Summary
Background
Asthma prevalence and severity have markedly increased with urbanisation, and children in low-income urban centres have among the greatest asthma morbidity. Outdoor air pollution has been associated with adverse respiratory effects in children with asthma. However, the mechanisms by which air pollution exposure exacerbates asthma, and how these mechanisms compare with exacerbations induced by respiratory viruses, are poorly understood. We aimed to investigate the associations between regional air pollutant concentrations, respiratory illnesses, lung function, and upper airway transcriptional signatures in children with asthma, with particular focus on asthma exacerbations occurring in the absence of respiratory virus.
Methods
We performed a retrospective analysis of data from the MUPPITS1 cohort and validated our findings in the ICATA cohort. The MUPPITS1 cohort recruited 208 children aged 6–17 years living in urban areas across nine US cities with exacerbation-prone asthma between Oct 7, 2015, and Oct 18, 2016, and monitored them during reported respiratory illnesses. The last MUPPITS1 study visit occurred on Jan 6, 2017. The ICATA cohort recruited 419 participants aged 6–20 years with persistent allergic asthma living in urban sites across eight US cities between Oct 23, 2006, and March 25, 2008, and the last study visit occurred on Dec 30, 2009. We included participants from the MUPPITS1 cohort who reported a respiratory illness at some point during the follow-up and participants from the ICATA cohort who had nasal samples collected during respiratory illness or at a scheduled visit. We used air quality index values and air pollutant concentrations for PM2·5, PM10, O3, NO2, SO2, CO, and Pb from the US Environmental Protection Agency spanning the years of both cohorts, and matched values and concentrations to each illness for each participant. We investigated the associations between regional air pollutant concentrations and respiratory illnesses and asthma exacerbations, pulmonary function, and upper airway transcriptional signatures by use of a combination of generalised additive models, case crossover analyses, and generalised linear mixed-effects models.
Findings
Of the 208 participants from the MUPPITS1 cohort and 419 participants from the ICATA cohort, 168 participants in the MUPPITS1 cohort (98 male participants and 70 female participants) and 189 participants in the ICATA cohort (115 male participants and 74 female participants) were included in our analysis. We identified that increased air quality index values, driven predominantly by increased PM2·5 and O3 concentrations, were significantly associated with asthma exacerbations and decreases in pulmonary function that occurred in the absence of a provoking viral infection. Moreover, individual pollutants were significantly associated with altered gene expression in coordinated inflammatory pathways, including PM2·5 with increased epithelial induction of tissue kallikreins, mucus hypersecretion, and barrier functions and O3 with increased type-2 inflammation.
Interpretation
Our findings suggest that air pollution is an important independent risk factor for asthma exacerbations in children living in urban areas and is potentially linked to exacerbations through specific inflammatory pathways in the airway. Further investigation of these potential mechanistic pathways could inform asthma prevention and management approaches.
Funding
National Institutes of Health, National Institute of Allergy and Infectious Diseases.
Research in contextEvidence before this studyRespiratory viral infections are the most common cause of asthma exacerbations in children and adolescents (ie, aged <21 years), and human studies of respiratory viruses in asthma have identified key inflammatory pathways mediating their effects. These findings have increasingly led towards targeted therapeutic strategies to prevent asthma exacerbations. Asthma exacerbations also occur independently of viral respiratory infections, but the causes and molecular mechanisms of non-viral exacerbations are, in comparison, poorly understood. Over the past several decades, many epidemiological studies have shown associations between air pollutant concentrations and the occurrence of asthma exacerbations. Mechanistic animal, cellular, and controlled human studies have suggested plausible mechanisms by which individual air pollutants can cause airway inflammation. However, studies linking air pollutant exposures to molecular mechanisms in the airways during naturally occurring asthma exacerbations have not been conducted. We searched PubMed for articles published in English between Jan 1, 2010, and Oct 1, 2021, using the terms “asthma exacerbation” AND “air pollution”, restricted to human studies. We also reviewed all references from two in-depth review articles on the topic of environmental exposures, outdoor air pollution, and asthma, published in 2014 and 2019.Added value of this studyWe identify that air quality in urban centres, related to increased concentrations of specific air pollutants, is significantly associated with asthma exacerbations in children who are underprivileged and living in areas with high disease burden. We show that air pollutants are associated with exacerbations occurring in the absence of a provoking respiratory virus. Crucially, we connect individual pollutants to changes in airway physiology and upper airway gene expression during acute exacerbations, identifying associations with decreased lung function and distinct molecular pathways of airway inflammation. We link fine particulate matter (PM2·5) exposure to several epithelial inflammatory responses, including induction of tissue kallikreins and inflammatory cytokines, which are absent in viral-induced exacerbations, and to airway remodelling pathways. Similarly, we link O3 exposure to type-2 inflammatory responses and decreased lung function. For the first time, to our knowledge, we identify associations between specific pollutant exposures and airway inflammatory patterns that are present in non-viral asthma exacerbations, contributing to asthma disparities in children living in urban settings.Implications of all the available evidenceRegional air pollutants are epidemiologically associated with asthma exacerbations and might represent an important trigger of asthma exacerbations occurring independently of respiratory viral infections. Compared with viral exacerbations, non-viral exacerbations associated with air pollution proceed through distinct and overlapping molecular mechanisms and also share some common mechanisms. This increased understanding of the potential causes and distinct molecular mechanisms of asthma exacerbation endotypes can inform targeted interventional strategies and bolster the public health argument for policies that reduce outdoor air pollution.
