Impacts of long-term ambient particulate matter and gaseous pollutants on circulating biomarkers of inflammation in male and female health professionals

Exposure to ambient air pollution mixture and senescence-associated secretory phenotype proteins among middle-aged and older women

Our study aimed to investigate the impact of environmental exposures, such as ambient air pollutants, on systemic inflammation and cellular senescence in middle-aged and older women. We utilized epidemiological data linked with exposure data of six air pollutants (particulate matters [PM10, PM2.5], sulphur dioxide [SO2], nitrogen dioxide [NO2], carbon monoxide [CO], and ozone [O3]) and blood samples of 380 peri- and postmenopausal women participants of the Korean Genome and Epidemiology Study. We measured blood high-sensitivity C-reactive protein (hsCRP) and age-related 27 circulatory senescence-associated secretory phenotypes (SASP) produced by senescent cells. We employed single exposure models to explore the general pattern of association between air pollution exposure and proteomic markers. Using quantile g-computation models, we assessed the association of six air pollutant mixtures with hsCRP and SASP proteins. In single-exposure, single-period models, nine out of the 27 SASP proteins including IFN-γ (β = 0.04, 95% CI: 0.01, 0.07 per interquartile range-increase), IL-8 (0.15, 95% CI: 0.09, 0.20), and MIP1α (0.11, 95% CI: 0.04, 0.18) were positively associated with the average level of O3 over one week. Among the age-related SASP proteins, IFN-γ (0.11, 95% CI: 0.03, 0.20) and IL-8 (0.22, 95% CI: 0.05, 0.39) were positively associated with exposure to air pollutant mixture over one week. The MIP1β was higher with an increasing one-month average concentration of the air pollutant mixture (0.11, 95% CI: 0.00, 0.21). The IL-8 showed consistently positive association with the ambient air pollutant mixture for the exposure periods ranging from one week to one year. O3 predominantly showed positive weights in the associations between air pollutant mixtures and IL-8. These findings underscore the potential of proteomic indicators as markers for biological aging attributed to short-term air pollution exposure.

Resistive Gas Sensors Based on 2D TMDs and MXenes

ConspectusGas sensors are used in various applications to sense toxic gases, mainly for enhanced safety. Resistive sensors are particularly popular owing to their ability to detect trace amounts of gases, high stability, fast response times, and affordability. Semiconducting metal oxides are commonly employed in the fabrication of resistive gas sensors. However, these sensors often require high working temperatures, bringing about increased energy consumption and reduced selectivity. Furthermore, they do not have enough flexibility, and their performance is significantly decreased under bending, stretching, or twisting. To address these challenges, alternative materials capable of operating at lower temperatures with high flexibility are needed. Two-dimensional (2D) materials such as MXenes and transition-metal dichalcogenides (TMDs) offer high surface area and conductivity owing to their unique 2D structure, making them promising candidates for realization of resistive gas sensors. Nevertheless, their sensing performance in pristine form is typically weak and unacceptable, particularly in terms of response, selectivity, and recovery time (trec). To overcome these drawbacks, several strategies can be employed to enhance their sensing properties. Noble-metal decoration such as (Au, Pt, Pd, Rh, Ag) is a highly promising method, in which the catalytic effects of noble metals as well as formation of potential barriers with MXenes or TMDs eventually contribute to boosted response. Additionally, bimetallic noble metals such as Pt-Pd and Au/Pd with their synergistic properties can further improve sensor performance. Ion implantation is another feasible approach, involving doping of sensing materials with the desired concentration of dopants through control over the energy and dosage of the irradiation ions as well as creation of structural defects such as oxygen vacancies through high-energy ion-beam irradiation, contributing to enhanced sensing capabilities. The formation of core-shell structures is also effective, creating numerous interfaces between core and shell materials that optimize the sensing characteristics. However, the shell thickness needs to be carefully optimized to achieve the best sensing output. To reduce energy consumption, sensors can operate in a self-heating condition where an external voltage is applied to the electrodes, significantly lowering the power requirements. This enables sensors to function in energy-constrained environments, such as remote or low-energy areas. An important advantage of 2D MXenes and TMDs is their high mechanical flexibility. Unlike semiconducting metal oxides that lack mechanical flexibility, MXenes and TMDs can maintain their sensing performance even when integrated onto flexible substrates and subjected to bending, tilting, or stretching. This flexibility makes them ideal for fabricating flexible and portable gas sensors that rigid sensors cannot achieve.

