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

Glycerophospholipid metabolism changes association with ozone exposure

Exposure to ozone (O3) has been associated with cardiovascular outcomes in humans, yet the underlying mechanisms of the adverse effect remain poorly understood. We aimed to investigate the association between O3 exposure and glycerophospholipid metabolism in healthy young adults. We quantified plasma concentrations of phosphatidylcholines (PCs) and lysophosphatidylcholines (lysoPCs) using a UPLC-MS/MS system. Time-weighted personal exposures were calculated to O3 and co-pollutants over 4 time windows, and we employed orthogonal partial least squares discriminant analysis to discern differences in lipids profiles between high and low O3 exposure. Linear mixed-effects models and mediation analysis were utilized to estimate the associations between O3 exposure, lipids, and cardiovascular physiology indicators. Forty-three healthy adults were included in this study, and the mean (SD) time-weighted personal exposures to O3 was 9.08 (4.06) ppb. With shorter exposure durations, O3 increases were associated with increasing PC and lysoPC levels; whereas at longer exposure times, the opposite relationship was shown. Furthermore, two specific lipids, namely lysoPC a C26:0 and lysoPC a C17:0, showed significantly positive mediating effects on associations of long-term O3 exposure with pulse wave velocity and systolic blood pressure, respectively. Alterations in specific lipids may underlie the cardiovascular effects of O3 exposure.

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

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

Higher ambient temperatures may worsen obstructive sleep apnea: A nationwide smartwatch-based analysis of 6.2 million person-days

Obstructive sleep apnea (OSA) is a serious type of sleep disorder that can lead to cardiometabolic and neurocognitive diseases. We utilized smart device-based photoplethysmography technology to collect sleep data from the Chinese population from 2019 to 2022. Distributed lag nonlinear models combined with a generalized nonlinear model or a linear mixed effects model were used to investigate the short-term associations between daily temperature and indicators of OSA severity. We included a total of 6,232,056 d of sleep monitoring data from 51,842 participants with moderate to severe risk of OSA from 313 Chinese cities. The relationships between ambient temperature and OSA exacerbation, apnea-hypopnea index (AHI), and minimum oxygen saturation (MinSpO2) were almost linear and present only on the same day. Higher temperatures were associated with a greater risk of OSA exacerbation, with an 8.4% (95% confidence interval (CI): 7.6%-9.3%) increase per 10 °C increase in temperature. A 10 °C increase in daily temperature corresponded to an AHI increase of 0.70 events/h (95% CI: 0.65-0.76) and a MinSpO2 decrease of 0.18% (95% CI: 0.16%-0.19%). Exposure to elevated temperatures during the night can also lead to adverse effects. The effects of higher temperatures on OSA severity were stronger among men, participants with a body mass index ≥ 24 kg/m2, those aged 45 years and older, individuals with a history of hypertension and diabetes, and during the cold season. This large-scale, nationwide, longitudinal study provides robust evidence suggesting that higher ambient temperatures may immediately worsen OSA.

Urine metabolomics signature reveals novel determinants of adrenal suppression in children taking inhaled corticosteroids to control asthma symptoms

BACKGROUND

Asthma is routinely treated with inhaled corticosteroids (ICS). Asthma patients on ICS are at increased risk of adrenal suppression, a potentially serious effect of long-term glucocorticoid exposure; however, this relationship is poorly understood. Therefore, this study aims to identify metabolite biomarkers related to adrenal suppression in asthma patients taking ICS.

METHODS

A total of 571 urine metabolites from 200 children with asthma on ICS in the Pharmacogenetics of Adrenal Suppression with Inhaled Steroids (PASS) cohort were profiled. Samples were grouped by peak plasma cortisol measurement as adrenal sufficient (>350 nmol/L) or insufficient (≤350 nmol/L) (outcome). Regression and discriminant-based statistical models combined with network analyses were utilized to assess relationships between metabolites and the outcome. Finally, prioritized metabolites were validated using data from an ancillary study of the Childhood Asthma Management (CAMP) cohort with similar characteristics to PASS.