Introduction
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,
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and exacerbation
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,
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,
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,
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of asthma, with many pollutants associated with asthma exacerbations, most notably fine particulate matter (PM2·5),
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,
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oxidising gases, including O3
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,
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and NO2,
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,
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and reductants, such as SO2.
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The negative effects of air pollution are likely to be particularly relevant in urban centres, where pollution exposure is high and the prevalence and morbidity of asthma in children is disproportionately high compared with rural and less dense urban areas. However, although physiological effects of air pollutants have been investigated, the molecular mechanisms by which air pollutants trigger asthma exacerbations are poorly understood, especially in susceptible populations, such as children with severe or uncontrolled asthma.
Studies of the molecular effects of air pollutants during respiratory illnesses have not been conducted in humans.
- Altman MC
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integrating data for air quality to investigate the contribution of air pollution to molecular and physiological mechanisms of exacerbation pathogenesis. We then validated key observations from this cohort in the Inner-City Anti-IgE Therapy for Asthma (ICATA) cohort.
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Methods
Study design and participants
- Altman MC
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- et al.
and validated our findings with data from a randomised, double-blind, placebo-controlled trial in an independent cohort (ICATA).
- Busse WW
- Morgan WJ
- Gergen PJ
- et al.
- Altman MC
- Gill MA
- Whalen E
- et al.
Briefly, participants were recruited between Oct 7, 2015, and Oct 18, 2016, across hospital clinics in major urban areas in nine US cities. An individual was eligible for enrolment if they were aged 6–17 years; were diagnosed with asthma by a clinician more than 1 year before recruitment; had at least two asthma exacerbations (ie, required systemic corticosteroids or hospital admission, or both) in the year before recruitment; were treated with at least one puff of fluticasone 250 μg twice daily, or its equivalent for children aged 6–11 years, or treated with at least one puff of fluticasone 250 μg plus salmeterol 50 μg twice daily, or its equivalent for children aged 12 years and older; had more than or equal to 150 peripheral blood eosinophils per mm3; did not smoke; and lived in a census tract with a density of more than or equal to 1000 families per square mile and with at least 10% of families with income below the poverty level (based on American Community Survey data
Data dictionary: ACS 2014 (5-year estimates).
). Participants were identified for recruitment through the Registry for Asthma Characterization and Recruitment 2 and site-approved recruitment sources (NCT02513264). Participants were followed up prospectively for up to two respiratory illnesses or approximately 6 months, whichever occurred first. Participants who reported a respiratory illness were asked to return to the clinic twice in the 6-day period after the start of symptoms for collection of nasal samples and pulmonary function testing. Each illness was defined as a viral (V+) or non-viral (V–) event on the basis of virological assessment of the first nasal blow sample by use of the Luminex Respiratory Viral Panel (Luminex, Austin, TX, USA), with (Ex+) or without an asthma exacerbation (Ex–) on the basis of whether the participant was treated with systemic corticosteroids within 10 days following the onset of the respiratory event or not (appendix p 11). The last study visit occurred on Jan 6, 2017.
- Busse WW
- Morgan WJ
- Gergen PJ
- et al.
