Benefits of improved air quality on ageing lungs: impacts of genetics and obesity

Airway inflammation in adolescents and elderly women: Chronic air pollution exposure and polygenic susceptibility

BACKGROUND AND AIM

The fractional exhaled nitric oxide (FeNO) concentration in the exhaled breath is a biomarker for eosinophilic airway inflammation. We explored the interplay between chronic air pollution exposure and polygenic susceptibility to airway inflammation at different critical age stages.

METHODS

Adolescents (15 yr) enrolled in the GINIplus/LISA birth cohorts (n = 2434) and 220 elderly women (75 yr on average) enrolled in the SALIA cohort with FeNO measurements available were investigated. Environmental main effects of the mean of ESCAPE land-use regression air pollutant concentrations within a time window of 15 years and main effects of the polygenic risk scores (PRS) using internal weights from elastic net regression of genome-wide derived single nucleotide polymorphisms were investigated. Furthermore, we examined gene-environment interaction (GxE) effects on natural log-transformed FeNO levels by adjusted linear regression models.

RESULTS

While we observed no significant environmental and polygenic main effects on airway inflammation in either age group, we found robust harmful effects of chronic nitrogen dioxide (NO₂) exposure in the GxE models for elderly women (16.2 % increase in FeNO, p-value = 0.027). Stratified analyses found GxE effects between the PRS and chronic NO₂ exposure in never-smoker elderly women and in adolescents without any inflammatory respiratory conditions.

CONCLUSIONS

FeNO measurement is a useful biomarker to detect higher risk of NO₂-induced eosinophilic airway inflammation in the elderly. There was limited evidence for GxE effects on airway inflammation in adolescents or the elderly. Further GxE studies in subpopulations should be conducted to investigate the assumption that susceptibility to airway inflammation differs between age stages.

Chronic air pollution-induced subclinical airway inflammation and polygenic susceptibility

Background

Air pollutants can activate low-grade subclinical inflammation which further impairs respiratory health. We aimed to investigate the role of polygenic susceptibility to chronic air pollution-induced subclinical airway inflammation.

Methods

We used data from 296 women (69–79 years) enrolled in the population-based SALIA cohort (Study on the influence of Air pollution on Lung function, Inflammation and Aging). Biomarkers of airway inflammation were measured in induced-sputum samples at follow-up investigation in 2007–2010. Chronic air pollution exposures at residential addresses within 15 years prior to the biomarker assessments were used to estimate main environmental effects on subclinical airway inflammation. Furthermore, we calculated internally weighted polygenic risk scores based on genome-wide derived single nucleotide polymorphisms. Polygenic main and gene-environment interaction (GxE) effects were investigated by adjusted linear regression models.

Results

Higher exposures to nitrogen dioxide (NO₂), nitrogen oxides (NO_x), particulate matter with aerodynamic diameters of ≤ 2.5 μm, ≤ 10 μm, and 2.5–10 µm significantly increased the levels of leukotriene (LT)B₄ by 19.7% (p-value = 0.005), 20.9% (p = 0.002), 22.1% (p = 0.004), 17.4% (p = 0.004), and 23.4% (p = 0.001), respectively. We found significant effects of NO₂ (25.9%, p = 0.008) and NO_x (25.9%, p-value = 0.004) on the total number of cells. No significant GxE effects were observed. The trends were mostly robust in sensitivity analyses.

Conclusions

While this study confirms that higher chronic exposures to air pollution increase the risk of subclinical airway inflammation in elderly women, we could not demonstrate a significant role of polygenic susceptibility on this pathway. Further studies are required to investigate the role of polygenic susceptibility.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02179-3.

Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals

BACKGROUND

Impaired lung function is predictive of mortality and is a key component of chronic obstructive pulmonary disease. Lung function has a strong genetic component but is also affected by environmental factors such as increased exposure to air pollution, but the effect of their interactions is not well understood.

OBJECTIVES

To identify interactions between genetic variants and air pollution measures which affect COPD risk and lung function. Additionally, to determine whether previously identified lung function genetic association signals showed evidence of interaction with air pollution, considering both individual effects and combined effects using a genetic risk score (GRS).

METHODS

We conducted a genome-wide gene-air pollution interaction analysis of spirometry measures with three measures of air pollution at home address: particulate matter (PM2.5 & PM10) and nitrogen dioxide (NO2), in approximately 300,000 unrelated European individuals from UK Biobank. We explored air pollution interactions with previously identified lung function signals and determined their combined interaction effect using a GRS.

