipids and amino acids) after PM2.5 exposure, simultaneously accompanied by activation of the cAMP signaling pathway. Health risk assessment presented that the risk values for the residents in Hefei were greater than the lower limits of non-cancer risk guidelines. This real-world investigation suggested that acute PM2.5 and its depositions exposures may increase health risks by elevating BP, inducing anxiety and depression, and altering urinary metabolomic profile via activating the cAMP signaling pathway. And the further health risk assessment indicated that there are potential non-carcinogenic risks of PM2.5 via the inhalation route in this area.

Proline is increased in allergic asthma and promotes airway remodeling

Proline and its synthesis enzyme pyrroline-5-carboxylate reductase 1 (PYCR1) are implicated in epithelial-mesenchymal transition (EMT), yet how proline and PYCR1 function in allergic asthmatic airway remodeling via EMT has not yet been addressed to our knowledge. In the present study, increased levels of plasma proline and PYCR1 were observed in patients with asthma. Similarly, proline and PYCR1 in lung tissues were high in a murine allergic asthma model induced by house dust mites (HDMs). Pycr1 knockout decreased proline in lung tissues, with reduced airway remodeling and EMT. Mechanistically, loss of Pycr1 restrained HDM-induced EMT by modulating mitochondrial fission, metabolic reprogramming, and the AKT/mTORC1 and WNT3a/β-catenin signaling pathways in airway epithelial cells. Therapeutic inhibition of PYCR1 in wild-type mice disrupted HDM-induced airway inflammation and remodeling. Deprivation of exogenous proline relieved HDM-induced airway remodeling to some extent. Collectively, this study illuminates that proline and PYCR1 involved with airway remodeling in allergic asthma could be viable targets for asthma treatment.

Saliva and Exhaled Breath Condensate Correlate With Serum in 4-12-Year-Olds Exposed to Secondhand Electronic Cigarette Vapors: A Pilot Study

Electronic cigarette use is highest among adults of child-bearing age. Many parents that use electronic cigarettes believe that secondhand exposure of electronic cigarette vapors for their children is not dangerous and is less harmful than secondhand exposure to traditional cigarette smoke. These beliefs may prompt excessive secondhand exposure to electronic cigarette vapors for their children. Little research has been done to document exposure in children. The traditional biological method of exposure detection is through a blood draw, which is difficult and undesirable in children. The purpose of this study was to assess the feasibility of using saliva and exhaled breath condensate as non-invasive biomatrices for detecting secondhand electronic cigarette vapor exposure in children. In this cross-sectionally designed study, we recruited 22 children exposed to electronic cigarette vapors and 26 non-exposed between the ages of 4-12 years. We compared metabolic features across three biomatrices, blood, saliva, and exhaled breath condensate. We noted moderate to strong pairwise, sample-specific, and feature-specific adjusted correlations. Annotated features associated with direct and secondhand electronic cigarette exposure were noted. These results demonstrate that less invasive biomatrices may be used to detect features associated with secondhand electronic cigarette vapor exposure in children.

Metabolic pathways altered by air pollutant exposure in association with lipid profiles in young adults

Mounting evidence suggests that air pollution influences lipid metabolism and dyslipidemia. However, the metabolic mechanisms linking air pollutant exposure and altered lipid metabolism is not established. In year 2014-2018, we conducted a cross-sectional study on 136 young adults in southern California, and assessed lipid profiles (triglycerides, total cholesterol, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, very-low-density lipoprotein (VLDL)-cholesterol), and untargeted serum metabolomics using liquid chromatography-high-resolution mass spectrometry, and one-month and one-year averaged exposures to NO2, O3, PM2.5 and PM10 air pollutants at residential addresses. A metabolome-wide association analysis was conducted to identify metabolomic features associated with each air pollutant. Mummichog pathway enrichment analysis was used to assess altered metabolic pathways. Principal component analysis (PCA) was further conducted to summarize 35 metabolites with confirmed chemical identity. Lastly, linear regression models were used to analyze the associations of metabolomic PC scores with each air pollutant exposure and lipid profile outcome. In total, 9309 metabolomic features were extracted, with 3275 features significantly associated with exposure to one-month or one-year averaged NO2, O3, PM2.5 and PM10 (p < 0.05). Metabolic pathways associated with air pollutants included fatty acid, steroid hormone biosynthesis, tryptophan, and tyrosine metabolism. PCA of 35 metabolites identified three main PCs which together explained 44.4% of the variance, representing free fatty acids and oxidative byproducts, amino acids and organic acids. Linear regression indicated that the free fatty acids and oxidative byproducts-related PC score was associated with air pollutant exposure and outcomes of total cholesterol and LDL-cholesterol (p < 0.05). This study suggests that exposure to NO2, O3, PM2.5 and PM10 contributes to increased level of circulating free fatty acids, likely through increased adipose lipolysis, stress hormone and response to oxidative stress pathways. These alterations were associated with dysregulation of lipid profiles and potentially could contribute to dyslipidemia and other cardiometabolic disorders.

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.

Respiratory Effects of Traffic-Related Air Pollution: A Randomized, Crossover Analysis of Lung Function, Airway Metabolome, and Biomarkers of Airway Injury

BACKGROUND

Exposure to traffic-related air pollution (TRAP) has been associated with increased risks of respiratory diseases, but the biological mechanisms are not yet fully elucidated.

OBJECTIVES

Our aim was to evaluate the respiratory responses and explore potential biological mechanisms of TRAP exposure in a randomized crossover trial.

