Abstract
Nonsteroidal anti‐inflammatory drugs (NSAIDs) used to treat pain in patients with sickle cell disease (SCD) are metabolized by the CYP2C9 enzyme. Racial differences in CYP2C9 allele frequencies impact NSAIDs efficacy and safety. We determined the frequencies of CYP2C9 alleles in an African American pediatric SCD cohort. Genomic DNA was isolated from blood samples of 30 patients aged between 7 and 17 years. Genotyping of nine CYP2C9 alleles (*1,*2, *3, *4, *5, *6, *8, *11, and *13) was performed using restriction fragment length polymorphism‐PCR assays and the Tag‐It™ Mutation Detection System. The wild type *1 allele frequency was 0.850. The most common variant allele detected was CYP2C9*8 (0.067). The combined frequency of the *2, *5, *6, *8, and *11 variants was 0.151. Seventy percent of the study cohort were predicted extensive metabolizers (*1/*1) and 30% were intermediate metabolizers due mainly to the *1/*8 genotype. Analysis of CYP2C9 using an expanded assay panel facilitated improved classification of predicted drug metabolic phenotypes in our cohort. However, the pharmacokinetic effects of the CYP2C9*5,*6,*8, and *11 alleles on NSAIDs metabolism has not been evaluated and underscores the need for studies on substrate‐specific effects of variant alleles common in populations with genetic susceptibility to SCD.
Keywords: NSAIDs, sickle cell disease, pharmacogenetics, CYP2C9, genotyping
Introduction
Sickle cell disease (SCD) is a genetic disorder that occurs predominantly in people of African ancestry. The characteristic clinical manifestation of SCD is recurrent episodes of severe pain commonly referred to as vaso‐occlusive crisis (VOC) often requiring frequent emergency department visits or hospital admissions.1 These painful episodes could start as early as 6 months of age in pediatric patients and continue to occur unpredictably throughout the adult life.2 Prodromal signs of pain crisis and early, mild forms of VOC pain are treated with traditional nonsteroidal anti‐inflammatory drugs (NSAIDs), because of their anti‐inflammatory, analgesic, and antipyretic effects.3 However, many individuals with SCD fail to achieve the adequate analgesia with standard doses of NSAIDs.
Genetic variation in the highly polymorphic CYP2C9 enzyme has been implicated in interindividual variability in analgesic response to NSAIDs.4 More than 40 allelic variants of the CYP2C9 gene have been identified (http://www.cypalleles.ki.se/cyp2c9.htm, accessed April 12, 2014). The frequency of the CYP2C9 allelic variants has been reported to differ among Caucasian, African, and Asian populations. The CYP2C9 *2 and *3 are the two commonly known alleles to result in decreased enzyme metabolic activity in varying magnitudes for CYP2C9 substrates. However, four other minor frequency alleles (* 5, *6, * 8, and *11) have been reported to have decreased function.4 Three predicted metabolic phenotypes are defined based on CYP2C9 allelic combinations, enzymatic activity and expression levels: poor metabolizers (PMs), intermediate metabolizers (IMs), and extensive metabolizers (EMs). PMs are homozygous or compound heterozygous for two reduced function alleles. IMs carry one functional allele and one reduced function allele but may demonstrate a wide range of levels of enzyme activity. EMs have two functional alleles.
Current NSAIDs dosing strategies in children with SCD are based on similar per kilogram dosing across the pediatric age range.5 Implicit in this dosing strategy is the assumption that the individual patient is an extensive metabolizer. However, differences in metabolic activity of allelic variants of the CYP2C9 enzyme may lead to differences in NSAIDs dose effect, particularly adverse effects in patients with deficient metabolic phenotypes.6 Gastrointestinal complications, renal impairment, fluid retention, and exacerbation of asthma are some of the adverse effects associated with impaired NSAIDs metabolism. To our knowledge, no study has investigated the frequency of pharmacologically relevant allelic variants of the CYP2C9 enzymes and their implications for NSAIDs therapy in SCD patients, which is the aim of this pilot study.