Environmental Exposome and Atrial Fibrillation: Emerging Evidence and Future Directions

There has been increased awareness of the linkage between environmental exposures and cardiovascular health and disease. Atrial fibrillation is the most common sustained cardiac arrhythmia, affecting millions of people worldwide and contributing to substantial morbidity and mortality. Although numerous studies have explored the role of genetic and lifestyle factors in the development and progression of atrial fibrillation, the potential impact of environmental determinants on this prevalent condition has received comparatively less attention. This review aims to provide a comprehensive overview of the current evidence on environmental determinants of atrial fibrillation, encompassing factors such as air pollution, temperature, humidity, and other meteorologic conditions, noise pollution, greenspace, and the social environment. We discuss the existing evidence from epidemiological and mechanistic studies, critically evaluating the strengths and limitations of these investigations and the potential underlying biological mechanisms through which environmental exposures may affect atrial fibrillation risk. Furthermore, we address the potential implications of these findings for public health and clinical practice and identify knowledge gaps and future research directions in this emerging field.

Real-Time Monitoring of Air Pollution Health Impacts Using Breath-Borne Gaseous Biomarkers from Rats

Offline techniques are adopted for studying air pollution health impacts, thus failing to provide in situ observations. Here, we have demonstrated their real-time monitoring by online analyzing an array of gaseous biomarkers from rats' exhaled breath using an integrated exhaled breath array sensor (IEBAS) developed. The biomarkers include total volatile organic compounds (TVOC), CO2, CO, NO, H2S, H2O2, O2, and NH3. Specific breath-borne VOCs were also analyzed by a gas chromatography-ion mobility spectrometer (GC-IMS). After real-life ambient air pollution exposures (2 h), the pollution levels of PM2.5 and O3 were both found to significantly affect the relative levels of multiple gaseous biomarkers in rats' breath. Eleven biomarkers, especially NO, H2S, and 1-propanol, were detected as significantly correlated with PM2.5 concentration, while heptanal was shown to be significantly correlated with O3. Likewise, significant changes were also detected in multiple breath-borne biomarkers from rats under lab-controlled O3 exposures with levels of 150, 300, and 1000 μg/m3 (2 h), compared to synthetic air exposure. Importantly, heptanal was experimentally confirmed as a reliable biomarker for O3 exposure, with a notable dose-response relationship. In contrast, conventional biomarkers of inflammation and oxidative stress in rat sera exhibited insignificant differences after the 2 h exposures. The results imply that breath-borne gaseous biomarkers can serve as an early and sensitive indicator for ambient pollutant exposure. This work pioneered a new research paradigm for online monitoring of air pollution health impacts while obtaining important candidate biomarker information for PM2.5 and O3 exposures.

Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity

BACKGROUND

Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements.

METHODS

Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time.

RESULTS

Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (β -0.010, 95%CI -0.025, 0.005; β -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (β -1.001, 95%CI -1.888, -0.131).

CONCLUSIONS

The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.

Coarse Particulate Matter and Markers of Inflammation and Coagulation in the Multi-Ethnic Study of Atherosclerosis (MESA) Population: A Repeat Measures Analysis

BACKGROUND

In contrast to fine particles, less is known of the inflammatory and coagulation impacts of coarse particulate matter (PM 10 - 2.5 , particulate matter with aerodynamic diameter ≤ 10 μ m  and > 2.5 μ m ). Toxicological research suggests that these pathways might be important processes by which PM 10 - 2.5 impacts health, but there are relatively few epidemiological studies due to a lack of a national PM 10 - 2.5 monitoring network.

