Use of high-resolution metabolomics for the identification of metabolic signals associated with traffic-related air pollution

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.

Assessing Dietary Pesticide Intake and Potential Health Effects: The Application of Global Metabolomics Analysis

Scientific information is not yet available to provide insight into how individual metabolome might be affected by the presence of pesticides in regular diets. This study aimed to evaluate the perturbation of metabolomic pathways in children who switched their diets from conventional foods to mostly organic foods for five consecutive days. We selected 46 child-matched spot urine samples with distinct differences of urinary pesticide metabolite levels between the conventional and organic eating days and then analyzed those urine samples on three analytical platforms to perform global metabolomics analysis. We found statistically significant perturbations of metabolic pathways relevant to inflammation, oxidative stress, and the demands of xenobiotic detoxification when children switched their conventional diets to mostly organic foods. The outcomes of this study allow us to extend the current understanding beyond organophosphate pesticides' acute toxicity of cholinesterase inhibition to the perturbation of metabolic pathways at dietary intake levels.

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.

PM2.5 Exposure associated with Microbiota Gut-Brain Axis: Multi-omics Mechanistic Implications from the China BAPE study

Recent studies have shown that PM_2.5 may activate the hypothalamus-pituitary-adrenal (HPA) axis by inducing hormonal changes, potentially explaining the increase in neurological and cardiovascular risks. In addition, an association between PM_2.5 and gut microbiota and metabolites was established. The above evidence represents crucial parts of the gut-brain axis (GBA). In view of this evidence, we proposed a hypothesis that PM_2.5 exposure may affect the HPA axis through the gastrointestinal tract microbiota pathway (GBA mechanism), leading to an increased risk of neurological and cardiovascular diseases. We conducted a real-world prospective repeated panel study in Jinan, China. At each visit, we measured real-time personal PM_2.5 and collected fecal and blood samples. A linear mixed-effects model was used to analyze the association between PM_2.5 and serum biomarkers, gut microbiota, and metabolites. We found that PM_2.5 was associated with increased serum levels of hormones, especially the adrenocorticotropic hormone (ACTH) and cortisol, which are reliable hormones of the HPA axis. Gut microbiota and tryptophan metabolites and inflammation, which are important components of the GBA, were significantly associated with PM_2.5. We also found links between PM_2.5 and changes in the nervous and cardiovascular outcomes, e.g., increases of 19.77% (95% CI: −36.44, 125.69) in anxiety, 1.19% (95% CI: 0.65, 1.74) in fasting blood glucose (FBG), 2.09% (95% CI: 1.48, 2.70) in total cholesterol (TCHOL), and 0.93% (95% CI: 0.14, 1.72) in triglycerides (TG), were associated with 10 μg/m³ increase in PM_2.5 at the lag 0–72 h, which represent the main effects of GBA. This study indicated the link between PM_2.5 and the microbiota GBA for the first time, providing evidence of the potential mechanism for PM_2.5 with neurological and cardiovascular system dysfunction.

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This is a real-world population based panel study using multi-omics technology

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Link between PM_2.5 and microbiota gut-brain axis is reported for the first time

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PM_2.5 affected gut microbiota, tryptophan metabolism, and inflammatory factors

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Important hormones of the HPA axis increased with PM_2.5 exposure

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PM_2.5 was associated with nervous and cardiovascular outcomes

PM2.5 and Serum Metabolome and Insulin Resistance, Potential Mediation by the Gut Microbiome: A Population-Based Panel Study of Older Adults in China

BACKGROUND

Insulin resistance (IR) affects the development of type 2 diabetes mellitus (T2DM), which is also influenced by accumulated fine particle air pollution [particulate matter (PM) with aerodynamic diameter of <2.5μm (PM2.5)] exposure. Previous experimental and epidemiological studies have proposed several potential mechanisms by which PM2.5 contributes to IR/T2DM, including inflammation imbalance, oxidative stress, and endothelial dysfunction. Recent evidence suggests that the imbalance of the gut microbiota affects the metabolic process and may precede IR. However, the underlying mechanisms of PM2.5, gut microbiota, and metabolic diseases are unclear.

OBJECTIVES

We investigated the associations between personal exposure to PM2.5 and fasting blood glucose and insulin levels, the IR index, and other related biomarkers. We also explored the potential underlying mechanisms (systemic inflammation and sphingolipid metabolism) between PM2.5 and insulin resistance and the mediating effects between PM2.5 and sphingolipid metabolism.

METHODS

We recruited 76 healthy seniors to participate in a repeated-measures panel study and conducted clinical examinations every month from September 2018 to January 2019. Linear mixed-effects (LME) models were used to analyze the associations between PM2.5 and health data (e.g., functional factors, the IR index, inflammation and other IR-related biomarkers, metabolites, and gut microbiota). We also performed mediation analyses to evaluate the effects of mediators (gut microbiota) on the associations between exposures (PM2.5) and featured metabolism outcomes.

RESULTS

Our prospective panel study illustrated that exposure to PM2.5 was associated with an increased risk of higher IR index and functional biomarkers, and our study provided mechanistic evidence suggesting that PM2.5 exposure may contribute to systemic inflammation and altered sphingolipid metabolism.

DISCUSSION

Our findings demonstrated that PM2.5 was associated with the genera of the gut microbiota, which partially mediated the association between PM2.5 and sphingolipid metabolism. These findings may extend our current understanding of the pathways of PM2.5 and IR. https://doi.org/10.1289/EHP9688.

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.

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.

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

BACKGROUND

Maternal exposure to traffic-related air pollution during pregnancy has been shown to increase the risk of adverse birth outcomes and childhood disorders. High-resolution metabolomics (HRM) has previously been employed to identify metabolic responses to traffic-related air pollution in adults, including pregnant women. Thus far, no studies have examined metabolic effects of air pollution exposure in utero on neonates.

