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

Serum metabolome perturbation in relation to noise exposure: Exploring the potential role of serum metabolites in noise-induced arterial stiffness

Noise pollution has grown to be a major public health issue worldwide. We sought to profile serum metabolite expression changes related to occupational noise exposure by untargeted metabolomics, as well as to evaluate the potential roles of serum metabolites in occupational noise-associated arterial stiffness (AS). Our study involved 30 noise-exposed industrial personnel (Lipo group) and 30 noise-free controls (Blank group). The untargeted metabolomic analysis was performed by employing a UPLC-HRMS. The associations of occupational noise and significant differential metabolites (between Blank/Lipo groups) with AS were evaluated using multivariable-adjusted generalized linear models. We performed the least absolute shrinkage and selection operator regression analysis to further screen for AS's risk metabolites. We explored 177 metabolites across 21 categories significantly differentially expressed between Blank/Lipo groups, and these metabolites were enriched in 20 metabolic pathways. Moreover, 15 metabolites in 4 classes (including food, glycerophosphocholine, sphingomyelin [SM] and triacylglycerols [TAG]) were adversely associated with AS (all P < 0.05). Meanwhile, five metabolites (homostachydrine, phosphatidylcholine (PC) (32:1e), PC (38:6p), SM (d41:2) and TAG (45:1) have been proven to be useful predictors of AS prevalence. However, none of these 15 metabolites were found to have a mediating influence on occupational noise-induced AS. Our study reveals specific metabolic changes caused by occupational noise exposure, and several metabolites may have protective effects on AS. However, the roles of serum metabolites in noise-AS association remain to be validated in future studies.

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

Background

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

Objectives

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

Methods

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

Results

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

Conclusions

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

DISCUSSION

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

Associations of residential greenness with bone mineral density and osteoporosis: the modifying effect of genetic susceptibility

OBJECTIVES

To investigate the associations of residential greenness with bone mineral density and incident osteoporosis, and further evaluate the potential modifying effect of genetic susceptibility.

METHODS

We used the Normalised Difference Vegetation Index (NDVI) at various buffer distances, including 300 m (NDVI300m), 500 m (NDVI500m), 1000 m (NDVI1000m) and 1500 m (NDVI1500m), to serve as indicators of greenness. We fitted linear regression, logistic regression and Cox proportional hazard models to assess the associations of residential greenness with estimated bone mineral density (eBMD), prevalent osteoporosis and incident osteoporosis, respectively. With the Polygenic Risk Score (PRS) for osteoporosis, we further assessed the joint effects of genetic risk and greenness on the risk of osteoporosis. We conducted causal mediation analyses to explore potential mediators.

RESULTS

Each IQR increase in NDVI300m was associated with 0.0007 (95% CI 0.0002 to 0.0013) increase in eBMD, 6% lower risk of prevalent osteoporosis (OR 0.94; 95% CI 0.92 to 0.97) and 5% lower risk of incident osteoporosis (HR 0.95; 95% CI 0.93 to 0.98). The joint effects of greenness and PRS on the risk of osteoporosis displayed a clear dose-response pattern. Compared with individuals exposed to low NDVI levels and high genetic risk, those exposed to high NDVI levels and low genetic risk had a 56% (95% CI 51% to 61%) lower risk of osteoporosis. The primary mediators in the association between greenness and incident osteoporosis were identified as PM2.5 and NO2.

CONCLUSIONS

Residential greenness was associated with higher bone mineral density and decreased risk of incident osteoporosis.

Bayesian functional analysis for untargeted metabolomics data with matching uncertainty and small sample sizes

Untargeted metabolomics based on liquid chromatography-mass spectrometry technology is quickly gaining widespread application, given its ability to depict the global metabolic pattern in biological samples. However, the data are noisy and plagued by the lack of clear identity of data features measured from samples. Multiple potential matchings exist between data features and known metabolites, while the truth can only be one-to-one matches. Some existing methods attempt to reduce the matching uncertainty, but are far from being able to remove the uncertainty for most features. The existence of the uncertainty causes major difficulty in downstream functional analysis. To address these issues, we develop a novel approach for Bayesian Analysis of Untargeted Metabolomics data (BAUM) to integrate previously separate tasks into a single framework, including matching uncertainty inference, metabolite selection and functional analysis. By incorporating the knowledge graph between variables and using relatively simple assumptions, BAUM can analyze datasets with small sample sizes. By allowing different confidence levels of feature-metabolite matching, the method is applicable to datasets in which feature identities are partially known. Simulation studies demonstrate that, compared with other existing methods, BAUM achieves better accuracy in selecting important metabolites that tend to be functionally consistent and assigning confidence scores to feature-metabolite matches. We analyze a COVID-19 metabolomics dataset and a mouse brain metabolomics dataset using BAUM. Even with a very small sample size of 16 mice per group, BAUM is robust and stable. It finds pathways that conform to existing knowledge, as well as novel pathways that are biologically plausible.