RESULTS

Ninety metabolites were significantly associated with adrenal suppression, of which 57 also could discriminate adrenal status. While 26 metabolites (primarily steroids) were present at lower levels in the adrenal insufficient patients, 14 were significantly elevated in this group; the top metabolite, mannitol/sorbitol, was previously associated with asthma exacerbations. Network analyses identified unique clusters of metabolites related to steroids, fatty acid oxidation, and nucleoside metabolism, respectively. Four metabolites including urocanic acid, acetylcarnitine, uracil, and sorbitol were validated in CAMP cohort for adrenal suppression.

CONCLUSIONS

Urinary metabolites differ among asthma patients on ICS, by adrenal status. While steroid metabolites were reduced in patients with poor adrenal function, our findings also implicate previously unreported metabolites involved in amino acid, lipid, and nucleoside metabolism.

Associations between plasma metabolites and heavy metal exposure in residents of environmentally polluted areas

Heavy metals are commonly released into the environment through industrial processes such as mining and refining. The rapid industrialization that occurred in South Korea during the 1960s and 1970s contributed significantly to the economy of the country; however, the associated mining and refining led to considerable environmental pollution, and although mining is now in decline in South Korea, the detrimental effects on residents inhabiting the surrounding areas remain. The bioaccumulation of toxic heavy metals leads to metabolic alterations in human homeostasis, with disruptions in this balance leading to various health issues. This study used metabolomics to explore metabolomic alterations in the plasma samples of residents living in mining and refining areas. The results showed significant increases in metabolites involved in glycolysis and the surrounding metabolic pathways, such as glucose-6-phosphate, phosphoenolpyruvate, lactate, and inosine monophosphate, in those inhabiting polluted areas. An investigation of the associations between metabolites and blood clinical parameters through meet-in-the-middle analysis indicated that female residents were more affected by heavy metal exposure, resulting in more metabolomic alterations. For women, inhabiting the abandoned mine area, metabolites in the glycolysis and pentose phosphate pathways, such as ribose-5-phosphate and 3-phosphoglycerate, have shown a negative correlation with albumin and calcium. Finally, Mendelian randomization(MR) was used to determine the causal effects of these heavy metal exposure-related metabolites on heavy metal exposure-related clinical parameters. Metabolite biomarkers could provide insights into altered metabolic pathways related to exposure to toxic heavy metals and improve our understanding of the molecular mechanisms underlying the health effects of toxic heavy metal exposure.

Exposure to ambient temperature and heat index in relation to DNA methylation age: A population-based study in Taiwan

BACKGROUND

Climate change caused an increase in ambient temperature in the past decades. Exposure to high ambient temperature could result in biological aging, but relevant studies in a warm environment were lacking. We aimed to study the exposure effects of ambient temperature and heat index (HI) in relation to age acceleration in Taiwan, a subtropical island in Asia.

METHODS

The study included 2,084 participants from Taiwan Biobank. Daily temperature and relative humidity data were collected from weather monitoring stations. Individual residential exposure was estimated by ordinary kriging. Moving averages of ambient temperature and HI from 1 to 180 days prior to enrollment were calculated to estimate the exposure effects in multiple time periods. Age acceleration was defined as the difference between DNA methylation age and chronological age. DNA methylation age was calculated by the Horvath's, Hannum's, Weidner's, ELOVL2, FHL2, phenotypic (Pheno), Skin & blood, and GrimAge2 (Grim2) DNA methylation age algorithms. Multivariable linear regression models, generalized additive models (GAMs), and distributed lag non-linear models (DLNMs) were conducted to estimate the effects of ambient temperature and HI exposures in relation to age acceleration.

RESULTS

Exposure to high ambient temperature and HI were associated with increased age acceleration, and the associations were stronger in prolonged exposure. The heat stress days with maximum HI in caution (80-90°F), extreme caution (90-103°F), danger (103-124°F), and extreme danger (>124°F) were also associated with increased age acceleration, especially in the extreme danger days. Each extreme danger day was associated with 571.38 (95 % CI: 42.63-1100.13), 528.02 (95 % CI: 36.16-1019.87), 43.9 (95 % CI: 0.28-87.52), 16.82 (95 % CI: 2.36-31.28) and 15.52 (95 % CI: 2.17-28.88) days increase in the Horvath's, Hannum's, Weidner's, Pheno, and Skin & blood age acceleration, respectively.