METHODS

We retrieved stored neonatal blood spots for 241 children born in California between 1998 and 2007. These children were randomly selected from all California birth rolls to serve as birth-year matched controls for children with retinoblastoma identified from the California cancer registry for a case control study of childhood cancer. We estimated prenatal traffic-related air pollution exposure (particulate matter less than 2.5 μm (PM_2.5)) during the third-trimester using the California Line Source Dispersion Model, version 4 (CALINE4) based on residential addresses recorded at birth. We employed untargeted HRM to obtain metabolic profiles, and metabolites associated with air pollution exposure were identified using partial least squares (PLS) regression and linear regressions. Biological effects were characterized using pathway enrichment analyses adjusting for potential confounders including maternal age, race/ethnicity, and education.

RESULTS

In total we extracted 4038 and 4957 metabolite features from neonatal blood spots in hydrophilic interaction (HILIC) chromatography (positive ion mode) and C18 reverse phase columns (negative ion mode), respectively. After controlling for confounding factors, partial least square regression (Variable Importance in Projection (VIP) ≥ 2) selected 402 HILIC positive and 182 C18 negative features as statistically significantly associated with increasing third trimester PM_2.5 exposure. Using pathway enrichment analysis, we identified metabolites in oxidative stress and inflammation pathways as being altered, primarily involving lipid metabolism.

CONCLUSION

The metabolite features and pathways associated with air pollution exposure in neonates suggest that maternal exposure during late pregnancy contributes to oxidative stress and inflammation in newborn children.

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

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

Traffic-related air pollution and endurance exercise: Characterizing non-targeted serum metabolomics profiling

Although the exposure to traffic-related air pollution (TRAP) has emerged as one of main problem worldwide to inhabitants' health in urban centers, its impact on metabolic responses during exercise is poorly understood. The aim of study was to characterize the profile of non-target serum metabolomics during prolonged exercise performed under TRAP conditions. Ten healthy men completed two 90 min constant-load cycling trials under conditions of either TRAP or filtered air. Experimental trials were performed in a chamber located on an avenue with a high volume of vehicle traffic. Blood samples were taken at 30 min, 60 min, and 90 min of exercise. Based on Nuclear Magnetic Resonance metabolomics, the non-target analysis was used to assess the metabolic profile. Twelve, 16 and 18 metabolites were identified as discriminants. These were: at 30 min of exercise, the coefficient of determination (R²) 0.98, the predictive relevance, (Q²) 0.12, and the area under the curve (AUC) 0.91. After 60 min of exercise: (R²: 0.99, Q²: 0.09, AUC: 0.94); and at 90 min of exercise (R²: 0.91, Q²: <0.01, AUC: 0.89), respectively. The discriminant metabolites were then considered for the target analysis, which demonstrated that the metabolic pathways of glycine and serine metabolism (p = 0.03) had been altered under TRAP conditions at 30 min of exercise; arginine and proline metabolism (p = 0.04) at 60 min of exercise; and glycolysis (p = 0.05) at 90 min of exercise. The present results suggest that exposure to TRAP during prolonged exercise leads to a significant change in metabolomics, characterized by a transitional pattern and lastly, impairs the glucose metabolism.

The exposome in practice: an exploratory panel study of biomarkers of air pollutant exposure in Chinese people aged 60-69 years (China BAPE Study)

The exposome overhauls conventional environmental health impact research paradigms and provides a novel methodological framework that comprehensively addresses the complex, highly dynamic interplays of exogenous exposures, endogenous exposures, and modifiable factors in humans. Holistic assessments of the adverse health effects and systematic elucidation of the mechanisms underlying environmental exposures are major scientific challenges with widespread societal implications. However, to date, few studies have comprehensively and simultaneously measured airborne pollutant exposures and explored the associated biomarkers in susceptible healthy elderly subjects, potentially resulting in the suboptimal assessment and management of health risks. To demonstrate the exposome paradigm, we describe the rationale and design of a comprehensive biomarker and biomonitoring panel study to systematically explore the association between individual airborne exposure and adverse health outcomes. We used a combination of personal monitoring for airborne pollutants, extensive human biomonitoring, advanced omics analysis, confounding information, and statistical methods. We established an exploratory panel study of Biomarkers of Air Pollutant Exposure in Chinese people aged 60-69 years (China BAPE), which included 76 healthy residents from a representative community in Jinan City, Shandong Province. During the period between September 2018 and January 2019, we conducted prospective longitudinal monitoring with a 3-day assessment every month. This project: (1) leveraged advanced tools for personal airborne exposure monitoring (external exposures); (2) comprehensively characterized biological samples for exogenous and endogenous compounds (e.g., targeted and untargeted monitoring) and multi-omics scale measurements to explore potential biomarkers and putative toxicity pathways; and (3) systematically evaluated the relationships between personal exposure to air pollutants, and novel biomarkers of exposures and effects using exposome-wide association study approaches. These findings will contribute to our understanding of the mechanisms underlying the adverse health impacts of air pollution exposures and identify potential adverse clinical outcomes that can facilitate the development of effective prevention and targeted intervention techniques.

The Association Between Long-term Exposure to Ambient Air Pollution and Bone Strength in China

CONTEXT

Evidence regarding the association of long-term exposure to air pollution on bone strength or osteoporosis is rare, especially in highly polluted low- and middle-income countries. Little is known about whether the association between air pollution and bone strength changes at different bone strength distributions.

OBJECTIVE

Using the baseline data from the China Multi-Ethnic Cohort, we investigated the association between long-term air pollution exposure and bone strength.

METHODS

We used multiple linear models to estimate the association between air pollution and bone strength, and we conducted quantile regression models to investigate the variation of this association in the distribution of bone strength. The 3-year concentrations of PM1, PM2.5, PM10, and NO2 for each participant were assessed using spatial statistical models. Bone strength was expressed by the calcaneus quantitative ultrasound index (QUI) measured by quantitative ultrasound, with higher QUI values indicating greater bone strength.

RESULTS

A total of 66 598 participants were included. Our analysis shows that every 10 μg/m3 increase in 3-year average PM1, PM2.5, PM10, and NO2 was associated with -5.38 units (95% CI: -6.17, -4.60), -1.89 units (95% CI: -2.33, -1.44), -0.77 units (95% CI: -1.08, -0.47), and -2.02 units (95% CI: -2.32, -1.71) changes in the QUI, respectively. In addition, populations with higher bone strength may be more susceptible to air pollution.