METHODS

We conducted a randomized crossover trial in 56 healthy adults. Each participant was exposed to high- and low-TRAP exposure sessions by walking in a park and down a road with high traffic volume for 4 h in random order. Respiratory symptoms and lung function, including forced expiratory volume in the first second (FEV 1 ), forced vital capacity (FVC), the ratio of FEV 1 to FVC, and maximal mid-expiratory flow (MMEF), were measured before and after each exposure session. Markers of 8-isoprostane, tumor necrosis factor- α (TNF- α ), and ezrin in exhaled breath condensate (EBC), and surfactant proteins D (SP-D) in serum were also measured. We used linear mixed-effects models to estimate the associations, adjusted for age, sex, body mass index, meteorological condition, and batch (only for biomarkers). Liquid chromatography-mass spectrometry was used to profile the EBC metabolome. Untargeted metabolome-wide association study (MWAS) analysis and pathway enrichment analysis using mummichog were performed to identify critical metabolomic features and pathways associated with TRAP exposure.

RESULTS

Participants had two to three times higher exposure to traffic-related air pollutants except for fine particulate matter while walking along the road compared with in the park. Compared with the low-TRAP exposure at the park, high-TRAP exposure at the road was associated with a higher score of respiratory symptoms [2.615 (95% CI: 0.605, 4.626), p = 1.2 × 10 - 2 ] and relatively lower lung function indicators [- 0.075 L (95% CI: - 0.138 , - 0.012 ), p = 2.1 × 10 - 2 ] for FEV 1 and - 0.190 L / s (95% CI: - 0.351 , - 0.029 ; p = 2.4 × 10 - 2 ) for MMEF]. Exposure to TRAP was significantly associated with changes in some, but not all, biomarkers, particularly with a 0.494 -ng / mL (95% CI: 0.297, 0.691; p = 9.5 × 10 - 6 ) increase for serum SP-D and a 0.123 -ng / mL (95% CI: - 0.208 , - 0.037 ; p = 7.2 × 10 - 3 ) decrease for EBC ezrin. Untargeted MWAS analysis revealed that elevated TRAP exposure was significantly associated with perturbations in 23 and 32 metabolic pathways under positive- and negative-ion modes, respectively. These pathways were most related to inflammatory response, oxidative stress, and energy use metabolism.

CONCLUSIONS

This study suggests that TRAP exposure might lead to lung function impairment and respiratory symptoms. Possible underlying mechanisms include lung epithelial injury, inflammation, oxidative stress, and energy metabolism disorders. https://doi.org/10.1289/EHP11139.

Oxidative potential of heavy-metal contaminated soil reflects its ecological risk on earthworm

The ecological risk of heavy metal-contaminated soil is usually evaluated by its oxidative stress on terrestrial animals, which are vulnerable to the impact of individual differences of animals and environmental conditions. Oxidative potential (OP) is the potential of particles to induce the formation of reactive oxygen species (ROS). In this study, OP of the in situ contaminated soils collected from an industrial site (i.e., 64.5-7783 mg/kg of Cu, 54.9-397 mg/kg of Pb, 278-2085 mg/kg of Zn and 0.615-121 mg/kg of Cd) were measured as 38.0-60.1 pmol/min/mg, and the water extractable Cu, Pb, Zn, and Cd in soils have been proved to contribute 89%-98% to OP. Oxidative stress in earthworms (Eisenia fetida) caused by the industrial contaminated soils can be reflected by the biomarkers such as 8-hydroxy-2'-deoxyguanosine, metallothionein, and antioxidant enzymes, and a negative correlation presents between the comprehensive biomarker response index and the OP of soils (r = -0.979, p < 0.01). This is the first time to propose a dose-response relationship between OP and oxidative stress. Metabolomic analysis also verified that the regulation of four ROS-related metabolites (i.e., l-pipecolate, 1-methylhistidine, 5-methoxytryptamine, and xanthosine) in earthworms treated with contaminated soil were directly correlated with OP values. These results indicate that OP can be used as an indicator for ecological risk assessment of heavy metal-contaminated soil, which provides a fast, stable and easily testable chemical method.

Metabolome-wide association study of four groups of persistent organic pollutants and abnormal blood lipids

Environmental exposure increases the risk of dyslipidemia, which affects human health. Research has shown that persistent organic pollutants (POPs), including per- and polyfluoroalkyl substances (PFASs), polychlorinated biphenyls, polybrominated diphenyl ethers, and phthalate metabolites, are associated with a higher risk of abnormal blood lipid levels in humans. However, the key molecules involved in dyslipidemia and the mechanisms are not fully understood. This study aims to investigate the biomarkers that mediate the relationships between blood lipids and four groups of POPs and revealed their potential mechanisms. Specifically, in 278 male blood samples, blood lipid and POPs levels were measured and metabolites were detected using untargeted metabolomics. Spearman's correlation analysis and binary logistic regression were employed to assess the relationship between POPs and lipid indexes. We observed that PFASs were associated with a higher risk of abnormal total cholesterol (TC) and low-density lipoprotein (LDL), while other POPs displayed little association with abnormal lipid indexes. Among all the PFASs, 6:2Cl-PFESA was associated with the fewest metabolites. A metabolome-wide association study combined with a meet-in-the-middle approach was used to identify potential biomarkers that mediate the association between POPs and abnormal blood lipids. The mediation analysis pointed to 105 significant mediators as potential biomarkers mediating the association between PFASs and TC, and 82 significant mediators were potential biomarkers that mediated the association between PFASs and LDL. 24-Hydroxycholesterol, 3alpha,7alpha-dihydroxy-5beta-cholestan-26-al, PC(18:0/0:0), PC(22:5/0:0), GPCho(18:1/18:1), LysoPC(22:2(13Z,16Z)), LysoPC(16:0), 9(S)-HODE, 9,10-DHOME, l-glutamate, 4-hydroxybutyric acid, cytosine, PC(14:1(9Z)/18:0), sphinganine, and (S)-beta-aminoisobutyrate were identified as important biomarkers. The mechanism may mainly involves glycerophospholipid metabolism, primary bile acid biosynthesis, and linoleic acid metabolism. PPARγ likely plays a role in the associations between PFASs and abnormal cholesterol metabolism. Overall, our study provides clues for the early detection of PFAS-induced dyslipidemia and brings forth a theoretical framework for further research into this mechanism.