CONCLUSION

High ambient temperature and HI may accelerate biological aging.

Concentration-dependent alterations in the human plasma proteome following controlled exposure to diesel exhaust

Traffic-related air pollution (TRAP) exposure is associated with systemic health effects, which can be studied using blood-based markers. Although we have previously shown that high TRAP concentrations alter the plasma proteome, the concentration-response relationship between blood proteins and TRAP is unexplored in controlled human exposure studies. We aimed to identify concentration-dependent plasma markers of diesel exhaust (DE), a model of TRAP. Fifteen healthy non-smokers were enrolled into a double-blinded, crossover study where they were exposed to filtered air (FA) and DE at 20, 50 and 150 μg/m3 PM2.5 for 4h, separated by ≥ 4-week washouts. We collected blood at 24h post-exposure and used label-free mass spectrometry to quantify proteins in plasma. Proteins exhibiting a concentration-response, as determined by linear mixed effects models (LMEMs), were assessed for pathway enrichment using WebGestalt. Top candidates, identified by sparse partial least squares discriminant analysis and LMEMs, were confirmed using enzyme-linked immunoassays. Thereafter, we assessed correlations between proteins that showed a DE concentration-response and acute inflammatory endpoints, forced expiratory volume in 1 s (FEV1) and methacholine provocation concentration causing a 20% drop in FEV1 (PC20). DE exposure was associated with concentration-dependent alterations in 45 proteins, which were enriched in complement pathways. Of the 9 proteins selected for confirmatory immunoassays, based on complementary bioinformatic approaches to narrow targets and availability of high-quality assays, complement factor I (CFI) exhibited a significant concentration-dependent decrease (-0.02 μg/mL per μg/m3 of PM2.5, p = 0.04). Comparing to FA at discrete concentrations, CFI trended downward at 50 (-2.14 ± 1.18, p = 0.08) and significantly decreased at 150 μg/m3 PM2.5 (-2.93 ± 1.18, p = 0.02). CFI levels were correlated with FEV1, PC20 and nasal interleukin (IL)-6 and IL-1β. This study details concentration-dependent alterations in the plasma proteome following DE exposure at concentrations relevant to occupational and community settings. CFI shows a robust concentration-response and association with established measures of airway function and inflammation.

Metabolites and Cognitive Decline in a Puerto Rican Cohort

Background

Recent studies have identified plasma metabolites associated with cognitive decline and Alzheimer's disease; however, little research on this topic has been conducted in Latinos, especially Puerto Ricans.

Objective

This study aims to add to the growing body of metabolomics research in Latinos to better understand and improve the health of this population.

Methods

We assessed the association between plasma metabolites and global cognition over 12 years of follow-up in 736 participants of the Boston Puerto Rican Health Study (BPRHS). Metabolites were measured with untargeted metabolomic profiling (Metabolon, Inc) at baseline. We used covariable adjusted linear mixed models (LMM) with a metabolite * time interaction term to identify metabolites (of 621 measured) associated with ∼12 years cognitive trajectory.

Results

We observed strong inverse associations between medium-chain fatty acids, caproic acid, and the dicarboxylic acids, azelaic and sebacic acid, and global cognition. N-formylphenylalanine, a tyrosine pathway metabolite, was associated with improvement in cognitive trajectory.

Conclusions

The metabolites identified in this study are generally consistent with prior literature and highlight a role medium chain fatty acid and tyrosine metabolism in cognitive decline.

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.

High temperature exacerbates ozone-induced airway inflammation: Implication of airway microbiota and metabolites