Methods
Human subjects
The study participants were pediatric patients with SCD receiving care at the Georgia Regents University Comprehensive Sickle Cell Center pediatric clinic. The study was approved by the Georgia Regents University Institutional Review Board. Written informed consent was obtained from each patient's parent or legal guardian. Each patient also provided written assent. Study participants were recruited between January 2011 and May 2011.
CYP2C9 genotyping
Whole blood samples (10 mL in tubes containing EDTA) were collected from the patients in steady state. Genomic DNA was extracted using the Puregene® DNA Purification Kit (Qiagen, CA, USA) according to the manufacturer's instructions. The CYP2C9 allele designations refer to those defined by the Cytochrome P450 Allele Nomenclature Committee.7 Nine CYP2C9 alleles (*1,*2, *3, *4, *5, *6, *8, *11, and *13) were genotyped across all patients. Genotyping of six CYP2C9 alleles (*1, *2, *3, *4, *5, and *6) was performed using the Tag‐It™ Mutation Detection Kit and analyzed by Tag‐It™ Data Analysis Software (Luminex Molecular Diagnostics, ON, Canada). The CYP2C9*8, *11, and *13 alleles were amplified by PCR, and interrogated using restriction fragment length polymorphism (RFLP) assays as previously described.8 CYP2C9*8 and *13 were amplified using CYP2C9 exon 2/3 primers and *11 was amplified using exon 7 primers as previously described.8 The wild‐type CYP2C9*1 allele was assigned in the absence of other detectable variant alleles.
Statistical analysis
CYP2C9 allele frequencies were presented with 95% confidence interval. Genotype frequencies were presented as percentage of the study cohort with 95% confidence interval. The observed genotype frequencies were compared with those expected for concordance with Hardy–Weinberg equilibrium using the chi‐square test.
Results
The study participants’ demographic features and clinical characteristics are summarized in Table 1. Thirty (13 males and 17 females) African American pediatric SCD patients were enrolled in the study. Race was self‐reported by either parent or study participant. The age of the participants ranged from 7 to 17 years. Nineteen study participants (63.3%) were prescribed hydroxyurea. In terms of treatment of SCD, hydroxyurea is the only FDA approved drug and has been associated with decreased frequency of VOC and morbidity.3 The allele and genotype frequencies for the study cohort are listed in Table 2. We surveyed nine CYP2C9 alleles (*1, *2,*3,*4, *5, *6, *8, *11, and *13). In our cohort, the wild type *1 occurred in the highest frequency (0.850). The CYP2C9*5 (0.033) and *8 (0.067) were the most common variant alleles. The combined frequency for the CYP2C9*2, *5, *6, *8, and *11 variants was 0.151. The high frequency (0.067) of the CYP2C9*8 allele made *1/*8 the most common genotype with a variant allele in the study cohort (12.9%). The CYP2C9*3, *4, and *13 variant alleles were not detected in our study cohort. The observed frequencies for the overall study cohort were concordant with Hardy–Weinberg equilibrium. CYP2C9 phenotypes have been designated extensive (two functional alleles), intermediate (one functional allele/one dysfunctional), and PMs (two nonfunctional alleles). Based on the observed genotypes (i.e., variant allelic combinations), the frequencies of the cohort predicted extensive and IMs were 70% and 30%, respectively. Because our study used an expanded assay panel which include the CYP2C9*5, *6, *8, and *11 variant alleles instead of a limited assay with only the CYP2C9*1,*2, and *3 alleles, we were able to properly reclassify the predicted metabolic phenotypes of 27% of the cohort.
Table 1.
