Pharmacogenetic analysis of GLCCI1 in three north European pediatric asthma populations with a reported use of inhaled corticosteroids

Pharmacogenomics and Pediatric Asthmatic Medications

Asthma is a respiratory condition often stemming from childhood, characterized by difficulty breathing and/or chest tightness. Current treatment options for both adults and children include beta-2 agonists, inhaled corticosteroids (ICS), and leukotriene modifiers (LTM). Despite recommendations by the Global Initiative for Asthma, a substantial number of patients are unresponsive to treatment and unable to control symptoms. Pharmacogenomics have increasingly become the front line of precision medicine, especially with the recent use of candidate gene and genome- wide association studies (GWAS). Screening patients preemptively could likely decrease adverse events and therapeutic failure. However, research in asthma, specifically in pediatrics, has been low. Although numerous adult trials have evaluated the impact of pharmacogenomics and treatment response, the lack of evidence in children has hindered progress towards clinical application. This review aims to discuss the impact of genetic variability and response to asthmatic medications in the pediatric population.

Effects of STIP1 and GLCCI1 polymorphisms on the risk of childhood asthma and inhaled corticosteroid response in Chinese asthmatic children

Background

Asthma is a common chronic lung disease in children. We aimed to determine the associations between stress-induced phosphoprotein 1 (STIP1) and glucocorticoid-induced transcript 1 (GLCCI1) polymorphisms and susceptibility of childhood asthma and inhaled corticosteroid (ICS) response in children.

Methods

A total of 263 Chinese Han asthmatic children were recruited from the Xiangya Hospital, Central South University. Pulmonary function tests were performed before the treatment and 3 months after the treatment. One hundred fifty non-asthmatic children were recruited. Each participant’s DNA was extracted from the peripheral blood and Method of MassARRAY was used to genotype the single-nucleotide polymorphisms (SNPs).

Results

STIP1 rs2236647 wild-type homozygote (CC) was associated with increased asthma risk of children (OR = 1.858, 95% CI:1.205–2.864), but not associated with the ICS response. GLCCI1 rs37969, rs37972 and rs37973 polymorphisms were not associated with the risk of childhood asthma. However, rs37969 mutant genotypes (TT/GT) were significantly associated with less improvement in PD20 (p = 0.028). We also found significant associations between rs37969, rs37972 and rs37973 mutant genotypes and less improvement in maximal midexpiratory flow (MMEF) after ICS treatment for 3 months (p = 0.036, p = 0.010 and p = 0.003, respectively).

Conclusions

STIP1 rs2236647 was associated with asthma risk of children and GLCCI1 rs37969 mutant genotypes were associated with less improvement in airway hyper-responsiveness. GLCCI1 rs37969, rs37972 and rs37973 polymorphisms might be associated with pulmonary function in childhood asthma patients after ICS treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-020-01332-2.

Insights into glucocorticoid responses derived from omics studies

Glucocorticoid drugs are commonly used in the treatment of several conditions, including autoimmune diseases, asthma and cancer. Despite their widespread use and knowledge of biological pathways via which they act, much remains to be learned about the cell type-specific mechanisms of glucocorticoid action and the reasons why patients respond differently to them. In recent years, human and in vitro studies have addressed these questions with genomics, transcriptomics and other omics approaches. Here, we summarize key insights derived from omics studies of glucocorticoid response, and we identify existing knowledge gaps related to mechanisms of glucocorticoid action that future studies can address.

Impact of Gene Expression Associated with Glucocorticoid-Induced Transcript 1 (GLCCI1) on Severe Asthma and Future Exacerbation

