Respiratory function declines in children with asthma associated with chemical species of fine particulate matter (PM2.5) in Nagasaki, Japan

Genome-Wide DNA methylation profile analysis identifies differentially methylated loci associated with personal PM2.5 exposure in adults with asthma

Particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5) is a major environmental risk factor for acute asthma exacerbation, and the underlying mechanism is not completely understood. Studies have indicated that DNA methylation is a potential mechanism linking PM2.5 to its health effects. We conducted a panel study involving 24 adult patients with asthma in Beijing,China between 2017 and 2019. PM2.5 and other atmospheric pollutant exposure data were repeatedly measured. Blood samples were collected for genome-wide DNA methylation analysis. A linear mixed-effects (LME) model was conducted to identify differentially methylated probes (DMPs) associated with PM2.5 exposure. After filtering out probes that did not meet the criteria through quality control, 811,001 CpG sites were included in the LME model, and 36 DMPs were strongly associated with personal PM2.5 exposure at false discovery rate (FDR) < 0.05, of which 22 and 14 DMPs negatively and positively correlated with personal PM2.5 exposure, respectively. Functional analysis revealed that DMPs affected smooth muscle cell contraction and development, extracellular matrix synthesis and secretion, T cell activation and differentiation, and inflammatory factor production. This study provides evidence linking personal PM2.5 exposure to genome-wide DNA methylation in adult patients with asthma. Identifying enrichment pathways can provide biological insights into the acute health effects of PM2.5.

Associations of incident female breast cancer with long-term exposure to PM2.5 and its constituents: Findings from a prospective cohort study in Beijing, China

This study aimed to investigate the association between long-term exposure to fine particulate matter (PM2.5) and its constituents (black carbon (BC), ammonium (NH4+), nitrate (NO3-), organic matter (OM), inorganic sulfate (SO42-)) and incident female breast cancer in Beijing, China. Data from a prospective cohort comprising 85,504 women enrolled in the National Urban Cancer Screening Program in Beijing (2013-2019) and the Tracking Air Pollution in China dataset are used. Monthly exposures were aggregated to calculate 5-year average concentrations to indicate long-term exposure. Cox models and mixture exposure models (weighted quantile sum, quantile-based g-computation, and explanatory machine learning model) were employed to analyze the associations. Findings indicated increased levels of PM2.5 and its constituents were associated with higher breast cancer risk, with hazard ratios per 1-μg/m3 increase of 1.02 (95% confidence interval (CI): 1.01, 1.03), 1.39 (95% CI: 1.16, 1.65), 1.28 (95% CI: 1.12, 1.46), 1.15 (95% CI: 1.05, 1.24), 1.05 (95% CI: 1.02, 1.08), and 1.15 (95% CI: 1.07, 1.23) for PM2.5, BC, NH4+, NO3-, OM, and SO42-, respectively. Exposure-response curves demonstrated a monotonic risk increase without an evident threshold. Mixture exposure models highlighted BC and SO42- as key factors, underscoring the importance of reducing emissions of these pollutants.

The impact of outdoor pollution and extreme temperatures on asthma-related outcomes: A systematic review for the EAACI guidelines on environmental science for allergic diseases and asthma

Air pollution is one of the biggest environmental threats for asthma. Its impact is augmented by climate change. To inform the recommendations of the EAACI Guidelines on the environmental science for allergic diseases and asthma, a systematic review (SR) evaluated the impact on asthma-related outcomes of short-term exposure to outdoor air pollutants (PM2.5, PM10, NO2, SO2, O3, and CO), heavy traffic, outdoor pesticides, and extreme temperatures. Additionally, the SR evaluated the impact of the efficacy of interventions reducing outdoor pollutants. The risk of bias was assessed using ROBINS-E tools and the certainty of the evidence by using GRADE. Short-term exposure to PM2.5, PM10, and NO2 probably increases the risk of asthma-related hospital admissions (HA) and emergency department (ED) visits (moderate certainty evidence). Exposure to heavy traffic may increase HA and deteriorate asthma control (low certainty evidence). Interventions reducing outdoor pollutants may reduce asthma exacerbations (low to very low certainty evidence). Exposure to fumigants may increase the risk of new-onset asthma in agricultural workers, while exposure to 1,3-dichloropropene may increase the risk of asthma-related ED visits (low certainty evidence). Heatwaves and cold spells may increase the risk of asthma-related ED visits and HA and asthma mortality (low certainty evidence).