Metabolomics of V2O5 nanoparticles and V2O5 nanofibers in human airway epithelial BEAS-2B cells

Vanadium is a toxic metal listed by the IARC as possibly carcinogenic to humans. Manufactured nanosize vanadium pentoxide (V2O5) materials are used in a wide range of industrial sectors and recently have been developed as nanomedicine for cancer therapeutics, yet limited information is available to evaluate relevant nanotoxicity. In this study we used high-resolution metabolomics to assess effects of two V2O5 nanomaterials, nanoparticles and nanofibers, at exposure levels (0.01, 0.1, and 1 ppm) that did not cause cell death (i.e., non-cytotoxic) in a human airway epithelial cell line, BEAS-2B. As prepared, V2O5 nanofiber exhibited a fibrous morphology, with a width approximately 63 ± 12 nm and length in average 420 ± 70 nm; whereas, V2O5 nanoparticles showed a typical particle morphology with a size 36 ± 2 nm. Both V2O5 nanoparticles and nanofibers had dose-response effects on aminosugar, amino acid, fatty acid, carnitine, niacin and nucleotide metabolism. Differential effects of the particles and fibers included dibasic acid, glycosphingolipid and glycerophospholipid pathway associations with V2O5 nanoparticles, and cholesterol and sialic acid metabolism associations with V2O5 nanofibers. Examination by transmission electron microscopy provided evidence for mitochondrial stress and increased lysosome fusion by both nanomaterials, and these data were supported by effects on mitochondrial membrane potential and lysosomal activity. The results showed that non-cytotoxic exposures to V2O5 nanomaterials impact major metabolic pathways previously associated with human lung diseases and suggest that toxico-metabolomics may be useful to evaluate health risks from V2O5 nanomaterials.

Metabolome-wide association study of the relationship between chlorpyrifos exposure and first trimester serum metabolite levels in pregnant Thai farmworkers

INTRODUCTION

Organophosphate (OP) insecticides, including chlorpyrifos, have been linked with numerous harmful health effects on maternal and child health. Limited data are available on the biological mechanisms and endogenous pathways underlying the toxicity of chlorpyrifos exposures on pregnancy and birth outcomes. In this study, we measured a urinary chlorpyrifos metabolite and used high-resolution metabolomics (HRM) to identify biological perturbations associated with chlorpyrifos exposure among pregnant women in Thailand, who are disparately exposed to high levels of OP insecticides.

METHODS

This study included 50 participants from the Study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE). We used liquid chromatography-high resolution mass spectrometry to conduct metabolic profiling on first trimester serum samples collected from participants to evaluate metabolic perturbations in relation to chlorpyrifos exposures. We measured 3,5,6-trichloro-2-pyridinol (TCPy), a specific metabolite of chlorpyrifos and chlorpyrifos-methyl, in first trimester urine samples to assess the levels of exposures. Following an untargeted metabolome-wide association study workflow, we used generalized linear models, pathway enrichment analyses, and chemical annotation to identify significant metabolites and pathways associated with urinary TCPy levels.

RESULTS

In the 50 SAWASDEE participants, the median urinary TCPy level was 4.36 μg TCPy/g creatinine. In total, 691 unique metabolic features were found significantly associated with TCPy levels (p < 0.05) after controlling for confounding factors. Pathway analysis of metabolic features associated with TCPy indicated perturbations in 24 metabolic pathways, most closely linked to the production of reactive oxygen species and cellular damage. These pathways include tryptophan metabolism, fatty acid oxidation and peroxisome metabolism, cytochromes P450 metabolism, glutathione metabolism, and vitamin B3 metabolism. We confirmed the chemical identities of 25 metabolites associated with TCPy levels, including glutathione, cystine, arachidic acid, itaconate, and nicotinamide adenine dinucleotide.

DISCUSSION

The metabolic perturbations associated with TCPy levels were related to oxidative stress, cellular damage and repair, and systemic inflammation, which could ultimately contribute to health outcomes, including neurodevelopmental deficits in the child. These findings support the future development of sensitive biomarkers to investigate the metabolic underpinnings related to pesticide exposure during pregnancy and to understand its link to adverse outcomes in children.

Use of high-resolution metabolomics to assess the biological perturbations associated with maternal exposure to Bisphenol A and Bisphenol F among pregnant African American women

BACKGROUND

Human and animal exposure to bisphenol A (BPA) has been associated with adverse developmental and reproductive effects. The molecular mechanisms by which BPA exposure exerts its effects are not well-understood, even less known about its analogues bisphenol F (BPF). To address these knowledge gaps, we conducted an untargeted metabolome-wide association study (MWAS) to identify metabolic perturbations associated with BPA/BPF exposures in a pregnant African American cohort.

METHODS

From a subset of study participants enrolled in the Atlanta African American Maternal-Child cohort, we collected both urine samples, for targeted exposure assessment of BPA (N = 230) and BPF (N = 48), and serum samples, for high-resolution metabolomics (HRM) profiling (N = 230), during early pregnancy (8-14 weeks' gestation). Using an established untargeted HRM workflow consisting of MWAS modeling, pathway enrichment analysis, and chemical annotation and confirmation, we investigated the potential metabolic pathways and features associated with BPA/BPF exposures.

RESULTS

The geometric mean creatinine-adjusted concentrations of urinary BPA and BPF were 0.85 ± 2.58 and 0.70 ± 4.71 µg/g creatinine, respectively. After false positive discovery rate correction at 20 % level, 264 and 733 unique metabolic features were significantly associated with urinary BPA and BPF concentrations, representing 10 and 12 metabolic pathways, respectively. Three metabolic pathways, including steroid hormones biosynthesis, lysine and lipoate metabolism, were significantly associated with both BPA and BPF exposure. Using chemical standards, we have confirmed the chemical identity of 16 metabolites significantly associated with BPA or BPF exposure.