Associations between metals and metabolomic profiles related to diabetes among adults in a rural region

INTRODUCTION

Exposure to metals is associated with increased risk of type 2 diabetes (T2D). Potential mechanisms for metals-T2D associations involve biological processes including oxidative stress and disruption of insulin-regulated glucose uptake. In this study, we assessed whether associations between metal exposure and metabolite profiles relate to biological pathways linked to T2D.

MATERIALS AND METHODS

We used data from 29 adults rural Colorado residents enrolled in the San Luis Valley Diabetes Study. Urinary concentrations of arsenic, cadmium, cobalt, lead, manganese, and tungsten were measured. Metabolic effects were evaluated using untargeted metabolic profiling, which included 61,851 metabolite signals detected in serum. We evaluated cross-sectional associations between metals and metabolites present in at least 50% of samples. Primary analyses adjusted urinary heavy metal concentrations for creatinine. Metabolite outcomes associated with each metal exposure were evaluated using pathway enrichment to investigate potential mechanisms underlying the relationship between metals and T2D.

RESULTS

Participants had a mean age of 58.5 years (standard deviation = 9.2), 48.3% were female, 48.3% identified as Hispanic/Latino, 13.8% were current smokers, and 65.5% had T2D. Of the detected metabolites, 455 were associated with at least one metal, including 42 associated with arsenic, 22 with cadmium, 10 with cobalt, 313 with lead, 66 with manganese, and two with tungsten. The metabolic features were linked to 24 pathways including linoleate metabolism, butanoate metabolism, and arginine and proline metabolism. Several of these pathways have been previously associated with T2D, and our results were similar when including only participants with T2D.

CONCLUSIONS

Our results support the hypothesis that metals exposure may be associated with biological processes related to T2D, including amino acid, co-enzyme, and sugar and fatty acid metabolism. Insight into biological pathways could influence interventions to prevent adverse health outcomes due to metal exposure.

Neonatal per- and polyfluoroalkyl substance exposure in relation to retinoblastoma

BACKGROUND

Neonatal per- and polyfluoroalkyl substance (PFAS) exposure can disrupt hormonal homeostasis and induce neuro- and immunotoxicity in children. In this exploratory study, we investigated associations between PFAS levels in neonatal dried blood spots and retinoblastoma risk.

MATERIALS AND METHODS

This study included 501 retinoblastoma cases born from 1983 to 2011 and 899 controls frequency-matched by birth year (20:1 matching ratio), born to 755 US-born and 366 Mexico-born mothers in California. Perfluorooctanesulfonic acid (PFOS), perflurooctanoic acid (PFOA), and perfluorononanoic acid (PFNA) feature intensities were identified from neonatal blood spots from California newborn Genetic Disease Screening Program. Using logistic regression, we assessed whether an interquartile range (IQR) increase of PFAS levels or having above-mean levels of PFAS in blood affects retinoblastoma risk overall or its subtypes (i.e., unilateral, bilateral). We assessed children of US-born and Mexico-born mothers, separately.

RESULTS AND DISCUSSION

Among all children, above-mean PFOS levels at birth increased the odds of retinoblastoma overall by 29% (95% Confidence Interval (CI): 1.00, 1.67) and unilateral retinoblastoma by 42% (95% CI: 1.03, 1.97). For children of Mexico-born mothers, we estimated the highest odds of retinoblastoma overall (adjusted odds ratio (aOR): 1.67; 95% CI: 1.06, 2.66) and bilateral retinoblastoma (aOR: 2.06; 95% CI: 1.12, 3.92) with above-mean PFOS levels. Among children of US-born mothers, higher PFOS levels increased the odds of unilateral retinoblastoma by 15% (95% CI: 0.99, 1.35) for each IQR increase and by 71% among children with above-mean PFOS levels (95% CI: 1.04, 2.90). In addition, for children of US-born mothers, PFOA increased the odds of retinoblastoma overall (aOR: 1.41; 95% CI: 1.00, 2.02 for above-mean levels, aOR: 1.06; 95% CI: 0.98, 1.16 per IQR increase). PFNA was not associated with retinoblastoma risk.