Elucidating disease-associated mechanisms triggered by pollutants via the epigenetic landscape using large-scale ChIP-Seq data

BACKGROUND

Despite well-documented effects on human health, the action modes of environmental pollutants are incompletely understood. Although transcriptome-based approaches are widely used to predict associations between chemicals and disorders, the molecular cues regulating pollutant-derived gene expression changes remain unclear. Therefore, we developed a data-mining approach, termed "DAR-ChIPEA," to identify transcription factors (TFs) playing pivotal roles in the action modes of pollutants.

METHODS

Large-scale public ChIP-Seq data (human, n = 15,155; mouse, n = 13,156) were used to predict TFs that are enriched in the pollutant-induced differentially accessible genomic regions (DARs) obtained from epigenome analyses (ATAC-Seq). The resultant pollutant-TF matrices were then cross-referenced to a repository of TF-disorder associations to account for pollutant modes of action. We subsequently evaluated the performance of the proposed method using a chemical perturbation data set to compare the outputs of the DAR-ChIPEA and our previously developed differentially expressed gene (DEG)-ChIPEA methods using pollutant-induced DEGs as input. We then adopted the proposed method to predict disease-associated mechanisms triggered by pollutants.

RESULTS

The proposed approach outperformed other methods using the area under the receiver operating characteristic curve score. The mean score of the proposed DAR-ChIPEA was significantly higher than that of our previously described DEG-ChIPEA (0.7287 vs. 0.7060; Q = 5.278 × 10-42; two-tailed Wilcoxon rank-sum test). The proposed approach further predicted TF-driven modes of action upon pollutant exposure, indicating that (1) TFs regulating Th1/2 cell homeostasis are integral in the pathophysiology of tributyltin-induced allergic disorders; (2) fine particulates (PM2.5) inhibit the binding of C/EBPs, Rela, and Spi1 to the genome, thereby perturbing normal blood cell differentiation and leading to immune dysfunction; and (3) lead induces fatty liver by disrupting the normal regulation of lipid metabolism by altering hepatic circadian rhythms.

CONCLUSIONS

Highlighting genome-wide chromatin change upon pollutant exposure to elucidate the epigenetic landscape of pollutant responses outperformed our previously described method that focuses on gene-adjacent domains only. Our approach has the potential to reveal pivotal TFs that mediate deleterious effects of pollutants, thereby facilitating the development of strategies to mitigate damage from environmental pollution.

Breathing zone pollutant levels are associated with asthma exacerbations in high-risk children

Background

Indoor and outdoor air pollution levels are associated with poor asthma outcomes in children. However, few studies have evaluated whether breathing zone pollutant levels associate with asthma outcomes.

Objective

Determine breathing zone exposure levels of NO 2 , O 3 , total PM 10 and PM 10 constituents among children with exacerbation-prone asthma, and examine correspondence with in-home and community measurements and associations with outcomes.

Methods

We assessed children's personal breathing zone exposures using wearable monitors. Personal exposures were compared to in-home and community measurements and tested for association with lung function, asthma control, and asthma exacerbations.

Results

81 children completed 219 monitoring sessions. Correlations between personal and community levels of PM 10 , NO 2 , and O 3 were poor, whereas personal PM 10 and NO 2 levels correlated with in-home measurements. However, in-home monitoring underdetected brown carbon (Personal:79%, Home:36.8%) and ETS (Personal:83.7%, Home:4.1%) personal exposures, and detected black carbon in participants without these personal exposures (Personal: 26.5%, Home: 96%). Personal exposures were not associated with lung function or asthma control. Children experiencing an asthma exacerbation within 60 days of personal exposure monitoring had 1.98, 2.21 and 2.04 times higher brown carbon (p<0.001), ETS (p=0.007), and endotoxin (p=0.012), respectively. These outcomes were not associated with community or in-home exposure levels.