Genetic variations in glucocorticoid-induced transcript 1 (GLCCI1) have been associated with the response to corticosteroid treatment. However, the associations of GLCCI1 polymorphisms or gene expression with the prognosis of asthma and pathophysiological factors related to steroid insensitivity remain unclear. We sought to investigate the associations of GLCCI1, nuclear factor (erythroid-derived 2)-like 2 (Nrf2), and histone deacetylase 2 (HDAC2) mRNA expression levels and the GLCCI1 rs37973 polymorphism with asthma severity and future exacerbation in patients with asthma. Subjects included 25 patients with severe asthma and 127 patients with nonsevere asthma. mRNA expression levels in peripheral blood mononuclear cells were measured and evaluated as predictors of severe asthma using receiver operating characteristic (ROC) analysis. The hazard ratios of the mRNA expression levels for time to first exacerbation in the 1-year follow-up period were calculated. GLCCI1, Nrf2, and HDAC2 mRNA expression levels were significantly lower in patients with severe asthma than in patients with nonsevere asthma and could predict severe asthma with an area under the ROC curve of 0.68, 0.71, and 0.65, respectively. In contrast, no relationship was found between the GLCCI1 rs37973 polymorphism and severe asthma. The hazard ratios for asthma exacerbation in patients with low GLCCI1, Nrf2, and HDAC2 mRNA expression levels were 3.24 (95% confidence interval, 1.42-7.40), 3.13 (1.37-7.16), and 2.98 (1.22-7.25), respectively. Patients with severe asthma could be distinguished by lower GLCCI1, Nrf2, and HDAC2 mRNA levels in peripheral blood cells, and all of these gene signatures could predict future asthma exacerbations.

Effects of Glucocorticoid-Induced Transcript 1 Gene Deficiency on Glucocorticoid Activation in Asthmatic Mice

Background:

Glucocorticoid (GC) is the first-line therapy for asthma, but some asthmatics are insensitive to it. Glucocorticoid-induced transcript 1 gene (GLCCI1) is reported to be associated with GCs efficiency in asthmatics, while its exact mechanism remains unknown.

Methods:

A total of 30 asthmatic patients received fluticasone propionate for 12 weeks. Forced expiratory volume in 1 s (FEV₁) and GLCCI1 expression were detected. Asthma model was constructed in wild-type and GLCCI1 knockout (GLCCI1^-/-) mice. Glucocorticoid receptor (GR) and mitogen-activated protein kinase phosphatase 1 (MKP-1) expression were detected by polymerase chain reaction and Western blotting (WB). The phosphorylation of p38 mitogen-activated protein kinase (MAPK) was also detected by WB.

Results:

In asthmatic patients, the change of FEV₁ was well positively correlated with change of GLCCI1 expression (r = 0.430, P = 0.022). In animal experiment, GR and MKP-1 mRNA levels were significantly decreased in asthmatic mice than in control mice (wild-type: GR: 0.769 vs. 1.000, P = 0.022; MKP-1: 0.493 vs. 1.000, P < 0.001. GLCCI1^-/-: GR: 0.629 vs. 1.645, P < 0.001; MKP-1: 0.377 vs. 2.146, P < 0.001). Hydroprednisone treatment significantly increased GR and MKP-1 mRNA expression levels than in asthmatic groups; however, GLCCI1^-/- asthmatic mice had less improvement (wild-type: GR: 1.517 vs. 0.769, P = 0.023; MKP-1: 1.036 vs. 0.493, P = 0.003. GLCCI1^-/-: GR: 0.846 vs. 0.629, P = 0.116; MKP-1: 0.475 vs. 0.377, P = 0.388). GLCCI1^-/- asthmatic mice had more obvious phosphorylation of p38 MAPK than wild-type asthmatic mice (9.060 vs. 3.484, P < 0.001). It was still higher even though after hydroprednisone treatment (6.440 vs. 2.630, P < 0.001).

Conclusions:

GLCCI1 deficiency in asthmatic mice inhibits the activation of GR and MKP-1 and leads to more obvious phosphorylation of p38 MAPK, leading to a decremental sensitivity to GCs.

Trial Registration:

ChiCTR.org.cn, ChiCTR-RCC-13003634; http://www.chictr.org.cn/showproj.aspx?proj=5926.

Genetic associations of the response to inhaled corticosteroids in asthma: a systematic review

There is wide variability in the response to inhaled corticosteroids (ICS) in asthma. While some of this heterogeneity of response is due to adherence and environmental causes, genetic variation also influences response to treatment and genetic markers may help guide treatment. Over the past years, researchers have investigated the relationship between a large number of genetic variations and response to ICS by performing pharmacogenomic studies. In this systematic review we will provide a summary of recent pharmacogenomic studies on ICS and discuss the latest insight into the potential functional role of identified genetic variants. To date, seven genome wide association studies (GWAS) examining ICS response have been published. There is little overlap between identified variants and methodologies vary largely. However, in vitro and/or in silico analyses provide additional evidence that genes discovered in these GWAS (e.g. GLCCI1, FBXL7, T gene, ALLC, CMTR1) might play a direct or indirect role in asthma/treatment response pathways. Furthermore, more than 30 candidate-gene studies have been performed, mainly attempting to replicate variants discovered in GWAS or candidate genes likely involved in the corticosteroid drug pathway. Single nucleotide polymorphisms located in GLCCI1, NR3C1 and the 17q21 locus were positively replicated in independent populations. Although none of the genetic markers has currently reached clinical practise, these studies might provide novel insights in the complex pathways underlying corticosteroids response in asthmatic patients.