CONCLUSIONS

Our results suggested that PFOS and PFOA might contribute to retinoblastoma risk in children born in California.

Metabolomics of natural samples: A tutorial review on the latest technologies

Metabolomics is the study of metabolites present in a living system. It is a rapidly growing field aimed at discovering novel compounds, studying biological processes, diagnosing diseases, and ensuring the quality of food products. Recently, the analysis of natural samples has become important to explore novel bioactive compounds and to study how environment and genetics affect living systems. Various metabolomics techniques, databases, and data analysis tools are available for natural sample metabolomics. However, choosing the right method can be a daunting exercise because natural samples are heterogeneous and require untargeted approaches. This tutorial review aims to compile the latest technologies to guide an early-career scientist on natural sample metabolomics. First, different extraction methods and their pros and cons are reviewed. Second, currently available metabolomics databases and data analysis tools are summarized. Next, recent research on metabolomics of milk, honey, and microbial samples is reviewed. Finally, after reviewing the latest trends in technologies, a checklist is presented to guide an early-career researcher on how to design a metabolomics project. In conclusion, this review is a comprehensive resource for a researcher planning to conduct their first metabolomics analysis. It is also useful for experienced researchers to update themselves on the latest trends in metabolomics.

The potential role of early life feeding patterns in shaping the infant fecal metabolome: implications for neurodevelopmental outcomes

Infant fecal metabolomics can provide valuable insights into the associations of nutrition, dietary patterns, and health outcomes in early life. Breastmilk is typically classified as the best source of nutrition for nearly all infants. However, exclusive breastfeeding may not always be possible for all infants. This study aimed to characterize associations between levels of mixed breastfeeding and formula feeding, along with solid food consumption and the infant fecal metabolome at 1- and 6-months of age. As a secondary aim, we examined how feeding-associated metabolites may be associated with early life neurodevelopmental outcomes. Fecal samples were collected at 1- and 6-months, and metabolic features were assessed via untargeted liquid chromatography/high-resolution mass spectrometry. Feeding groups were defined at 1-month as 1) exclusively breastfed, 2) breastfed >50% of feedings, or 3) formula fed ≥50% of feedings. Six-month groups were defined as majority breastmilk (>50%) or majority formula fed (≥50%) complemented by solid foods. Neurodevelopmental outcomes were assessed using the Bayley Scales of Infant Development at 2 years. Changes in the infant fecal metabolome were associated with feeding patterns at 1- and 6-months. Feeding patterns were associated with the intensities of a total of 57 fecal metabolites at 1-month and 25 metabolites at 6-months, which were either associated with increased breastmilk or increased formula feeding. Most breastmilk-associated metabolites, which are involved in lipid metabolism and cellular processes like cell signaling, were associated with higher neurodevelopmental scores, while formula-associated metabolites were associated with lower neurodevelopmental scores. These findings offer preliminary evidence that feeding patterns are associated with altered infant fecal metabolomes, which may be associated with cognitive development later in life.

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

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

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Serum and follicular fluid metabolome and markers of ovarian stimulation

STUDY QUESTION

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

SUMMARY ANSWER

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

WHAT IS KNOWN ALREADY

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

STUDY DESIGN, SIZE, DURATION

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

PARTICIPANTS/MATERIALS, SETTING, METHODS

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

MAIN RESULTS AND ROLE OF CHANCE

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

LIMITATIONS, REASONS FOR CAUTION

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

WIDER IMPLICATIONS OF THE FINDINGS

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

STUDY FUNDING/COMPETING INTEREST(S)

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

TRIAL REGISTRATION NUMBER

N/A.

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

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

Metabolite Stability in Archived Neonatal Dried Blood Spots Used for Epidemiologic Research

Epidemiologic studies of low-frequency exposures or outcomes using metabolomics analyses of neonatal dried blood spots (DBS) often require assembly of samples with substantial differences in duration of storage. Independent assessment of stability of metabolites in archived DBS will enable improved design and interpretation of epidemiologic research utilizing DBS. Neonatal DBS routinely collected and stored as part of the California Genetic Disease Screening Program between 1983 and 2011 were used. The study population included 899 children without cancer before age 6 years, born in California. High-resolution metabolomics with liquid-chromatography mass spectrometry was performed, and the relative ion intensities of common metabolites and selected xenobiotic metabolites of nicotine (cotinine and hydroxycotinine) were evaluated. In total, we detected 26,235 mass spectral features across 2 separate chromatography methods (C18 hydrophobic reversed-phase chromatography and hydrophilic-interaction liquid chromatography). For most of the 39 metabolites related to nutrition and health status, we found no statistically significant annual trends across the years of storage. Nicotine metabolites were captured in the DBS with relatively stable intensities. This study supports the usefulness of DBS stored long-term for epidemiologic studies of the metabolome. -Omics-based information gained from DBS may also provide a valuable tool for assessing prenatal environmental exposures in child health research.