CONCLUSIONS

Our findings support that exposure to BPA and BPF in pregnant women is associated with the perturbation of aromatic amino acid metabolism, xenobiotics metabolism, steroid biosynthesis, and other amino acid metabolism closely linked to stress responses, inflammation, neural development, reproduction, and weight regulation.

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.

Impact of PM2.5 exposure on plasma metabolome in healthy adults during air pollution waves: A randomized, crossover trial

Air pollution, especially PM_2.5 (particulate matter with an aerodynamic diameter ≤2.5 µm) in China, is severe and related to a variety of diseases while the potential mechanisms have not been clearly clarified yet. This study was conducted using a randomized crossover trial protocol among young and healthy college students. Plasma samples were collected before, during, and post two typical air pollution waves with a washout interval of at least 2 weeks under true and sham air purification treatments, respectively. A total of 144 blood samples from 24 participants were included in the final analysis. Metabolomics analysis for the plasma samples was completed by Ultrahigh Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS). Orthogonal Partial Least Squares Discrimination Analysis (OPLS-DA) and linear mixed-effect models were used to identify the differentially expressed metabolites and their associations with PM_2.5 exposure. MetaboAnalyst 5.0 was further used to conduct pathway enrichment analysis and correlation analysis of differentially expressed metabolites. A total of 40 metabolites were identified to be differentially expressed between the true and sham air purification treatments, and eleven metabolites showed consistent significant changes upon outdoor, indoor, and time-weighted personal PM_2.5 exposures. Short-term exposure to PM_2.5 may cause disturbances in metabolic pathways such as linoleic acid metabolism, arachidonic acid metabolism, and tryptophan metabolism.

Deciphering the Metabolomics-Based Intervention of Yanghe Decoction on Hashimoto's Thyroiditis

Background

Yanghe decoction is a famous formula consisting of Rehmannia, deer horn gum, cinnamon, rue, Ephedra, ginger charcoal, and licorice. However, few studies have explored the role of the potential mechanism of Yanghe decoction in the treatment of Hashimoto's thyroiditis by metabolomics.

Methods

Nine mice were randomly divided into three groups: control group (group C), model group (group M), and drug administration group (group T), with three mice in each group. Mice in groups M and T were established as models of Hashimoto's thyroiditis, and group T was treated with Yanghe decoction. The metabolome of plasma samples from each group of mice was determined using mass spectrometry coupled with high-performance liquid and gas phases, and nuclear magnetic resonance. Based on the three assays, principal component analysis was performed on all samples, as well as orthogonal partial least squares-discriminant analysis and differential metabolite molecules for groups M and T. Subsequently, pathway enrichment analysis was performed, and the intersection was taken for the differential metabolites screened in the M and T groups. The levels of inflammatory factors IL-35 and IL-6 within the serum of each group of mice were detected.

Results

The difference analysis showed that a total of 38 differential metabolites were screened based on mass spectrometry coupled with the high-performance liquid phase, 120 differential metabolites were screened based on mass spectrometry coupled with gas phase, and a total of α-glucose and β-glucose were the differential metabolites analyzed based on NMR test results. The pathways enriched by the differential metabolites in the M and T groups were intersected, and a total of 5 common pathways were obtained (amino acid tRNA biosynthesis, D-glutamine and D-glutamate metabolism, tryptophan metabolism, nitrogen metabolism, and arginine and proline metabolism). The results also showed a significant decrease in the serum inflammatory factor IL-35 and a significant increase in IL-6 in mice from group M compared with group C, while a significant increase in the serum inflammatory factor IL-35 and a significant decrease in IL-6 in mice from group T compared with group M.

Conclusion

Our study reveals the metabolites as well as a metabolic network that can be altered by Yanghe decoction treatment of Hashimoto's thyroiditis and shows that Yanghe decoction can effectively reduce the level of inflammatory factors in Hashimoto's thyroid.

The Oxidative Potential of Fine Particulate Matter and Biological Perturbations in Human Plasma and Saliva Metabolome

Particulate oxidative potential may comprise a key health-relevant parameter of particulate matter (PM) toxicity. To identify biological perturbations associated with particulate oxidative potential and examine the underlying molecular mechanisms, we recruited 54 participants from two dormitories near and far from a congested highway in Atlanta, GA. Fine particulate matter oxidative potential ("FPMOP") levels at the dormitories were measured using dithiothreitol assay. Plasma and saliva samples were collected from participants four times for longitudinal high-resolution metabolic profiling. We conducted metabolome-wide association studies to identify metabolic signals with FPMOP. Leukotriene metabolism and galactose metabolism were top pathways associated with ≥5 FPMOP-related indicators in plasma, while vitamin E metabolism and leukotriene metabolism were found associated with most FPMOP indicators in saliva. We observed different patterns of perturbed pathways significantly associated with water-soluble and -insoluble FPMOPs, respectively. We confirmed five metabolites directly associated with FPMOP, including hypoxanthine, histidine, pyruvate, lactate/glyceraldehyde, and azelaic acid, which were implications of perturbations in acute inflammation, nucleic acid damage and repair, and energy perturbation. The unique metabolic signals were specific to FPMOP, but not PM mass, providing initial indication that FPMOP might constitute a more sensitive, health-relevant measure for elucidating etiologies related to PM_2.5 exposures.

Evaluation of the Use of Saliva Metabolome as a Surrogate of Blood Metabolome in Assessing Internal Exposures to Traffic-Related Air Pollution

In the omics era, saliva, a filtrate of blood, may serve as an alternative, noninvasive biospecimen to blood, although its use for specific metabolomic applications has not been fully evaluated. We demonstrated that the saliva metabolome may provide sensitive measures of traffic-related air pollution (TRAP) and associated biological responses via high-resolution, longitudinal metabolomics profiling. We collected 167 pairs of saliva and plasma samples from a cohort of 53 college student participants and measured corresponding indoor and outdoor concentrations of six air pollutants for the dormitories where the students lived. Grand correlation between common metabolic features in saliva and plasma was moderate to high, indicating a relatively consistent association between saliva and blood metabolites across subjects. Although saliva was less associated with TRAP compared to plasma, 25 biological pathways associated with TRAP were detected via saliva and accounted for 69% of those detected via plasma. Given the slightly higher feature reproducibility found in saliva, these findings provide some indication that the saliva metabolome offers a sensitive and practical alternative to blood for characterizing individual biological responses to environmental exposures.