Briefly, participants were enrolled between Oct 23, 2006, and March 25, 2008, across hospital clinics in major urban areas in eight US cities. An individual was eligible for enrolment if they were aged 6–20 years; were diagnosed with asthma by a clinician more than a year before recruitment or diagnosed with asthma and had symptoms for longer than 1 year; had bodyweight and total serum IgE suitable for omalizumab dosing and a positive skin-prick test to at least one perennial allergen; did not smoke; and lived in a census tract with a density of more than or equal to 1000 families per square mile with and at least 10% of families with income below the poverty level. In an exploratory substudy of 189 of 419 participants in four of eight US cities (ie, New York, NY, Chicago, IL, Dallas, TX, and Cleveland, OH), 100 nasal samples were collected within 7 days of the onset of an asthma exacerbation (ie, required systemic corticosteroids; Ex+) and 165 nasal samples were collected at study week 48 in the absence of an exacerbation. The last study visit occurred on Dec 30, 2009. The nasal samples were used for virological assessment by use of the Eragen Multi-Code Respiratory Virus Panel (Eragen Biosciences, Madison, WI, USA) and defined as V+ or V– (appendix pp 12–13).
In this analysis, we included participants from the MUPPITS1 cohort who reported a respiratory event at some point during the follow-up and participants from the ICATA cohort who had nasal samples collected due to a respiratory event or at a scheduled visit. Sex was self-reported by participants, with the options of male or female.
was reviewed by a single institutional review board, and the ICATA protocol
was reviewed by the institutional review boards of all participating institutions. Written informed consent for the MUPPITS1 and ICATA studies was obtained from the parents or legal guardians of all participants and applies to this analysis.
Procedures
Pre-generated data files.
spanning the years of the studies (2015–17 for MUPPITS1 and 2006–09 for ICATA) and the cities of participant recruitment. The EPA uses set formulas to convert raw measurements of pollutants into a summary AQI (on the basis of the single pollutant with the most hazardous concentration on a given day) for each day and each core-based statistical area (ie, geographical area anchored by an urban centre of at least 10 000 people plus adjacent areas with socioeconomic ties).
Technical assistance document for the reporting of daily air quality—the air quality index (AQI).
AQI data were matched to each event for each participant according to the core-based statistical area in which they lived and the date in relation to their reported respiratory illness symptoms. For each pollutant, monitors within each core-based statistical area were subset to include only those in the recruitment census tract, excluding monitors that were in the core-based statistical area but outside of the census tract. For each pollutant, the maximum concentration was then taken for each city census tract and day and similarly matched to each event according to core-based statistical area and date.
- Altman MC
- Gill MA
- Whalen E
- et al.
Briefly, viral status was established on the basis of the results of multiplex PCR (Luminex Respiratory Viral Panel, Luminex, Austin, TX, USA) and partial sequencing of nasal blow samples to identify respiratory virus species; cell differentials were determined by cytospin of nasal lavage samples quantifying neutrophils, lymphocytes, macrophages, eosinophils, respiratory epithelium, and squamous cells; and RNA-sequencing was performed on bulk RNA extracted from nasal lavage cell pellets and is publicly available at Gene Expression Omnibus, accession number GSE115824. RNA-sequencing data were summarised into cell-associated modules of coexpressed genes by use of combined cell association by correlation and weighted gene correlation network analysis
and annotated by use of Database for Annotation, Visualization and Integrated Discovery
- Huang W
- Sherman BT
- Lempicki RA
and Search Tool for the Retrieval of Interacting Genes/Proteins;
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- Franceschini A
- Wyder S
- et al.
the modules used in this analysis have been previously described.
- Altman MC
- Gill MA
- Whalen E
- et al.
Spirometry and the measurement of fractional exhaled NO (FeNO) were collected according to American Thoracic Society and European Respiratory Society guidelines.
- Miller MR
- Hankinson J
- Brusasco V
- et al.
In the ICATA cohort, nasal-secretion samples were collected at the onset of an asthma exacerbation or at a routine study visit 48 weeks after study enrolment, and RNA was extracted and analysed for respiratory viruses by the Eragen Multi-Code Respiratory Virus Panel.
- Busse WW
- Morgan WJ
- Gergen PJ
- et al.