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

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

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

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Exposome epidemiology for suspect environmental chemical exposures during pregnancy linked to subsequent breast cancer diagnosis

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry of pregnancy cohort biospecimens in the Child Health and Development Studies to test for associations with breast cancer identified via the California Cancer Registry. Second and third trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both second and third trimesters to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol, linked to variations in amino acid and nucleotide pathways in second trimester and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in third trimester. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

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

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

Exposome Epidemiology for Suspect Environmental Chemical Exposures during Pregnancy Linked to Subsequent Breast Cancer Diagnosis

Breast cancer is now the most common cancer globally, accounting for 12% of all new annual cancer cases worldwide. Despite epidemiologic studies having established a number of risk factors, knowledge of chemical exposure risks is limited to a relatively small number of chemicals. In this exposome research study, we used non-targeted, high-resolution mass spectrometry (HRMS) of pregnancy cohort biospecimens in the Child Health and Development Studies (CHDS) to test for associations with breast cancer identified via the California Cancer Registry. Second (T2) and third (T3) trimester archival samples were analyzed from 182 women who subsequently developed breast cancer and 384 randomly selected women who did not develop breast cancer. Environmental chemicals were annotated with the Toxin and Toxin-Target Database (T3DB) for chemical signals that were higher in breast cancer cases and used with an exposome epidemiology analytic framework to identify suspect chemicals and associated metabolic networks. Network and pathway enrichment analyses showed consistent linkage in both T2 and T3 to inflammation pathways, including linoleate, arachidonic acid and prostaglandins, and identified new suspect environmental chemicals associated with breast cancer, i.e., an N-substituted piperidine insecticide and a common commercial product, 2,4-dinitrophenol (DNP), linked to variations in amino acid and nucleotide pathways in T2 and benzo[a]carbazole and a benzoate derivative linked to glycan and amino sugar metabolism in T3. The results identify new suspect environmental chemical risk factors for breast cancer and provide an exposome epidemiology framework for discovery of suspect environmental chemicals and potential mechanistic associations with breast cancer.

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

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

Metabolic Modeling of Hermetia illucens Larvae Resource Allocation for High-Value Fatty Acid Production

All plant and animal kingdom organisms use highly connected biochemical networks to facilitate sustaining, proliferation, and growth functions. While the biochemical network details are well known, the understanding of the intense regulation principles is still limited. We chose to investigate the Hermetia illucens fly at the larval stage because this stage is a crucial period for the successful accumulation and allocation of resources for the subsequent organism's developmental stages. We combined iterative wet lab experiments and innovative metabolic modeling design approaches to simulate and explain the H. illucens larval stage resource allocation processes and biotechnology potential. We performed time-based growth and high-value chemical compound accumulation wet lab chemical analysis experiments on larvae and the Gainesville diet composition. We built and validated the first H. illucens medium-size, stoichiometric metabolic model to predict the effects of diet-based alterations on fatty acid allocation potential. Using optimization methods such as flux balance and flux variability analysis on the novel insect metabolic model, we predicted that doubled essential amino acid consumption increased the growth rate by 32%, but pure glucose consumption had no positive impact on growth. In the case of doubled pure valine consumption, the model predicted a 2% higher growth rate. In this study, we describe a new framework for researching the impact of dietary alterations on the metabolism of multi-cellular organisms at different developmental stages for improved, sustainable, and directed high-value chemicals.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Longitudinal profiles of the fecal metabolome during the first 2 years of life

During the first 2 years of life, the infant gut microbiome is rapidly developing, and gut bacteria may impact host health through the production of metabolites that can have systemic effects. Thus, the fecal metabolome represents a functional readout of gut bacteria. Despite the important role that fecal metabolites may play in infant health, the development of the infant fecal metabolome has not yet been thoroughly characterized using frequent, repeated sampling during the first 2 years of life. Here, we described the development of the fecal metabolome in a cohort of 101 Latino infants with data collected at 1-, 6-, 12-, 18-, and 24-months of age. We showed that the fecal metabolome is highly conserved across time and highly personalized, with metabolic profiles being largely driven by intra-individual variability. Finally, we also identified several novel metabolites and metabolic pathways that changed significantly with infant age, such as valerobetaine and amino acid metabolism, among others.

