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No Relationship Between Drug Transporter Genetic Variants and Tenofovir Plasma Concentrations or Changes in Glomerular Filtration Rate in HIV-Infected Adults

Sirirungsi, Wasna PhD*; Urien, Saik MD†,‡,§; Harrison, Linda MSc*,‖; Kamkon, Jiraporn MT*,‖; Tawon, Yardpiroon MT*,‖; Luekamlung, Nuananong MD; Thongpaen, Suchart MD#; Nilmanat, Ampaipith MD**; Jourdain, Gonzague MD*,‖,††; Lallemant, Marc MD*,‖,††; Le Coeur, Sophie MD, PhD*,‖,††; Ngo-Giang-Huong, Nicole PhD*,‖,††; Owen, Andrew PhD‡‡; Cressey, Tim R. PhD*,‖,††

JAIDS Journal of Acquired Immune Deficiency Syndromes: April 1st, 2015 - Volume 68 - Issue 4 - p e56–e59
doi: 10.1097/QAI.0000000000000504
Letters to the Editor
Free

*Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand

EAU08 University Paris Descartes and CIC1419 Inserm, Paris, France

Hopital Cochin, Assistance Publique-Hopitaux de Paris, Paris, France

§Unite de Recherche clinique, AP-HP, Hopital Tarnier, Paris, France

Institut de Recherche pour le Développement (IRD) UMI 174-Program for HIV Prevention and Treatment (PHPT), Marseille, France

Lamphun Hospital, Lamphun, Thailand

#Maha Sarakham Hospital, Maha Sarakham, Thailand

**Hat Yai Hospital, Songkhla, Thailand

††Harvard School of Public Health, Boston, MA

‡‡Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, United Kingdom

Supported by the National Research University Project under Thailand's Office of the Higher Education Commission, The Global Fund to Fight AIDS, Tuberculosis, and Malaria, Thailand (Grant Round 1 sub recipient PR-A-N-008); National Institutes of Health, NICHD (HD042964), USA, Ministry of Public Health, Thailand; Institut de Recherche pour le Developpement, France; Institut National d'etudes Demographiques, France; Department of Technical and Economic Cooperation, Thailand.

The authors have no conflicts of interest to disclose.

To the Editors:

Host genetics of drug transporters located in the renal tubule may contribute toward tenofovir disoproxil fumarate (TDF)–associated kidney disease susceptibility.1,2 Genetic variants in the ATP-binding cassette (ABC) transporters ABCC2 (1249G>A) and ABCC4 (3463A>G) have been associated with a greater decline in creatinine clearance (CrCL) over 96 weeks of TDF-based treatment.3 High plasma tenofovir (TFV) trough concentrations have been correlated with a decrease in glomerular filtration rate.4 A recent study in Thailand reported that TFV “mid-dose” plasma concentrations were significantly lower in ABCC2 -24CT/TT carriers compared with CC carriers after 24 weeks of TDF/3TC/EFV treatment and independently associated with decreased glomerular rate after 48 weeks.5 We investigated the association between drug transporter genetic polymorphisms implicated in TFV excretion and/or associated nephrotoxicity with TFV plasma concentrations and changes in kidney glomerular filtration rate in antiretroviral-naive HIV-infected adults initiating TDF as part of a NNRTI-based regimen.

This was a retrospective analysis of adults enrolled in an observational cohort study in Thailand [NCT00433030]. Criteria for treatment initiation were CDC clinical stage B/C or CD4 <250 cells per cubic millimeter. TFV-DF was prescribed 300 mg once daily. Patients were followed up monthly during the first 3 months of treatment and then trimonthly thereafter. A single random blood sample was collected at each visit and plasma frozen at −70°C. The exact time of last drug intake and blood draw was recorded. Creatinine clearance was calculated using the Cockcroft–Gault equation to estimate glomerular filtration rate (eGFR). Local institutional review boards approved the protocol, and signed informed consent was obtained from all subjects.

Human genomic DNA isolated from EDTA cell pellets stored at −20°C. Ten single nucleotide polymorphisms (SNPs) linked with TFV excretion and/or associated nephrotoxicity were genotyped: ABCC2: -24C>T (rs717620), 1249G>A (rs2273697), 3563T>A (rs8187694), 3972C>T (rs3740066), and 4544G>A (rs8187710); ABCC4: 3463A>G (rs1751034); ABCC10: G>A (rs9349256), 2843T>C (rs2125739), and SLC22A2: -1604T>C (rs3127573), G>A (rs316009). Primers/probes were designed by the TaqMan “Assays-by-Design” SNP Genotyping Assay Service (Applied Biosystems, Foster City, CA), and SNPs were identified using real-time polymerase chain reaction.