Glucocorticoid-Induced Transcription Factor 1 (GLCCI1) Variant Impacts the Short-Term Response to Intranasal Corticosteroids in Chinese Han Patients with Seasonal Allergic Rhinitis

Background

Genetic correlations with the response to intranasal corticosteroids (INCS) in seasonal allergic rhinitis (SAR) treatment are unknown. This study aimed to evaluate the role of gene polymorphisms in the response to INCS in Chinese Han patients with moderate to severe SAR.

Material/Methods

In this study, 286 Chinese Han patients with SAR were genotyped for 4 candidate genes: the glucocorticosteroid receptor (NR3C1) gene, glucocorticoid-induced transcription factor 1 (GLCCI1) gene, T-box 21 gene (TBX21), and ATP binding cassette subfamily B member 1 (ABCB1) gene. Patients were treated with INCS for 4 weeks. The total nasal symptom score (TNSS), total ocular symptom score (TOSS), and visual analogue scale (VAS) score were assessed at baseline and on week 4. The primary endpoint was the effective rate after 4 weeks of INCS therapy.

Results

In addition to the known contributing factors, one genotype of GLCCI1, namely, rs37973, was significantly associated with the INCS response (OR=0.598, 95% confidence interval: 0.41 to 0.87, P=0.007). The effective rate of the GG group was lower than those of the AA and AG groups (AA vs. GG: 73.7% vs. 51.6%, P=0.007; AG vs. GG: 78.8% vs. 51.6%, P=0.000). In addition, the TNSS, TOSS, and VAS were higher for the patients in the GG group than for those in the AA and AG groups on week 4.

Conclusions

The GLCCI1 rs37973 variant is a risk factor for glucocorticoid resistance in Chinese patients with SAR who receive short-term INCS treatment.

Variants in genes coding for glutathione S-transferases and asthma outcomes in children

Our hypothesis was that children with mutations in genes coding for glutathione S-transferases (GST) have worse asthma outcomes compared with children with active type genotype. Data were collected in five populations. The rs1695 single nucleotide polymorphism (GSTP1) was determined in all cohorts (3692 children) and GSTM1 and GSTT1 null genotype were determined in three cohorts (2362 children). GSTT1 null (but not other genotypes) was associated with a minor increased risk for asthma attack and there were no significant associations between GST genotypes and asthma severity. Interactions between GST genotypes and SHS exposure or asthma severity with the study outcomes were nonsignificant. We find no convincing evidence that the GST genotypes studied are related to asthma outcomes.

Pharmacogenetics of asthma: toward precision medicine

PURPOSE OF REVIEW

Although currently available drugs to treat asthma are effective in most patients, a proportion of patients do not respond or experience side-effects; which is partly genetically determined. Pharmacogenetics is the study of how genetic variations influence drug response. In this review, we summarize prior results and recent studies in pharmacogenetics to determine if we can use genetic profiles for personalized treatment of asthma.

RECENT FINDINGS

The field of pharmacogenetics has moved from candidate gene studies in single populations toward genome-wide association studies and meta-analysis of multiple studies. New technologies have been used to enrich results, and an expanding number of genetic loci have been associated with therapeutic responses to asthma drugs. Prospective, genotype-stratified treatment studies have been conducted for β2-agonists, showing attenuated response in children carrying the Arg16 variant in the β2-adrenoreceptor gene.

SUMMARY

Although there has been much progress, many findings have not been replicated and currently known genetic loci only account for a fraction of variability in drug response. More research is necessary to translate into clinical practice. A polygenic predictive approach integrated in complex networks with other 'omics' technologies could aid to achieve this goal. Finally, to change clinical practice, studies that compare precision medicine with traditional medicine are needed.

Systems biology and in vitro validation identifies family with sequence similarity 129 member A (FAM129A) as an asthma steroid response modulator

BACKGROUND

Variation in response to the most commonly used class of asthma controller medication, inhaled corticosteroids, presents a serious challenge in asthma management, particularly for steroid-resistant patients with little or no response to treatment.