Short-term exposure to ozone (O3) has been associated with airway inflammation. Given that high temperature (HT) accelerates O3 production, it is of significance to determine whether co-exposure to HT exacerbates O3-induced airway inflammation. The aim of this study was to examine the possible promotive effect of HT on O3-induced airway inflammation and underlying mechanisms. Forty-eight C57BL/6 N male mice were randomly divided into four groups: filtered air (control), O3, HT, and HT + O3 (co-exposure) groups. Mice in control and O3 groups were exposed to filtered air or 1 ppm O3 at 24 °C, respectively, while mice in HT and co-exposure groups were exposed to filtered air or 1 ppm O3 at 36 °C, respectively. The exposure scenario for four groups was 4 h/d for 5 consecutive days. Bronchoalveolar lavage fluids (BALF) were collected 24 h after the last exposure and subjected to examinations of oxidative stress and inflammation biomarkers, 16S rRNA sequencing, and metabolic profiling. Lung tissues were processed for H&E histological staining. The results showed that O3 inhalation triggered oxidative stress and inflammation in the airways, which was worsen by co-exposure to HT. Further studies revealed that co-exposure to HT strengthened O3-induced decline in Firmicutes and Allobaculum in airways. Moreover, co-exposure to HT promoted O3-induced airway metabolic disorder. Spearman correlation analysis revealed correlations among microbiota dysbiosis, metabolic disorder, oxidative stress and inflammation induced by co-exposure to HT and O3. Taken together, HT exposure aggravates O3-induced airway oxidative stress and inflammation, possibly through modulation of microbiota and metabolism of the airways.

Metabolomics and mitochondrial dysfunction in cardiometabolic disease

Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.

Exposure to ambient air pollutants is associated with an increased incidence of hyperuricemia: A longitudinal cohort study among Chinese government employees

BACKGROUND

It is widely recognized that ambient air pollution can induce various detrimental health outcomes. However, evidence linking ambient air pollutants and hyperuricemia incidence is scarce.

OBJECTIVES

To assess the association between long-term air pollution exposure and the risk of hyperuricemia.

METHODS

In this study, a total of 5854 government employees without hyperuricemia were recruited and followed up from January 2018 to June 2021 in Hunan Province, China. Hyperuricemia was defined as serum uric acid (SUA) level of >420 μmol/L for men and >360 μmol/L for women or use of SUA-lowering medication or diagnosed as hyperuricemia during follow-up. Data from local air quality monitoring stations were used to calculate individual exposure levels of PM10, PM2.5, SO2 and NO2 by inverse distance weightingn (IDW) method. Cox proportional hazard model was applied to evaluate the causal relationships between air pollutant exposures and the risk of hyperuricemia occurrence after adjustment for potential confounders and meanwhile, restricted cubic spline was used to explore the dose-response relationships.

RESULTS

The results indicated that exposures to PM10 (hazard ratio, HR = 1.042, 95% conficence interal, 95% CI: 1.028, 1.057), PM2.5 (HR = 1.204, 95% CI: 1.141, 1.271) and NO2 (HR = 1.178, 95% CI: 1.125,1.233) were associated with an increased HR of hyperuricemia. In addition, a nonlinear dose-response relationship was found between PM10 exposure level and the HR of hyperuricemia (p for nonlinearity = 0.158) with a potential threshold of 50.11 μg/m3. Subgroup analysis demonstrated that participants usually waking up at night and using natural ventilation were more vulnerable to the exposures of PM10, PM2.5, NO2, and SO2.

CONCLUSION

Long-term exposures to ambient PM10, PM2.5 and NO2 are associated with an increased incidence of hyperuricemia among Chinese government employees.

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.

The Exposome and Cardiovascular Health

The study of the interplay between social factors, environmental hazards, and health has garnered much attention in recent years. The term "exposome" was coined to describe the total impact of environmental exposures on an individual's health and well-being, serving as a complementary concept to the genome. Studies have shown a strong correlation between the exposome and cardiovascular health, with various components of the exposome having been implicated in the development and progression of cardiovascular disease. These components include the natural and built environment, air pollution, diet, physical activity, and psychosocial stress, among others. This review provides an overview of the relationship between the exposome and cardiovascular health, highlighting the epidemiologic and mechanistic evidence of environmental exposures on cardiovascular disease. The interplay between various environmental components is discussed, and potential avenues for mitigation are identified.

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.

A precision environmental health approach to prevention of human disease

Human health is determined by the interaction of our environment with the genome, epigenome, and microbiome, which shape the transcriptomic, proteomic, and metabolomic landscape of cells and tissues. Precision environmental health is an emerging field leveraging environmental and system-level ('omic) data to understand underlying environmental causes of disease, identify biomarkers of exposure and response, and develop new prevention and intervention strategies. In this article we provide real-life illustrations of the utility of precision environmental health approaches, identify current challenges in the field, and outline new opportunities to promote health through a precision environmental health framework.

