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. 2012 Dec;22(12):858-67.
doi: 10.1097/FPC.0b013e32835a450b.

Genome-wide association study of plasma efavirenz pharmacokinetics in AIDS Clinical Trials Group protocols implicates several CYP2B6 variants

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Genome-wide association study of plasma efavirenz pharmacokinetics in AIDS Clinical Trials Group protocols implicates several CYP2B6 variants

Emily R Holzinger et al. Pharmacogenet Genomics. 2012 Dec.

Abstract

Objectives: Prior candidate gene studies have associated CYP2B6 516G→T [rs3745274] and 983T→C [rs28399499] with increased plasma efavirenz exposure. We sought to identify novel variants associated with efavirenz pharmacokinetics.

Materials and methods: Antiretroviral therapy-naive AIDS Clinical Trials Group studies A5202, A5095, and ACTG 384 included plasma sampling for efavirenz pharmacokinetics. Log-transformed trough efavirenz concentrations (Cmin) were previously estimated by population pharmacokinetic modeling. Stored DNA was genotyped with Illumina HumanHap 650Y or 1MDuo platforms, complemented by additional targeted genotyping of CYP2B6 and CYP2A6 with MassARRAY iPLEX Gold. Associations were identified by linear regression, which included principal component vectors to adjust for genetic ancestry.

Results: Among 856 individuals, CYP2B6 516G→T was associated with efavirenz estimated Cmin (P=8.5×10). After adjusting for CYP2B6 516G→T, CYP2B6 983T→C was associated (P=9.9×10). After adjusting for both CYP2B6 516G→T and 983T→C, a CYP2B6 variant (rs4803419) in intron 3 was associated (P=4.4×10). After adjusting for all the three variants, non-CYP2B6 polymorphisms were associated at P-value less than 5×10. In a separate cohort of 240 individuals, only the three CYP2B6 polymorphisms replicated. These three polymorphisms explained 34% of interindividual variability in efavirenz estimated Cmin. The extensive metabolizer phenotype was best defined by the absence of all three polymorphisms.

Conclusion: Three CYP2B6 polymorphisms were independently associated with efavirenz estimated Cmin at genome-wide significance, and explained one-third of interindividual variability. These data will inform continued efforts to translate pharmacogenomic knowledge into optimal efavirenz utilization.

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Conflict of interest statement

Conflicts of interest

Eric S. Daar: Research grants from Bristol–Myers Squibb, Abbott, Merck, Pfizer, ViiV, and Gilead and a consultant/advisor to Bristol–Myers Squibb, Merck, ViiV, and Gilead. Roy M. Gulick: Research Grants from Gilead, Janssen, Pfizer, and ViiV, ad-hoc consultant to Gilead, Glaxo-SmithKline, Janssen, and Koronis. Gregory K. Robbins: Research support from Gilead Sciences and Schering–Plough. Received royalties from Wolters Kluwer. David B. Clifford: Serves on Data Safety Boards for Biogen, Millennium, Genzyme, Genentech, and Pfizer. He has been a consultant to Genentech, Genzyme, Bristol–Myers Squibb, Millennium, Biogen Idec, Janssen, and Pfizer. He has received research support from Biogen Idec, NeurogesX, Tibotec, and Pfizer. David W. Haas: Research grants from Bristol–Myers Squibb, Boehringer Ingelheim, Merck, and Gilead Sciences. For the remaining authors there are no conflicts of interest.

Figures

Fig. 1
Fig. 1
Genome-wide associations with efavirenz estimated Cmin values by multiple linear regression analysis. Manhattan plots of associations between genetic polymorphisms and efavirenz log-transformed estimated Cmin values. Linear regression was used. Each analysis includes the top 10 principal component vectors to adjust for potential confounding by ancestry. The – log10 of P-values are shown. Note the different y-axis scale on each panel. (a) Adjusting only for principal component vectors. (b) Also adjusting for CYP2B6 516G→T. (c) Also adjusting for CYP2B6 516G→T and 983TC. (d) Also adjusting for CYP2B6 516G→T, 983T→C, and rs4803419 C→T. Arrows indicate non-CYP2B6 polymorphisms that achieved (or nearly achieved) P=5×10−8 genome-wide significance in the final model.
Fig. 2
Fig. 2
Association between polymorphisms in the CYP2B6 locus and efavirenz estimated Cmin values, considering linkage disequilibrium (LD). Synthesis-View plots [40] of associations for the chromosome 19 region of interest are shown. At the top are chromosome positions, below which are panels showing – log10 P-values, β values, and minor allele frequencies (MAF). At the bottom shown LD between polymorphisms. Blue markers: Adjusting only for principal component vectors; Red markers: Also adjusting for CYP2B6 516G→T; Orange markers: Also adjusting for CYP2B6 516G→T and 983T→C. The blue, red, and orange markers correspond to Fig. 1a–c, respectively. Only polymorphisms with P≤5×10−8 are shown.
Fig. 3
Fig. 3
Relationships with CYP2B6 variants and efavirenz estimated Cmin values. Efavirenz Cmin values were estimated as described in the Materials and Methods section. (a) All participants (self-identified white, black, and Hispanic); (b) Self-identified white participants; (c) Self-identified black participants; (d) Self-identified Hispanic participants. On x-axis, CYP2B6 haplotypes represent (in order) CYP2B6 rs4803419 C→T (CC, CT, TT), 516G→T (GG, GT, TT), and 983T→C (TT, TC, CC). The need to convert measured efavirenz concentrations to percentiles to derive estimated Cmin values creates a spurious plateau of concentrations at approximately 7 mg/l. Actual Cmin values for some individuals undoubtedly exceed this value.

References

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