Effect of CYP3A5*3 on asthma control among children treated with inhaled beclomethasone

The Cytochrome P450 2C8*3 Variant (rs11572080) Is Associated with Improved Asthma Symptom Control in Children and Altered Lipid Mediator Production and Inflammatory Response in Human Bronchial Epithelial Cells

This study investigated an association between the cytochrome P450 (CYP) 2C8*3 polymorphism with asthma symptom control in children and changes in lipid metabolism and pro-inflammatory signaling by human bronchial epithelial cells (HBECs) treated with cigarette smoke condensate (CSC). CYP genes are inherently variable in sequence, and while such variations are known to produce clinically relevant effects on drug pharmacokinetics and pharmacodynamics, the effects on endogenous substrate metabolism and associated physiologic processes are less understood. In this study, CYP2C8*3 was associated with improved asthma symptom control among children: Mean asthma control scores were 3.68 (n = 207) for patients with one or more copies of the CYP2C8*3 allele versus 4.42 (n = 965) for CYP2C8*1/*1 (P = 0.0133). In vitro, CYP2C8*3 was associated with an increase in montelukast 36-hydroxylation and a decrease in linoleic acid metabolism despite lower mRNA and protein expression. Additionally, CYP2C8*3 was associated with reduced mRNA expression of interleukin-6 (IL-6) and C-X-C motif chemokine ligand 8 (CXCL-8) by HBECs in response to CSC, which was replicated using the soluble epoxide hydrolase inhibitor, 12-[[(tricyclo[3.3.1.13,7]dec-1-ylamino)carbonyl]amino]-dodecanoic acid. Interestingly, 9(10)- and 12(13)- dihydroxyoctadecenoic acid, the hydrolyzed metabolites of 9(10)- and 12(13)- epoxyoctadecenoic acid, increased the expression of IL-6 and CXCL-8 mRNA by HBECs. This study reveals previously undocumented effects of the CYP2C8*3 variant on the response of HBECs to exogenous stimuli. SIGNIFICANCE STATEMENT: These findings suggest a role for CYP2C8 in regulating the epoxyoctadecenoic acid:dihydroxyoctadecenoic acid ratio leading to a change in cellular inflammatory responses elicited by environmental stimuli that exacerbate asthma.

Impact of CYP3A5 Polymorphisms on Pediatric Asthma Outcomes

Genetic variation among inhaled corticosteroid (ICS)-metabolizing enzymes may affect asthma control, but evidence is limited. This study tested the hypothesis that single-nucleotide polymorphisms (SNPs) in Cytochrome P450 3A5 (CYP3A5) would affect asthma outcomes. Patients aged 2-18 years with persistent asthma were recruited to use the electronic AsthmaTracker (e-AT), a self-monitoring tool that records weekly asthma control, medication use, and asthma outcomes. A subset of patients provided saliva samples for SNP analysis and participated in a pharmacokinetic study. Multivariable regression analysis adjusted for age, sex, race, and ethnicity was used to evaluate the impact of CYP3A5 SNPs on asthma outcomes, including asthma control (measured using the asthma symptom tracker, a modified version of the asthma control test or ACT), exacerbations, and hospital admissions. Plasma corticosteroid and cortisol concentrations post-ICS dosing were also assayed using liquid chromatography-tandem mass spectrometry. Of the 751 patients using the e-AT, 166 (22.1%) provided saliva samples and 16 completed the PK study. The e-AT cohort was 65.1% male, and 89.6% White, 6.0% Native Hawaiian, 1.2% Black, 1.2% Native American, 1.8% of unknown race, and 15.7% Hispanic/Latino; the median age was 8.35 (IQR: 5.51-11.3) years. CYP3A5*3/*3 frequency was 75.8% in White subjects, 50% in Native Hawaiians and 76.9% in Hispanic/Latino subjects. Compared with CYP3A5*3/*3, the CYP3A5*1/*x genotype was associated with reduced weekly asthma control (OR: 0.98; 95% CI: 0.97-0.98; p < 0.001), increased exacerbations (OR: 6.43; 95% CI: 4.56-9.07; p < 0.001), and increased asthma hospitalizations (OR: 1.66; 95% CI: 1.43-1.93; p < 0.001); analysis of 3/*3, *1/*1 and *1/*3 separately showed an allelic copy effect. Finally, PK analysis post-ICS dosing suggested muted changes in cortisol concentrations for patients with the CYP3A5*3/*3 genotype, as opposed to an effect on ICS PK. Detection of CYP3A5*3/3, CYPA35*1/*3, and CYP3A5*1/*1 could impact inhaled steroid treatment strategies for asthma in the future.