Study participants’ demographic and clinical characteristics
| No (%) of children | |
|---|---|
| Sex | |
| Male | 13 (43%) |
| Female | 17 (57%) |
| Age group | |
| 7–10 years | 12 (38.7%) |
| 11–14 years | 12 (38.7%) |
| 15–17 years | 6 (22.6%) |
| Ethnic origin | |
| African American | 30 (100%) |
| SCD genotype | |
| SS | 27 (90.1%) |
| SC | 1 (3.3%) |
| SB Thal | 1 (3.3%) |
| S‐Los Angeles | 1 (3.3%) |
| SCD related morbidity | |
| Abdominal pain | 3 (9.7%) |
| Renal impairment | 2 (6.5%) |
| Asthma | 9 (29.0%) |
| Hypertension | 3 (9.7%) |
| NSAIDs | |
| Ibuprofen (motrin) | 14 (47%) |
| Hydroxyurea therapy | |
| Yes | 19 (63.3%) |
Table 2.
CYP2C9 allele, genotype, and phenotype frequencies
| CYP2C9 alleles | Genetic alteration | Enzyme activity | Number of alleles | Frequency | 95% CI range |
|---|---|---|---|---|---|
| *1 | Wild type | Normal | 51 | 0.850 | 0.760–0.940 |
| *2 | Missense mutation | Decreased | 1 | 0.017 | 0.000–0.049 |
| *3 | Missense mutation | Decreased | 0 | 0.000 | 0.000–0.000 |
| *4 | Missense mutation | NA | 0 | 0.000 | 0.000–0.000 |
| *5 | Missense mutation | Decreased | 2 | 0.033 | 0.000–0.079 |
| *6 | Frame shift | None | 1 | 0.017 | 0.000–0.049 |
| *8 | Missense mutation | Decreased | 4 | 0.067 | 0.000–0.130 |
| *11 | Missense mutation | Decreased | 1 | 0.017 | 0.000–0.049 |
| *13 | Missense mutation | Decreased | 0 | 0.000 | 0.000–0.000 |
| Total | 60 | 1.0 | |||
| Genotypes and phenotypes | |||||
| Metabolizer phenotype and genotype | Number of subjects | Observed frequency (%) | Predicted frequency (%) |
|---|---|---|---|
| Extensive metabolizer | |||
| *1/*1 | 21 | 70.0 | 72.3 |
| Intermediate metabolizer | |||
| *1/*2 | 1 | 3.3 | 2.8 |
| *1/*5 | 2 | 6.7 | 5.7 |
| *1/*6 | 1 | 3.3 | 2.8 |
| *1/*8 | 4 | 13.3 | 11.3 |
| *1/*11 | 1 | 3.3 | 2.8 |
| Total | 30 | 100 | 98 |
The distribution of CYP2C9 genotype/phenotype, NSAIDs and hydroxyurea use, and SCD related morbidity profiles for the individual study participants is shown in Table 3. Seventeen children had history of morbidities that could be exacerbated by NSAIDs therapy, including asthma, abdominal pain, and renal impairment. Three participants with abdominal pain, asthma, and renal impairment respectively, and one patient with vascular disease had the impaired CYP2C9 intermediate metabolizer genotype.
Table 3.