OBJECTIVES

We used new spatiotemporal exposure models to examine associations of both 1-y and 1-month average PM 10 - 2.5 concentrations with markers of inflammation and coagulation.

METHODS

We leveraged data from 7,071 Multi-Ethnic Study of Atherosclerosis and ancillary study participants 45-84 y of age who had repeated plasma measures of inflammatory and coagulation biomarkers. We estimated PM 10 - 2.5 at participant addresses 1 y and 1 month before each of up to four exams (2000-2012) using spatiotemporal models that incorporated satellite, regulatory monitoring, and local geographic data and accounted for spatial correlation. We used random effects models to estimate associations with interleukin-6 (IL-6), C-reactive protein (CRP), fibrinogen, and D-dimer, controlling for potential confounders.

RESULTS

Increases in PM 10 - 2.5 were not associated with greater levels of inflammation or coagulation. A 10 - μ g / m 3 increase in annual average PM 10 - 2.5 was associated with a 2.5% decrease in CRP [95% confidence interval (CI): - 5.5 , 0.6]. We saw no association between annual average PM 10 - 2.5 and the other markers (IL-6: - 0.7 % , 95% CI: - 2.6 , 1.2; fibrinogen: - 0.3 % , 95% CI: - 0.9 , 0.3; D-dimer: - 0.2 % , 95% CI: - 2.6 , 2.4). Associations consistently showed that a 1 0 - μ g / m 3 increase in 1-month average PM 10 - 2.5 was associated with reduced inflammation and coagulation, though none were distinguishable from no association (IL-6: - 1.2 % , 95% CI: - 3.0   , 0.5; CRP: - 2.5 % , 95% CI: - 5.3 , 0.4; fibrinogen: - 0.4 % , 95% CI: - 1.0 , 0.1; D-dimer: - 2.0 % , 95% CI: - 4.3 , 0.3).

DISCUSSION

We found no evidence that PM 10 - 2.5 is associated with higher inflammation or coagulation levels. More research is needed to determine whether the inflammation and coagulation pathways are as important in explaining observed PM 10 - 2.5 health impacts in humans as they have been shown to be in toxicology studies or whether PM 10 - 2.5 might impact human health through alternative biological mechanisms. https://doi.org/10.1289/EHP12972.

Associations between air pollution, residential greenness, and glycated hemoglobin (HbA1c) in three prospective cohorts of U.S. adults

BACKGROUND

While studies suggest impacts of individual environmental exposures on type 2 diabetes (T2D) risk, mechanisms remain poorly characterized. Glycated hemoglobin (HbA1c) is a biomarker of glycemia and diagnostic criterion for prediabetes and T2D. We explored associations between multiple environmental exposures and HbA1c in non-diabetic adults.

METHODS

HbA1c was assessed once in 12,315 women and men in three U.S.-based prospective cohorts: the Nurses' Health Study (NHS), Nurses' Health Study II (NHSII), and Health Professionals Follow-up Study (HPFS). Residential greenness within 270 m and 1,230 m (normalized difference vegetation index, NDVI) was obtained from Landsat. Fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were estimated from nationwide spatiotemporal models. Three-month and one-year averages prior to blood draw were assigned to participants' addresses. We assessed associations between single exposure, multi-exposure, and component scores from Principal Components Analysis (PCA) and HbA1c. Fully-adjusted models built on basic models of age and year at blood draw, BMI, alcohol use, and neighborhood socioeconomic status (nSES) to include diet quality, race, family history, smoking status, postmenopausal hormone use, population density, and season. We assessed interactions between environmental exposures, and effect modification by population density, nSES, and sex.

RESULTS

Based on HbA1c, 19% of participants had prediabetes. In single exposure fully-adjusted models, an IQR (0.14) higher 1-year 1,230 m NDVI was associated with a 0.27% (95% CI: 0.05%, 0.49%) lower HbA1c. In basic component score models, a SD increase in Component 1 (high loadings for 1-year NDVI) was associated with a 0.19% (95% CI: 0.04%, 0.34%) lower HbA1c. CI's crossed the null in multi-exposure and fully-adjusted component score models. There was little evidence of associations between air pollution and HbA1c, and no evidence of effect modification.