Plasma TFV concentrations were measured using a validated reversed-phase high-performance liquid chromatography assay.6 This assay was internally validated, and the average accuracy was 99%–102% and precision (inter-assay/intra-assay) was <5% of the coefficient of variation. Population means and variances of TFV pharmacokinetic parameters were estimated using non-linear mixed-effects regression (Monolix v4.2, http://www.lixoft.eu).7 Individual patient characteristics including weight, sex, age, body mass index, serum creatinine, and CrCL were evaluated for their inclusion in the model using a stepwise forward inclusion and backward elimination procedure. Validity of the model was evaluated using a visual predictive check. Post hoc subject-specific pharmacokinetic parameters were used to estimate individual TFV trough concentrations (C24) and area under the concentration–time curve (AUC0–24h).

With ∼240 subjects, we had 90% power to detect a difference in TFV C24 of 0.02 μg/mL between combined variants (homozygous and heterozygous), and homozygosity of the common allele provided at least 6% (∼14 subjects) were in the combined variant group (using a 2-sided test, with a standard deviation of 0.02 μg/mL). Differences in TFV C24 between variants (homozygous and heterozygous) and homozygosity of the common allele were assessed by Wilcoxon rank-sum tests (due to nonnormal C24 distribution). To control the false discovery rate, q values were determined.8 CrCL was assumed to be normally distributed, so t-tests were used to compare differences in change in CrCL between variants and homozygosity of the common allele (adjusted for baseline CrCL level). All statistical tests performed were 2-sided using STATA (v11.1).

Two hundred thirty-eight HIV-infected adults (58% female) were included. At treatment initiation, the median (interquartile range) age was 36 (31–42) years, weight 52 (48–59) kg, serum creatinine (SCr) 0.8 (0.7–0.9) mg/dL, creatinine clearance (CrCL) 89 (74–105) mL/min, HIV-1 RNA viral load 4.8 (4.3–5.2) log10 copies per milliliter, and CD4 count 144 (91–208) cells per cubic millimeter. Antiretroviral regimens were either TDF/emtricitabine/efavirenz (n = 191, 80%) or TDF/emtricitabine/nevirapine (n = 47, 20%).

One thousand one hundred twenty-three plasma samples from 238 patients were included. Median (range) number of samples per patient was 5 (1–6), and median time after dose was 13 (0.17–26.75) hours. TFV plasma concentrations were best described by a 2-compartment model, with the absorption and the distribution rate constants equal. Residual variability was described using a proportional error model. For the final model, TFV CL/F (L/h) was estimated using the equation CL/F = TVCL × (CrCL/89)0.534 (where TVCL was the typical population CL/F value and 89 was the median CrCL in this study). Population estimates (interindividual variability) for TFV CL/F, Vc/F, Q, and Vp/F were 51.2 (0.19) L/h, 244 (1.25) L, 121 L/h, and 2430 L, respectively. Proportional residual variability was 0.23. All relative standard errors were <31% and <10% for structural and variability parameters, respectively. The median (IQR) TFV plasma AUC0–24h and C24 were 2.62 (1.72–3.90) μg·h−1·mL−1 and 0.064 (0.038–0.14) μg/mL, respectively, after 1 year of treatment. These values were similar after 3 years of treatment.

Minor allele frequency for ABCC2 -24C>T, 1249G>A, 3563T>A, 3972C>T, and 4544G>A were 0.200, 0.042, 0.004, 0.227, and 0.004, respectively; ABCC4 3463A>G was 0.187; ABCC10 G>A (rs9349256) and 2843T>C were 0.498 and 0.076, respectively; and SLC22A2 -1604T>C and G>A (rs316009) were 0.095 and 0.034, respectively.

For each SNP, no significant difference in TFV C24 was observed between homozygosity of the common allele, heterozygous, and homozygous variant genotypes after 1 and 3 years of TDF treatment. Heterozygous and homozygous variants were combined and compared with patients with homozygosity of the common allele. However, there was no significant difference in TFV C24 after 1 and 3 years of treatment for any of the SNPs (Fig. 1). Weak trends toward lower TFV C24 with ABCC2 -24CT/TT variants at 1 year (P = 0.06) and higher TFV C24 with ABCC4 3463AG/GG variants at 1 year (P = 0.07) were observed but removed with the false discovery rate analysis (q = 0.25). No association between TFV AUC0–24h and SNPs was found.

FIGURE 1

FIGURE 1

No relationship between the individual SNPs (or combining heterozygous or homozygous variants vs. the common allele) and change in CrCL from baseline and after 1 and 3 years of treatment was observed.