Effect of short-term air pollution exposure on migraine: A protocol for systematic review and meta-analysis on human observational studies

BACKGROUND

The World Health Organization (WHO) has identified air pollution as one of the greatest environmental risks to public health. High levels of ambient air pollution are known to have adverse health effects, but the relationship between exposure to air pollutants and migraine attack has not been established.

OBJECTIVES

This study aims to systematically review the effects of short-term exposure to fine and coarse particulate matter (PM), ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide on migraine attack.

METHODS

The systematic review and meta-analysis will follow the WHO handbook for guideline development. Our protocol will comply with the guidelines of the Preferred Reporting Items for Systematic Review and meta-Analysis Protocols.

ELIGIBILITY CRITERIA

Original peer-reviewed studies conducted in the general population regardless of age and sex to investigate the association between short-term exposure to ambient air pollutants and migraine will be eligible for inclusion. Only time-series, case-crossover, and panel studies will be included.

INFORMATION SOURCES

We will search the electronic databases MEDLINE, Embase, Web of Science, Global Health, Cumulative Index to Nursing and Allied Health Literature in accordance with the pre-established search strategy. We will also check the reference list of included papers and previous reviews for supplementary search.

DATA SYNTHESIS METHOD

We will perform data extraction in accordance with the predesigned table. Using random-effects meta-analysis, we will present summary statistics (RRs and corresponding 95% CIs) associated with standardized increases in each pollutant level. Heterogeneity between studies will be assessed using 80% prediction intervals (PI). Subgroup analyzes will be performed to explore sources of heterogeneity, if any. The main findings will be presented in summary of finding table, visual display and narrative synthesis. We will review the impact of each air pollutant exposure separately.

EVIDENCE APPRAISAL

We will employ the adaption of Grading of Recommendations, Assessment, Development, and Evaluations tool to assess the confidence in the body of evidence.

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.

Targeting Lung-Gut Axis for Regulating Pollution Particle-Mediated Inflammation and Metabolic Disorders

Cigarette smoking (CS) or ambient particulate matter (PM) exposure is a risk factor for metabolic disorders, such as insulin resistance (IR), increased plasma triglycerides, hyperglycemia, and diabetes mellitus (DM); it can also cause gut microbiota dysbiosis. In smokers with metabolic disorders, CS cessation decreases the risks of serious pulmonary events, inflammation, and metabolic disorder. This review included recent studies examining the mechanisms underlying the effects of CS and PM on gut microbiota dysbiosis and metabolic disorder development; one of the potential mechanisms is the disruption of the lung-gut axis, leading to gut microbiota dysbiosis, intestinal dysfunction, systemic inflammation, and metabolic disease. Short-chain fatty acids (SCFAs) are the primary metabolites of gut bacteria, which are derived from the fermentation of dietary fibers. They activate G-protein-coupled receptor (GPCR) signaling, suppress histone deacetylase (HDAC) activity, and inhibit inflammation, facilitating the maintenance of gut health and biofunction. The aforementioned gut microbiota dysbiosis reduces SCFA levels. Treatment targeting SCFA/GPCR signaling may alleviate air pollution-associated inflammation and metabolic disorders, which involve lung-gut axis disruption.

Correlation Between Air Quality Index and Tear Film Lipid Layer Thickness: Comparison Between Patients with Sjogren's Syndrome and with Meibomian Gland Dysfunction