CONCLUSIONS

Among non-diabetic adults, environmental exposures were not consistently associated with HbA1c. More work is needed to elucidate biological pathways between the environment and prediabetes.

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.

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.

Particulate matter, traffic-related air pollutants, and circulating C-reactive protein levels: The Multiethnic Cohort Study

Inhaled particles and gases can harm health by promoting chronic inflammation in the body. Few studies have investigated the relationship between outdoor air pollution and inflammation by race and ethnicity, socioeconomic status, and lifestyle risk factors. We examined associations of particulate matter (PM) and other markers of traffic-related air pollution with circulating levels of C-reactive protein (CRP), a biomarker of systemic inflammation. CRP was measured from blood samples obtained in 1994-2016 from 7,860 California residents participating in the Multiethnic Cohort (MEC) Study. Exposure to PM (aerodynamic diameter ≤2.5 μm [PM2.5], ≤10 μm [PM10], and between 2.5 and 10 μm [PM10-2.5]), nitrogen oxides (NOx, including nitrogen dioxide [NO2]), carbon monoxide (CO), ground-level ozone (O3), and benzene averaged over one or twelve months before blood draw were estimated based on participants' addresses. Percent change in geometric mean CRP levels and 95% confidence intervals (CI) per standard concentration increase of each pollutant were estimated using multivariable generalized linear regression. Among 4,305 females (55%) and 3,555 males (45%) (mean age 68.1 [SD 7.5] years at blood draw), CRP levels increased with 12-month exposure to PM10 (11.0%, 95% CI: 4.2%, 18.2% per 10 μg/m3), PM10-2.5 (12.4%, 95% CI: 1.4%, 24.5% per 10 μg/m3), NOx (10.4%, 95% CI: 2.2%, 19.2% per 50 ppb), and benzene (2.9%, 95% CI: 1.1%, 4.6% per 1 ppb). In subgroup analyses, these associations were observed in Latino participants, those who lived in low socioeconomic neighborhoods, overweight or obese participants, and never or former smokers. No consistent patterns were found for 1-month pollutant exposures. This investigation identified associations of primarily traffic-related air pollutants, including PM, NOx, and benzene, with CRP in a multiethnic population. The diversity of the MEC across demographic, socioeconomic, and lifestyle factors allowed us to explore the generalizability of the effects of air pollution on inflammation across subgroups.

Assessing the timing and the duration of exposure to air pollution on cardiometabolic biomarkers in patients suspected of coronary artery disease

Air pollution can affect cardiometabolic biomarkers in susceptible populations, but the most important exposure window (lag days) and exposure duration (length of averaging period) are not well understood. We investigated air pollution exposure across different time intervals on ten cardiometabolic biomarkers in 1550 patients suspected of coronary artery disease. Daily residential PM2.5 and NO2 were estimated using satellite-based spatiotemporal models and assigned to participants for up to one year before the blood collection. Distributed lag models and generalized linear models were used to examine the single-day-effects by variable lags and cumulative effects of exposures averaged over different periods before the blood draw. In single-day-effect models, PM2.5 was associated with lower apolipoprotein A (ApoA) in the first 22 lag days with the effect peaking on the first lag day; PM2.5 was also associated with elevated high-sensitivity C-reactive protein (hs-CRP) with significant exposure windows observed after the first 5 lag days. For the cumulative effects, short- and medium-term exposure was associated with lower ApoA (up to 30wk-average) and higher hs-CRP (up to 8wk-average), triglycerides and glucose (up to 6 d-average), but the associations were attenuated to null over the long term. The impacts of air pollution on inflammation, lipid, and glucose metabolism differ by the exposure timing and durations, which can inform our understanding of the cascade of underlying mechanisms among susceptible patients.