OBJECTIVE

We applied a systems biology approach to primary clinical and genomic data to identify and validate genes that modulate steroid response in asthmatic children.

METHODS

We selected 104 inhaled corticosteroid-treated asthmatic non-Hispanic white children and determined a steroid responsiveness endophenotype (SRE) using observations of 6 clinical measures over 4 years. We modeled each subject's cellular steroid response using data from a previously published study of immortalized lymphoblastoid cell lines under dexamethasone (DEX) and sham treatment. We integrated SRE with immortalized lymphoblastoid cell line DEX responses and genotypes to build a genome-scale network using the Reverse Engineering, Forward Simulation modeling framework, identifying 7 genes modulating SRE.

RESULTS

Three of these genes were functionally validated by using a stable nuclear factor κ-light-chain-enhancer of activated B cells luciferase reporter in A549 human lung epithelial cells, IL-1β cytokine stimulation, and DEX treatment. By using small interfering RNA transfection, knockdown of family with sequence similarity 129 member A (FAM129A) produced a reduction in steroid treatment response (P < .001).

CONCLUSION

With this systems-based approach, we have shown that FAM129A is associated with variation in clinical asthma steroid responsiveness and that FAM129A modulates steroid responsiveness in lung epithelial cells.

Treatment response heterogeneity in asthma: the role of genetic variation

INTRODUCTION

Asthmatic patients show a large heterogeneity in response to asthma medication. Rapidly evolving genotyping technologies have led to the identification of various genetic variants associated with treatment outcomes. Areas covered: This review focuses on the current knowledge of genetic variants influencing treatment response to the most commonly used asthma medicines: short- and long-acting beta-2 agonists (SABA/LABA), inhaled corticosteroids (ICS) and leukotriene modifiers. This review shows that various genetic variants have been identified, but none are currently used to guide asthma treatment. One of the most promising genetic variants is the Arg16 variant in the ADRB2 gene to guide LABA treatment in asthmatic children. Expert commentary: Poor replication of initially promising results and the low fraction of variability accounted for by single genetic variants inhibit pharmacogenetic findings to reach the asthma clinic. Nevertheless, the identification of genetic variation influencing treatment response does provide more insights in the complex processes underlying response and might identify novel targets for treatment. There is a need to report measures of clinical validity, to perform precision-medicine guided trials, as well as to understand how genetic variation interacts with environmental factors. In addition, systems biology approaches might be able to show a more complete picture of these complex interactions.

What is precision medicine?

The term “precision medicine” has become very popular over recent years, fuelled by scientific as well as political perspectives. Despite its popularity, its exact meaning, and how it is different from other popular terms such as “stratified medicine”, “targeted therapy” or “deep phenotyping” remains unclear. Commonly applied definitions focus on the stratification of patients, sometimes referred to as a novel taxonomy, and this is derived using large-scale data including clinical, lifestyle, genetic and further biomarker information, thus going beyond the classical “signs-and-symptoms” approach.

While these aspects are relevant, this description leaves open a number of questions. For example, when does precision medicine begin? In which way does the stratification of patients translate into better healthcare? And can precision medicine be viewed as the end-point of a novel stratification of patients, as implied, or is it rather a greater whole?

To clarify this, the aim of this paper is to provide a more comprehensive definition that focuses on precision medicine as a process. It will be shown that this proposed framework incorporates the derivation of novel taxonomies and their role in healthcare as part of the cycle, but also covers related terms.

Rationale and design of the multiethnic Pharmacogenomics in Childhood Asthma consortium

AIM

International collaboration is needed to enable large-scale pharmacogenomics studies in childhood asthma. Here, we describe the design of the Pharmacogenomics in Childhood Asthma (PiCA) consortium.

MATERIALS & METHODS

Investigators of each study participating in PiCA provided data on the study characteristics by answering an online questionnaire.

RESULTS

A total of 21 studies, including 14,227 children/young persons (58% male), from 12 different countries are currently enrolled in the PiCA consortium. Fifty six percent of the patients are Caucasians. In total, 7619 were inhaled corticosteroid users. Among patients from 13 studies with available data on asthma exacerbations, a third reported exacerbations despite inhaled corticosteroid use. In the future pharmacogenomics studies within the consortium, the pharmacogenomics analyses will be performed separately in each center and the results will be meta-analyzed.

CONCLUSION

PiCA is a valuable platform to perform pharmacogenetics studies within a multiethnic pediatric asthma population.