Conclusions

Monitoring pollutant levels in the breathing zone is essential to understand how exposures influence asthma outcomes, as agreement between personal and in-home monitors is limited. Inhaled exposure to PM 10 constituents modifies asthma exacerbation risk, suggesting efforts to limit these exposures among high-risk children may decrease their asthma burden.

CLINICAL IMPLICATIONS

In-home and community monitoring of environmental pollutants may underestimate personal exposures. Levels of inhaled exposure to PM 10 constituents appear to strongly influence asthma exacerbation risk. Therefore, efforts should be made to mitigate these exposures.

CAPSULE SUMMARY

Leveraging wearable, breathing-zone monitors, we show exposures to inhaled pollutants are poorly proxied by in-home and community monitors, among children with exacerbation-prone asthma. Inhaled exposure to multiple PM 10 constituents is associated with asthma exacerbation risk.

Monitoring ambient air pollution and pulmonary function in asthmatic children by mobile applications in COVID-19 pandemic

BACKGROUND

Several public health measures were implemented during the COVID-19 pandemic. However, little is known about the real-time assessment of environmental exposure on the pulmonary function of asthmatic children. Therefore, we developed a mobile phone application for capturing real-time day-to-day dynamic changes in ambient air pollution during the pandemic. We aim to explore the change in ambient air pollutants between pre-lockdown, lockdowns, and lockdowns and analyze the association between pollutants and PEF mediated by mite sensitization and seasonal change.

METHOD

A prospective cohort study was conducted among 511 asthmatic children from January 2016 to February 2022. Smartphone-app used to record daily ambient air pollution, particulate matter (PM2.5, PM10) Ozon (O₃), nitrogen dioxide (NO₂), Carbon Monoxide (CO), sulfur dioxide (SO₂), average temperature, and relative humidity, which measured and connected from 77 nearby air monitoring stations by linking to Global Positioning System (GPS)-based software. The outcome of pollutants' effect on peak expiratory flow meter (PEF) and asthma is measured by a smart peak flow meter from each patient or caregiver's phone for real-time assessment.

RESULTS

The lockdown (May 19th, 2021, to July 27th, 2021) was associated with decreased levels of all ambient air pollutants aside from SO₂ after adjusting for 2021. NO₂ and SO₂ were constantly associated with decreased levels of PEF across lag 0 (same day when the PEF was measured), lag 1 (one day before PEF was measured), and lag 2 (two days prior when the PEF was measured. Concentrations of CO were associated with PEF only in children who were sensitized to mites in lag 0, lag 1, and lag 2 in the stratification analysis for a single air pollutant model. Based on the season, spring has a higher association with the decrease of PEF in all pollutant exposure than other seasons.

CONCLUSION

Using our developed smartphone apps, we identified that NO₂, CO, and PM10 were higher at the pre-and post-COVID-19 lockdowns than during the lockdown. Our smartphone apps may help collect personal air pollution data and lung function, especially for asthmatic patients, and may guide protection against asthma attacks. It provides a new model for individualized care in the COVID era and beyond.

Ambient particulate matter associates with asthma in high altitude region: A population-based study

Background

Exposure to particulate matter (PM) has been a major public health threat, but the potentially differential effects on asthma of PM remain largely unknown in high altitude settings. We evaluated the effects of ambient PM on asthma in high altitude settings.

Methods

The study recruited a representative sample from high altitude settings using a multistage stratified sampling procedure. Asthma was defined by a self-reported history of diagnosis by a physician or by wheezing symptoms in the preceding 12 months. The annual mean PM_2.5 and PM₁₀ concentrations were calculated for each grid cell at 1-km spatial resolution based on the geographical coordinates.