Gene-environment interactions in childhood asthma revisited; expanding the interaction concept

Investigation of gene-environment interactions (GxE) may provide important insights into the gene regulatory framework in response to environmental factors of relevance for childhood asthma. Over the years, different methodological strategies have been applied, more recently using genome-wide approaches. The best example to date is the major asthma locus on the 17q12-21 chromosome region, viral infections, and airway epithelium processes where recent studies have shed much light on mechanisms in childhood asthma. However, there are challenges with the traditional single variant-single exposure interaction models, as they do not encompass the complexity and cumulative effects of multiple exposures or multiple genetic variants. As such, we need to redefine our traditional GxE thinking, and we propose in this review to expand the GxE concept by also evaluating other omics layers, such as epigenetics, transcriptomics, metabolomics, and proteomics. In addition, host factors such as age, gender, and other exposures are very likely to influence GxE effects and need firmly to be considered in future studies.

Assessment of metabolic perturbations associated with exposure to phthalates among pregnant African American women

BACKGROUND

Phthalates have been linked with numerous harmful health effects. Limited data are available on the molecular mechanism underlying phthalate toxicity on human health. In this study, we measured urinary phthalate metabolites and used high-resolution metabolomics (HRM) to identify biological perturbations associated with phthalate exposures among pregnant African American (AA) women, who are disproportionately exposed to high phthalates levels.

METHODS

We used untargeted HRM profiling to characterize serum samples collected during early (8-14 weeks gestation) and late (24-30 weeks gestation) pregnancy from 73 participants from the Atlanta AA Maternal-Child cohort. We measured eight urinary phthalate metabolites in early and late pregnancy, including Monoethyl phthalate (MEP), Mono(2-ethlyhexyl) phthalate (MEHP), and Mono (2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), to assess maternal exposures to phthalates. Metabolite and metabolic pathway perturbation were evaluated using an untargeted HRM workflow.

RESULTS

Geometric mean creatinine-adjusted levels of urinary MEP, MEHP, and MEHHP were 67.3, 1.4, and 4.1 μg/g creatinine, respectively, with MEP and MEHP higher than the mean levels of non-Hispanic blacks in the general US population (2015-2016). There were 73 and 1435 metabolic features significantly associated with at least one phthalate metabolite during early and late pregnancy (p < 0.005), respectively. Pathway enrichment analysis revealed perturbations in four inflammation- and oxidative-stress-related pathways associated with phthalate metabolite levels during both early and late pregnancy, including glycerophospholipid, urea cycle, arginine, and tyrosine metabolism. We confirmed 10 metabolites with level-1 evidence, which are associated with urinary phthalates, including thyroxine and thiamine, which were negatively associated with MEP, as well as tyramine and phenethylamine, which were positively associated with MEHP and MEHHP.

CONCLUSION

Our results demonstrated that urinary phthalate levels were associated with perturbations in biological pathways connected with inflammation, oxidative stress, and endocrine disruption. The findings support future targeted investigations on molecular mechanisms underlying the impact of maternal phthalates exposure on adverse health outcomes.

Exposure to air pollutants during pregnancy and after birth increases the risk of neonatal hyperbilirubinemia

OBJECTIVES

Exposure to air pollution is associated with increased risks of several adverse conditions in newborns, such as preterm birth. Whether air pollution is associated with neonatal hyperbilirubinemia remains unclear. We aimed to develop and validate an air-quality-based model to better predict neonatal hyperbilirubinemia.

METHODS

A multicenter, population-based cohort of neonates with a gestational age (GA) ≥35 weeks and birth weight ≥2000 g was enrolled in the study. The study was conducted in Shanghai, China, from July 2017 to December 2018. The daily average concentrations of particulate matter (PM) with aerodynamic diameters≤2.5 μm (PM2.5) and ≤10 μm (PM10), sulfur dioxide (SO₂), nitrogen dioxide (NO2) and carbon monoxide (CO) were measured. Neonatal hyperbilirubinemia was diagnosed according to the American Academy of Pediatrics (AAP) guidelines by trained neonatologists. We used logistic least absolute shrinkage and selection operator (LASSO) regression to screen air pollutant indicators related to neonatal hyperbilirubinemia and build an air-quality signature for each patient. An air-quality-based nomogram was then established to predict the risk of neonatal hyperbilirubinemia.

RESULTS

A total of 11196 neonates were evaluated. Prenatal PM10, CO and NO₂ exposure and postpartum SO₂ exposure were significantly associated with neonatal hyperbilirubinemia. The air-quality score was calculated according to the hyperbilirubinemia-related pollutants. The air-quality score of the hyperbilirubinemia group was significantly higher than that of the nonhyperbilirubinemia group (P < .01, odds ratio = 2.97). An air-quality-based logistic regression model was built and showed good discrimination (C-statistic of 0.675 [95% CI (confidence interval), 0.658 to 0.692]) and good calibration. Decision curve analysis showed that the air-quality-based model was better than the traditional clinical model in predicting neonatal hyperbilirubinemia.

CONCLUSIONS

The findings of this study suggest that ambient air pollution exposure is associated with an increased risk of neonatal hyperbilirubinemia. Our results encourage further exploration of this possibility in future studies.