A Roadmap for Using Causal Inference and Machine Learning to Personalize Asthma Medication Selection

Inhaled corticosteroid (ICS) is a mainstay treatment for controlling asthma and preventing exacerbations in patients with persistent asthma. Many types of ICS drugs are used, either alone or in combination with other controller medications. Despite the widespread use of ICSs, asthma control remains suboptimal in many people with asthma. Suboptimal control leads to recurrent exacerbations, causes frequent ER visits and inpatient stays, and is due to multiple factors. One such factor is the inappropriate ICS choice for the patient. While many interventions targeting other factors exist, less attention is given to inappropriate ICS choice. Asthma is a heterogeneous disease with variable underlying inflammations and biomarkers. Up to 50% of people with asthma exhibit some degree of resistance or insensitivity to certain ICSs due to genetic variations in ICS metabolizing enzymes, leading to variable responses to ICSs. Yet, ICS choice, especially in the primary care setting, is often not tailored to the patient's characteristics. Instead, ICS choice is largely by trial and error and often dictated by insurance reimbursement, organizational prescribing policies, or cost, leading to a one-size-fits-all approach with many patients not achieving optimal control. There is a pressing need for a decision support tool that can predict an effective ICS at the point of care and guide providers to select the ICS that will most likely and quickly ease patient symptoms and improve asthma control. To date, no such tool exists. Predicting which patient will respond well to which ICS is the first step toward developing such a tool. However, no study has predicted ICS response, forming a gap. While the biologic heterogeneity of asthma is vast, few, if any, biomarkers and genotypes can be used to systematically profile all patients with asthma and predict ICS response. As endotyping or genotyping all patients is infeasible, readily available electronic health record data collected during clinical care offer a low-cost, reliable, and more holistic way to profile all patients. In this paper, we point out the need for developing a decision support tool to guide ICS selection and the gap in fulfilling the need. Then we outline an approach to close this gap via creating a machine learning model and applying causal inference to predict a patient's ICS response in the next year based on the patient's characteristics. The model uses electronic health record data to characterize all patients and extract patterns that could mirror endotype or genotype. This paper supplies a roadmap for future research, with the eventual goal of shifting asthma care from one-size-fits-all to personalized care, improve outcomes, and save health care resources.

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.

Pharmacogenomic Response of Inhaled Corticosteroids for the Treatment of Asthma: Considerations for Therapy

There is a large interindividual variability in response to ICSs in asthma. About 70% of the variance in ICS response is likely due at least partially to genetically determined characteristics of target genes. In this article, we examine the effects on the ICS response of gene variations in the corticosteroid pathway, and in the pharmacokinetics of corticosteroids, and also those outside the corticosteroid pathway, which have the potential to influence corticosteroid activity. Although the available evidence indicates that responses to ICSs in asthma are influenced by different genetic variants, there are still deep uncertainties as to whether a real association between these genetic variants and corticosteroid response could also possibly exist because there are difficulties in reproducing pharmacogenetic findings. This explains at least partly the insufficient use of pharmacogenomic data when treating asthmatic patients, which creates a real limitation to the proper use of ICSs in an era of precision medicine that links the right patient to the right treatment. Knowing and dealing with the genetic factors that influence the therapeutic ICS response is a fundamental condition for prescribing the right dose of ICS to the right patient at the right time.

Toward precision medicine in pediatric population using cytochrome P450 phenotyping approaches and physiologically based pharmacokinetic modeling

The activity of drug-metabolizing enzymes (DME) shows high inter- and intra-individual variability. Genetic polymorphisms, exposure to drugs, and environmental toxins are known to significantly alter DME expression. In addition, the activity of these enzymes is highly age-dependent due to maturation processes that occur during development. Currently, there is a vast choice of phenotyping methods in adults using exogenous probes to characterize the activity of these enzymes. However, this can hardly be applied to children since it requires the intake of non-therapeutic xenobiotics. In addition, sampling may be challenging in the pediatric population for a variety of reasons: limited volume (e.g., blood), inappropriate sampling methods for age (e.g., urine), and metric requiring invasive or multiple blood samples. This review covers the main existing methods that can be used in the pediatric population to determine DME activity, with a particular focus on cytochrome P450 enzymes. Less invasive tools are described, including phenotyping using endogenous probes. Finally, the potential of pediatric model-informed precision dosing using physiologically based pharmacokinetic modeling is discussed.

Correlations of CYP2C9*3/CYP2D6*10/CYP3A5*3 gene polymorphisms with efficacy of etanercept treatment for patients with ankylosing spondylitis: A case-control study

BACKGROUND

The tumor necrosis factor alpha (TNF-α) inhibitor etanercept has been proven to be effective in the treatment of ankylosing spondylitis (AS), while genetic polymorphism may affect drug metabolism or drug receptor, resulting in interindividual variability in drug disposition and efficacy. The purpose of this study is to investigate the correlations between CYP2C9*3/CYP2D6*10/CYP3A5*3 gene polymorphisms and the efficacy of etanercept treatment for patients with AS.

