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Age by Single Nucleotide Polymorphism Interactions on Bronchodilator Response in Asthmatics
Kirsten Voorhies1, Joanne E Sordillo1, Michael McGeachie2
1Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA 02215, USA.
Journal of Personalized Medicine
|January 22, 2021
Summary
Age may influence how genetic variations affect asthma patients' response to short-acting beta2-agonists. This study investigated age-related genetic interactions impacting bronchodilator response (BDR) in asthma.
Area of Science:
- Pharmacogenomics
- Asthma Research
- Genetic Epidemiology
Background:
- Short-acting beta2-agonists are crucial for asthma management.
- The influence of age on genetic associations with bronchodilator response (BDR) in asthma is not well understood.
- Identifying age-modified genetic effects can personalize asthma treatment.
Purpose of the Study:
- To determine if age modifies the association between single nucleotide polymorphisms (SNPs) and BDR to beta2-agonists in asthma patients.
- To investigate age-SNP interactions for BDR across multiple cohorts.
Main Methods:
- Genome-wide interaction study (GWIS) analyzing SNP by age interactions with BDR in three cohorts (n=892).
- Fixed-effect meta-analysis to combine GWIS results.
- Examination of previously identified BDR SNPs and candidate genes from genome-wide association studies (GWAS) for age interactions.
Main Results:
- No genome-wide significant SNP by age interactions for BDR were detected at the 5 × 10-8 threshold.
- Three SNP by age interactions, including one within *PRAG1* (rs4840337), reached suggestive significance (5 × 10-6) and replicated at p < 0.05.
- Marginally significant age interactions (p < 0.05) were observed for three SNPs in candidate genes: rs10476900 (near *ADRB2*), rs10827492 (*CREM*), and rs72646209 (*NCOA3*).
Conclusions:
- Age may be a significant modifier of genetic associations influencing bronchodilator response in asthma.
- Further research is warranted to elucidate the role of age in asthma pharmacogenomics.
- These findings could contribute to age-stratified genetic risk prediction for asthma treatment response.
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