Transcriptomic and metabolomic associations with exposures to air pollutants among young adults with childhood asthma history

Ambient air pollutants are well-known risk factors for childhood asthma and asthma exacerbation. It is unknown whether different air pollutants individually or jointly affect pathophysiological mechanisms of asthma. In this study, we aim to integrate transcriptome and untargeted metabolome to identify dysregulated genetic and metabolic pathways that are associated with exposures to a mixture of ambient and traffic-related air pollutants among adults with asthma history. In this cross-sectional study, 102 young adults with childhood asthma history were enrolled from southern California in 2012. Whole blood transcriptome was measured with 20,869 expression signatures, and serum untargeted metabolomics including 937 metabolites were analyzed by Metabolon, Inc. Participants' exposures to regional air pollutants (NO₂, O₃, PM₁₀, PM_2.5) and near-roadway air pollutants averaged at one month and one year before study visit were estimated based on residential addresses. xMWAS network analysis and joint-pathway analysis were performed to identify subnetworks and genetic and metabolic pathways that were associated with exposure to air pollutants adjusted for socio-characteristic covariates. Network analysis found that exposures to air pollutants mixture were connected to 357 gene markers and 92 metabolites. One-year and one-month averaged PM_2.5 and NO₂ were associated with several amino acids related to serine, glycine, and beta-alanine metabolism. Lower serum levels of carnosine and aspartate, which are involved in the beta-alanine metabolic pathway, as well as choline were also associated with worse asthma control (p < 0.05). One-year and one-month averaged PM₁₀ and one-month averaged O₃ were associated with higher gene expression levels of HSPA5, LGMN, CTSL and HLA-DPB1, which are involved in antigen processing and presentation. These results indicate that exposures to various air pollutants are associated with altered genetic and metabolic pathways that affect anti-oxidative capacity and immune response and can potentially contribute to asthma-related pathophysiology.

DNA damage, serum metabolomic alteration and carcinogenic risk associated with low-level air pollution

Outdoor air pollution has been classified as carcinogenic to humans (Group 1) for lung cancer, but the underlying mechanism and key toxic components remain incompletely understood. Since DNA damage and metabolite alterations are associated with cancer progression, exploring potential mechanisms linking air pollution and cancer might be meaningful. In this study, a real-time ambient air exposure system was established to simulate the real-world environment of adult male SD rats in Beijing from June 13th, 2018, to October 8th, 2018. 8-OHdG in the urine, γ-H2AX in the lungs and mtDNA copy number in the peripheral blood were analyzed to explore DNA damage at different levels. Serum non-targeted metabolomics analysis was performed. Pair-wise spearman was used to explore the correlation between DNA damage biomarkers and serum differential metabolites. Carcinogenic risks of heavy metals and PAHs via inhalation were assessed according to US EPA guidelines. Results showed that PM_2.5 and O₃ were the major air pollutants in the exposure group and not detected in the control group. Compared with control group, higher levels of 8-OHdG, mtDNA copy number, γ-H2AX and PCNA-positive nuclei cells were observed in the exposure group. Histopathological evaluation suggested ambient air induced alveolar wall thickening and inflammatory cell infiltration in lungs. Perturbed metabolic pathways identified included glycolysis/gluconeogenesis metabolism, purine and pyrimidine metabolism, etc. γ-H2AX was positively correlated with serum ADP, 3-phospho-D-glyceroyl phosphate and N-acetyl-D-glucosamine. The BaPeq was 0.120 ng/m³. Risks of Cr(VI), As, V, BaP, BaA and BbF were above 1 × 10^-6. We concluded that low-level air pollution was associated with DNA damage and serum metabolomic alterations in rats. Cr(VI) and BaP were identified as key carcinogenic components in PM_2.5. Our results provided experimental evidence for hazard identification and risk assessment of low-level air pollution.

Air pollution and high-intensity interval exercise: Implications to anti-inflammatory balance, metabolome and cardiovascular responses

High-intensity interval exercise (HIIE) is an effective non-pharmacological tool for improving physiological responses related to health. When HIIE is performed in urban centers, however, the exerciser is exposed to traffic-related air pollution (TRAP), which is associated with metabolic, anti-inflammatory imbalance and cardiovascular diseases. This paradoxical combination has the potential for conflicting health effects. Thus, the aim of this study was to determine the effects of HIIE performed in TRAP exposure on serum cytokines, non-target metabolomics and cardiovascular parameters. Fifteen participants performed HIIE in a chamber capable to deliver filtered air (FA condition) or non-filtered air (TRAP condition) from a polluted site adjacent to the exposure chamber. Non-target blood serum metabolomics, blood serum cytokines and blood pressure analyses were collected in both FA and TRAP conditions at baseline, 10 min after exercise, and 1 h after exercise. The TRAP increased IL-6 concentration by 1.7 times 1 h after exercise (p < 0.01) and did not change the anti-inflammatory balance (IL-10/TNF-α ratio). In contrast, FA led to an increase in IL-10 and IL-10/TNF-α ratio (p < 0.01), by 2.1 and 2.3 times, respectively. The enrichment analysis showed incomplete fatty acid metabolism under the TRAP condition (p < 0.05) 10 min after exercise. There was also an overactivity of ketone body metabolism (p < 0.05) at 10 min and at 1 h after exercise with TRAP. Exercise-induced acute decrease in systolic blood pressure (SBP) was not observed at 10 min and impaired at 1 h after exercise (p < 0.05). These findings reveal that TRAP potentially attenuates health benefits often related to HIIE. For instance, the anti-inflammatory balance was impaired, accompanied by accumulation of metabolites related to energy supply and reduction to exercise-induced decrease in SBP.