Dose-response mapping of MEHP exposure with metabolic changes of trophoblast cell and determination of sensitive markers

Mono(2-ethylhexyl) phthalate (MEHP) is a metabolite of DEHP which is one of phthalic acid esters (PAEs) widely used in daily necessities. Moreover, MEHP has been proven to have stronger biological toxicity comparing to DEHP. In particular, several recent population-based studies have reported that intrauterine exposure to MEHP results in adverse pregnancy outcomes. To explore the mechanisms and metabolic biomarkers of MEHP exposure, we examined the metabolic status of HTR-8/Svneo cell lines exposed to different doses of MEHP (0, 1.25, 5.0, 20 μM). Global and dose-response metabolomics tools were used to identify metabolic perturbations and sensitive markers associated with MEHP. Only 22 metabolic features (accounted for <1 %) were significantly changed when exposed to 1.25 μM. However, when the exposure dose was increased to 5 or 20 μM, the number of significantly changed metabolic features exceeded 300 (approximately 10 %). In particular, amino acid metabolism, pyrimidine metabolism and glutathione metabolism were widely affected according to the enrich analysis of those significant altered metabolites, which has and have previously been reported to be closely related to fetal development. Moreover, 5'-UMP and N-acetylputrescine with the lowest effective concentrations (EC_-10 = 0.1 μM and EC₊₁₀ = 0.11 μM, respectively) were identified as sensitive endogenous biomarkers of MEHP exposure.

Linking Air Pollution Exposure to Blood-Based Metabolic Features in a Community-Based Aging Cohort with and without Dementia

BACKGROUND

Long-term exposure to air pollution has been associated with changes in levels of metabolites measured in the peripheral blood. However, most research has been conducted in ethnically homogenous, young or middle-aged populations.

OBJECTIVE

To study the relationship between the plasma metabolome and long-term exposure to three air pollutants: particulate matter (PM) less than 2.5μm in aerodynamic diameter (PM2.5), PM less than 10μm in aerodynamic diameter (PM10), and nitrogen dioxide (NO2) in an ethnically diverse, older population.

METHODS

Plasma metabolomic profiles of 107 participants of the Washington Heights and Inwood Community Aging Project in New York City, collected from 1995-2015, including non-Hispanic white, Caribbean Hispanic, and non-Hispanic Black older adults were used. We estimated the association between each metabolic feature and predicted annual mean exposure to the air pollutants using three approaches: 1) A metabolome wide association study framework; 2) Feature selection using elastic net regression; and 3) A multivariate approach using partial-least squares discriminant analysis.

RESULTS

79 features associated with exposure to PM2.5 but none associated with PM10 or NO2. PM2.5 exposure was associated with altered amino acid metabolism, energy production, and oxidative stress response, pathways also associated with Alzheimer's disease. Three metabolites were associated with PM2.5 exposure through all three approaches: cysteinylglycine disulfide, a diglyceride, and a dicarboxylic acid. The relationship between several features and PM2.5 exposure was modified by diet and metabolic diseases.

CONCLUSIONS

These relationships uncover the mechanisms through which PM2.5 exposure can lead to altered metabolic outcomes in an older population.

Outdoor particulate matter exposure affects metabolome in chronic obstructive pulmonary disease: Preliminary study

Introduction

The metabolomic changes caused by airborne fine particulate matter (PM_2.5) exposure in patients with chronic obstructive pulmonary disease (COPD) remain unclear. The aim of this study was to determine whether it is possible to predict PM_2.5-induced acute exacerbation of COPD (AECOPD) using metabolic markers.

Methods

Thirty-eight patients with COPD diagnosed by the 2018 Global Initiative for Obstructive Lung Disease were selected and divided into high exposure and low exposure groups. Questionnaire data, clinical data, and peripheral blood data were collected from the patients. Targeted metabolomics using liquid chromatography-tandem mass spectrometry was performed on the plasma samples to investigate the metabolic differences between the two groups and its correlation with the risk of acute exacerbation.