Outcomes
The key outcome was association between AQI values and pollutant concentrations and the respiratory event type. Other outcomes included associations with pulmonary function and nasal module expression values. All outcomes were modelled in relation to the AQI value and concentrations of pollutants.
Statistical analysis
,
,
including the day relative to respiratory illness symptom onset as the smoothed, continuous variable, and a term for event group. Covariates were added for city of residence or season, where specified. The generalised additive model tested whether the four (or two) groups were different over the entire timespan included in the model. For the four-group comparisons, ANOVA was run to establish whether the four groups were different by use of the Wald test in the generalised additive model, followed by post-hoc pairwise comparisons. The same model syntax and data visualisation were used for both MUPPITS1 and ICATA. Responsible pollutants for AQI values for each day were those defined by the EPA. Case crossover analyses of Ex+ events in MUPPITS1 were performed comparing days –7 to +1 (case) relative to the date of exacerbation onset (designated day 0) to days –16 to –8 (control) or days –37 to –8 (control) as specified. Longitudinal differences were visualised by generalised additive models, and statistical comparisons between time periods were tested by conditional logistic regression,
including a covariate for day of the week. Lung function measurements (forced expiratory volume in 1 s as a percentage of predicted [FEV1% predicted] and ratio of forced expiratory volume in 1 s to forced vital capacity [FEV1/FVC]) were compared with AQI values or pollutant concentrations from the same day by use of generalised linear mixed-effects models split by event subgroup with a random effect for participant to account for the correlation between values from the same participants; values collected after the initiation of systemic corticosteroids were excluded for this analysis, and for FEV1/FVC the model also controlled for age and sex. After testing AQI and pollutants, p values were adjusted with the Benjamini-Hochberg method to identify those with a false discovery rate (FDR) of less than 0·05. Module expression was compared with AQI values or pollutant concentrations summed over 3 days (ie, the day of sample collection and the preceding 2 days) by use of a generalised linear mixed-effects model adjusted for cell percentages in the nasal lavage sample and the number of counts in the RNA-sequencing library with a random effect for participant to account for the correlation between values from the same participants; samples collected after the initiation of systemic corticosteroids were excluded for this analysis. Multiple-testing correction for module analysis was performed with the Benjamini-Hochberg method and modules with FDR less than 0·05 were considered significant. Demographic and clinical characteristic variables among event or sample subgroups in each cohort were summarised with median and IQR for continuous variables and count and percentage for categorical variables. Within each cohort, V+ and V– events or samples were compared by use of generalised linear mixed-effect models, assuming a binomial distribution for the categorical variables and ranked continuous variables, and included a random effect for participant to account for the correlation between values from the same participants. In cases where at least one of the categories of a categorical variable was zero, a Fisher’s exact test was used instead.
Wherever data were missing they were excluded from the analysis. The number of samples for each analysis are indicated in the figure legends. Every reported respiratory event in MUPPITS1 and every timepoint with a nasal sample in ICATA were included. For all analyses we used R (version 4.1.0) and all figures were constructed with R package ggplot2 (version 3.3.6).
Role of the funding source
National Institute of Allergy and Infectious Disease project scientists had no role in study design or data analysis but participated collaboratively in the interpretation and writing of the report.
Results
Of the 208 participants from the MUPPITS1 cohort and 419 participants from the ICATA cohort, 168 participants in the MUPPITS1 cohort (98 male participants and 70 female participants) and 189 participants in the ICATA cohort (115 male participants and 74 female participants) were included in our analysis.
Table 1MUPPITS1 demographic and clinical characteristics
Data are median (IQR) or n (%) and represent the number of events. Events are the number of unique illness events. Participants are the number of unique participants with illness events. For participants with two respiratory illnesses meeting specified criteria, both illnesses are included in the table. Summaries apply to the first visit during that illness. p values represent the significance of any difference between the proportion of V+Ex+ versus V–Ex+ or V+Ex– versus V–Ex–. All p values are from generalised linear mixed-effect models with a random effect for participant to account for correlation between values from the same participant, except for instances where at least one of the categories of a categorical variable is zero and p values are from a Fisher’s exact test. Ex+=exacerbation. Ex–=non-exacerbation. V+Ex+=viral event with exacerbation. V–Ex+=non-viral event with exacerbation. V+Ex–=viral event without exacerbation. V–Ex–=non-viral event without exacerbation. FEV1% predicted=FEV1 as a percentage of predicted. FEV1/FVC=ratio of FEV1 to forced vital capacity. FEV1=forced expiratory volume in 1 s. WURSS=Wisconsin Upper Respiratory Symptom Survey for kids—daily symptom report. AUC=area under the curve. NA=not applicable.