The WHO recommends TDF/emtricitabine/efavirenz for the first-line antiretroviral therapy for adults.9 It is important to identify patients with a higher risk for developing TDF-associated kidney dysfunction. Low body weight was an independent risk factor of renal dysfunction (>25% decrease of eGFR from baseline) in Thai10 and Japanese patients.11 Perhaps, it is reasonable to speculate that individuals with lower body weight may be exposed to higher TFV concentrations and consequently at higher risk forf renal drug toxicity. However, the TFV AUC0–24h and C24 observed were similar to those reported in non-Asian populations.12 The allele frequency of the SNPs were similar to the United States and Europe populations, except for ABCC2 1249G>A, which was lower (4% vs. 22%).13,14

We found no significant associations between the drug transporter polymorphisms tested and TFV trough concentrations after 1 and 3 years of treatment. This result is in contrast to a recent study also performed in Thailand, which reported significantly lower TFV concentrations in ABCC2 -24CT/TT carriers after 24 weeks of TDF/3TC/EFV treatment (CC vs. CT/TT, P = 0.018).5 Although the larger sample size of our cohort (2-fold) may support the lack of an association, it is possible that the shorter duration of TDF treatment and different TFV measurements (ie, C24 vs. mid-dose) may explain this difference. A study in 30 HIV-infected adults in the United States found that ABCC2 -24CT/TT carriers excreted 19% more TFV than CC genotype and ABCC4 3463A>G carriers had higher TFV AUC (↑32%) than AA genotype.14 More data in larger diverse populations are needed to determine the strength of these associations and TFV plasma concentrations.

Also, none of the SNPs assessed were associated with the mean change in CrCL after 3 years of TDF treatment. The ABCC2 -24CC genotype was independently associated with decreased glomerular rate after 48 weeks of TDF treatment (although not at 96 weeks) in a prior study in Thailand.5 Baseline age, body weight, and serum creatinine were similar between studies; however, there was a higher proportion of women and higher baseline CD4 count (114 vs. 42 cells/mm3) in this study. Different formulas were also used to estimate glomerular filtration (Cockcroft–Gault vs. Modification of Diet in Renal Disease). Other studies have also reported contrasting results regarding the association between transporter polymorphisms and changes in eGFR. ABCC2 1249G>A and ABCC4 3463A>G reported to be associated with a greater decline in CrCL over 96 weeks3 were not confirmed in a larger study.15 In these studies, concomitant lopinavir/ritonavir use may have been a factor as lopinavir/ritonavir increases TFV exposure, likely by drug-interactions with transporters in the renal tubule.2,16 Transporter genetic polymorphisms may have a better predictive value for kidney dysfunction with ritonavir-boosted protease inhibitors than NNRTI-based regimens.

Overall, transporter polymorphisms implicated to be involved in TFV excretion and/or associated nephrotoxicity were not associated with plasma TFV trough concentrations or changes in glomerular filtration rate after 3 years of a first-line NNRTI-based treatment.

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ACKNOWLEDGMENTS

The authors wish to thank the patients who participated in the study and the staff of the participating clinical sites. Site investigators: Lamphun Hospital: Nuananong Luekamlung; Phayao Provincial Hospital: Guttiga Halue; Chiangrai Prachanukroh Hospital: Pacharee Kantipong; Chiang Kham Hospital: Yuwadee Buranawanitchakorn; Mae Chan Hospital: Sudanee Buranabanjasatean; Prapokklao Hospital: Malee Techapornroong; Chonburi Hospital: Chureeratana Bowonwatanuwong; Rayong Hospital: Sukit Banchongkit; Bhuddasothorn Hospital: Pakorn Wittayapraparat; Nakornping Hospital: Prattana Leenasirimakul; Buddhachinaraj Hospital: Somboon Tansuphasawasdikul; Hat Yai Hospital: Ampaipith Nilmanat; Regional Health Promotion Centre 6, Khon Kaen: Narong Winiyakul; Nong Khai Hospital: Naruepon Yutthakasemsunt; Samutsakhon Hospital: Apichat Chutanunta; Samutprakarn Hospital: Naree Eiamsirikit; Mahasarakam Hospital: Srisuda Thongbuaban; Ratchaburi Hospital: Pensiriwan Sang-a-gad; Lampang Hospital: Panita Pathipvanich; Maharat Nakhon Ratchasima Hospital: Rittha Lertkoonalak; Sanpatong Hospital: Virat Klinbuayaem. PHPT clinical trial unit: P. Sukrakanchana, S. Chalermpantmetagul, R. Peongjakta, Y. S. Thammajitsagul, R. Wongchai, N. Kruenual, N. Krapunpongsakul, W. Pongchaisit, T. Thimakam, R. Wongsrisai, J. Wallapachai, J. Thonglo, S. Jinasa, J. Khanmali, P. Chart, J. Chalasin, B. Ratchanee, N. Thuenyeanyong, P. Krueduangkam, P. Thuraset, S. Thongsuwan, W. Khamjakkaew, K. Yoddee, N. Chaiboonruang, P. Tungyai, L. Laomanit, N. Wangsaeng, S. Tanasri, S. Chailert, K. Than-in-at, N. Jaisieng, D. Chinwong. The authors also thank J. Rooney at Gilead, who helped making Truvada available to patients.

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