Results

Metabolomic analysis identified 311 metabolites in the plasma of patients with COPD, among which 21 metabolites showed significant changes between the two groups, involving seven pathways, including glycerophospholipid, alanine, aspartate, and glutamate metabolism. Among the 21 metabolites, arginine and glycochenodeoxycholic acid were positively associated with AECOPD during the three months of follow-up, with an area under the curve of 72.50% and 67.14%, respectively.

Discussion

PM_2.5 exposure can lead to changes in multiple metabolic pathways that contribute to the development of AECOPD, and arginine is a bridge between PM_2.5 exposure and AECOPD.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

INTRODUCTION

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

METHODS

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

RESULTS

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

DISCUSSION

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

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND AND AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Characterizing the follicular fluid metabolome: quantifying the correlation across follicles and differences with the serum metabolome

OBJECTIVE

To compare the variability in metabolomes between the serum and follicular fluid, as well as across 3 dominant follicles.

DESIGN

Prospective cohort study.

SETTING

An academic fertility clinic in the northeastern United States, 2005-2015.

PATIENTS

One hundred thirty-five women undergoing in vitro fertilization treatment who provided a serum sample during ovarian stimulation and up to 3 follicular fluid samples during oocyte retrieval.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Samples were analyzed using liquid chromatography with high-resolution mass spectrometry and 2 chromatography columns (C18 hydrophobic negative and hydrophilic interaction chromatography [HILIC] positive). We calculated overall, feature-specific, and subject-specific correlation coefficients to describe how strongly the intensity of overlapping metabolic features were associated between the serum and follicular fluid and between the 1st-2nd, 1st-3rd, and 2nd-3rd follicles. Feature-specific correlations were adjusted for age, body mass index, infertility diagnosis, ovarian stimulation protocol, and year.

RESULT(S)

From the C18-negative column and the high-resolution mass spectrometry, 7,830 serum features and 10,790 follicular fluid features were detected in ≥20% of samples. After screening retention times and checking for 1:1 matching, 1,928 features overlapped between the 2 metabolomes. From the HILIC-positive column and the high-resolution mass spectrometry, after applying the same exclusion criteria, there were 9,074 serum features, 5,542 follicular fluid features, and 1,149 features that overlapped. When comparing the feature intensity of overlapping metabolites in the serum and the follicular fluid, the overall (C18, 0.45; HILIC, 0.63), median feature-specific (C18, 0.35; HILIC, 0.37), and median subject-specific (C18, 0.42; HILIC, 0.59) correlations were low to moderate. In contrast, among the overlapping features across all 3 follicles, the overall (C18, all 0.99; HILIC, all 0.99), median feature-specific (C18, 0.74-0.81; HILIC, 0.79-0.85), and median subject-specific (C18, 0.88-0.89; HILIC, 0.90-0.91) correlations between follicular fluid metabolomics features within a woman were high.

CONCLUSION(S)

We observed minimal overlap and weak-to-moderate correlation between metabolomic features in the serum and follicular fluid but a large overlap and strong correlation between metabolomic features across follicles within a woman. The follicular fluid appears to represent a novel matrix, distinct from serum, which may be a rich source of biologic predictors of female fertility and reproductive outcomes.

Long-term exposure to air pollution might decrease bone mineral density T-score and increase the prevalence of osteoporosis in Hubei province: evidence from China Osteoporosis Prevalence Study

We hypothesized that air pollution could cause oxidative damage and inflammation in the human body, which was linked to bone loss. Our result showed that long-term exposure to air pollution might decrease bone mineral density (BMD) T-score and increase the prevalence of osteoporosis in Hubei province.

INTRODUCTION

Osteoporosis is becoming an increasingly serious public health problem with the advent of global aging. Long-term exposure to air pollution has been linked to multitudinous adverse health outcomes, but evidence is still relatively limited and inconsistent for BMD T-score and osteoporosis. This study aimed at exploring the associations between long-term exposure to air pollution and BMD T-score and osteoporosis.

METHODS

The Hubei part of the China Osteoporosis Prevalence Study was extracted. Data on air pollutants were collected by the national air quality real-time release platform of China Environmental Monitoring Station. Linear mixed models and multilevel logistic regression analyses were performed to assess the associations between air pollution and BMD T-score and osteoporosis, respectively. Subgroup analyses were conducted to identify vulnerable populations.