CONCLUSION

Long-term exposure to PM1, PM2.5, PM10, and NO2 was significantly associated with decreased bone strength in southwestern China adults. Air pollution exposure has a more substantial adverse effect on bones among populations with higher bone strength.

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

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

Periconception air pollution, metabolomic biomarkers, and fertility among women undergoing assisted reproduction

BACKGROUND

Air pollution exposure has been linked with diminished fertility. Identifying the metabolic changes induced by periconception air pollution exposure among women could enhance our understanding of the potential biological pathways underlying air pollution's reproductive toxicity.

OBJECTIVE

To identify serum metabolites associated with periconception air pollution exposure and evaluate the extent to which these metabolites mediate the association between air pollution and live birth.

METHODS

We included 200 women undergoing a fresh assisted reproductive technology (ART) cycle at Massachusetts General Hospital Fertility Center (2005-2015). A serum sample was collected during stimulation, and untargeted metabolic profiling was conducted using liquid chromatography with ultra-high-resolution mass spectrometry. Exposure to nitrogen dioxide (NO₂), ozone (O₃), fine particulate matter <2.5 µm (PM_2.5), and black carbon (BC) was estimated using validated spatiotemporal models. Multivariable linear regression models were used to evaluate the associations between the air pollutants, live birth, and metabolic feature intensities. A meet in the middle approach was used to identify overlapping features and metabolic pathways.

RESULTS

From the C18 and HILIC chromatography columns, 10,803 and 12,968 metabolic features were extracted. There were 190 metabolic features and 18 pathways that were significantly associated with both air pollution and live birth (P < 0.05) across chromatography columns. Eight features were confirmed metabolites implicated in amino acid and nutrient metabolism with downstream effects on oxidative stress and inflammation. Six confirmed metabolites fell into two intuitive clusters - "antioxidants" and "oxidants"- which could potentially mediate some of the association between air pollution and lower odds of live birth. Tryptophan and vitamin B3 metabolism were common pathways linking air pollution exposure to decreased probability of live birth.

CONCLUSION

Higher periconception air pollution exposure was associated with metabolites and biologic pathways involved in inflammation and oxidative stress that may mediate the observed associations with lower probability of live birth following ART.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

Maternal and cord plasma metabolomics were used to elucidate biological pathways associated with increased diagnosis risk for autism spectrum disorders (ASD). Metabolome-wide associations were assessed in both maternal and umbilical cord plasma in relation to diagnoses of ASD and other non-typical development (Non-TD) compared to typical development (TD) in the Markers of Autism risk in Babies: Learning Early Signs (MARBLES) cohort study of children born to mothers who already have at least one child with ASD. Analyses were stratified by sample matrix type, machine mode, and annotation confidence level. Dimensionality reduction techniques were used [i.e, principal component analysis (PCA) and random subset weighted quantile sum regression (WQSRS)] to minimize the high multiple comparison burden. With WQSRS, a metabolite mixture obtained from the negative mode of maternal plasma decreased the odds of Non-TD compared to TD. These metabolites, all related to the prostaglandin pathway, underscored the relevance of neuroinflammation status. No other significant findings were observed. Dimensionality reduction strategies provided confirming evidence that a set of maternal plasma metabolites are important in distinguishing Non-TD compared to TD diagnosis. A lower risk for Non-TD was linked to anti-inflammatory elements, thereby linking neuroinflammation to detrimental brain function consistent with studies ranging from neurodevelopment to neurodegeneration.

Fine particulate matter exposure and perturbation of serum metabolome: A longitudinal study in Baoding, China

Metabolomics represents a powerful tool for measuring environmental exposures and biological responses to unveil potential mechanisms. Few studies have investigated the effects of exposure to fine particulate matter (PM_2.5) longitudinally on serum metabolomics in regions with high-level PM_2.5. Therefore, we examined the changes of serum metabolomics corresponding to individual PM_2.5 exposure levels in spring and autumn among 63 healthy college students in Baoding city, Hebei, China. The metabolic profiling was determined by ultra-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The average level of individual PM_2.5 in the spring was 1.82-fold higher than in the autumn (240 μg/m³ vs 132 μg/m³). Males were exposed to a higher level of PM_2.5 than females in the spring. Metabolic profiling was clearly separated by orthogonal partial least square-discriminant analysis in males but not in females. In the analysis of the associations between the metabolome and PM_2.5 of the two seasons, the changes of 14 serum metabolites were significantly associated with PM_2.5 in males. The metabolites related to heme metabolism (bilirubin, biliverdin), energy metabolism and oxidative stress (2-Octenoylcarnitine, N-Heptanoylglycine, and acetylcysteine), phospholipid metabolism (lysophosphatidic acid, phospholipid acid, and lysophosphatidylethanolamine), and tryptophan metabolism (N-Acetylserotonin, indolepyruvate, and melatonin) were decreased in the range of 2.16%-6.80% for each 10 μg/m³ increase of PM_2.5, while thyrotropin-releasing hormone, glutathione, and phosphatidylethanolamine related to energy metabolism and oxidative stress, and phospholipid metabolism were increased in the range of 2.95%-4.90% for each 10 μg/m³ increase of PM_2.5. This longitudinal study suggests that higher PM_2.5 exposure may induce perturbations in serum metabolic signaling related to oxidative stress and inflammation, and males may be more prone to these metabolic perturbations.

Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms

Environmental pollution causes significant toxicity to ecosystems. Thus, acquiring a deeper understanding of the concentration of environmental pollutants in ecosystems and, clarifying their potential toxicities is of great significance. Environmental metabolomics is a powerful technique in investigating the effects of pollutants on living organisms in the environment. In this review, we cover the different aspects of the environmental metabolomics approach, which allows the acquisition of reliable data. A step-by-step procedure from sample preparation to data interpretation is also discussed. Additionally, other factors, including model organisms and various types of emerging environmental toxicants are discussed. Moreover, we cover the considerations for successful environmental metabolomics as well as the identification of toxic effects based on data interpretation in combination with phenotype assays. Finally, the effects induced by various types of environmental toxicants in model organisms based on the application of environmental metabolomics are also discussed.