METHODS

From March 2012 to June 2015, 312 AS patients (174 males and 138 females, mean age: 35.2 ± 5.83 years) from 18 to 56 years old were enrolled in this study. Polymerase chain reaction-restriction fragment length polymorphism was applied to detect the allele and genotype frequencies of CYP2C93, CYP2D610, and CYP3A53 gene polymorphisms. The joint swelling score, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) level of AS patients were compared before and after 24-week etanercept treatment. Assessment in Ankylosing Spondylitis (ASAS) and bath ankylosing spondylitis disease activity index (BASDAI) scores were recorded to assess the efficacy of etanercept treatment.

RESULTS

The AS patients with wild-type 1/1 and heterozygous 1/3 genotypes of CYP2C93 polymorphism accounted for 93.59% and 6.41%, respectively, without 3/3 genotype. The AS patients with wild-type CC, heterozygous CT, and mutation homozygous TT genotypes of CYP2D610 polymorphism accounted for 19.23%, 39.10%, and 41.67%, respectively. The AS patients with wild-type 1/1, heterozygous 1/3, and mutation homozygous 3/3 genotypes of CYP3A53 polymorphism accounted for 7.69%, 36.22%, and 56.09%, respectively. After 24-week treatment, AS patients with wild-type 1/1 genotype of CYP2C93, CC genotype of CYP2D610, and 3/3 genotype of CYP3A53 polymorphisms had lower joint swelling score, ESR, and CRP level. The joint swelling score, ESR, and CRP levels were significantly lower in the patients with CC genotype of CYP2D610 polymorphism than in CT and TT genotype patients, and they were lower in patients with 3/3 genotype of CYP3A53 polymorphism compared to those with 1/1 and 1/3 genotypes. Average visual analog scale scores of 4 ASAS20 indexes were decreased after treatment. The patients with CC genotype of CYP2D610 polymorphism and 3/3 genotype of CYP3A53 polymorphism exhibited higher scores of >ASAS20, >BASDAI50%, and effective rate.

CONCLUSION

Our results indicate that CC genotype of CYP2D610 polymorphism and 33 genotype of CYP3A53 polymorphism are correlated with the efficacy of etanercept treatment for AS patients.

Genetic variation in the glucocorticoid pathway involved in interindividual differences in the glucocorticoid treatment

Glucocorticoids (GCs) are widely used for treating asthma, rheumatoid arthritis, nephrotic syndrome, acute lymphoblastic leukemia and other autoimmune diseases. However, in a subgroup of patients, failure to respond to GCs is known as GC resistance or GC insensitivity. This represents an important barrier to effective treatment and a clinical problem requiring an urgent solution. Genetic variation in the GC pathway is a significant factor in interindividual differences in GC treatment. This article reviews the pharmacogenetics of GCs in diverse diseases based on the GC pathway.

Characterization of Transient Receptor Potential Vanilloid-1 (TRPV1) Variant Activation by Coal Fly Ash Particles and Associations with Altered Transient Receptor Potential Ankyrin-1 (TRPA1) Expression and Asthma

Transient receptor potential (TRP) channels are activated by environmental particulate materials. We hypothesized that polymorphic variants of transient receptor potential vanilloid-1 (TRPV1) would be uniquely responsive to insoluble coal fly ash compared with the prototypical soluble agonist capsaicin. Furthermore, these changes would manifest as differences in lung cell responses to these agonists and perhaps correlate with changes in asthma symptom control. The TRPV1-I315M and -T469I variants were more responsive to capsaicin and coal fly ash. The I585V variant was less responsive to coal fly ash particles due to reduced translation of protein and an apparent role for Ile-585 in activation by particles. In HEK-293 cells, I585V had an inhibitory effect on wild-type TRPV1 expression, activation, and internalization/agonist-induced desensitization. In normal human bronchial epithelial cells, IL-8 secretion in response to coal fly ash treatment was reduced for cells heterozygous for TRPV1-I585V. Finally, both the I315M and I585V variants were associated with worse asthma symptom control with the effects of I315M manifesting in mild asthma and those of the I585V variant manifesting in severe, steroid-insensitive individuals. This effect may be due in part to increased transient receptor potential ankyrin-1 (TRPA1) expression by lung epithelial cells expressing the TRPV1-I585V variant. These findings suggest that specific molecular interactions control TRPV1 activation by particles, differential activation, and desensitization of TRPV1 by particles and/or other agonists, and cellular changes in the expression of TRPA1 as a result of I585V expression could contribute to variations in asthma symptom control.