RESULTS

A total of 1845 participants were included in this cross-section study. Per 10 ug/m³ increase in PM_2.5 and SO₂ were associated with 0.20 (95% CI: 0.04, 0.36) and 0.31 (95% CI: 0.11, 0.51) decrease in BMD T-score of the neck of femur, respectively. Per 10 ug/m³ increase in CO was linked with 0.03 (95% CI: 0.02, 0.05) decrease in BMD T-score of the total hip. Per 1 ug/m³ increase in PM_2.5 was associated with 5% increase in the prevalence of osteoporosis in all participants. In general, the higher concentrations of PM_2.5 with the more adverse effect on osteoporosis (P for trend = 0.01). The impact of PM_2.5 on osteoporosis in males was higher than that in females [1.29, 95% CI (1.11, 1.50) vs 1.01, 95% CI (0.95, 1.07)]. Per 1 ug/m³ increase in PM₁₀ corresponded with 4% elevation in the risks of osteoporosis in rural population. The ORs (95% CI) for the association of osteoporosis and NO₂ in ever/current smoking and drinking population were 1.07 (1.01, 1.13) and 1.05 (1.00, 1.09), respectively. SO₂ had a statistically significant positive effect on people with comorbidity [OR = 1.10, (95% CI: 1.00 to 1.21)], while none in people without comorbidity [OR = 0.96, (95% CI: 0.88 to 1.05)].

CONCLUSION

Our study provided evidence that long-term exposure to PM_2.5 was linked with the decreased BMD T-score and increased risk of osteoporosis among all participants. The adverse impacts of PM_2.5, PM₁₀, and NO₂ were larger in males than in females. People having comorbidity, living in rural areas, and current/ever smoking or drinking were more vulnerable to air pollution. Public health departments should consider air pollution to formulate better preventive measures for osteoporosis.

Mechanistic insights into the health benefits of fish-oil supplementation against fine particulate matter air pollution: a randomized controlled trial

BACKGROUND

Dietary fish-oil supplementation might attenuate the associations between fine particulate matter (PM_2.5) and subclinical biomarkers. However, the molecular mechanisms remain to be elucidated. This study aimed to explore the molecular mechanisms of fish-oil supplementation against the PM_2.5-induced health effects.

METHODS

We conducted a randomized, double-blinded, and placebo-controlled trial among healthy college students in Shanghai, China, from September 2017 to January 2018. A total of 70 participants from the Fenglin campus of Fudan University were included. We randomly assigned participants to either supplementation of 2.5-gram fish oil (n = 35) or sunflower-seed oil (placebo) (n = 35) per day and conducted four rounds of health measurements in the last two months of the trial. As a post hoc exploratory study, the present untargeted metabolomics analysis used remaining blood samples collected in the previous trial and applied a Metabolome-Wide Association Study framework to compare the effects of PM_2.5 on the metabolic profile between the sunflower-seed oil and fish oil groups.

RESULTS

A total of 65 participants completed the trial (34 of the fish oil group and 31 of the sunflower-seed oil group). On average, ambient PM_2.5 concentration on the day of health measurements was 34.9 µg/m³ in the sunflower-seed oil group and 34.5 µg/m³ in the fish oil group, respectively. A total of 3833 metabolites were significantly associated with PM_2.5 in the sunflower-seed oil group and 1757 in the fish oil group. Of these, 1752 metabolites showed significant between-group differences. The identified differential metabolites included arachidonic acid derivatives, omega-3 fatty acids, omega-6 fatty acids, and omega-9 fatty acids that were related to unsaturated fatty acid metabolism, which plays a role in the inflammatory responses.

CONCLUSION

This trial suggests fish-oil supplementation could mitigate the PM_2.5-induced inflammatory responses via modulating fatty acid metabolism, providing biological plausibility for the health benefits of fish-oil supplementation against PM_2.5 exposure.

TRIAL REGISTRATION

This study is registered at ClinicalTrails.gov (NCT03255187).

Living near greenness is associated with higher bone strength: A large cross-sectional epidemiological study in China

BACKGROUND

Living near green spaces may benefit various health outcomes. However, no studies have investigated the greenness-bone linkage in the general population. Moreover, to which extent ambient air pollution (AAP), physical activity (PA), and body mass index (BMI) mediate this relationship remains unclear. We aimed to explore the association between greenness and bone strength and the potential mediating roles of AAP, PA, and BMI in Chinese adults.

METHODS

This cross-sectional analysis enrolled 66,053 adults from the China Multi-Ethnic Cohort in 2018-2019. The normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were employed to define residential greenness. The calcaneus quantitative ultrasound index (QUI) was used to indicate bone strength. Multiple linear regression models and mediation analyses were used to estimate the residential greenness-bone strength association and potential pathways operating through AAP (represented by PM_2.5 [particulate matter <2.5 μm in diameter]), PA, and BMI. Stratification analyses were performed to identify susceptible populations.