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

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Estimating climate change-related impacts on outdoor air pollution infiltration

BACKGROUND

Rising temperatures due to climate change are expected to impact human adaptive response, including changes to home cooling and ventilation patterns. These changes may affect air pollution exposures via alteration in residential air exchange rates, affecting indoor infiltration of outdoor particles. We conducted a field study examining associations between particle infiltration and temperature to inform future studies of air pollution health effects.

METHODS

We measured indoor fine particulate matter (PM_2.5) in Atlanta in 60 homes (810 sampling-days). Indoor-outdoor sulfur ratios were used to estimate particle infiltration, using central site outdoor sulfur concentrations. Linear and mixed-effects models were used to examine particle infiltration ratio-temperature relationships, based on which we incorporated projected meteorological values (Representative Concentration Pathways intermediate scenario RCP 4.5) to estimate particle infiltration ratios in 20-year future (2046-2065) and past (1981-2000) scenarios.

RESULTS

The mean particle infiltration ratio in Atlanta was 0.70 ± 0.30, with a 0.21 lower ratio in summer compared to transition seasons (spring, fall). Particle infiltration ratios were 0.19 lower in houses using heating, ventilation, and air conditioning (HVAC) systems compared to those not using HVAC. We observed significant associations between particle infiltration ratios and both linear and quadratic models of ambient temperature for homes using natural ventilation and those using HVAC. Future temperature was projected to increase by 2.1 °C in Atlanta, which corresponds to an increase of 0.023 (3.9%) in particle infiltration ratios during cooler months and a decrease of 0.037 (6.2%) during warmer months.

DISCUSSION

We estimated notable changes in particle infiltration ratio in Atlanta for different 20-year periods, with differential seasonal patterns. Moreover, when stratified by HVAC usage, increases in future ambient temperature due to climate change were projected to enhance seasonal differences in PM_2.5 infiltration in Atlanta. These analyses can help minimize exposure misclassification in epidemiologic studies of PM_2.5, and provide a better understanding of the potential influence of climate change on PM_2.5 health effects.

High-Resolution Metabolomic Assessment of Pesticide Exposure in Central Valley, California

Pesticides are widely used in the agricultural Central Valley region of California. Historically, this has included organophosphates (OPs), organochlorines (OCs), and pyrethroids (PYRs). This study aimed to identify perturbations of the serum metabolome in response to each class of pesticide and mutual associations between groups of metabolites and multiple pesticides. We conducted high-resolution metabolomic profiling of serum samples from 176 older adults living in the California Central Valley using liquid chromatography with high-resolution mass spectrometry. We estimated chronic pesticide exposure (from 1974 to year of blood draw) to OPs, OCs, and PYRs from ambient sources at homes and workplaces with a geographic information system (GIS)-based model. Based on partial least-squares regression and pathway enrichment analysis, we identified metabolites and metabolic pathways associated with one or multiple pesticide classes, including mitochondrial energy metabolism, fatty acid and lipid metabolism, and amino acid metabolism. Utilizing an integrative network approach, we found that the fatty acid β-oxidation pathway is a common pathway shared across all three pesticide classes. The disruptions of the serum metabolome suggested that chronic pesticide exposure might result in oxidative stress, inflammatory reactions, and mitochondrial dysfunction, all of which have been previously implicated in a wide variety of diseases. Overall, our findings provided a comprehensive view of the molecular mechanisms of chronic pesticide toxicity, and, for the first time, our approach informs exposome research by moving from macrolevel population exposures to microlevel biologic responses.

Metabolomic Changes after Subacute Exposure to Polycyclic Aromatic Hydrocarbons: A Natural Experiment among Healthy Travelers from Los Angeles to Beijing

Emerging epidemiological evidence has associated exposure to polycyclic aromatic hydrocarbons (PAHs) with chronic diseases including cardiometabolic diseases and neurodegeneration. However, little information is available about their subacute effects, which may accumulate over years and contribute to chronic disease development. To fill this knowledge gap, we designed a natural experiment among 26 healthy young adults who were exposed to elevated PAHs for 10 weeks after traveling from Los Angeles to Beijing in 2014 and 2015. Serum was collected before, during, and after the trip for metabolomics analysis. We identified 50 metabolites that significantly changed 6-8 weeks after the travel to Beijing (FDR < 5%). The network analysis revealed two main independent modules. Module 1 was allocated to oxidative homeostasis-related response and module 2 to delayed enzymatic deinduction response. Remarkably, the module 1 metabolites were recovered 4-7 weeks after participants' return, while the module 2 metabolites were not. Urinary hydroxylated PAHs were significantly associated with metabolites from both modules, while PAH carboxylic acids, likely metabolites of alkylated PAHs, were only associated with antioxidation-related metabolites. These results suggested differential subacute effects of unsubstituted and alkylated PAHs. Further studies are warranted to elucidate the role of the reversibility of metabolite changes in adverse health effects of PAHs.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

How Do Inflammatory Mediators, Immune Response and Air Pollution Contribute to COVID-19 Disease Severity? A Lesson to Learn

Inflammatory and immune processes are defensive mechanisms that aim to remove harmful agents. As a response to infections, inflammation and immune response contribute to the pathophysiological mechanisms of diseases. Coronavirus disease 2019 (COVID-19), whose underlying mechanisms remain not fully elucidated, has posed new challenges for the knowledge of pathophysiology. Chiefly, the inflammatory process and immune response appear to be unique features of COVID-19 that result in developing a hyper-inflammatory syndrome, and air pollution, the world's largest health risk factor, may partly explain the behaviour and fate of COVID-19. Understanding the mechanisms involved in the progression of COVID-19 is of fundamental importance in order to avoid the late stage of the disease, associated with a poor prognosis. Here, the role of the inflammatory and immune mediators in COVID-19 pathophysiology is discussed.

Application of high-resolution metabolomics to identify biological pathways perturbed by traffic-related air pollution

BACKGROUND

Substantial research has investigated the adverse effects of traffic-related air pollutants (TRAP) on human health. Convincing associations between TRAP and respiratory and cardiovascular diseases are known, but the underlying biological mechanisms are not well established. High-resolution metabolomics (HRM) is a promising platform for untargeted characterization of molecular mechanisms between TRAP and health indexes.

