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Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
Published on: June 21, 2018
Pharmacogenetics of asthma.
John J Lima1, Kathryn V Blake, Kelan G Tantisira
1Centers for Pediatric Clinical Pharmacology and Pharmacogenetics, Nemours Children's Clinic, Jacksonville, Florida 32207, USA. Jlima@nemours.org
Current Opinion in Pulmonary Medicine
|December 17, 2008
Summary
Genetic variations influence how patients respond to asthma medications like bronchodilators and corticosteroids. Identifying these genetic markers is key to developing personalized asthma treatment strategies.
Area of Science:
- Pharmacogenetics and pharmacogenomics
- Genetics of asthma treatment response
Background:
- Patient response to asthma medications (bronchodilators, inhaled corticosteroids, leukotriene modifiers) shows significant variability.
- Genetic variations are a key factor contributing to this heterogeneity in drug response.
Purpose of the Study:
- To review and update the current understanding of pharmacogenetics and pharmacogenomics for common asthma drugs.
- To highlight genetic influences on patient response to different asthma medication classes.
Main Methods:
- Review of early and recent studies, including genome-wide association studies (GWAS).
- Analysis of genetic variants associated with drug response and safety.
- Examination of gene variants impacting lung function, airway responsiveness, and exacerbations.
Main Results:
- ADRB2 Gly16Arg genotype linked to bronchodilator response and asthma worsening with beta-agonists in early studies.
- GWAS implicate other genes in bronchodilator response heterogeneity; continuous beta-agonist safety needs more research.
- Variants in CRHR1, TBX21, FCER2, ALOX5, LTA4H, LTC4S, ABCC1, CYSLTR2, and SLCO2B1 are associated with variable responses to inhaled corticosteroids and leukotriene modifiers.
Conclusions:
- Discovery of novel genetic variants influencing response heterogeneity supports further research.
- Future studies should incorporate gene expression and GWAS.
- Predictive genomic models are essential for advancing personalized asthma medicine.
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