The mediating effect of immune markers on the association between ambient air pollution and adult-onset asthma

Impact of climate change on immune responses and barrier defense

Climate change is not just jeopardizing the health of our planet but is also increasingly affecting our immune health. There is an expanding body of evidence that climate-related exposures such as air pollution, heat, wildfires, extreme weather events, and biodiversity loss significantly disrupt the functioning of the human immune system. These exposures manifest in a broad range of stimuli, including antigens, allergens, heat stress, pollutants, microbiota changes, and other toxic substances. Such exposures pose a direct and indirect threat to our body's primary line of defense, the epithelial barrier, affecting its physical integrity and functional efficacy. Furthermore, these climate-related environmental stressors can hyperstimulate the innate immune system and influence adaptive immunity-notably, in terms of developing and preserving immune tolerance. The loss or failure of immune tolerance can instigate a wide spectrum of noncommunicable diseases such as autoimmune conditions, allergy, respiratory illnesses, metabolic diseases, obesity, and others. As new evidence unfolds, there is a need for additional research in climate change and immunology that covers diverse environments in different global settings and uses modern biologic and epidemiologic tools.

Prenatal exposure to ambient air pollution is associated with early life immune perturbations

BACKGROUND

Exposure to ambient air pollution has been linked to asthma, allergic rhinitis, and other inflammatory disorders, but little is known about the underlying mechanisms.

OBJECTIVE

We studied the potential mechanisms leading from prenatal ambient air pollution exposure to asthma and allergy in childhood.

METHODS

Long-term exposure to nitrogen dioxide (NO₂) as well as to particulate matter with a diameter of ≤2.5 and ≤10 μm (PM_2.5 and PM₁₀) were modeled at the residence level from conception to 6 years of age in 700 Danish children followed clinically for development of asthma and allergy. Nasal mucosal immune mediators were assessed at age 4 weeks and 6 years, inflammatory markers in blood at 6 months, and nasal epithelial DNA methylation and gene expression at age 6 years.

RESULTS

Higher prenatal air pollution exposure with NO₂, PM_2.5, and PM₁₀ was associated with an altered nasal mucosal immune profile at 4 weeks, conferring an increased odds ratio [95% confidence interval] of 2.68 [1.58, 4.62] for allergic sensitization and 2.63 [1.18, 5.81] for allergic rhinitis at age 6 years, and with an altered immune profile in blood at age 6 months conferring increased risk of asthma at age 6 years (1.80 [1.18, 2.76]). Prenatal exposure to ambient air pollution was not robustly associated with immune mediator, epithelial DNA methylation, or gene expression changes in nasal cells at age 6 years.

CONCLUSION

Prenatal exposure to ambient air pollution was associated with early life immune perturbations conferring risk of allergic rhinitis and asthma. These findings suggest potential mechanisms of prenatal exposure to ambient air pollution on the developing immune system.

Long-term air pollution exposure and COVID-19 case-severity: An analysis of individual-level data from Switzerland

Several studies are pointing out that exposure to elevated air pollutants could contribute to increased COVID-19 mortality. However, literature on the associations between air pollution exposure and COVID-19 severe morbidity is rather sparse. In addition, the majority of the studies used an ecological study design and were applied in regions with rather high air pollution levels. Here, we study the differential effects of long-term exposure to air pollution on severe morbidity and mortality risks from COVID-19 in various population subgroups in Switzerland, a country known for clean air. We perform individual-level analyses using data covering the first two major waves of COVID-19 between February 2020 and May 2021. High-resolution maps of particulate matter (PM_2.5) and nitrogen dioxide (NO₂) concentrations were produced for the 6 years preceding the pandemic using Bayesian geostatistical models. Air pollution exposure for each patient was measured by the long-term average concentration across the municipality of residence. The models were adjusted for the effects of individual characteristics, socio-economic, health-system, and climatic factors. The variables with an important association to COVID-19 case-severity were identified using Bayesian spatial variable selection. The results have shown that the individual-level characteristics are important factors related to COVID-19 morbidity and mortality in all the models. Long-term exposure to air pollution appears to influence the severity of the disease only when analyzing data during the first wave; this effect is attenuated upon adjustment for health-system related factors during the entire study period. Our findings suggest that the burden of air pollution increased the risks of COVID-19 in Switzerland during the first wave of the pandemic, but not during the second wave, when the national health system was better prepared.

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.