Impact of the genetic variants of GLCCI1 on clinical features of asthmatic patients

BACKGROUND

Several gene variants are associated with a response to an inhaled corticosteroids (ICSs) treatment in patients with bronchial asthma. A variant of the glucocorticoid-induced transcript 1 (GLCCI1) genes has previously been associated with decreased lung function improvement upon treatment with ICSs in patients with bronchial asthma. Another report has also demonstrated that this genetic biomarker did not influence the change in flow volume in 1 second. However, no studies have considered the treatment content and the GLCCI1 variants. We were able to determine the relationship between the pulmonary function and clinical features and the variant of the GLCCI1 in Japanese asthmatic patients receiving long-term ICS treatment.

MATERIALS AND METHODS

In this study, 405 patients with bronchial asthma, who were receiving ICS and living in Japan, were recruited, genotyped and underwent pulmonary function tests. To identify the GLCCI1 protein expression cells, endobronchial biopsy specimens were examined.

RESULTS

We found that the pulmonary function was not significantly different in the homozygotes compared to the wild types. Also, the homozygotes increased the risk of a sustained step-up of the asthma treatment when compared to the wild type and heterozygotes. GLCCI1-positive cells were localized to the bronchial epithelial cells. The amount of GLCCI1 protein that cultured epithelial cells harboring GLCCI1 variants produced was less than the GLCCI1 wild type in the presence of a corticosteroid.

CONCLUSIONS

A worsening of pulmonary function caused by GLCCI1 variants could be prevented due to recently used medications based on new action mechanisms.

Pharmacogenomics of inhaled corticosteroids and leukotriene modifiers: a systematic review

BACKGROUND

Pharmacogenetics studies of anti-inflammatory medication of asthma have expanded rapidly in recent decades, but the clinical value of their findings remains limited.

OBJECTIVE

To perform a systematic review of pharmacogenomics and pharmacogenetics of inhaled corticosteroids (ICS) and leukotriene modifiers (LTMs) in patients with asthma.

METHODS

Articles published between 1999 and June 2015 were searched using PubMed and EMBASE. Pharmacogenomics/genetics studies of patients with asthma using ICS or LTMs were included if ≥1 of the following outcomes were studied: lung function, exacerbation rates or asthma symptoms. The studies of Single Nucleotide Polymorphisms (SNPs) that had been replicated at least once were assessed in more detail.

RESULTS

In total, 59 publications were included in the systematic review: 26 addressed LTMs (including two genomewide Genome-Wide association studies [GWAS]) and 33 addressed ICS (including four GWAS). None of the GWAS reported similar results. Furthermore, none of the SNPs assessed in candidate gene studies were identified in a GWAS. No consistent reports were found for candidate gene studies of LTMs. In candidate gene studies of ICS, the most consistent results were found for rs28364072 in FCER2. This SNP was associated with all three outcomes of poor response, and the largest effect was reported with the risk of exacerbations (hazard ratio, 3.95; 95% CI, 1.64-9.51).

CONCLUSION AND CLINICAL RELEVANCE

There is a lack of replication of genetic variants associated with poor ICS or LTM response. The most consistent results were found for the FCER2 gene [encoding for a low-affinity IgE receptor (CD23)] and poor ICS response. Larger studies with well-phenotyped patients are needed to assess the clinical applicability of ICS and LTM pharmacogenomics/genetics.

Pharmacogenomics in Pediatric Patients: Towards Personalized Medicine

It is well known that drug responses differ among patients with regard to dose requirements, efficacy, and adverse drug reactions (ADRs). The differences in drug responses are partially explained by genetic variation. This paper highlights some examples of areas in which the different responses (dose, efficacy, and ADRs) are studied in children, including cancer (cisplatin), thrombosis (vitamin K antagonists), and asthma (long-acting β2 agonists). For childhood cancer, the replication of data is challenging due to a high heterogeneity in study populations, which is mostly due to all the different treatment protocols. For example, the replication cohorts of the association of variants in TPMT and COMT with cisplatin-induced ototoxicity gave conflicting results, possibly as a result of this heterogeneity. For the vitamin K antagonists, the evidence of the association between variants in VKORC1 and CYP2C9 and the dose is clear. Genetic dosing models have been developed, but the implementation is held back by the impossibility of conducting a randomized controlled trial with such a small and diverse population. For the long-acting β2 agonists, there is enough evidence for the association between variant ADRB2 Arg16 and treatment response to start clinical trials to assess clinical value and cost effectiveness of genotyping. However, further research is still needed to define the different asthma phenotypes to study associations in comparable cohorts. These examples show the challenges which are encountered in pediatric pharmacogenomic studies. They also display the importance of collaborations to obtain good quality evidence for the implementation of genetic testing in clinical practice to optimize and personalize treatment.