Figure 1AQI values and individual pollutant concentrations over time
NAAQS table.
Similarly, mean AQI assessments did not reach EPA concentrations designated as unhealthy (defined as AQI of 151–200) or unhealthy for sensitive groups (defined as 101–150 for people with heart and lung disease, older adults, children, people with diabetes, and people of lower socioeconomic status) but rather were at concentrations in the moderate category (defined as 51–100 AQI) for several days.
Particle pollution and your patients’ health.
Figure 2Associations of pulmonary functions with AQI values
Associations of FEV1% predicted (A) and FEV1/FVC ratio (B) with AQI measured on the same day. Regression lines, 95% CIs, and all data points are shown for each group. There were 16 data points for the V–Ex+ group, 36 data points for the V+Ex+ group, 70 data points for the V–Ex– group, and 116 data points for the V+Ex– group. AQI=air quality index. FEV1% predicted=forced expiratory volume in 1 s as a percentage of predicted. FEV1/FVC=ratio of forced expiratory volume in 1 s to forced vital capacity. V–Ex+=non-viral event without exacerbation. V+Ex+=viral event with exacerbation. V–Ex–=non-viral event without exacerbation. V+Ex–=viral event without exacerbation.
- Altman MC
- Gill MA
- Whalen E
- et al.
Absolute values of the effect sizes ranged from 0·0015 to 0·0039, where the coefficient represents a change of 0·0015 to 0·0039 in module expression (log2) for a 1 unit increase in AQI over 3 days; expressed differently, this means, for example, a mean 10 unit increase in AQI for 3 days equates to a 3·2–8·5% increase in expression of these modules. A detailed description of these modules was previously published,
- Altman MC
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,
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- et al.
along with their relationships to V–Ex+ and V+Ex+ events
- Altman MC
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- et al.
and details of their contents and annotation.
Peds asthma modules.
AQI values were associated with modules that were specifically increased in the V–Ex+ event subgroup but also with core exacerbation modules that were increased in both V+Ex+ and V–Ex+ event subgroups in this population, suggesting a broad effect of air pollution on asthma pathobiological pathways.
Table 2Gene expression modules differentially expressed during asthma exacerbations
Expression of some modules was significantly associated with AQI values, PM2·5concentrations, and O3 concentrations. Module expression was compared with AQI and pollutant values summed over the two preceding days and day of nasal sample collections (V–Ex+ n=17, V+Ex+ n=38, V–Ex– n=72, V+Ex– n=120). Significance was determined by generalised linear mixed effect models with a random effect for participant. Results were considered significant if the FDR was <0·05. AQI=air quality index. FDR=false discovery rate. NS=not significant. NA=not applicable. V–Ex+=non-viral event with exacerbation. V+Ex+=viral event with exacerbation.
Discussion
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,
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,
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However, the high proportion of non-viral events is consistent with past observations of respiratory illnesses in infants from impoverished urban areas (96 [33%] of 295) compared with suburban (63 [11%] of 586).
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Furthermore, our findings suggest that moderate increases in local air pollution relative to the US national air quality standards adversely affect these susceptible populations. This association suggests either that exposure to mixtures of pollutants over several days at low concentrations can trigger exacerbations or that high AQI levels exist in these urban communities but are not well captured by regionally reported AQI values on the basis of EPA monitors and public data.
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and a large set of epithelial barrier function genes, which are unique to V–Ex+ events.
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The results suggest that increases in PM2·5 concentrations trigger many epithelial immune pathways, which might provoke an exacerbation in the absence of a respiratory virus. This inference is consistent with the observed peak of PM2·5 in the first several days of V–Ex+ events. Furthermore, PM2·5 was associated with pathways that are functionally linked to airway remodelling, including TGFβ signalling, SMAD3 signalling, EGFR signalling, mucus hypersecretion, and extracellular matrix production. These results are consistent with histological and animal model data supporting particulate air pollution as a driver of airway remodelling in part through TGFβ
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,
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and mucus production.