Integrated single-cell RNA-seq and DNA methylation reveal the effects of air pollution in patients with recurrent spontaneous abortion

Background

Maternal air pollutants exposure is associated with a number of adverse pregnancy outcomes, including recurrent spontaneous abortion (RSA). However, the underlying mechanisms are still unknown. The present study aimed to understand the mechanism of RSA and its relationship with air pollution exposure. We compared data of decidual tissue from individuals with induced abortions and those with RSA by bulk RNA sequencing (RNA-seq), reduced representation bisulfite sequencing (RRBS), and single-cell RNA sequencing (scRNA-seq). Differentially expressed genes (DEGs) were verified using RT-qPCR and pyrosequencing. A logistic regression model was used to investigate the association between air pollutants exposure and RSA.

Results

We identified 98 DEGs with aberrant methylation by overlapping the RRBS and RNA-seq data. Nineteen immune cell subsets were identified. Compared with normal controls, NK cells and macrophages accounted for different proportions in the decidua of patients with RSA. We observed that the methylation and expression of IGF2BP1 were different between patients with RSA and controls. Furthermore, we observed significant positive associations between maternal air pollutants exposure during the year prior to pregnancy and in early pregnancy and the risk of RSA. Mediation analyses suggested that 24.5% of the effects of air pollution on the risk of RSA were mediated through IGF2BP1 methylation.

Conclusion

These findings reveal a comprehensive cellular and molecular mechanism of RSA and suggest that air pollution might cause pregnancy loss by affecting the methylation level of the IGF2BP1 promoter.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01327-2.

Spatio-temporal modelling of changes in air pollution exposure associated to the COVID-19 lockdown measures across Europe

The lockdown and related measures implemented by many European countries to stop the spread of the SARS-CoV-2 virus (COVID-19) pandemic have altered the economic activities and road transport in many cities. To rigorously evaluate how these measures have affected air quality in Europe, we developed Bayesian spatio-temporal (BST) models that assess changes in the surface nitrogen dioxide (NO₂) and fine particulate matter (PM_2.5) concentration across the continent. We fitted BST models to measurements of the two pollutants in 2020 using a lockdown indicator covariate, while accounting for the spatial and temporal correlation present in the data. Since other factors, such as weather conditions, local combustion sources and/or land surface characteristics may contribute to the variation of pollutant concentrations, we proposed two model formulations that allowed the differentiation between the variations in pollutant concentrations due to seasonality from the variations associated to the lockdown policies. The first model compares the changes in 2020, with the ones during the same period in the previous five years, by introducing an offset term, which controls for the long-term average concentrations of each pollutant during 2014–2019. The second approach models only the 2020 data, but adjusts for confounding factors. The results indicated that the latter can better capture the lockdown effect. The measures taken to tackle the virus in Europe reduced the average surface concentrations of NO₂ and PM_2.5 by 29.5% (95% Bayesian credible interval: 28.1%, 30.9%) and 25.9% (23.6%, 28.1%), respectively. To our knowledge, this research is the first to account for the spatio-temporal correlation present in the monitoring data during the pandemic and to assess how it affects estimation of the lockdown effect while accounting for confounding. The proposed methodology improves our understanding of the effect of COVID-19 lockdown policies on the air pollution burden across the continent.

Long-term exposure to ambient air pollution and road traffic noise and asthma incidence in adults: The Danish Nurse cohort

BACKGROUND

Ambient air pollution is likely a risk factor for asthma, and recent evidence suggests the possible relevance of road traffic noise.

OBJECTIVES

We examined the associations of long-term exposure to air pollution and road traffic noise with adult-asthma incidence.

METHODS

We followed 28,731 female nurses (age > 44 years) from the Danish Nurse Cohort, recruited in 1993 and 1999, for first hospital contact for asthma from 1977 until 2015. We estimated residential annual mean concentrations of particulate matter with diameter < 2.5 µm (PM_2.5) since 1990 and nitrogen dioxide (NO₂) since 1970 with the Danish DEHM/UBM/AirGIS modeling system, and road traffic noise (L_den) since 1970 with the Nord2000 model. Time-varying Cox regression models were used to associate air pollution and road traffic noise exposure with asthma incidence.

RESULTS

During 18.6 years' mean follow-up, 528 out of 23,093 participants had hospital contact for asthma. The hazard ratios (HR) and 95% confidence intervals for asthma incidence associated with 3-year moving average exposures were 1.29 (1.03, 1.61) per 6.3 µg/m³ for PM_2.5, 1.16 (1.07, 1.27) per 8.2 µg/m³ for NO₂, and 1.12 (1.00, 1.25) per 10 dB for L_den. The HR for NO₂ remained unchanged after adjustment for either PM_2.5 or L_den, while the HRs for PM_2.5 and L_den attenuated to unity after adjustment for NO₂.

