As shown in Table 2, the allele frequencies of CYP3A4*22 and CYP3A5*3 were significantly higher in Whites, and distributions in the various genotype-defined groups were significantly different between Whites and African-Americans. In both races, CYP3A4*22 and CYP3A5*3 distributions were in Hardy–Weinberg equilibrium. The alleles were determined to be in partial linkage disequilibrium (LD), and the degree of LD was different for Whites and African-Americans (r 2=0.06 and 0.14, respectively). As shown in Table 1, race, BMI, and smoking status had significant associations with genotype-defined groups. Race and BMI, however, were the only clinical characteristics with significant associations (P<0.05) with simvastatin concentrations, predicating that analyses be stratified by race and simvastatin concentrations be adjusted for BMI. Analyses were also repeated with concentrations adjusted for body weight.
Single-gene and combined-gene analyses of SV and SVA are presented in Figs 1 and 2. In the single-gene analyses of self-reported Whites, CYP3A5*3 allele status was not significantly associated with SV or SVA concentrations, and CYP3A4*22 carriers had 14% higher concentrations of SVA (P=0.04) and 20% higher concentrations of SV (P=0.06) compared with noncarriers. In the single-gene analyses of self-reported African-Americans, CYP3A4*22 carriers had 170% higher concentrations of SV than did noncarriers (P<0.01), but no significant difference was detected for concentrations of SVA; and CYP3A5 nonexpressors (CYP3A5*3/*3) had 33% higher concentrations of SV than CYP3A5 expressors (CYP3A5*1/*3 or *1/*1) (P=0.02), but no significant difference was detected for concentrations of SVA.
In the analysis of CYP3A4/5 genotype-defined groups (PMs, IMs, and EMs), SV concentrations appeared to decrease across the rank-ordered groups; however, no statistically significant associations were identified. Furthermore, similar trends were not observed for SVA concentrations. BMI adjustment had no appreciable effect in any analysis (results not shown).
Both White and African American CYP3A4*22 carriers had greater SVA than noncarriers (P<0.05); however, this effect was much more remarkable in the African-Americans than Whites (170 vs. 14% increase, respectively). A nonstatistically significant trend of greater SV in CYP3A4*22 carriers was also observed. The effect of CYP3A5 status was significant only for African-Americans; SV was 33% greater in CYP3A5 nonexpressors (*3/*3) compared with CYP3A5 expressors (*1/*3 or *1/*1) (P=0.02).
This report describes associations between in-vivo simvastatin concentrations and CYP3A5*3 and CYP3A4*22 alleles, and the observed associations were consistent with the known functional effects of these alleles 4,6. The DOF CYP3A4*22 allele was associated with increased simvastatin concentrations for both self-reported Whites and self-reported African-Americans. However, CYP3A5 was influential in only the self-reported African-Americans. Although our results are not unexpected, to date this is the first report that has specifically tested the associations between plasma simvastatin concentration and CYP3A4*22, alone or in the combined CYP3A4/5 genotype-defined classification.
Observed differences in CYP3A allele frequencies and LD between African-Americans and Whites are consistent with previously reported allele frequency analyses 15. We observed that the majority (nearly 90%) of African-Americans were categorized as EMs in the combined CYP3A4/5 genotype-defined classification system (Fig. 2). We previously reported that simvastatin treatment has reduced efficacy for low-density lipoprotein-cholesterol lowering in African-Americans compared with Whites 9. This difference may partially be attributed to the disproportionate number of EMs in African-Americans; however, further investigation is warranted.
Our analyses failed to identify a statistically significant relationship between CYP3A5 genotype and plasma SV or SVA concentrations in Whites. This is consistent with the analyses reported by Kim et al. 4 in which a statistically significant difference was determined for simvastatin concentration AUC12 but not for 12-h postdose concentration. The LOF CYP3A5*3 allele is the major allele in Whites, and it is likely that variation in other similar enzymes, such as CYP3A4 or CYP3A7, may compensate for the loss of CYP3A5 function associated with the *3 allele.
Of the covariates tested, we only found evidence of a modest association between BMI and statin concentrations. This finding was not surprising because SV and SVA are lipophilic 16,17, the average BMI in the CAP study classifies as overweight (i.e. average BMI was 27.8), and BMI can alter the pharmacokinetic parameters of lipophilic substances. However, as the BMI range of the cohort was quite narrow and the effect size of BMI on SV and SVA was marginal, it was not unexpected that BMI adjustment did not impact the observed genotype–concentration associations. Similarly, all analyses were repeated with adjustments for body weight and the observed genotype–concentration associations were not significantly altered (results not shown).
There are several limitations to the present report. It is based on a retrospective pharmacokinetic analysis in a study designed primarily for measuring pharmacodynamic endpoints and did not examine polymorphisms in other genes known to affect simvastatin pharmacokinetics (e.g. SLC01B1). In addition, racial categories were self-reported, and although race stratification does account for racial differences in LD, it does not account for unbalanced allele status among polymorphism-carrier groups. Finally, some genotype-determined groups were inadequately represented (e.g. only two of 275 African-American participants represented the CYP3A4/5 PM group).
Nevertheless, the study has several strengths for investigating influence of CYP3A: the overall sample size was large, the simplicity of the genotype groupings allowed for utilization of robust nonparametric statistical analyses, the sex profile was well balanced, the ranges of BMI and age were marginal, and simvastatin dose, strength, and duration were homogenous. Furthermore, the study design prohibited the use of concomitant medications and certain foods that could induce or inhibit CYP3A.
The genotype–concentration associations reported here are preliminary observations and are not intended to guide the dose selection of simvastatin. However, these results may be combined with additional data to account for ancestry, LD, and other polymorphic genes involved in the pharmacokinetics of simvastatin, possibly providing a more predictive model in the future.
Here, we presented the first report specifically testing the associations between plasma simvastatin concentration and CYP3A4*22, alone or in the combined CYP3A4/5 genotype-defined classification. Our analyses revealed associations between simvastatin concentrations and CYP3A4*22 in both racial categories and an association for CYP3A5 in only the self-reported African-Americans.
Guidance for statin pharmacotherapy is of increasing relevance given the dramatic expansion of statin-use recommendations outlined in the clinical guidelines recently issued by the American Heart Association 18. Although CYP3A genotype is currently not considered when prescribing statins, future guidance and recommendations may be derived in part from models incorporating genotype status along with concomitant use of enzyme inhibitors or inducers.
The authors thank Elizabeth Theusch, Sarah King, Larry Wong, and Ann Wang for their assistance in genotyping and data generation.
This research was supported by the following grants from the National Institutes of Health: U19 HL069757, R01 HL104133, K23 GM100372, and U01 GM092655.
Conflicts of interest
There are no conflicts of interest.
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Keywords:Copyright © 2014 Wolters Kluwer Health, Inc. All rights reserved.
CYP3A4; CYP3A5; metabolism; pharmacogenetics; simvastatin