Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Melbourne, Carl A., Mesut Erzurumluoglu, A., Shrine, Nick, Chen, Jing, Tobin, Martin D., Hansell, Anna L., Wain, Louise V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science 2022
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
_version_ 1784629128134131712
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
work_keys_str_mv AT melbournecarla genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals
AT mesuterzurumluoglua genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals
AT shrinenick genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals
AT chenjing genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals
AT tobinmartind genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals
AT hansellannal genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals
AT wainlouisev genomewidegeneairpollutioninteractionanalysisoflungfunctionin300000individuals