OBJECTIVES

We examined metabolic perturbations associated with short-term exposures to TRAP, including carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (PM2.5), organic carbon (OC), and elemental carbon (EC) among 180 participants of the Center for Health Discovery and Well-Being (CHDWB), a cohort of Emory University-affiliated employees.

METHODS

A cross-sectional study was conducted on baseline visits of 180 CHDWB participants enrolled during 2008-2012, in whom HRM profiling was determined in plasma samples using liquid chromatography-high-resolution mass spectrometry with positive and negative electrospray ionization (ESI) modes. Ambient pollution concentrations were measured at an ambient monitor near downtown Atlanta. Metabolic perturbations associated with TRAP exposures were assessed following an untargeted metabolome-wide association study (MWAS) framework using feature-specific Tobit regression models, followed by enriched pathway analysis and chemical annotation.

RESULTS

Subjects were predominantly white (76.1%) and non-smokers (95.6%), and all had at least a high school education. In total, 7821 and 4123 metabolic features were extracted from the plasma samples by the negative and positive ESI runs, respectively. There are 3421 features significantly associated with at least one air pollutant by negative ion mode, and 1691 features by positive ion mode. Biological pathways enriched by features associated with the pollutants are primarily involved in nucleic acids damage/repair (e.g., pyrimidine metabolism), nutrient metabolism (e.g., fatty acid metabolism), and acute inflammation (e.g., histidine metabolism and tyrosine metabolism). NO2 and EC were associated most consistently with these pathways. We confirmed the chemical identity of 8 metabolic features in negative ESI and 2 features in positive ESI, including metabolites closely linked to oxidative stress and inflammation, such as histamine, tyrosine, tryptophan, and proline.

CONCLUSIONS

We identified a range of ambient pollutants, including components of TRAP, associated with differences in the metabolic phenotype among the cohort of 180 subjects. We found Tobit models to be a robust approach to handle missing data among the metabolic features. The results were encouraging of further use of HRM and MWAS approaches for characterizing molecular mechanisms underlying exposure to TRAP.

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

PURPOSE OF REVIEW

Review how to use metabolomic profiling in causal mediation analysis to assess epidemiological evidence for air pollution impacts on birth outcomes.

RECENT FINDINGS

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

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

PURPOSE OF REVIEW

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

RECENT FINDINGS

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Association between traffic-related air pollution and hospital readmissions for rheumatoid arthritis in Hefei, China: A time-series study

Air pollution is an important risk factor for autoimmune diseases, but its association with the recurrence of rheumatoid arthritis (RA) remains unclear so far. This study aimed to investigate the short-term association between traffic-related air pollutants and hospital readmissions for RA in Hefei, China. Data on daily hospital readmissions for RA and traffic-related air pollutants, including particulate matter (PM_2.5 and PM₁₀), nitrogen dioxide (NO₂), and carbon monoxide (CO), from 2014 to 2018 were retrieved. A time-series approach using generalized linear regression model was employed. The analysis was further stratified by sex, age and season. A total of 1153 readmissions for RA were reported during the study period. A significant association between high-concentration PM_2.5 (90th percentile) and RA readmissions was observed on lag1 (relative risk (RR) = 1.09, 95% confidence interval (CI): 1.01-1.19) and lasted until lag3 (RR = 1.06, 95%CI: 1.01-1.12). From lag2 to lag5, high-concentration NO₂ (90th percentile) was associated with increased risk of RA readmissions, with the highest RR observed at lag 4 (1.11, 95%CI: 1.05-1.17). Stratified analyses indicated that females and the elderly appeared to be more vulnerable to high-concentration PM_2.5 and NO₂ exposure. High-concentration PM_2.5 and NO₂ in cold seasons were consistently significantly associated with increased risk of RA readmissions. Exposure to high-concentration PM_2.5 and NO₂ was associated with increased risk of RA readmissions. Protective measures against the exposure to high-concentration PM_2.5 and NO₂ should be taken to reduce the recurrence risk in RA patients, especially in females, the elderly and during cold seasons.

Non-targeted metabolomic profiling of atrazine in Caenorhabditis elegans using UHPLC-QE Orbitrap/MS

The widespread use of the herbicides Atrazine (ATR) has been raised attention due to its ubiquitous occurrence in the environment. As an endocrine disruptor, ATR causes reproductive, immune, nervous system toxicity in biota. In this study, we aimed to investigate metabolic profile characteristics and potential metabolic biomarker that reflects specific damage in toxic effect after ATR exposure. Hence, a metabolomics study was performed to determine the significantly affected metabolites and the reproduction and locomotion of C. elegans were investigated. Mediation analysis was used to evaluate the mediating effect of metabolites on association between ATR exposure and toxic effect. ATR (≥0.04 mg/L) caused the significant dose dependent reduction of brood size and locomotion behavior, however, the body length and width were significantly decreased only in 40 mg/L group. These results suggesting that brood size, head thrashes and body bends are more sensitive indictor to assessment ATR toxicity in C. elegans. Meanwhile, metabolomics analysis revealed that ATR exposure can induce metabolic profiles significant alterations in C. elegans. We found that 9 metabolites significantly increased and 18 metabolites significantly decreased, such as phosphatidylcholine, GMP, CDP-choline, neopterin etc. Those alteration of metabolites were mainly involved in the pathways: glycerophospholipid metabolism, glycolysis/gluconeogenesis, folate biosynthesis, glycine, serine and threoninemetabolism, pyrimidine and purine metabolism. Overall, these changes are signs of possible oxidative stress and ATP synthesis disruption modification. Mediation analysis showed a significant indirect effect of ATR exposure on brood size, via 7,8-dihydroneopterin 2',3'-cyclic-p, and phosphatidylcholine might mediate association between ATR exposure and body bends, suggesting that 7,8-dihydroneopterin 2',3'-cyclic-p and phosphatidylcholine might be potentially specificity marker for brood size and body bend respectively. This preliminary analysis investigates metabolic characteristics in C. elegans after ATR exposure, helping to understand the pathways involved in the response to ATR exposure and provide potential biomarkers for the safety evaluation of ATR.