Study participants’ individual pharmacogenetic, drugs, and SCD morbidity profile
| Number of subjects | Genotype | Phenotype | Hu therapy | NSAIDs prescription | SCD related morbidity |
|---|---|---|---|---|---|
| 1 | *1/*1 | EM | Y | Y | Abdominal pain, asthma |
| 2 | *1/*1 | EM | Y | Y | – |
| 3 | *1/*1 | EM | Y | Y | Asthma |
| 4 | *1/*1 | EM | Y | – | |
| 5 | *1/*1 | EM | Y | Y | Abdominal pain |
| 6 | *1/*1 | EM | Y | Y | – |
| 7 | *1/*5 | IM | Y | Y | Renal impairment |
| 8 | *1/*1 | EM | Y | Y | Asthma |
| 9 | *1/*1 | EM | Y | Asthma | |
| 10 | *1/*1 | EM | – | ||
| 11 | *1/*1 | EM | Y | Asthma | |
| 12 | *1/*1 | EM | Y | – | |
| 13 | *1/*11 | IM | Y | – | |
| 14 | *1/*6 | IM | Y | Y | Asthma |
| 15 | *1/*1 | EM | Y | Hypertension, renal impairment | |
| 16 | *1/*8 | IM | Y | – | |
| 17 | *1/*1 | EM | Y | Hypertension | |
| 18 | *1/*8 | IM | Y | – | |
| 19 | *1/*1 | EM | – | ||
| 20 | *1/*5 | IM | Abdominal pain | ||
| 21 | *1/*8 | IM | Y | Y | – |
| 22 | *1/*1 | EM | Asthma | ||
| 23 | *1/*1 | EM | Y | – | |
| 24 | *1/*1 | EM | Y | Y | – |
| 25 | *1/*2 | IM | Y | Vasculopathy | |
| 26 | *1/*1 | EM | Y | Asthma | |
| 27 | *1/*8 | IM | – | ||
| 28 | *1/*1 | EM | Asthma | ||
| 29 | *1/*1 | EM | – | ||
| 30 | *1/*1 | EM | Y | Migraine |
EM = extensive metabolizer; HU = hydroxyurea; IM = intermediate metabolizer; Y = yes.
Discussion
To our knowledge, our study is the first to report CYP2C9 allelic data in a pediatric African American SCD cohort using an expanded genotyping panel. Table 4 which compare our study results with data previously reported in other racial, and ethnic populations affirmed the geographic and racial clustering of the reduced activity CYP2C9 alleles.8, 9, 10, 11, 12, 13 The *2 allele is present primarily in Caucasians at approximately 16%, whereas the *3 allele is present in approximately 3–8% of Caucasians, Hispanics, and East Asians.9 Among African Americans, the *8 allele has a prevalence close to 9% and is the most common of the variant CYP2C9 alleles.11 The impaired activity CYP2C9*13, *26, *28, and *30 alleles have been identified in Asian populations, but not in African and African American populations.4
Table 4.
CYP2C9 Frequencies in previously studied populations
| Alleles frequency (%) | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Racial & ethnic group | *1 | *2 | *3 | *4 | *5 | *6 | *8 | *9 | *11 | *12 | *13 | References |
| African American (n = 30) | 0.850 | 0.017 | 0.000 | 0.000 | 0.033 | 0.017 | 0.067 | – | 0.017 | – | 0.000 | This study |
| African American (n = 300) | 0.867 | 0.028 | 0.020 | 0.000 | 0.015 | 0.010 | 0.047 | – | 0.013 | – | 0.000 | 8 |
| African American frequency range | 0–0.036 | 0.003–0.020 | 0.007–0.015 | 0.004–0.017 | 0.047–0.072 | 0.010–0.040 | 8 | |||||
| Ghanaian (n = 204) | – | 0.000 | 0.000 | 0.000 | 0.000 | – | – | – | 0.020 | – | – | 10 |
| Beninese (n = 111) | 0.955 | 0.000 | 0.000 | 0.000 | 0.018 | – | – | – | 0.027 | – | – | 12 |
| Mozambican (n = 206) | – | 0.000 | 0.010 | – | 0.019 | 0.000 | 0.146 | – | 0.024 | – | – | 13 |
| Africans (n = 250) | 0.810 | 0.120 | 0.000 | – | 0.010 | 0.012 | 0.040 | 0.095 | 0.022 | 0.020 | – | 9 |
| Caucasian (n = 454) | 0.780 | 0.160 | 0.060 | – | 0.000 | 0.000 | 0.001 | 0.000 | 0.002 | 0.002 | – | 9 |
| Hispanics (n = 202) | 0.822 | 0.069 | 0.064 | 0.000 | 0.015 | 0.005 | 0.015 | – | 0.010 | 0.000 | 11 | |
| Ashkenazi Jewish (n = 1,004) | 0.788 | 0.128 | 0.083 | 0.000 | 0.001 | 0.000 | 0.000 | – | 0.000 | – | 0.000 | 11 |
| Chinese (n = 398) | 0.960 | 0.001 | 0.041 | – | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | – | 9 |
| Korean (n = 200) | 0.953 | 0.000 | 0.045 | – | 0.000 | 0.000 | 0.003 | 0.000 | 0.000 | 0.000 | – | 9 |
| Japanese (n = 500) | 0.970 | 0.000 | 0.034 | – | 0.000 | 0.000 | 0.001 | 0.000 | 0.000 | 0.000 | – | 9 |