Purpose: To evaluate the effect of air pollution on the tear film stability by analyzing the correlation between Air Quality Index (AQI) and Lipid Layer thickness (LLT) in Xuzhou.Methods: As a prospective descriptive observational study, 284 patients with meibomian gland dysfunction (MGD), 157 patients with Sjögren's syndrome (SS), and 264 healthy volunteers were included. The tear film lipid layer thickness of the three groups of subjects was measured weekly and compared with the air quality index to analyze the correlation between the two indicators. Logistic regression analysis and linear regression analysis were used to analyze the effect of AQI on the thickness of the tear film lipid layer. The change of LLT with air pollution at different AQI levels was also analyzed.Results: There are obvious seasonal differences in the changes of air pollution index in Xuzhou. Significant differences could be observed in the thickness of the lipid layer of the tear film among the three groups. LLT in the MGD group and SS group decreased with the aggravation of air pollution, while remained unchanged in the control group. There was strong evidence of correlation between LLT of the MGD group (F = 353.494, p < 0.01, adjusted R2 = 0.695) and the SS group (F = 502.404, p < 0.01, adjusted R2 = 0.764) with AQI, while there was minor correlation between LLT with AQI in control group (F = 8.525, p < 0.01, adjusted R2 = 0.046).Conclusions: Air pollution can cause a decrease in the thickness of the tear film lipid layer, thereby affecting tear film stability, leading to the occurrence of dry eye.

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.

DNA Damage as a Mechanistic Link between Air Pollution and Obesity?

It has been shown that the risk of developing obesity, a serious modern health problem, increases with air pollution. However, the molecular links are yet to be fully elucidated. Herein, we propose a hypothesis via which air pollution-induced DNA damage would be the mechanistic link between air pollution and the enhanced risk of obesity and overweight. Indeed, whereas air pollution leads to DNA damage, DNA damage results in inflammation, oxidative stress and metabolic impairments that could be behind energy balance changes contributing to obesity. Such thoughts, worth exploring, seems an important starting point to better understand the impact of air pollution on obesity development independently from the two main energy balance pillars that are diet and physical activity. This could possibly lead to new applications both for therapies as well as for policies and regulations.

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.

Concentration-dependent increase in symptoms due to diesel exhaust in a controlled human exposure study

Background

Traffic-related air pollution (TRAP) exposure causes adverse effects on wellbeing and quality of life, which can be studied non-invasively using self-reported symptoms. However, little is known about the effects of different TRAP concentrations on symptoms following controlled exposures, where acute responses can be studied with limited confounding. We investigated the concentration–response relationship between diesel exhaust (DE) exposure, as a model TRAP, and self-reported symptoms.

Methods

We recruited 17 healthy non-smokers into a double-blind crossover study where they were exposed to filtered air (FA) and DE standardized to 20, 50, 150 µg/m3 PM2.5 for 4 h, with a ≥ 4-week washout between exposures. Immediately before, and at 4 h and 24 h from the beginning of the exposure, we administered visual analog scale (VAS) questionnaires and grouped responses into chest, constitutional, eye, neurological, and nasal categories. Additionally, we assessed how the symptom response was related to exposure perception and airway function.

Results

An increase in DE concentration raised total (β ± standard error = 0.05 ± 0.03, P = 0.04), constitutional (0.01 ± 0.01, P = 0.03) and eye (0.02 ± 0.01, P = 0.05) symptoms at 4 h, modified by perception of temperature, noise, and anxiety. These symptoms were also correlated with airway inflammation. Compared to FA, symptoms were significantly increased at 150 µg/m3 for the total (8.45 ± 3.92, P = 0.04) and eye (3.18 ± 1.55, P = 0.05) categories, with trends towards higher values in the constitutional (1.49 ± 0.86, P = 0.09) and nasal (1.71 ± 0.96, P = 0.08) categories.

Conclusion

DE exposure induced a concentration-dependent increase in symptoms, primarily in the eyes and body, that was modified by environmental perception. These observations emphasize the inflammatory and sensory effects of TRAP, with a potential threshold below 150 µg/m3 PM2.5. We demonstrate VAS questionnaires as a useful tool for health monitoring and provide insight into the TRAP concentration–response at exposure levels relevant to public health policy.

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

BACKGROUND AND AIM

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

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

Distinct brain lipid signatures in response to low-level PM2.5 exposure in a 3xTg-Alzheimer's disease mouse inhalation model

