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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739564/ https://www.ncbi.nlm.nih.gov/pubmed/34923368 http://dx.doi.org/10.1016/j.envint.2021.107041 |
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author | Melbourne, Carl A. Mesut Erzurumluoglu, A. Shrine, Nick Chen, Jing Tobin, Martin D. Hansell, Anna L. Wain, Louise V. |
author_facet | Melbourne, Carl A. Mesut Erzurumluoglu, A. Shrine, Nick Chen, Jing Tobin, Martin D. Hansell, Anna L. Wain, Louise V. |
author_sort | Melbourne, Carl A. |
collection | PubMed |
description | 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 (PM(2.5) & PM(10)) and nitrogen dioxide (NO(2)), 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 ([Formula: see text]), and a further ten suggestive interaction signals ([Formula: see text]). Additionally, we found statistical evidence of interaction for FEV(1)/FVC between PM(2.5) 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. |
format | Online Article Text |
id | pubmed-8739564 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-87395642022-01-15 Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals Melbourne, Carl A. Mesut Erzurumluoglu, A. Shrine, Nick Chen, Jing Tobin, Martin D. Hansell, Anna L. Wain, Louise V. Environ Int Article 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 (PM(2.5) & PM(10)) and nitrogen dioxide (NO(2)), 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 ([Formula: see text]), and a further ten suggestive interaction signals ([Formula: see text]). Additionally, we found statistical evidence of interaction for FEV(1)/FVC between PM(2.5) 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. Elsevier Science 2022-01-15 /pmc/articles/PMC8739564/ /pubmed/34923368 http://dx.doi.org/10.1016/j.envint.2021.107041 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Melbourne, Carl A. Mesut Erzurumluoglu, A. Shrine, Nick Chen, Jing Tobin, Martin D. Hansell, Anna L. Wain, Louise V. Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
title | Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
title_full | Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
title_fullStr | Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
title_full_unstemmed | Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
title_short | Genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
title_sort | genome-wide gene-air pollution interaction analysis of lung function in 300,000 individuals |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739564/ https://www.ncbi.nlm.nih.gov/pubmed/34923368 http://dx.doi.org/10.1016/j.envint.2021.107041 |
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