The CYP2C9 variant alleles play a significant role in the metabolism, analgesic effects, and toxicity of NSAIDs. These drugs continue to be the backbone of pain management of children with SCD. Our study shows that 30% of our subjects have genotypes with at least one allele associated with reduced function (*2,*5, *8, and *11). The available pharmacokinetics (PK) and pharmacodynamics studies (PD) associate variant CYP2C9 with interindividual variations in response and adverse effects to traditional NSAIDs.4 For instance, recent ibuprofen PK data showed that carriers of two CYP2C9*3 alleles experience 50% reduction in clearance of racemic and enantiomeric S‐ibuprofen compared with individuals homozygous for the CYP2C9*1 allele.14 In a study of 130 healthy individuals who received single oral dose of 400 mg racemic ibuprofen, the metabolic clearance values for ibuprofen were 4.43, 3.26, 2.91, 2.05, 1.83, and 1.13 1/hour for individuals with CYP2C9*1/*1, *1/*2, *1/*3, *2/*2, *2/*3, and *3/*3 genotypes, respectively.15 Interestingly, the effect of variant CYP2C9 alleles does not seem to be similar for all NSAIDs. In a study of 20 research participants who received a single dose of 275 mg naproxen, no significant differences were observed in oral clearance of naproxen between CYP2C9*1/*1, and *1/*3 individuals, which the investigators attributed to contributions from other CYP450 metabolic enzymes such as the CYP2C8.16
PD studies have also evaluated the relationship between CYP2C9 genotypes and gastrointestinal toxicity of NSAIDs. Martinez and colleagues found CYP2C9*2 and *3 associated with a 2.5‐fold increased risk of gastric bleeding episode after dosing with NSAIDs such as celecoxib, diclofenac, ibuprofen, indomethacin, lornoxicam, piroxicam or naproxen. The increased risk was attributed to the *2 allele which was detected in 23.4% of the study subjects with gastric bleeding episode compared with 13.7% of the control subjects.17 A similar study by Pilotto et al found that a significantly higher frequency of CYP2C9*1/*3 and *1/*2 genotypes were identified in patients with endoscopically documented NSAIDs‐related gastroduodenal bleeding lesions compared to a matched control group. In the study described, the presence of the CYP2C9*3 allelic variant was associated with a significant high risk of bleeding (OR: 7:3).18
The untoward effects of impairment in CYP2C9 metabolic activity provide clinical rationale for preemptive CYP2C9 genotyping for a number of commonly prescribed drugs. Genotyping of CYP2C9 alleles is recommended for patients with diabetes mellitus to determine appropriate dose of tolbutamide to regulate blood glucose level.19 CYP2C9*2 and *3 genotyping has also been recommended prior to initiating warfarin for patients who are at a greater risk of bleeding.20 Consequently, for pediatric SCD patients, the application of preemptive CYP2C9 genotyping to rationalize NSAIDs therapy will enable clinicians to identify patients with impaired drug metabolic profile. Additionally, preemptive genotyping would provide explanation for those individuals with unsatisfactory drug response or side effects profiles enabling clinicians to make distinctions between a compliance problem and a metabolic defect.21
Ultimately, the goal of determining SCD patients’ CYP2C9 genotypes is the development of algorithms that would inform genomic‐based drug prescribing practice. However, this would require additional studies of not only CYP2C9 variant alleles but other drug metabolizing genes involved in analgesic drug metabolism, the genomic mechanisms impacting metabolic genes expressions and functionality, as well as environment factors. Perhaps more immediately is the need for appropriate PK and PD studies to determine the effects of minor frequency allelic variants present in our patient population. As depicted in Table 4, the CYP2C9*5,*6,*8, and *11 variant alleles are common in populations with genetic susceptibility for SCD, usually populations of African ancestry. While the PK and PD effects of CYP2C9*2 and *3 alleles on the PK and PD of NSAIDs are well delineated, to the best of our knowledge, the effects of the CYP2C9*5,*6,*8, and *11 alleles on NSAIDs metabolism has not been evaluated in PK studies in African American populations. This lack of PK data represents a crucial knowledge gap in the use of genetic background to potentially guide NSAIDs dosing in our patient population.