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,
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Notably, the directionality of these associations was not unique to V–Ex+ events but congruent in all four groups, suggesting that the airway effects of PM2·5 exposure were present in each respiratory event type but that the degree of exposure and hence magnitude of transcriptional change of these modules was highest, and presumably clinically most consequential, in the V–Ex+ group.
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,
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O3 concentrations appeared to be higher for the week leading up to V–Ex+ events, and to a lesser extent V+Ex+ events, than for Ex– events during this period, which could help to explain the observation of sustained type-2 inflammation during V+Ex+ and V–Ex+ events.
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Supporting evidence has linked air pollution to asthma symptoms, and the biological plausibility that PM2·5 and O3 exert their effects through the observed airway inflammatory mechanisms is supported by animal and in-vitro models
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and gene-by-environment studies.
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,
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There was probably a range in the number and degree of pollutant exposures even among individuals living in regions with identical regional pollutant concentrations, which should be a focus of future studies. We cannot definitively establish that the measured pollutants triggered the airway transcriptome responses in the development of asthma exacerbations given the observational nature of the study. It is possible that unmeasured covariates could also be associated with V–Ex+ events, most notably non-viral infections, indoor pollutants, and inhaled allergens. In a separate analysis of this cohort, we did not find upper airway bacterial or fungal microbes as a cause of the V–Ex+ events, but instead observed that the nasal microbiome showed seasonal dynamics that might predispose to viral infections in the autumn.
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We were unable to measure indoor air pollutants during this study, although other studies have shown outdoor air pollution as an important source of indoor air pollution in low-income homes.
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,
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We noted non-significant increases in V–Ex+ events in the spring and summer months relative to V+Ex+ events, suggesting that seasonal inhaled allergens might also have contributed to V–Ex+ events, but we did not measure inhaled allergen exposures in this study and were able to adjust only for season and site in our analyses, which did not affect our findings. Adjusting for season and site does not entirely address the potential role of inhaled allergen as a contributor to asthma exacerbations in our study. Future studies that can accurately measure acute allergen exposures will be needed to understand their relative contributions. Our study focused on children with persistent asthma with a type-2 phenotype component (ie, peripheral blood eosinophils ≥150/mm3 in MUPPITS1 and aeroallergen sensitisation in ICATA). Although we cannot definitively conclude that the results would be generalisable to any asthma phenotype, these results are also highly relevant to type-2 low asthma (ie, often defined as eosinophils 3), in which respiratory irritants might have an even greater role than in persistent asthma with a type-2 high phenotype component.
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Our sample size for V–Ex+ events was small in our primary dataset (n=14), and thus showing a similar association of pollution to non-viral illnesses with exacerbations in an independent dataset was an important validation, although the ICATA cohort did not have data to validate the transcriptome results. Finally, this study did not have sufficient power to analyse the potential combined effects of more than one asthma trigger. We hypothesise that viruses, pollution, and other covariates can act independently or synergise to initiate asthma exacerbations in children living in urban areas. In fact, the effects of pollutants might overlap with the effects of viruses, as the associations between several module expression levels and pollutants were congruent in all four event groups. Notably, our data showed combined increases of O3 and PM2·5 in the V–Ex+ event subgroup, but each pollutant was associated with distinct inflammatory pathways. These pollutants are chemically coupled, can increase concomitantly, especially in warm weather,
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and can have additive deleterious effects on the airway. Larger studies will be needed to investigate combined effects among asthma triggers and mechanisms.
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around periods of risk (ie, when AQI values or concentrations of O3 and PM2·5 are predicted to be in the moderate or higher EPA categories for a sustained period of a couple of days or more), treatment approaches to counteract deleterious effects of pollutants on the airway epithelium, and targeted therapies aimed at the kallikrein–kinin system or other epithelial pathways and cytokines identified in these modules, in addition to current treatments for type-2 inflammation. Importantly, these data add to the growing body of evidence supporting the need to reduce outdoor air pollution
,
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as a means to decrease respiratory illnesses and asthma-related morbidity in children living in urban areas.
