Genome-wide gene-air pollution interaction analysis of lung function in 300, 000 individuals. (15th January 2022)

• Record Type: Journal Article
• Authors: Melbourne, Carl A.; Mesut Erzurumluoglu, A.; Shrine, Nick; Chen, Jing; Tobin, Martin D.; Hansell, Anna L.; Wain, Louise V.
• Is Part Of: Environment international. Volume 159(2022)
• Publication Date: 2022-01-15
• Subjects: Gene-air pollution interactions -- Air pollution -- Genome-wide -- Lung function -- Chronic Obstructive Pulmonary Disease -- UK Biobank; Environmental protection -- Periodicals; Environmental health -- Periodicals; Environmental monitoring -- Periodicals; Environmental Monitoring -- Periodicals; Environnement -- Protection -- Périodiques; Hygiène du milieu -- Périodiques; Environnement -- Surveillance -- Périodiques; Environmental health; Environmental monitoring; Environmental protection; Periodicals; 333.705
• DOI: 10.1016/j.envint.2021.107041
• Languages: English
• ISSNs: 0160-4120

Abstract

Graphical abstract: Highlights: Gene-air pollution interaction effects on lung function are poorly understood. Seven new potential gene-air pollution interaction signals identified. Interaction effects identified are large enough to be clinically relevant. Observed interactions include one previously identified lung function signal. High-risk genetic subgroups potentially more susceptible to outdoor air pollution. Abstract: 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/m 3 ). 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.