No evidence of large genetic effects on steroid response in asthma patients

BACKGROUND

Inhaled corticosteroids (ICSs) are considered the most effective anti-inflammatory therapy for asthma control and management; however, there is substantial treatment response variability.

OBJECTIVE

We sought to identify genetic markers of ICS response by conducting the largest pharmacogenetic investigation to date in 2672 ICS-treated patients with asthma.

METHODS

Genotyping and imputation was performed in fluticasone furoate (FF) or fluticasone propionate-treated patients with asthma from 3 phase IIB and 4 phase IIIA randomized, double-blind, placebo-controlled, parallel group, multicenter studies. The primary end point analyzed was change in trough FEV₁ (ΔFEV₁) from baseline to 8 to 12 weeks of treatment.

RESULTS

More than 9.8 million common genetic variants (minor allele frequency ≥ 1%) were analyzed to test for association with ΔFEV₁. No genetic variant met the prespecified threshold for statistical significance.

CONCLUSIONS

This study provides no evidence to confirm previously reported associations between candidate genetic variants and ICS response (ΔFEV₁) in patients with asthma. In addition, no variant satisfied the criterion for genome-wide significance in our study. Common genetic variants are therefore unlikely to prove useful as predictive biomarkers of ICS response in patients with asthma.

GLCCI1 Variation Is Associated with Asthma Susceptibility and Inhaled Corticosteroid Response in a Chinese Han Population

BACKGROUND AND AIMS

GLCCI1 variations are found to be associated with response to glucocorticoid therapy in non-Hispanic white subjects with asthma. However, there are also other relevant studies that were not consistent with this finding. In this study we aimed to evaluate the association of GLCCI1 variations with asthma susceptibility and inhaled corticosteroid (ICS) response in a Chinese adult Han population.

METHODS

We genotyped 24 single nucleotide polymorphisms of GLCCI1 in 182 asthmatic patients and 180 healthy controls. Furthermore, we analyzed the association of GLCCI1 variations with ICS response in 30 mild-to-moderate asthmatics.

RESULTS

rs11976862 homozygote mutant genotype GG was nominally associated with increased asthma risk (OR = 2.435, 95% CI: 1.221-4.854, p = 0.01148, p(corr) = 0.0127). Recessive model of rs37972, rs37973 and rs11976862 showed that the rare alleles were correlated with less improvement in FEV1 after fluticasone treatment for 12 weeks (p = 0.004, p = 0.009 and p = 0.039, respectively). The GLCCI1 mRNA expression level decreased obviously in asthmatics than in healthy controls (0.037663 ± 0.0216833 vs. 0.046352 ± 0.0235812, p = 0.000). For asthmatics, GLCCI1 mRNA expression level significantly increased after fluticasone treatment for 12 weeks (0.067641 ± 0.031547 vs. 0.030048 ± 0.014613, p = 0.000). Moreover, changes of GLCCI1 mRNA expression were significantly related with rs37973 and rs11976862 in a recessive model (p = 0.014 and p = 0.033, respectively).

CONCLUSIONS

GLCCI1 variations are associated with asthma susceptibility and ICS response in a Chinese Han adult population. GLCCI1 variations may affect ICS response by modulating GLCCI1 expression.

Asthma Pharmacogenomics: 2015 Update

There is evidence that genetic factors are implicated in the observed differences in therapeutic responses to the common classes of asthma therapy such as β2-agonists, corticosteroids, and leukotriene modifiers. Pharmacogenomics explores the roles of genetic variation in drug response and continues to be a field of great interest in asthma therapy. Prior studies have focused on candidate genes and recently emphasized genome-wide association analyses. Newer integrative omics and system-level approaches have recently revealed novel understanding of drug response pathways. However, the current known genetic loci only account for a fraction of variability in drug response and ongoing research is needed. While the field of asthma pharmacogenomics is not yet fully translatable to clinical practice, ongoing research should hopefully achieve this goal in the near future buttressed by the recent precision medicine efforts in the USA and worldwide.