Metabolic Signatures of the Exposome-Quantifying the Impact of Exposure to Environmental Chemicals on Human Health

Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the “chemical exposome” (exposures to environmental chemicals), affect the host’s metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome.

Combined exposure to formaldehyde and PM2.5: Hematopoietic toxicity and molecular mechanism in mice

PM2.5 and formaldehyde (FA) are major outdoor and indoor air pollutants in China, respectively, and both are known to be harmful to human health and to be carcinogenic. Of all the known chronic health effects, leukaemia is one of the most serious health risks associated with these two pollutants. To explore the influence and underlying mechanisms of exposure to formaldehyde and PM2.5 on hematopoietic toxicity, we systematically studied the toxicity induced in hematopoietic organs: bone marrow (BM); spleen; and myeloid progenitor cells (MPCs). Male Balb/c mice were exposed to: PM2.5 (20, 160 μg/kg·d) at a dose of 40 μL per mouse or formaldehyde (0.5, 3.0 mg/m3) for 8 h per day for 2 weeks or co-exposed to formaldehyde and PM2.5 (20 μg/kg·d PM2.5 + 0.5 mg/m3 FA, 20 μg/kg·d PM2.5 + 3 mg/m3 FA, 160 μg/kg·d PM2.5 + 0.5 mg/m3 FA, 160 μg/kg·d PM2.5 + 3 mg/m3 FA) for 2 weeks. Similar toxic effects were found in the formaldehyde-only and PM2.5-only groups, including significant decrease of blood cells and MPCs, along with decreased expression of hematopoietic growth factors. In addition, individual exposure of formaldehyde or PM2.5 increased oxidative stress, DNA damage and immune system disorder by destroying the balance of Th1/Th2, and Treg/Th17. DNA repair was markedly inhibited by deregulating the mammalian target of rapamycin (mTOR) pathway. Combined exposure to PM2.5 and formaldehyde led to more severe effects. Administration of Vitamin E (VE) was shown to attenuate these effects. In conclusion, our findings suggested that PM2.5 and formaldehyde may induce hematopoietic toxicity by reducing the expression of hematopoietic growth factors, increasing oxidative stress and DNA damage, activating the 'immune imbalance' pathway and suppressing the DNA-repair related mTOR pathway. The hematopoietic toxicity induced by combined exposure of PM2.5 and formaldehyde might provide further insights into the increased incidence of hematological diseases, including human myeloid leukaemia.

Toxicity of airborne particles-established evidence, knowledge gaps and emerging areas of importance

Epidemiological research has taught us a great deal about the health effects of airborne particulate matter (PM), particularly cardiorespiratory effects of combustion-related particles. This has been matched by toxicological research to define underlying mechanistic pathways. To keep abreast of the substantial challenges that air pollution continues to throw at us requires yet more strides to be achieved. For example, being aware of the most toxic components/sources and having a definitive idea of the range of associated disease outcomes. This review discusses approaches designed to close some of these knowledge gaps. These include a focus on particles arising from non-exhaust PM at the roadside and microplastics-both of which are becoming more relevant in the light of a shift in PM composition in response to global pressure to reduce combustion emissions. The application of hypothesis-free approaches in both mechanistic studies and epidemiology in unveiling unexpected relationships and generating novel insights is also discussed. Previous work, strengthening the evidence for both the adverse effects and benefits of intervention tell us that the sooner we act to close knowledge gaps, increase awareness and develop creative solutions, the sooner we can reduce the public health burden attributable to these complex and insidious environmental pollutants. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

Background

The novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 600,000 lives worldwide, causing tremendous public health, social, and economic damages. Although the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis.

Methods

We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010–2016) county-level exposures to NO₂, PM_2.5, and O₃ and county-level COVID-19 case-fatality and mortality rates in the United States. We used both single- and multi-pollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level health care capacity, phase of epidemic, population mobility, population density, sociodemographics, socioeconomic status, race and ethnicity, behavioral risk factors, and meteorology.

Results

From January 22, 2020, to July 17, 2020, 3,659,828 COVID-19 cases and 138,552 deaths were reported in 3,076 US counties, with an overall observed case-fatality rate of 3.8%. County-level average NO₂ concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models. When adjusted for co-pollutants, per interquartile-range (IQR) increase in NO₂ (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 11.3% (95% CI 4.9%–18.2%) and 16.2% (95% CI 8.7%–24.0%), respectively. We did not observe significant associations between COVID-19 case-fatality rate and long-term exposure to PM_2.5 or O₃, although per IQR increase in PM_2.5 (2.6 μg/m³) was marginally associated, with a 14.9% (95% CI 0.0%–31.9%) increase in COVID-19 mortality rate when adjusted for co-pollutants.

Discussion

Long-term exposure to NO₂, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM_2.5 and O₃ exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO₂ levels. Continuation of current efforts to lower traffic emissions and ambient air pollution may be an important component of reducing population-level risk of COVID-19 case fatality and mortality.

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One of the first US studies on air pollution exposures and COVID-19 death outcomes

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Urban air pollutants, especially NO₂, may enhance population susceptibility to death fromCOVID-19

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Reduction in air pollution would have avoided over 14,000 COVID-19 deaths in the US as of July 17, 2020

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Public health actions needed to protect populations from COVID-19 in areas with historically high NO₂ exposure

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Expansion of efforts to lower air pollution may reduce population-level risk of COVID-19

Advances in Comprehensive Exposure Assessment: Opportunities for the US Military

OBJECTIVE

Review advances in exposure assessment offered by the exposome concept and new -omics and sensor technologies.

METHODS

Narrative review of advances, including current efforts and potential future applications by the US military.

RESULTS

Exposure assessment methods from both bottom-up and top-down exposomics approaches are advancing at a rapid pace, and the US military is engaged in developing both approaches. Top-down approaches employ various -omics technologies to identify biomarkers of internal exposure and biological effect. Bottom-up approaches use new sensor technology to better measure external dose. Key challenges of both approaches are largely centered around how to integrate, analyze, and interpret large datasets that are multidimensional and disparate.

