GWAS reveals Genetic Susceptibility to Air Pollution-Related Asthma Exacerbations in Children of African Ancestry

Abstract

Background The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, mitigation efforts have yielded mixed results, potentially due to genetic variability in the response to AAP. We hypothesize that common single nucleotide polymorphisms (SNPs) are linked to AAP sensitivity and test this through a Genome Wide Association Study (GWAS).

Methods We selected a cohort of pediatric asthma patients frequently exposed to AAP. Patients experiencing exacerbations immediately following AAP spikes were deemed sensitive. A GWAS compared sensitive versus non-sensitive patients. Findings were validated using data from the All of Us program.

Results Our study included 6,023 pediatric asthma patients. Due to the association between AAP exposure and race, GWAS analysis was feasible only in the African ancestry cohort. Seven risk loci reached genome-wide significance, including four non-intergenic variants. Two variants were validated: rs111970601 associated with sensitivity to CO (odds ratio [OR], 6.58; PL=L1.63L×L10−8; 95% CI, 3.42-12.66) and rs9836522 to PM2.5 sensitivity (OR 0.75; PL=L3,87 ×L10−9; 95% CI, 0.62-0.91).

Interpretation While genetic variants have been previously linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. The identified variants implicate genes with a known role in asthma and established links to AAP. Future research should explore how clinical interventions interact with genetic risk to mitigate the effects of AAP, particularly to enhance health equity for vulnerable populations.

What is already known on this topic The relationship between ambient air pollution (AAP) exposure and asthma exacerbations is well-established. However, efforts to mitigate the impact of AAP on children with asthma have yielded mixed results, potentially due to genetic variability in response to AAP.

What this study adds Using publicly available AAP data, we identify which children with asthma experience exacerbations immediately following spikes in AAP. We then conduct a Genome Wide Association Study (GWAS) comparing these patients with those who have no temporal association between AAP spikes and asthma exacerbations, identifying several Single Nucleotide Polymorphisms (SNPs) significantly associated with AAP sensitivity.

How this study might affect research, practice, or policy While genetic variants have previously been linked to asthma incidence and AAP exposure, this study is the first to link specific SNPs with AAP-related asthma exacerbations. This creates a framework for identifying children especially at risk when exposed to AAP. These children should be targeted with policy interventions to reduce exposure and may require specific treatments to mitigate the effects of ongoing AAP exposure in the interim.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

Research reported in this publication was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number TL1TR001880, the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number T32HL160493, and grant number P30 ES013508 from the National Institute of Environmental Health Sciences of the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

This research was approved by the institutional review board of the Childrens Hospital of Philadelphia under IRB 16-013278.

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Data Availability

Data and code used to analyze the data available from the corresponding author upon reasonable request.

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