Fine particulate matter (PM_2.5) poses a significant risk to human health. The molecular mechanisms underlying low-level PM_2.5-induced neurotoxicity in the central nervous system remain unclear. In addition, changes in lipids in response to PM_2.5 exposure have not yet been fully elucidated. In this study, 3xTg-Alzheimer's disease (AD) mice experienced continuous whole-body exposure to non-concentrated PM_2.5 for three consecutive months, while control mice inhaled particulate matter-filtered air over the same time span. A liquid chromatography-mass spectrometry-based lipidomic platform was used to determine the distinct lipid profiles of various brain regions. The average PM_2.5 concentration during the exposure was 11.38 μg/m³, which was close to the regulation limits of USA and Taiwan. The partial least squares discriminant analysis model showed distinct lipid profiles in the cortex, hippocampus, and olfactory bulb, but not the cerebellum, of mice in the exposure group. Increased levels of fatty acyls, glycerolipids, and sterol lipids, as well as the decreased levels of glycerophospholipids and sphingolipids in PM_2.5-exposed mouse brains may be responsible for the increased energy demand, membrane conformation, neuronal loss, antioxidation, myelin function, and cellular signaling pathways associated with AD development. Our research suggests that subchronic exposure to low levels of PM_2.5 may cause neurotoxicity by changing the lipid profiles in a susceptible model. Lipidomics is a powerful tool to study the early effects of PM_2.5-induced AD toxicity.

Metabolome and transcriptome analyses of plants grown in naturally attenuated soil after hydrogen fluoride exposure

Accidental chemical leaks and illegal chemical discharges are a global environmental issue. In 2012, a hydrogen fluoride leak in Gumi, South Korea, killed several people and contaminated the environment. This leak also led to a significant decline in crop yield, even after the soil concentration of hydrogen fluoride decreased to below the standard level following natural attenuation. To determine the cause of this decreased plant productivity, we designed direct and indirect exposure tests by evaluating the metabolome, transcriptome, and phenome of the plants. In an indirect exposure test, soil metabolomics revealed downregulation of metabolites in vitamin B6, lipopolysaccharide, osmolyte, and exopolysaccharide metabolism. Next-generation sequencing of the plants showed that ABR1 and DREB1A were overexpressed in response to stress. Plant metabolomics demonstrated upregulation of folate biosynthesis and nicotinate and nicotinamide metabolism associated with detoxification of reactive oxygen species. These results demonstrate impaired metabolism of soil microbes and plants even after natural attenuation of hydrogen fluoride in soil. The novel chemical exposure testing used in this study can be applied to identify hidden damage to organisms after natural attenuation of chemicals in soil, as well as biomarkers for explaining the decline in yield of plants grown in soil near pollutant-emitting industrial facilities.

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.

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

Background:

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

Methods:

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

Results:

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

Conclusions:

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

Operationalizing the Exposome Using Passive Silicone Samplers

The exposome, which is defined as the cumulative effect of environmental exposures and corresponding biological responses, aims to provide a comprehensive measure for evaluating non-genetic causes of disease. Operationalization of the exposome for environmental health and precision medicine has been limited by the lack of a universal approach for characterizing complex exposures, particularly as they vary temporally and geographically. To overcome these challenges, passive sampling devices (PSDs) provide a key measurement strategy for deep exposome phenotyping, which aims to provide comprehensive chemical assessment using untargeted high-resolution mass spectrometry for exposome-wide association studies. To highlight the advantages of silicone PSDs, we review their use in population studies and evaluate the broad range of applications and chemical classes characterized using these samplers. We assess key aspects of incorporating PSDs within observational studies, including the need to preclean samplers prior to use to remove impurities that interfere with compound detection, analytical considerations, and cost. We close with strategies on how to incorporate measures of the external exposome using PSDs, and their advantages for reducing variability in exposure measures and providing a more thorough accounting of the exposome. Continued development and application of silicone PSDs will facilitate greater understanding of how environmental exposures drive disease risk, while providing a feasible strategy for incorporating untargeted, high-resolution characterization of the external exposome in human studies.

Metabolomic differences in lung function metrics: evidence from two cohorts

RATIONALE

The biochemical mechanisms underlying lung function are incompletely understood.

OBJECTIVES

To identify and validate the plasma metabolome of lung function using two independent adult cohorts: discovery-the European Prospective Investigation into Cancer-Norfolk (EPIC-Norfolk, n=10 460) and validation-the VA Normative Aging Study (NAS) metabolomic cohort (n=437).