Our study has limitations. While we used an expanded genotyping assay to determine CYP2C9 genotypes, the assignment of predicted metabolic phenotypes in our cohort was based on allelic combinations reported in the literature.8, 9, 10, 11, 12 PK study remains the gold standard for discerning individuals’ metabolic phenotypes for analgesic drug response. Another study limitation is that the number of subjects in our cohort is too small to compare the frequency of null and reduced function alleles to ranges reported in other healthy African American populations. Even though the CYP2C9 allelic frequencies reported in our study are comparable to those recently reported for a large adult African American cohort,8 our small sample size limits the determination within our patient subgroup whether some CYP2C9 alleles are under‐ or overrepresented because of founder effect compared to health African Americans.22 For instance, SCD patients are reported to have a slightly higher frequency of the CYP2D6 gene deletions compared to healthy African Americans.23 CYP2D6 gene deletions are associated with the poor metabolizer phenotype and impaired ability to convert opioids, such as codeine and hydrocodone into their active analgesic forms, and as such are implicated in SCD pain phenotype and analgesic drug response.24 These limitations notwithstanding, or study attempts to bridge the concept of pharmacogenetic variability as a determinant of interindividual response to analgesic drug therapy in SCD patients. Preemptive CYP2C9 genotyping aided by appropriate PK and PD studies bring into sharp relief the potential for genomic‐based dosing strategies in this patient population. In this regard, our pilot study is the first phase of a large prospective study investigating suboptimal analgesic prescribing in SCD patients focusing on genetic polymorphisms in the major cytochrome P450 genes which are known to play a role in analgesic drug metabolism and could help identify patients with higher risk for therapy failure.
Conclusion
In conclusion, we report the frequency of CYP2C9 alleles in a pediatric SCD cohort. We elucidate from prior studies how these variants contribute to impaired metabolism of NSAIDs. Several of the reduced function variant alleles are being reported for the first time among SCD patients due to our use of an expanded genotype panel. The CYP2C9 variant alleles play a significant role in the analgesic effects and toxicity of the NSAIDs. These drugs are the backbone of pain management of children with SCD. Our study attempts to bridge the concept of pharmacogenetic variability as a determinant of interindividual response to analgesic drug therapy in SCD patients, and should make health providers more aware of the potential side effects of NSAIDs therapy in this vulnerable patient population. Future studies should determine the CYP2C9 metabolic profiles of pediatric SCD patients with appropriate PK and PD studies that could potentially enable clinicians to identify patients with impaired CYP2C9 metabolic capacity and tailor NSAIDs dosing accordingly to achieve optimal analgesic response.
Conflict of Interest
The authors have no financial disclosures or conflicts of interest to declare.
Acknowledgments
The authors wish to thank the nursing staff at the Georgia Regents University Pediatric Sickle Cell Clinics. This work was presented in abstract form at the NIDDK Network of Minority Health Research Investigators 10 Annual Workshop. Bethesda, MD, April 19–20, 2012. This study was supported in part by a grant from the Georgia Regents University Child Health Discovery Institute and National Institute of Nursing Research, NIH, grant #1K01NR012465. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute for Nursing Research.
References
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