RESULTS

We identified seven new genome-wide interaction signals (P<5×10-8), and a further ten suggestive interaction signals (P<5×10-7). Additionally, we found statistical evidence of interaction for FEV1/FVC between PM2.5 and previously identified lung function signal, rs10841302, near AEBP2, suggesting increased susceptibility as copies of the G allele increased (but size of the impact was small - interaction beta: -0.363 percentage points, 95% CI: -0.523, -0.203 per 5 µg/m3). There was no observed interaction between air pollutants and the weighted GRS.

DISCUSSION

We carried out the largest genome-wide gene-air pollution interaction study of lung function and identified potential effects of clinically relevant size and significance. We observed up to 440 ml lower lung function for certain genotypes when exposed to mean levels of outdoor air pollution, which is approximately equivalent to nine years of average normal loss of lung function in adults.

Reduced ambient PM2.5, better lung function, and decreased risk of chronic obstructive pulmonary disease

BACKGROUND

Several studies reported that long-term exposure to fine particulate matter (PM_2.5) was associated with an increased risk of chronic obstructive pulmonary disease (COPD). It remains unclear whether reduced PM_2.5 can decrease the risk of COPD development.

OBJECTIVE

To investigate the associations of dynamic changes (including deterioration and improvement) in long-term exposure to ambient PM_2.5 with changes in lung function and the incidence of COPD.

METHODS

A total of 133,119 adults (aged 18 years or older) were recruited in Taiwan between 2001 and 2014. All participants underwent at least two standard medical examinations including spirometry test. We estimated PM_2.5 concentrations using a high-resolution (1 km²) satellite-based spatio-temporal model. The change in PM_2.5 (ΔPM_2.5) was defined as the difference in concentration of PM_2.5 between the respective visit and the previous visit. We used a multivariable mixed linear model and time-varying Cox model to investigate the associations of change in PM_2.5 with annual change of lung function and the incidence of COPD, respectively.

RESULT

The PM_2.5 concentration in Taiwan increased during 2002-2004 and began to decrease around 2005. Every 5-µg/m³/year decrease in the annual change of PM_2.5 (i.e., ΔPM_2.5/year of 5 µg/m³/year) was associated with an average increase of 19.93 mL/year (95 %CI: 17.42,22.43) in forced expiratory volume in 1 s (FEV₁), 12.76 mL/year (95 %CI: 9.84,15.66) in forced vital capacity (FVC), 70.22 mL/s/year (95 %CI: 64.69,76.16) in midexpiratory flow between 25 and 75% of the forced vital capacity (MEF25-75), 0.27%/year (95 %CI: 0.21%, 0.32%) in FEV₁/FVC/year. Every 5 µg/m³ decrease in PM_2.5 (i.e., ΔPM_2.5 of 5 µg/m³) was associated with a 12% (95 %CI: 7%, 17%) reduced risk of COPD development. The stratified and sensitivity analyses generally yielded similar results.

CONCLUSION

An improvement in PM_2.5 pollution exposure was associated with an attenuated decline in lung function parameters of FEV₁, FVC, MEF25-75, and FEV₁/FVC, and a decreased risk of COPD development. Our findings suggest that strategies aimed at reducing air pollution may effectively combat the risk of COPD development.

Associations of Reduced Ambient PM2.5 Level With Lower Plasma Glucose Concentration and Decreased Risk of Type 2 Diabetes in Adults: A Longitudinal Cohort Study

It remains unknown whether reduced air pollution levels can prevent type 2 diabetes mellitus. In this study, we investigated the associations between dynamic changes in long-term exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter ≤2.5 μm (PM2.5), and changes in fasting plasma glucose (FPG) levels and incidence of type 2 diabetes. A total of 151,398 adults (ages ≥18 years) were recruited in Taiwan between 2001 and 2014. All participants were followed up for a mean duration of 5.0 years. Change in PM2.5 (ΔPM2.5) was defined as the value at a follow-up visit minus the corresponding value at the immediately preceding visit. The PM2.5 concentration in Taiwan increased during 2002-2004 and began to decrease in 2005. Compared with participants with little or no change in PM2.5 exposure, those with the largest decrease in PM2.5 had a decreased FPG level (β = -0.39, 95% confidence interval: -0.47, -0.32) and lower risk of type 2 diabetes (hazard ratio = 0.86, 95% confidence interval: 0.80, 0.93). The sensitivity analysis and analyses stratified by sex, age, body mass index, smoking, alcohol drinking, and hypertension generally yielded similar results. Improved PM2.5 air quality is associated with a better FPG level and a decreased risk of type 2 diabetes development.

