1. A single nucleotide polymorphism in CYP2B6 leads to >3-fold increases in efavirenz concentrations in intensive pharmacokinetic curves and hair samples M. Gandhi, R.M. Greenblatt, P. Bacchetti, C. Jin, Y. Huang, M. Cohen, J. Dehovitz, K. Anastos, S.J. Gange, C. Liu, S. Hanson, B. Aouizerat for the Women’s Interagency HIV Study (WIHS) Pharmacokinetics and Pharmacogenomics of ART: Coming of Age Oral poster discussion, AIDS 2012, Washington DC, July 24 TUPDB0104

2. Background EFV mainstay of current cART, high rates of AEs Pharmacogenomics (PG) “personalize” selection, dosing; optimize outcomes Studies investigating PG & EFV exposure limited by Single plasma levels of EFV as exposure measure Small # single nucleotide polymorphisms (SNPs) examined Failure to model non-genetic contributors Women’s Interagency HIV Study (WIHS): Multicenter prospective cohort study HIV-infected and at-risk women

3. Methods: EFV AUC- “Short-term exposure” 24 hour intensive PK studies performed in 111 WIHS women on EFV under conditions of actual use Areas under the curve (AUCs) calculated Median PK curve Efavirenz concentration (mg/ml) Time of blood draw (hours)

4. Hair EFV levels: “Long-term exposure” Average exposure over time Not snapshot (AUC of AUC) Easy and cheap to collect Stored at room temp Shipped without biohazard Not subject to white coat effects Integrates behavior (adherence) and biology (PK)

5. Methods (cont.) Multivariate linear regression between predictors and short/long-term exposure Genetic predictors: 182 SNPs/ 45 haplotypes in 9 genes (ABCB1, ABCC2, CYP2B6, CYP2C19, CYP2D6, CYP3A5, CYP3A4, SCL22A6, UGT1A1) Literature-based: SNPs -EFV absorption, distribution, metabolism, elimination (ADME) Tag SNPs: Neighboring regions in high LD across coding/noncoding regions of ADME genes Non-genetic: Diet, age, race, HepB/C status, smoking, substance use, hepatic, renal function, etc.

6. Results Factors associated with short-term EFV exposure (AUC/dose, n=111) Factor Effect on AUC (±95%CI) p-value Distribution of factor Oranges or orange juice in preceding 5 days 1.26 (1.05 -1.50) 0.01276 (68.5%) Per doubling of ALT level 1.23 (1.11-1.36) 0.0001 Median ALT (range) 23 (8-117) IU/L CYP2B6 983 T>C (rs28399499) 0 doses of minor allele (TT) 1 or 2 doses of minor allele (TC/CC) 1.00 1.96 (1.54-2.5) 2.2 x 10 -10 95 (85.6%) -0 dose 16 (14.4%) -1/2 dose CYP2B6 516 G>T (rs3745274) 0 or 1 doses of minor allele (GG, GT) 2 doses of minor allele (TT) 1.00 3.5 (2.7-4.5) 1.4 x 10 -18 97 (87.4%) – 0/1 dose 14 (12.6%)-2 doses ABCB1 haplotype (2 SNPs: rs7779562 & rs4148745) 0 doses of the haplotype 1 or 2 doses of haplotype 1.00 1.60 (1.24-2.1) 0.0004 14 (12.6%)-0 dose 97 (87.4%)- 1/2 doses

7. Results Factors associated with long-term exposure (hair levels/dose, n=87) –models include adherence Factor Effect on hair (±95%CI) p-value Distribution of factor ALT, Orange juice, ABCB1 haplotype, and self-reported adherence (below) not significantly associated with hair levels CYP2B6 983 T>C ( rs28399499) 0 doses of minor allele (TT) 1 or 2 doses of minor allele (TC/CC) 1.00 1.70 (1.09-2.7) 0.021 77 (88.5%) -0 dose 10 (11.5%) -1/2 doses CYP2B6 516 G>T (rs3745274) 0 or 1 dose of minor allele (GG, GT) 2 doses of minor allele (TT) 1.00 3.2 (2.2-4.7) 1.0 x 10 -10 74 (85.1%) -0/1 dose 13 (14.9%) – 2 doses Self-reported adherence ≤74% 75-94% ≥95% 1.00 0.94 (0.45-2.0) 1.10 (0.56-2.2) 0.88 0.77 4 (4.6%) 14 (16.1%) 69 (79.3%)

8. Conclusions Individuals homozygous CYP2B6 516 rare (TT) allele >3- fold increases in short-term (AUCs) and long-term (hair) EFV exposure in this diverse cohort of HIV-infected women AUCs more robust than single plasma levels (and self- reported adherence) as short-term measures, cumbersome Hair levels better in averaging exposure over time Effect of CYP2B6 516 TT on long-term exposure signifies durable effects Genetic testing coupled with hair measurement may enable EFV dosing optimization in clinical setting, especially when non-genetic risk factors for high exposure are present

9. Acknowledgements Participants and staff of the WIHS Funding  NIAID/NIH RO1 AI065233 (Greenblatt); UO1 AI034989 (Greenblatt); NIAID ARRA 3U01AI034989-17S1 (Greenblatt, Aouizerat); K23 AI067065 (Gandhi ) THANK YOU!