CONCLUSIONS

Long-term exposure to air pollution was associated with adult-asthma incidence independently of road traffic noise, with NO₂ most relevant. Road traffic noise was not independently associated with adult-asthma incidence.

The Role of Upper Airway Microbiome in the Development of Adult Asthma

Clinical and molecular phenotypes of asthma are complex. The main phenotypes of adult asthma are characterized by eosinophil and/or neutrophil cell dominant airway inflammation that represent distinct clinical features. Upper and lower airways constitute a unique system and their interaction shows functional complementarity. Although human upper airway contains various indigenous commensals and opportunistic pathogenic microbiome, imbalance of this interactions lead to pathogen overgrowth and increased inflammation and airway remodeling. Competition for epithelial cell attachment, different susceptibilities to host defense molecules and antimicrobial peptides, and the production of proinflammatory cytokine and pattern recognition receptors possibly determine the pattern of this inflammation. Exposure to environmental factors, including infection, air pollution, smoking is commonly associated with asthma comorbidity, severity, exacerbation and resistance to anti-microbial and steroid treatment, and these effects may also be modulated by host and microbial genetics. Administration of probiotic, antibiotic and corticosteroid treatment for asthma may modify the composition of resident microbiota and clinical features. This review summarizes the effect of some environmental factors on the upper respiratory microbiome, the interaction between host-microbiome, and potential impact of asthma treatment on the composition of the upper airway microbiome.

Biological effect of PM10 on airway epithelium-focus on obstructive lung diseases

Recently, a continuous increase in environmental pollution has been observed. Despite wide-scale efforts to reduce air pollutant emissions, the problem is still relevant. Exposure to elevated levels of airborne particles increased the incidence of respiratory diseases. PM₁₀ constitute the largest fraction of air pollutants, containing particles with a diameter of less than 10 μm, metals, pollens, mineral dust and remnant material from anthropogenic activity. The natural airway defensive mechanisms against inhaled material, such as mucus layer, ciliary clearance and macrophage phagocytic activity, may be insufficient for proper respiratory function. The epithelium layer can be disrupted by ongoing oxidative stress and inflammatory processes induced by exposure to large amounts of inhaled particles as well as promote the development and exacerbation of obstructive lung diseases. This review draws attention to the current state of knowledge about the physical features of PM₁₀ and its impact on airway epithelial cells, and obstructive pulmonary diseases.

Smart-Mobility Services for Climate Mitigation in Urban Areas: Case Studies of Baltic Countries and Germany

The transport sector is one of the largest contributors of CO2 emissions and other greenhouse gases. In order to achieve the Paris goal of decreasing the global average temperature by 2 °C, urgent and transformative actions in urban mobility are required. As a sub-domain of the smart-city concept, smart-mobility-solutions integration at the municipal level is thought to have environmental, economic and social benefits, e.g., reducing air pollution in cities, providing new markets for alternative mobility and ensuring universal access to public transportation. Therefore, this article aims to analyze the relevance of smart mobility in creating a cleaner environment and provide strategic and practical examples of smart-mobility services in four European cities: Berlin (Germany), Kaunas (Lithuania), Riga (Latvia) and Tartu (Estonia). The paper presents a systematized literature review about the potential of smart-mobility services in reducing the negative environmental impact to urban environments in various cities. The authors highlight broad opportunities from the European Union and municipal documents for smart-mobility initiatives. The theoretical part is supplemented by socioeconomic and environmental descriptions, as well as experience, related to smart-mobility services in the four cities selected.