RESULTS

Higher residential exposure to greenness was significantly associated with an increase in QUI, with changes (95% confidence interval) of 3.28 (3.05, 3.50), 3.57 (3.34, 3.80), 2.68 (2.46, 2.90), and 2.93 (2.71, 3.15) for every interquartile range increase in NDVI_500m, NDVI_1000m, EVI_500m, and EVI_1000m, respectively. Sex, urbanicity, annual family income, smoking, and drinking significantly modified the association of greenness-bone strength, with more remarkable associations in males, urban residents, subjects from wealthier families, smokers, and drinkers. For the NDVI_500m/EVI_500m-QUI relationship, the positive mediating roles of PM_2.5 and PA were 6.70%/8.50 and 2.43%/2.69%, respectively, whereas those negative for BMI and PA-BMI were 0.88%/1.06% and 0.05%/0.05%, respectively.

CONCLUSION

Living in a greener area may predict higher bone strength, particularly among males, urban residents, wealthier people, smokers, and drinkers. AAP, PA, BMI, and other factors may partially mediate the positive association. Our findings underscore the importance of optimizing greenness planning and management policies.

Association of nanoparticle exposure with serum metabolic disorders of healthy adults in printing centers

Printers are everyday devices in both our homes and workplaces. We have previously found high occupational exposure levels to toner-based printer emitted nanoparticles (PEPs) at printing centers. To elucidate the potential health effects from exposure to PEPs, a total of 124 human serum samples were collected from 32 workers in the printing centers during the repeated follow-up measurements, and global serum metabolomics were analyzed in three ways: correlation between metabolic response and personal exposure (dose response exposure); metabolite response changes between Monday and Friday of a work week (short-term exposure), and metabolite response in relation to length of service in a center (long-term exposure). A total of 52 key metabolites changed significantly in relation to nanoparticle exposure levels. The primary dysregulated pathways included inflammation and immunity related arginine and tryptophan metabolism. Besides, some distinct metabolite expression patterns were found to occur during the transition from short-term to long-term exposures, suggesting cumulative effect of PEPs exposure. These findings, for the first time, highlight the inhalation exposure responses to printer emitted nanoparticles at the metabolite level, potentially serving as pre-requisites for whole organism and population responses, and are inline with emerging findings on potential health effects.

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

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

Association between traffic-related air pollution and anxiety hospitalizations in a coastal Chinese city: are there potentially susceptible groups?

Motor vehicle exhaust emissions have become the main source of urban air pollution in China, but few studies have explored the association of short-term exposure to traffic-related air pollutants (TRAPs) with anxiety disorders. Thus, we used an overdispersed, generalized additive model (GAM) to investigate the association between TRAPs and hospital admissions (HAs) for anxiety in Qingdao, a coastal Chinese city with high vehicle ownership. In addition, stratified analyses were performed by gender, age, season and hospitalization frequency (first admission and readmission). A positive association between TRAPs and HAs for anxiety was observed. Both inhalable particulate matter (PM₁₀) and nitrogen dioxide (NO₂) showed significant effects at lag 3 in the single-day lag structure, and each 10 μg/m³ increase in the concentrations was significantly associated with increases of 0.88% [95% confidence interval (CI): 0.04%, 1.72%] for PM₁₀ and 2.74% (0.45%, 5.08%) for NO₂ on anxiety hospitalizations. For fine particulate matter (PM_2.5) and carbon monoxide (CO), the strongest effects were found at lag05 and lag04 [2.67% (0.77%, 4.62%) and 0.19% (0.04%, 0.34%), respectively] in the multiday lag structure. The estimates of PM_2.5 were relatively robust after adjusting for other pollutants in the two-pollutant model. Stratified analyses indicated that the associations were stronger in females and younger individuals (<45 in age) than in males and elderly individuals (≥45 in age). Furthermore, the effects of PM_2.5 and CO were most obvious during the cold season. Regarding hospitalization frequency, only PM_2.5 was found to have a significant effect in the first-admission group. The results showed that short-term exposure to TRAPs, especially to PM_2.5, was significantly associated with the increased risk of daily HAs for anxiety, which can help clinicians and policymakers better understand the effects of TRAPs to implement targeted interventions.

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

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.