The mediating role of lung function on air pollution-induced cardiopulmonary mortality in elderly women: The SALIA cohort study with 22-year mortality follow-up

BACKGROUND

Air pollution exposure is associated with reduced lung function and increased cardio-pulmonary mortality (CPM).

OBJECTIVES

We analyzed the potential mediating effect of reduced lung function on the association between air pollution exposure and CPM.

METHODS

We used data from the German SALIA cohort including 2527 elderly women (aged 51-56 years at baseline 1985-1994) with 22-year follow-up to CPM. Exposures to PM₁₀, PM_2.5, PM_2.5 absorbance, NO₂ and NO_x were assessed by land-use regression modelling and back-extrapolated to estimate exposures at baseline. Lung function (FVC, FEV₁) was measured by spirometry and transformed to GLI z-scores. Adjusted Cox proportional hazards and causal proportional hazards mediation analysis models were fitted.

RESULTS

The survival analysis showed that reduced lung function (z-scores of FVC or FEV₁ below 5% predicted) reflected significantly lower survival probability from CPM (p < 0.0001). Longterm exposures to NO_x and NO₂ were associated with increased risks of CPM (eg. HR = 1.215; 95%CI: 1.017-1.452 for IQR increase in NO_x and HR = 1.209; 95%CI: 1.011-1.445 for IQR increase in NO₂) after adjusting for reduced lung function and additional covariates. The associations of PM_2.5 absorbance and CPM remained significant in models adjusted for FEV₁/FVC, but the associations with PM₁₀ and PM_2.5 were not significant. The mediation analysis showed significant indirect effects of NO₂ and NO_x on CPM mediated through reduced FEV₁ and FVC. The largest indirect effects were found for exposures to NO₂ (HR = 1.037; 95%CI: 1.005-1.070) and NO_x (HR = 1.028; 95%CI: 1.004-1.052) mediated through reduced FVC. The mediated proportion effect ranged from 13.9% to 19.6% in fully adjusted models.

DISCUSSION

This study provides insights into the mechanism of reduced lung function in association between long-term air pollution exposure and CPM. The mediated effect was substantial for exposure to nitrogen oxides (NO_x and NO₂), but less pronounced for PM₁₀ and PM_2.5.

Genetic susceptibility to asthma increases the vulnerability to indoor air pollution

INTRODUCTION

Indoor air pollution and maternal smoking during pregnancy are associated with respiratory symptoms in infants, but little is known about the direct association with lung function or interactions with genetic risk factors. We examined associations of exposure to indoor particulate matter with a 50% cut-off aerodynamic diameter of 10 µm (PM₁₀) and maternal smoking with infant lung function and the role of gene-environment interactions.

METHODS

Data from the Drakenstein Child Health Study, a South African birth cohort, were analysed (n=270). Lung function was measured at 6 weeks and 1 year of age, and lower respiratory tract infection episodes were documented. We measured pre- and postnatal PM₁₀ exposures using devices placed in homes, and prenatal tobacco smoke exposure using maternal urine cotinine levels. Genetic risk scores determined from associations with childhood-onset asthma in the UK Biobank were used to investigate effect modifications.

RESULTS

Pre- and postnatal exposure to PM₁₀ as well as maternal smoking during pregnancy were associated with reduced lung function at 6 weeks and 1 year as well as with lower respiratory tract infection in the first year. Due to a significant interaction between the genetic risk score and prenatal exposure to PM₁₀, infants carrying more asthma-related risk alleles were more susceptible to PM₁₀-associated reduced lung function (p_interaction=0.007). This interaction was stronger in infants with Black African ancestry (p_interaction=0.001) and nonexistent in children with mixed ancestry (p_interaction=0.876).

CONCLUSIONS

PM₁₀ and maternal smoking exposures were associated with reduced lung function, with a higher susceptibility for infants with an adverse genetic predisposition for asthma that also depended on the infant's ancestry.

Methodological challenges in constructing DNA methylation risk scores

Polygenic approaches often access more variance of complex traits than is possible by single variant approaches. For genotype data, genetic risk scores (GRS) are widely used for risk prediction as well as in association and interaction studies. Recently, interest has been growing in transferring GRS approaches to DNA methylation data (methylation risk scores, MRS), which can be used 1) as biomarkers for environmental exposures, 2) in association analyses in which single CpG sites do not achieve significance, 3) as dimension reduction approach in interaction and mediation analyses, and 4) to predict individual risks of disease or treatment success. Most GRS approaches can directly be transferred to methylation data. However, since methylation data is more sensitive to confounding, e.g. by age and tissue, it is more complex to find appropriate external weights. In this review, we will outline the adaption of current GRS approaches to methylation data and highlight occurring challenges.