The effect of air pollution on immunological, antioxidative and hematological parameters, and body condition of Eurasian tree sparrows

Air pollution constitutes potential threats to wildlife and human health; therefore, it must be monitored accurately. However, little attention has been given to understanding the toxicological effects induced by air pollution and the suitability of bird species as bioindicators. The Eurasian tree sparrow (Passer montanus), a human commensal species, was used as a study model to examine toxic metal accumulation, retention of particulate matter (PM), immunological and antioxidant capacities, and hematological parameters in birds inhabiting those areas with relatively higher (Shijiazhuang city) or lower (Chengde city) levels of PM_2.5 and PM₁₀ in China. Our results showed that Shijiazhuang birds had significantly more particle retention in the lungs and toxic metal (including aluminum, arsenic, cadmium, iron, manganese, and lead) accumulation in the feathers relative to Chengde birds. They also had lower superoxide dismutase, albumin, immunoglobulin M concentrations in the lung lavage fluid, and total antioxidant capacity (T-AOC) in the lungs and hearts. Furthermore, although they had higher proportions of microcytes, hypochromia, and polychromatic erythrocytes in the peripheral blood (a symptom of anemia), both populations exhibited comparable body conditions, white cell counts, heterophil and lymphocyte ratios, and plasma T-AOC and corticosterone levels. Therefore, our results not only confirmed that Shijiazhuang birds experienced a greater burden from environmental PM and toxic metals but also identified a suite of adverse effects of environmental pollution on immunological, antioxidative, and hematological parameters in multiple tissues. These findings contribute to our understanding of the physiological health consequences induced by PM exposure in wild animals. They suggest that free-living birds inhabiting urban areas could be used as bioindicators for evaluating the adverse effects induced by environmental pollution.

Air pollution and indoor settings

Indoor environments contribute significantly to total human exposure to air pollutants, as people spend most of their time indoors. Household air pollution (HAP) resulting from cooking with polluting ("dirty") fuels, which include coal, kerosene, and biomass (wood, charcoal, crop residues, and animal manure) is a global environmental health problem. Indoor pollutants are gases, particulates, toxins, and microorganisms among others, that can have an impact especially on the health of children and adults through a combination of different mechanisms on oxidative stress and gene activation, epigenetic, cellular, and immunological systems. Air pollution is a major risk factor and contributor to morbidity and mortality from major chronic diseases. Children are significantly affected by the impact of the environment due to biological immaturity, prenatal and postnatal lung development. Poor air quality has been related to an increased prevalence of clinical manifestations of allergic asthma and rhinitis. Health professionals should increase their role in managing the exposure of children and adults to air pollution with better methods of care, prevention, and collective action. Interventions to reduce household pollutants may promote health and can be achieved with education, community, and health professional involvement.

Modification of caesarean section on the associations between air pollution and childhood asthma in seven Chinese cities

It is unknown whether giving birth via caesarean section (c-section) is a modifier for the association between air pollution and asthma. From 2012 to 2013, 59,754 children between the ages of 2 and 17 were randomly selected from 94 middle schools, elementary schools and kindergartens in seven Chinese cities for a cross-sectional study. The children's parents or guardians completed questionnaires, from which data on asthma as well as asthma-related symptoms were obtained. Participants' exposure to particles with an aerodynamic diameter ≤1.0 μm (PM₁), ≤2.5 μm (PM_2.5), and ≤10 μm (PM₁₀) and exposure to nitrogen dioxide (NO₂) were estimated using random forest models. We used mixed effects logistic regression models and added an interaction term between mode of delivery and ambient air pollution into the model to estimate effect modification from c-sections after appropriate adjustments for potential confounding variables. Among children delivered by c-section, the adjusted ORs for asthma and its symptoms per interquartile range (IQR) increase of PM₁, PM_2.5, PM₁₀ and NO₂ (1.20 95% CI: 1.07-1.34 to 2.04 95% CI: 1.87-2.24) were significantly higher than those of children delivered vaginally (1.05 95% CI: 0.92-1.19 to 1.33 95%CI: 1.21-1.47). The interactions between c-sections and ambient air pollution were statistically significant for all studied respiratory disorders, except current wheeze. Delivery via c-section may increase the risks of air pollution on asthma and its symptoms in Chinese children.

Associations between persistent organic pollutants and endometriosis: A multipollutant assessment using machine learning algorithms