Dynamic molecular choreography induced by traffic exposure: A randomized, crossover trial using multi-omics profiling

The biological mechanism of adverse health outcomes related to exposure to traffic-related air pollution (TRAP) needs elucidation. We conducted a randomized, crossover trial among healthy young students in Shanghai, China. Participants wore earplugs and were randomly assigned to a 4-hour walking treatment either along a traffic-polluted road or through a traffic-free park. We conducted untargeted analyses of plasma exosome transcriptomics, serum mass spectrometry-based proteomics, and serum metabolomics to evaluate changes in genome-wide transcription, protein, and metabolite profiles in 35 randomly selected participants. Mean personal exposure levels of ultrafine particles, black carbon, nitrogen dioxide, and carbon monoxide in the road were 2-3 times higher than that in the park. We observed 3449 exosome mRNAs, 58 serum proteins, and 128 serum metabolites that were significantly associated with TRAP. The multi-omics analysis showed dozens of regulatory pathways altered in response to TRAP, such as inflammation, oxidative stress, coagulation, endothelin-1 signaling, and renin-angiotensin signaling. We found that several novel pathways activated in response to TRAP exposure: growth hormone signaling, adrenomedullin signaling, and arachidonic acid metabolism. Our study served as a demonstration and proof of concept on the evidence that associated TRAP exposure with global molecular changes based on the multi-omics level.

Pesticide residue intake from fruits and vegetables and alterations in the serum metabolome of women undergoing infertility treatment

BACKGROUND

Pesticide exposure is linked to a myriad of negative health effects; however, the mechanisms underlying these associations are less clear. We utilized metabolomics to describe the alterations in the serum metabolome associated with high and low pesticide residue intake from fruits and vegetables (FVs), the most common route of exposure in humans.

METHODS

This analysis included 171 women undergoing in vitro fertilization who completed a validated food frequency questionnaire and provided a serum sample during controlled ovarian stimulation (2007-2015). FVs were categorized as high or low-to-moderate pesticide residue using a validated method based on pesticide surveillance data from the USDA. We conducted untargeted metabolic profiling using liquid chromatography with high-resolution mass spectrometry and two chromatography columns. We used multivariable generalized linear models to identified metabolic features (p < 0.005) associated with high and low-to-moderate pesticide residue FV intake, followed by enriched pathway analysis.

RESULTS

We identified 50 and 109 significant features associated with high pesticide residue FV intake in the C18 negative and HILIC positive columns, respectively. Additionally, we identified 90 and 62 significant features associated with low-to-moderate pesticide residue FV intake in the two columns, respectively. Four metabolomic pathways were associated with intake of high pesticide residue FVs including those involved in energy, vitamin, and enzyme metabolism. 12 pathways were associated with intake of low-to-moderate pesticide residue FVs including cellular receptor, energy, intercellular signaling, lipid, vitamin, and xenobiotic metabolism. One energy pathway was associated with both high and low-to-moderate pesticide residue FVs.

CONCLUSIONS

We identified limited overlap in the pathways associated with intake of high and low-to-moderate pesticide residue FVs, which supports findings of disparate health effects associated with these two exposures. The identified pathways suggest there is a balance between the dietary antioxidant intake associated with FVs intake and heightened oxidative stress as a result of dietary pesticide exposure.

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.

Fine particulate matter and vasoactive 20-hydroxyeicosatetraenoic acid: Insights into the mechanisms of the prohypertensive effects of particulate air pollution

BACKGROUND

Emerging evidence suggests that biological intermediates play an important role in initiating fine particulate matter (PM_2.5)-associated prohypertensive pathways, but sensitive biomarkers for this pathway are lacking.

AIM

To explore whether short-term exposure to PM_2.5 is associated with the concentration of 20-hydroxyeicosatetraenoic acid (20-HETE), a potent vasoactive lipid relevant to the pathophysiology of hypertension.

METHODS

In this longitudinal panel study, we repeatedly (up to seven times) measured the blood concentrations of 20-HETE in 120 adults living in Beijing, China. Ambient exposure metrics included the concentrations of hourly PM_2.5 mass and daily PM_2.5 constituents, including three carbonaceous components, eight water-soluble ions, and 16 trace elements. Linear mixed-effects models were used to examine the associations between the change in the 20-HETE concentration and short-term exposure to ambient PM_2.5 metrics after adjustment for age, sex, body mass index, behavioral exposure, socioeconomic characteristics, and meteorological factors.

RESULTS

The interquartile range (IQR) increase in the 7-15-hour-lag exposure to PM_2.5 (80 μg/m³) was associated significantly with a 5.3% (95% confidence interval [CI], 0.1-10.7%) to 6.5% (95% CI, 1.7-11.6%) increase in the blood concentration of 20-HETE. The magnitude of the association differed by age, sex, prediabetic status, obesity, and hypertensive status, with a significantly greater increase in 20-HETE observed among those with fasting plasma glucose concentrations ≥ 6.1 mmol/L. In addition to the PM_2.5 mass, the 20-HETE concentration was associated consistently with IQR increases in the 1-day lag exposure to organic carbon (5.7%), black carbon (9.5%), nitrate (3.9%), chloride (2.9%), copper (5.5%), zinc (4.7%), barium (4.1%), and lead (6.2%). The organic carbon estimate was robust in the two-pollutant models. Furthermore, increased 20-HETE correlated with elevated blood pressure (BP), although no mediation of 20-HETE on PM_2.5-associated BP change was found.

CONCLUSIONS

The 20-HETE blood concentration increased significantly in response to short-term exposure to ambient PM_2.5, which may be partly responsible for the prohypertensive effects of PM_2.5.

Metabolome-wide association study of serum exogenous chemical residues in a cohort with 5 major chronic diseases

BACKGROUND

Chronic diseases have become main killers affecting the health of human, and environmental pollution is a major health risk factor that cannot be ignored. It has been reported that exogenous chemical residues including pesticides, herbicides, fungicides, veterinary drugs and persistent organic pollutants are associated with chronic diseases. However, the evidence for their relationship is equivocal and the underlying mechanisms are unclear.

OBJECTIVES

We aim to investigate the linkages between serum exogenous chemical residues and 5 main chronic diseases including obesity, hyperuricemia, hypertension, diabetes and dyslipidemia, and further reveal the metabolic perturbations of chronic diseases related to exogenous chemical residue exposure, then gain potential mechanism insight at the metabolic level.