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Contributors
MCA, AT, WWB, and DJJ designed the study. MCA, MK, GTO, RCM, JEG, and DJJ wrote the manuscript. EW, PL, AC, and MCA performed the statistical analyses and accessed and verified the data. MK, GTO, MAG, RSG, AHL, SL-D, JAP, CMK, GKKH, EMZ, SJT, and LBB are the site principal investigators responsible for sample collection. LMW, SMS, PJG, AT, WWB, and DJJ coordinated the study. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. The authors are responsible for the study design, data collection, data analysis, results interpretation, and manuscript preparation.
Data sharing
Declaration of interests
MCA, MK, GTO, RCM, EW, PL, AC, MAG, RSG, AHL, SL-D, JAP, CMK, GKKH, EMZ, SJT, LBB, WWB, JEG, and DJJ report grants from the US National Institutes of Health (NIH), National Institute of Allergy and Infectious Diseases, and Division of Allergy, Immunology, and Transplantation during the conduct of study. MCA reports personal fees for consulting from Regeneron, outside the submitted work. AHL reports personal fees from Phadia ThermoFisher as consulting honoraria; grants and non-financial support from ResMed–Propeller Health; non-financial support from Revenio; grants and personal fees from Avillion; and personal fees from Labcorp, all outside the submitted work. SL-D reports funding from the National Heart, Lung, and Blood Institute (NHLBI) and the Robert Wood Johnson Foundation. JAP reports provisions of study drug for other asthma studies from GlaxoSmithKline, Boehringer Ingelheim, and Genentech–Novartis. CMK reports royalties from UpToDate. SJT reports grant meetings to support the CAUSE network from NIH–NIAID, payment for episode on biologics in asthma care from Medscape, and personal fees from UpToDate, all outside the submitted work. LBB reports personal fees from GlaxoSmithKline, Genentech–Novartis, Teva, AstraZeneca, WebMD–Medscape, DBV Technologies, Sanofi–Regeneron, OM Pharma, Kinaset, Vertex, and the American Board of Allergy and Immunology; non-financial support from the American Academy of Allergy Asthma and Immunology; and royalties from Elsevier, all outside the submitted work. WWB reports personal fees from Novartis, GlaxoSmithKline, Genentech, Sanofi, AstraZeneca, Regeneron, and Elsevier, outside the submitted work. JEG reports personal fees and stock options from Meissa Vaccines, personal fees from AstraZeneca and Ena Therapeutics, and a patent on methods for production of rhinoviruses. DJJ reports personal fees from Novartis, Avillion, Pfizer, AstraZeneca, and Sanofi; grants and personal fees from GlaxoSmithKline and Regeneron; and grants from NIH–NHLBI, all outside the submitted work. LMW, SMS, PJG, and AT declare no competing interests.
Acknowledgments
We thank all the participants and their families who took part in this study. We thank Prescott Woodruff, Joshua Boyce, and Stephen Durham for assistance with methodological development, advice, and discussion. The study was funded by the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services (contract numbers NO1-AI-25496, NO1-AI-25482, 1UM1AI114271-01, UM2AI117870, and 5UM1AI114271). Additional support was provided by the National Center for Research Resources and National Center for Advancing Translational Sciences, National Institutes of Health (grants NCRR/NIH M01RR00533, NCRR/NIH, 1UL1RR025771, NCRR/NIH UL1RR025741, NCRR/NIH UL1TR000451, UL1RR024982, NCRR/NIH 1UL1RR025780, NCRR/NIH M01RR00071, 1UL1RR024156, NCRR/NIH 5M01RR020359-04, NCRR/NIH UL1RR031988, UL1TRG01422, CTSA Grant UL1RR025741, CTSA Grant UL1TR000150, CTSA Grant UL1TR001422, NIH/NCATS Colorado CTSA UL1 TR002535, NCATS/NIH UL1TR001876, and NIH/CTSA 5UL1TR001425-03). In the ICATA study, Novartis Pharmaceuticals provided the study drug, under a clinical trial agreement with the University of Wisconsin–Madison, Dey Pharma (EpiPens), and SC Johnson (household pest control). None of these companies had a role in the development or approval of the protocol, conduct of the trial, data analysis, manuscript preparation, or the decision to submit for publication. PJG, AT, SMS, and LMW’s co-authorship of this publication does not necessarily constitute endorsement by the National Institute of Allergy and Infectious Diseases, the National Institutes of Health or any other agency of the US Government..
Supplementary Material
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DOI: https://doi.org/10.1016/S2542-5196(22)00302-3
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