Endometriosis is a gynaecological disease characterised by the presence of endometriotic tissue outside of the uterus impacting a significant fraction of women of childbearing age. Evidence from epidemiological studies suggests a relationship between risk of endometriosis and exposure to some organochlorine persistent organic pollutants (POPs). However, these chemicals are numerous and occur in complex and highly correlated mixtures, and to date, most studies have not accounted for this simultaneous exposure. Linear and logistic regression models are constrained to adjusting for multiple exposures when variables are highly intercorrelated, resulting in unstable coefficients and arbitrary findings. Advanced machine learning models, of emerging use in epidemiology, today appear as a promising option to address these limitations. In this study, different machine learning techniques were compared on a dataset from a case-control study conducted in France to explore associations between mixtures of POPs and deep endometriosis. The battery of models encompassed regularised logistic regression, artificial neural network, support vector machine, adaptive boosting, and partial least-squares discriminant analysis with some additional sparsity constraints. These techniques were applied to identify the biomarkers of internal exposure in adipose tissue most associated with endometriosis and to compare model classification performance. The five tested models revealed a consistent selection of most associated POPs with deep endometriosis, including octachlorodibenzofuran, cis-heptachlor epoxide, polychlorinated biphenyl 77 or trans-nonachlor, among others. The high classification performance of all five models confirmed that machine learning may be a promising complementary approach in modelling highly correlated exposure biomarkers and their associations with health outcomes. Regularised logistic regression provided a good compromise between the interpretability of traditional statistical approaches and the classification capacity of machine learning approaches. Applying a battery of complementary algorithms may be a strategic approach to decipher complex exposome-health associations when the underlying structure is unknown.

Smoke exposure from chronic biomass burning induces distinct accumulative systemic inflammatory cytokine alterations compared to tobacco smoking in healthy women

Long-term exposure to biomass-burning smoke (BS) is associated with chronic obstructive pulmonary disease (COPD), asthma, and other chronic inflammatory lung diseases. BS results from such processes as the burning of wood for indoor cooking and heating, with women and children having the highest exposure rate. This study aimed to analyze the accumulative alterations in cytokine levels associated with BS (from wood) compared to tobacco smoke (TS) in healthy adult women. The levels of 27 cytokines were analyzed in the serum of 100 women, including 40 tobacco smokers/non-exposed to BS (TS+/BS-), 30 never-smokers/exposed to BS (TS-/BS+) and 30 never-smokers/non-exposed to BS (TS-/BS-) as controls, using 27-Plex immunoassay. The chronic BS exposure index was rated at ≥100 h-years, and the tobacco-smoking index was ≥10 pack-years. Compared to TS-/BS-, TS+/BS- had higher levels of IL-2, IL-9, MCP-1, MIP-1β, and VEGF, while TS-/BS+ showed higher levels of IL-1ra, IL-6, IL-8, Eotaxin, IP-10, RANTES, and VEGF, presenting a distinct inflammatory profile that may favor an eosinophil-derived inflammatory response to BS exposure. Compared to TS+/BS-, TS-/BS+ expressed higher levels of IP-10 and IL-8, but lower levels of IL-2 and MIP-1β. Gene-disease database analysis showed that altered cytokines in both TS+/BS- and TS-/BS+ are associated with asthma, COPD, lung fibrosis, and lung cancer. In conclusion, chronic BS exposure induces distinct systemic inflammatory cytokine alterations compared to tobacco smokers in healthy women. These findings provide new insights into how long-term exposure to BS affects the inflammatory response-and potentially the health-of adult women.

Emergence of Blue Sky Over Delhi Due to Coronavirus Disease (COVID-19) Lockdown Implications

Due to coronavirus pandemic (COVID-19) prevailing in more than 210 countries, out of them only few have promulgated lockdown and on March 24, 2020 India also implemented lockdown for 21 days to prevent the community spread of virus among people. Since then, lockdown heavily restricts travel movements of flights, rail, intercity bus services besides industrial activity halt throughout the country. The significant improvement in the air quality of Delhi region was observed due to strict implementation of lockdown. During the lockdown period, improvement in ambient air quality helped us in circumventing the coronavirus community spread. The preliminary results showing the decrease in horizontal advection of pollutants has given an opportunity to understand the background concentrations of air pollutants over Delhi. To analyse this peculiar situation, we have assessed the pollutants datasets collected by twelve different online ambient air quality monitoring stations (AQMS) of Central Pollution Control Board (CPCB), New Delhi, India and observed a colossal improvement in the ambient air quality. The analysis of data confirms the sharp decline in concentrations (nearly 200%) of PM_2.5 and PM₁₀. The concentration of nitrous oxides (NO_x), recorded its maximum (342 ppb) on 12 January 2020 in CRRI–Mathura Road, Delhi with the lowest value as 24 ppb on 30 March 2020 (reduced to nearly 14 times of the peak value). In the triad of this infectious disease, the role of environment is not linked better however, the ground reality cannot be ignored due to environment around us receives, maintains, protects and transports the aetiological agents to host prevailing in polluted environment which makes our lungs more susceptible to viral attacks. Therefore, a cleaner environment would prove to be an effective measure to halt and reduce the transmission of viral infections.