METHODS

LC-MS-based targeted and nontargeted methods were respectively performed to quantify exogenous chemical residues and acquire metabolic profiling of 496 serum samples from chronic disease patients. Non-parametric test, correlation and regression analyses were carried out to investigate the association between exogenous chemical residues and chronic diseases. Metabolome-wide association study combined with the meeting-in-the-middle strategy and mediation analysis was performed to reveal and explain exposure-related metabolic disturbances and their risk to chronic diseases.

RESULTS

In the association analysis of 106 serum exogenous chemical residues and 5 chronic diseases, positive associations of serum perfluoroalkyl substances (PFASs) with hyperuricemia were discovered while other associations were not significant. 240 exposure markers of PFASs and 84 disease markers of hyperuricemia were found, and 47 of them were overlapped and considered as putative effective markers. Serum uric acid, amino acids, cholesterol, carnitines, fatty acids, glycerides, glycerophospholipids, ceramides, and a part of sphingolipids were positively correlated with PFASs and associated with increased risk for hyperuricemia. Creatine, creatinine, glyceryl monooleate, phosphatidylcholine 36:6, phosphatidylethanolamine 40:6, cholesterol and sphingolipid 36:1;2O were significant markers which mediated the associations of the residues with hyperuricemia.

CONCLUSIONS

Our study demonstrated a significantly positive association between PFASs exposure and hyperuricemia. The most significant metabolic abnormality was lipid metabolism which not only was positively associated with PFASs, but also increased the risk of hyperuricemia.

High-resolution metabolomics of exposure to tobacco smoke during pregnancy and adverse birth outcomes in the Atlanta African American maternal-child cohort

Exposure to tobacco smoke during pregnancy has been associated with a series of adverse reproductive outcomes; however, the underlying molecular mechanisms are not well-established. We conducted an untargeted metabolome-wide association study to identify the metabolic perturbations and molecular mechanisms underlying the association between cotinine, a widely used biomarker of tobacco exposure, and adverse birth outcomes. We collected early and late pregnancy urine samples for cotinine measurement and serum samples for high-resolution metabolomics (HRM) profiling from 105 pregnant women from the Atlanta African American Maternal-Child cohort (2014-2016). Maternal metabolome perturbations mediating prenatal tobacco smoke exposure and adverse birth outcomes were assessed by an untargeted HRM workflow using generalized linear models, followed by pathway enrichment analysis and chemical annotation, with a meet-in-the-middle approach. The median maternal urinary cotinine concentrations were 5.93 μg/g creatinine and 3.69 μg/g creatinine in early and late pregnancy, respectively. In total, 16,481 and 13,043 metabolic features were identified in serum samples at each visit from positive and negative electrospray ionization modes, respectively. Twelve metabolic pathways were found to be associated with both cotinine concentrations and adverse birth outcomes during early and late pregnancy, including tryptophan, histidine, urea cycle, arginine, and proline metabolism. We confirmed 47 metabolites associated with cotinine levels, preterm birth, and shorter gestational age, including glutamate, serine, choline, and taurine, which are closely involved in endogenous inflammation, vascular reactivity, and lipid peroxidation processes. The metabolic perturbations associated with cotinine levels were related to inflammation, oxidative stress, placental vascularization, and insulin action, which could contribute to shorter gestations. The findings will support the further understanding of potential internal responses in association with tobacco smoke exposures, especially among African American women who are disproportionately exposed to high tobacco smoke and experience higher rates of adverse birth outcomes.

Per- and polyfluoroalkyl substance (PFAS) exposure, maternal metabolomic perturbation, and fetal growth in African American women: A meet-in-the-middle approach

BACKGROUND

Prenatal exposures to per- and polyfluoroalkyl substances (PFAS) have been linked to reduced fetal growth. However, the detailed molecular mechanisms remain largely unknown. This study aims to investigate biological pathways and intermediate biomarkers underlying the association between serum PFAS and fetal growth using high-resolution metabolomics in a cohort of pregnant African American women in the Atlanta area, Georgia.

METHODS

Serum perfluorohexane sulfonic acid (PFHxS), perfluorooctane sulfonic acid (PFOS), perfluorooctanoic acid (PFOA), and perfluorononanoic acid (PFNA) measurements and untargeted serum metabolomics profiling were conducted in 313 pregnant African American women at 8-14 weeks gestation. Multiple linear regression models were applied to assess the associations of PFAS with birth weight and small-for-gestational age (SGA) birth. A high-resolution metabolomics workflow including metabolome-wide association study, pathway enrichment analysis, and chemical annotation and confirmation with a meet-in-the-middle approach was performed to characterize the biological pathways and intermediate biomarkers of the PFAS-fetal growth relationship.

RESULTS

Each log2-unit increase in serum PFNA concentration was significantly associated with higher odds of SGA birth (OR = 1.32, 95% CI 1.07, 1.63); similar but borderline significant associations were found in PFOA (OR = 1.20, 95% CI 0.94, 1.49) with SGA. Among 25,516 metabolic features extracted from the serum samples, we successfully annotated and confirmed 10 overlapping metabolites associated with both PFAS and fetal growth endpoints, including glycine, taurine, uric acid, ferulic acid, 2-hexyl-3-phenyl-2-propenal, unsaturated fatty acid C18:1, androgenic hormone conjugate, parent bile acid, and bile acid-glycine conjugate. Also, we identified 21 overlapping metabolic pathways from pathway enrichment analyses. These overlapping metabolites and pathways were closely related to amino acid, lipid and fatty acid, bile acid, and androgenic hormone metabolism perturbations.

CONCLUSION

In this cohort of pregnant African American women, higher serum concentrations of PFOA and PFNA were associated with reduced fetal growth. Perturbations of biological pathways involved in amino acid, lipid and fatty acid, bile acid, and androgenic hormone metabolism were associated with PFAS exposures and reduced fetal growth, and uric acid was shown to be a potential intermediate biomarker. Our results provide opportunities for future studies to develop early detection and intervention for PFAS-induced fetal growth restriction.