CONCLUSIONS

Advances in -omics and sensor technologies may dramatically enhance exposure assessment and improve our ability to characterize health risks related to occupational and environmental exposures, including for the US military.

Metabolome-Wide Association Study of Deployment to Balad, Iraq or Bagram, Afghanistan

OBJECTIVE

To use high-resolution metabolomics (HRM) to identify metabolic changes in military personnel associated with deployment to Balad, Iraq, or Bagram, Afghanistan.

METHODS

Pre- and post-deployment samples were obtained from the Department of Defense Serum Repository (DoDSR). HRM and bioinformatics were used to identify metabolic differences associated with deployment.

RESULTS

Differences at baseline (pre-deployment) between personnel deployed to Bagram compared with Balad or Controls included sex hormone and keratan sulfate metabolism. Deployment to Balad was associated with alterations to amino acid and lipid metabolism, consistent with inflammation and oxidative stress, and pathways linked to metabolic adaptation and repair. Difference associated with deployment to Bagram included lipid pathways linked to cell signaling and inflammation.

CONCLUSIONS

Metabolic variations in pre- and post-deployment are consistent with deployment-associated responses to air pollution and other environmental stressors.

NLRP3 Inflammasome: A Potential Therapeutic Target in Fine Particulate Matter-Induced Neuroinflammation in Alzheimer's Disease

As one of the most harmful air pollutants, fine particulate matter (PM2.5) has been implicated as a risk factor for multiple diseases, which has generated widespread public concern. Accordingly, a growing literature links PM2.5 exposure with Alzheimer's disease (AD). A critical gap in our understanding of the adverse effects of PM2.5 on AD is the mechanism triggered by PM2.5 that contributes to disease progression. Recent evidence has demonstrated that PM2.5 can activate NLRP3 inflammasome-mediated neuroinflammation. In this review, we highlight the novel evidence between PM2.5 exposure and AD incidence, which is collected and summarized from neuropathological, epidemiological, and neuroimaging studies to in-depth deciphering molecular mechanisms. First, neuropathological, epidemiological, and neuroimaging studies will be summarized. Then, the transport pathway for central nervous system delivery of PM2.5 will be presented. Finally, the role of NLRP3 inflammasome-mediated neuroinflammation in PM2.5 induced-effects on AD will be recapitulated.

Use of an Exposome Approach to Understand the Effects of Exposures From the Natural, Built, and Social Environments on Cardio-Vascular Disease Onset, Progression, and Outcomes

Obesity, diabetes, and hypertension have increased by epidemic proportions in recent years among African Americans in comparison to Whites resulting in significant adverse cardiovascular disease (CVD) disparities. Today, African Americans are 30% more likely to die of heart disease than Whites and twice as likely to have a stroke. The causes of these disparities are not yet well-understood. Improved methods for identifying underlying risk factors is a critical first step toward reducing Black:White CVD disparities. This article will focus on environmental exposures in the external environment and how they can lead to changes at the cellular, molecular, and organ level to increase the personal risk for CVD and lead to population level CVD racial disparities. The external environment is defined in three broad domains: natural (air, water, land), built (places you live, work, and play) and social (social, demographic, economic, and political). We will describe how environmental exposures in the natural, built, and social environments "get under the skin" to affect gene expression though epigenetic, pan-omics, and related mechanisms that lead to increased risk for adverse CVD health outcomes and population level disparities. We also will examine the important role of metabolomics, proteomics, transcriptomics, genomics, and epigenomics in understanding how exposures in the natural, built, and social environments lead to CVD disparities with implications for clinical, public health, and policy interventions. In this review, we apply an exposome approach to Black:White CVD racial disparities. The exposome is a measure of all the exposures of an individual across the life course and the relationship of those exposures to health effects. The exposome represents the totality of exogenous (external) and endogenous (internal) exposures from conception onwards, simultaneously distinguishing, characterizing, and quantifying etiologic, mediating, moderating, and co-occurring risk and protective factors and their relationship to disease. Specifically, it assesses the biological mechanisms and underlying pathways through which chemical and non-chemical environmental exposures are associated with CVD onset, progression and outcomes. The exposome is a promising approach for understanding the complex relationships among environment, behavior, biology, genetics, and disease phenotypes that underlie population level, Black: White CVD disparities.

Molecular and cellular mechanisms linking air pollution and bone damage

Air pollution is the second most important risk factor associated with noncommunicable diseases after smoking. The effects of pollution on health are commonly attributable to particulate matter (PM), a complex mixture of particles suspended in the air. PM can penetrate the lower respiratory tract and has harmful direct and indirect effects on different organs and tissues. Direct effects are caused by the ability of PM components to cross the respiratory membrane and enter the bloodstream; indirect effects are systemic consequences of the local airway response. Recent work suggests that PM is an independent risk factor for low bone mineral density and osteoporosis-related fractures. Osteoporosis is a common age-related disease closely linked to bone fractures, with severe clinical consequences affecting quality of life, morbidity, and mortality. In this review, we discuss potential mechanisms behind the association between outdoor air pollution, especially PM, and bone damage. The discussion features four main mechanisms: 1) several different atmospheric pollutants can induce low-grade systemic inflammation, which affects bone metabolism through a specific effect of cytokines such as TNFα, IL-1β, IL-6, and IL-17 on osteoblast and osteoclast differentiation and function; 2) some pollutants, particularly certain gas and metal compounds, can cause oxidative damage in the airway and bone cells; 3) different groups of pollutants can act as endocrine disruptors when binding to the receptors in bone cells, changing their functioning; and 4) air pollution can directly and indirectly cause vitamin D deficiency. Characterizing these mechanisms will better define the physiopathology of bone damage, and recognizing air pollution as a modifiable risk factor for osteoporosis will inform environmental policies. Such knowledge will also guide the prevention of fractures due to fragility and help reduce health-related costs.