METHODS

We ran linear regression models for 693 metabolites to identify associations with forced expiratory volume in one second (FEV₁) and the ratio of FEV₁ to forced vital capacity (FEV₁/FVC), in EPIC-Norfolk then validated significant findings in NAS. Significance in EPIC-Norfolk was denoted using an effective number of tests threshold of 95%; a metabolite was considered validated in NAS if the direction of effect was consistent and p<0.05.

MEASUREMENTS AND MAIN RESULTS

Of 156 metabolites that associated with FEV₁ in EPIC-Norfolk after adjustment for age, sex, body mass index, height, smoking and asthma status, 34 (21.8%) validated in NAS, including several metabolites involved in oxidative stress. When restricting the discovery sample to men only, a similar percentage, 18 of 79 significant metabolites (22.8%) were validated. A smaller number of metabolites were validated for FEV₁/FVC, 6 of 65 (9.2%) when including all EPIC-Norfolk as the discovery population, and 2 of 34 (5.9%) when restricting to men. These metabolites were characterised by involvement in respiratory track secretants. Interestingly, no metabolites were validated for both FEV₁ and FEV₁/FVC.

CONCLUSIONS

The validation of metabolites associated with respiratory function can help to better understand mechanisms of lung health and may assist the development of biomarkers.

Assessment of XCMS Optimization Methods with Machine-Learning Performance

The metabolomics field is under rapid development. In particular, biomarker identification and pathway analysis are growing, as untargeted metabolomics is usable for discovery research. Frequently, new processing and statistical strategies are proposed to accommodate the increasing demand for robust and standardized data. One such algorithm is XCMS, which processes raw data into integrated peaks. Multiple studies have tried to assess the effect of optimizing XCMS parameters, but it is challenging to quantify the quality of the XCMS output. In this study, we investigate the effect of two automated optimization tools (Autotuner and isotopologue parameter optimization (IPO)) using the prediction power of machine learning as a proxy for the quality of the data set. We show that optimized parameters outperform default XCMS settings and that manually chosen parameters by liquid chromatography-mass spectrometry (LC-MS) experts remain the best. Finally, the machine-learning approach of quality assessment is proposed for future evaluations of newly developed optimization methods because its performance directly measures the retained signal upon preprocessing.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

Metabolic Phenotypes in Asthmatic Adults: Relationship with Inflammatory and Clinical Phenotypes and Prognostic Implications

Bronchial asthma is a chronic disease that affects individuals of all ages. It has a high prevalence and is associated with high morbidity and considerable levels of mortality. However, asthma is not a single disease, and multiple subtypes or phenotypes (clinical, inflammatory or combinations thereof) can be detected, namely in aggregated clusters. Most studies have characterised asthma phenotypes and clusters of phenotypes using mainly clinical and inflammatory parameters. These studies are important because they may have clinical and prognostic implications and may also help to tailor personalised treatment approaches. In addition, various metabolomics studies have helped to further define the metabolic features of asthma, using electronic noses or targeted and untargeted approaches. Besides discriminating between asthma and a healthy state, metabolomics can detect the metabolic signatures associated with some asthma subtypes, namely eosinophilic and non-eosinophilic phenotypes or the obese asthma phenotype, and this may prove very useful in point-of-care application. Furthermore, metabolomics also discriminates between asthma and other “phenotypes” of chronic obstructive airway diseases, such as chronic obstructive pulmonary disease (COPD) or Asthma–COPD Overlap (ACO). However, there are still various aspects that need to be more thoroughly investigated in the context of asthma phenotypes in adequately designed, homogeneous, multicentre studies, using adequate tools and integrating metabolomics into a multiple-level approach.

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

BACKGROUND

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Emerging role of air pollution and meteorological parameters in COVID-19

Exposure to air pollutants has been associated with respiratory viral infections. Epidemiological studies have shown that air pollution exposure is related to increased cases of SARS-COV-2 infection and COVID-19-associated mortality. In addition, the changes of meteorological parameters have also been implicated in the occurrence and development of COVID-19. However, the molecular mechanisms by which pollutant exposure and changes of meteorological parameters affects COVID-19 remains unknown. This review summarizes the biology of COVID-19 and the route of viral transmission, and elaborates on the relationship between air pollution and climate indicators and COVID-19. Finally, we envisaged the potential roles of air pollution and meteorological parameters in COVID-19.