Results

We analyzed data for participants (mean age 39.1 years, 51.4% female) and 183 (3.7%, 95% confidence interval (CI): 3.2-4.2) of the participants had asthma. Prevalence was higher in women (4.3%, 95% CI 3.5-5.1) than in men (3.1%, 2.4-3.8) and increasing with higher concentration of PM exposures. For an interquartile range (IQR) difference (8.77 μg/m³) in PM_2.5 exposure, the adjusted odds ratio (OR) was 1.64 (95% CI 1.46-1.83, P < 0.001) for risk of asthma. For PM₁₀, there was evidence for an association with risk of asthma (OR 2.34, 95% CI: 1.75-3.15, P < 0.001 per IQR of 43.26 μg/m³). Further analyses showed that household mold or damp exposure may aggravate PM exposure associated risks of asthma.

Conclusions

This study identified that PM exposure could be a dominate environmental risk factor for asthma but largely unconsidered in the high-altitude areas. The association between PM exposure and asthma should be of interest for planners of national policies and encourage programs for prevention of asthma in residents living at high altitudes.

Spatiotemporal distribution, trend, forecast, and influencing factors of transboundary and local air pollutants in Nagasaki Prefecture, Japan

The study of PM_2.5 and NO₂ has been emphasized in recent years due to their adverse effects on public health. To better understand these pollutants, many studies have researched the spatiotemporal distribution, trend, forecast, or influencing factors of these pollutants. However, rarely studies have combined these to generate a more holistic understanding that can be used to assess air pollution and implement more effective strategies. In this study, we analyze the spatiotemporal distribution, trend, forecast, and factors influencing PM_2.5 and NO₂ in Nagasaki Prefecture by using ordinary kriging, pearson's correlation, random forest, mann-kendall, auto-regressive integrated moving average and error trend and seasonal models. The results indicated that PM_2.5, due to its long-range transport properties, has a more substantial spatiotemporal variation and affects larger areas in comparison to NO₂, which is a local pollutant. Despite tri-national efforts, local regulations and legislation have been effective in reducing NO₂ concentration but less effective in reducing PM_2.5. This multi-method approach provides a holistic understanding of PM_2.5 and NO₂ pollution in Nagasaki prefecture, which can aid in implementing more effective pollution management strategies. It can also be implemented in other regions where studies have only focused on one of the aspects of air pollution and where a holistic understanding of air pollution is lacking.

Joint association between ambient air pollutant mixture and pediatric asthma exacerbations

Exposure to air pollutants is known to exacerbate asthma, with prior studies focused on associations between single pollutant exposure and asthma exacerbations. As air pollutants often exist as a complex mixture, there is a gap in understanding the association between complex air pollutant mixtures and asthma exacerbations. We evaluated the association between the air pollutant mixture (52 pollutants) and pediatric asthma exacerbations.

Method

This study focused on children (age ≤ 19 years) who lived in Douglas County, Nebraska, during 2016-2019. A seasonal-scale joint association between the outdoor air pollutant mixture adjusting for potential confounders (temperature, precipitation, wind speed, and wind direction) in relation to pediatric asthma exacerbation-related emergency department (ED) visits was evaluated using the generalized weighted quantile sum (qWQS) regression with repeated holdout validation.

Results

We observed associations between air pollutant mixture and pediatric asthma exacerbations during spring (lagged by 5 days), summer (lag 0-5 days), and fall (lag 1-3 days) seasons. The estimate of the joint outdoor air pollutant mixture effect was higher during the summer season (adjusted-β_WQS = 1.11, 95% confidence interval [CI]: 0.66, 1.55), followed by spring (adjusted-β_WQS = 0.40, 95% CI: 0.16, 0.62) and fall (adjusted-β_WQS = 0.20, 95% CI: 0.06, 0.33) seasons. Among the air pollutants, PM_2.5, pollen, and mold contributed higher weight to the air pollutant mixture.

Conclusion

There were associations between outdoor air pollutant mixture and pediatric asthma exacerbations during the spring, summer, and fall seasons. Among the 52 outdoor air pollutant metrics investigated, PM_2.5, pollen (sycamore, grass, cedar), and mold (Helminthosporium, Peronospora, and Erysiphe) contributed the highest weight to the air pollutant mixture.