Associations of air pollution with obesity and body fat percentage, and modification by polygenic risk score for BMI in the UK Biobank

Air pollution has consistently been associated with cardiometabolic outcomes, although associations with obesity have only been recently reported. Studies of air pollution and adiposity have mostly relied on body mass index (BMI) rather than body fat percentage (BF%), and most have not accounted for noise as a possible confounder. Additionally, it is unknown whether genetic predisposition for obesity increases susceptibility to the obesogenic effects of air pollution. To help fill these gaps, we used the UK Biobank, a large, prospective cohort study in the United Kingdom, to explore the relationship between air pollution and adiposity, and modification by a polygenic risk score for BMI. We used 2010 annual averages of air pollution estimates from land use regression (NO₂, NO_X, PM_2.5, PM_{2.5absorbance}, PM_2.5-10, PM₁₀), traffic intensity (TI), inverse distance to road (IDTR), along with examiner-measured BMI, waist-hip-ratio (WHR), and impedance measures of BF%, which were collected at enrollment (2006-2010, n = 473,026) and at follow-up (2012-2013, n = 19,518). We estimated associations of air pollution with BMI, WHR, and BF% at enrollment and follow-up, and with obesity, abdominal obesity, and BF%-obesity at enrollment and follow-up. We used linear and logistic regression and controlled for noise and other covariates. We also assessed interactions of air pollution with a polygenic risk score for BMI. On average, participants at enrollment were 56 years of age, 54% were female, and 32% had completed college or a higher degree. Almost all participants (~95%) were white. All air pollution measures except IDTR were positively associated with at least one continuous measure of adiposity at enrollment. However, NO₂ was negatively associated with BMI but positively associated with WHR at enrollment, and IDTR was also negatively associated with BMI. At follow-up (controlling for enrollment adiposity), we observed positive associations for PM_2.5-10 with BMI, PM₁₀ with BF%, and TI with BF% and BMI. Associations were similar for binary measures of adiposity, with minor differences for some pollutants. Associations of NO_X, NO₂, PM_{2.5absorbance}, PM_2.5 and PM₁₀, with BMI at enrollment, but not at follow-up, were stronger among individuals with higher BMI polygenic risk scores (interaction p <0.05). In this large, prospective cohort, air pollution was associated with several measures of adiposity at enrollment and follow-up, and associations with adiposity at enrollment were modified by a polygenic risk score for obesity.

Urban Air Pollution May Enhance COVID-19 Case-Fatality and Mortality Rates in the United States

BACKGROUND

The novel human coronavirus disease 2019 (COVID-19) pandemic has claimed more than 240,000 lives worldwide, causing tremendous public health, social, and economic damages. While the risk factors of COVID-19 are still under investigation, environmental factors, such as urban air pollution, may play an important role in increasing population susceptibility to COVID-19 pathogenesis.

METHODS

We conducted a cross-sectional nationwide study using zero-inflated negative binomial models to estimate the association between long-term (2010-2016) county-level exposures to NO2, PM2.5 and O3 and county-level COVID-19 case-fatality and mortality rates in the US. We used both single and multipollutant models and controlled for spatial trends and a comprehensive set of potential confounders, including state-level test positive rate, county-level healthcare capacity, phase-of-epidemic, population mobility, sociodemographic, socioeconomic status, behavior risk factors, and meteorological factors.

RESULTS

1,027,799 COVID-19 cases and 58,489 deaths were reported in 3,122 US counties from January 22, 2020 to April 29, 2020, with an overall observed case-fatality rate of 5.8%. Spatial variations were observed for both COVID-19 death outcomes and long-term ambient air pollutant levels. County-level average NO2 concentrations were positively associated with both COVID-19 case-fatality rate and mortality rate in single-, bi-, and tri-pollutant models (p-values<0.05). Per inter-quartile range (IQR) increase in NO2 (4.6 ppb), COVID-19 case-fatality rate and mortality rate were associated with an increase of 7.1% (95% CI 1.2% to 13.4%) and 11.2% (95% CI 3.4% to 19.5%), respectively. We did not observe significant associations between long-term exposures to PM2.5 or O3 and COVID-19 death outcomes (p-values>0.05), although per IQR increase in PM2.5 (3.4 ug/m3) was marginally associated with 10.8% (95% CI: -1.1% to 24.1%) increase in COVID-19 mortality rate.

DISCUSSIONS AND CONCLUSIONS

Long-term exposure to NO2, which largely arises from urban combustion sources such as traffic, may enhance susceptibility to severe COVID-19 outcomes, independent of long-term PM2.5 and O3 exposure. The results support targeted public health actions to protect residents from COVID-19 in heavily polluted regions with historically high NO2 levels. Moreover, continuation of current efforts to lower traffic emissions and ambient air pollution levels may be an important component of reducing population-level risk of COVID-19 deaths.

Evaluating a multipollutant metric for use in characterizing traffic-related air pollution exposures within near-road environments

Accurately characterizing human exposures to traffic-related air pollutants (TRAPs) is critical to public health protection. However, quantifying exposure to this single source is challenging, given its extremely heterogeneous chemical composition. Efforts using single-species tracers of TRAP are, thus, lacking in their ability to accurately reflect exposures to this complex mixture. There have been recent discussions centered on adopting a multipollutant perspective for sources with many emitted pollutants to maximize the benefits of control expenditures as well as to minimize population and ecosystem exposure. As part of a larger study aimed to assess a complete emission-to-exposure pathway of primary traffic pollution and understand exposure of individuals in the near-road environment, an intensive field campaign measured TRAPs and related data (e.g., meteorology, traffic counts, and regional air pollutant levels) in Atlanta along one of the busiest highway corridors in the US. Given the dynamic nature of the near-road environment, a multipollutant exposure metric, the Integrated Mobile Source Indicator (IMSI), which was generated based on emissions-based ratios, was calculated and compared to traditional single-species methods for assessing exposure to mobile source emissions. The current analysis examined how both traditional and non-traditional metrics vary spatially and temporally in the near-road environment, how they compare with each other, and whether they have the potential to offer more accurate means of assigning exposures to primary traffic emissions. The results indicate that compared to the traditional single pollutant specie, the multipollutant IMSI metric provided a more spatially stable method for assessing exposure, though variations occurred based on location with varying results among the six sites within a kilometer of the highway.