Original Article

Evaluating the association of single-nucleotide polymorphisms with tenofovir exposure in a diverse prospective cohort of women living with HIV

Received:
Revised:
Accepted:
Published online:

Results from this paper were presented, in part, at the 22nd Conference on Retroviruses and Opportunistic Infections in Seattle, WA, USA, from 23–26 February 2015.

Abstract

Higher exposure to tenofovir (TFV) increases the risk for kidney function decline, but the impact of genetic factors on TFV exposure is largely unknown. We investigated whether single-nucleotide polymorphisms (SNPs, n=211) in 12 genes are potentially involved in TFV exposure. Participants (n=91) from the Women’s Interagency HIV Study, underwent a 24 h intensive pharmacokinetic sampling of TFV after witnessed dose and TFV area under the time–concentration curves (AUCs) were calculated for each participant. SNPs were assayed using a combination of array genotyping and Sanger sequencing. Linear regression models were applied to logarithmically transformed AUC. Those SNPs that met an a priori threshold of P<0.001 were considered statistically associated with TFV AUC. ABCG2 SNP rs2231142 was associated with TFV AUC with rare allele carriers displaying 1.51-fold increase in TFV AUC (95% confidence interval: 1.26, 1.81; P=1.7 × 10−5). We present evidence of a moderately strong effect of the rs2231142 SNP in ABCG2 on a 24 h TFV AUC.

  • Subscribe to The Pharmacogenomics Journal for full access:

    $532

    Subscribe

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

References

  1. 1.

    , . Sex differences in pharmacokinetics and toxicity of antiretroviral therapy. Expert Opin Drug Metab Toxicol 2006; 2: 273–283.

  2. 2.

    , , , , , et al. Higher tenofovir exposure is associated with longitudinal declines in kidney function in women living with HIV. AIDS 2016; 30: 609–618.

  3. 3.

    , , , , . Antiretroviral drug toxicity in relation to pharmacokinetics, metabolic profile and pharmacogenetics. Expert Opin Drug Metab Toxicol 2011; 7: 609–622.

  4. 4.

    , , , , , et al. Therapeutic drug monitoring of nelfinavir and indinavir in treatment-naive HIV-1-infected individuals. AIDS 2003; 17: 1157–1165.

  5. 5.

    , , , , , et al. Indinavir trough concentration as a determinant of early nephrolithiasis in HIV-1-infected adults. Ther Drug Monit 2007; 29: 164–170.

  6. 6.

    , , , , . Long-term treatment with tenofovir: prevalence of kidney tubular dysfunction and its association with tenofovir plasma concentration. Antivir Ther 2014; 19: 765–771.

  7. 7.

    , , , , , et al. Prediction of neuropsychiatric adverse events associated with long-term efavirenz therapy, using plasma drug level monitoring. Clin Infect Dis 2005; 41: 1648–1653.

  8. 8.

    , , , , , et al. Are adverse events of nevirapine and efavirenz related to plasma concentrations? Antivir Ther 2005; 10: 489–498.

  9. 9.

    , , , , , . Efavirenz plasma levels can predict treatment failure and central nervous system side effects in HIV-1-infected patients. AIDS 2001; 15: 71–75.

  10. 10.

    , , , , , et al. Nevirapine plasma concentrations are associated with virologic response and hepatotoxicity in Chinese patients with HIV infection. PLoS ONE 2011; 6: e26739.

  11. 11.

    WHOGuideline on When to Start Antiretroviral Therapy and on Pre-Exposure Prophylaxis for HIV. WHO: Geneva, Switzerland, 2015.

  12. 12.

    WHOConsolidated Guidelines on the Use of Antiretroviral Drugs for Treating and Preventing HIV Infection: Recommendations for a Public Health Approach. WHO: Geneva, Switzerland, 2013.

  13. 13.

    , , , , , . Association of tenofovir exposure with kidney disease risk in HIV infection. AIDS 2012; 26: 867–875.

  14. 14.

    , , , , , et al. Common clinical conditions - age, low BMI, ritonavir use, mild renal impairment - affect tenofovir pharmacokinetics in a large cohort of HIV-infected women. AIDS 2014; 28: 59–66.

  15. 15.

    , , , , , et al. Low body weight in females is a risk factor for increased tenofovir exposure and drug-related adverse events. PLoS ONE 2013; 8: e80242.

  16. 16.

    , , , , . Should the dose of tenofovir be reduced to 200-250 mg/day, when combined with protease inhibitors? J Int AIDS Soc 2014; 17: 19583.

  17. 17.

    , , , , , . Pharmacokinetics and safety of tenofovir disoproxil fumarate on coadministration with lopinavir/ritonavir. J Acquir Immune Defic Syndr 2006; 43: 278–283.

  18. 18.

    , , , , . Clinical and genetic determinants of intracellular tenofovir diphosphate concentrations in HIV-infected patients. J Acquir Immune Defic Syndr 2008; 47: 298–303.

  19. 19.

    , , , , , et al. The effect of lopinavir/ritonavir on the renal clearance of tenofovir in HIV-infected patients. Clin Pharmacol Ther 2008; 83: 265–272.

  20. 20.

    , , , , , et al. Impact of small body weight on tenofovir-associated renal dysfunction in HIV-infected patients: a retrospective cohort study of Japanese patients. PLoS ONE 2011; 6: e22661.

  21. 21.

    , , , , , et al. Renal impairment in patients receiving a tenofovir-cART regimen: impact of tenofovir trough concentration. J Acquir Immune Defic Syndr 2013; 62: 375–380.

  22. 22.

    , , , , , et al. Impairment in kidney tubular function in patients receiving tenofovir is associated with higher tenofovir plasma concentrations. AIDS 2010; 24: 1064–1066.

  23. 23.

    . Renal dysfunction and tenofovir toxicity in HIV-infected patients. Top HIV Med 2008; 16: 122–126.

  24. 24.

    , , , , , et al. Association between ABCC2 gene haplotypes and tenofovir-induced proximal tubulopathy. J Infect Dis 2006; 194: 1481–1491.

  25. 25.

    , , , , , et al. Predictors of kidney tubular dysfunction in HIV-infected patients treated with tenofovir: a pharmacogenetic study. Clin Infect Dis 2009; 48: e108–e116.

  26. 26.

    , . Pharmacogenetics of tenofovir treatment. Pharmacogenomics 2009; 10: 1675–1685.

  27. 27.

    , , , , , . Functional defect caused by the 4544G>A SNP in ABCC2: potential impact for drug cellular disposition. Pharmacogenet Genomics 2011; 21: 884–893.

  28. 28.

    , , , , , et al. Genetic variants of ABCC10, a novel tenofovir transporter, are associated with kidney tubular dysfunction. J Infect Dis 2011; 204: 145–153.

  29. 29.

    , , , , , et al. Tenofovir renal proximal tubular toxicity is regulated by OAT1 and MRP4 transporters. Lab Invest 2011; 91: 852–858.

  30. 30.

    , , , , , et al. Single nucleotide polymorphisms in ABCC2 associate with tenofovir-induced kidney tubular dysfunction in Japanese patients with HIV-1 infection: a pharmacogeneticstudy. Clin Infect Dis 2012; 55: 1558–1567.

  31. 31.

    , , , , , et al. The Women's Interagency HIV Study. WIHS Collaborative Study Group. Epidemiology 1998; 9: 117–125.

  32. 32.

    , , , , , et al. The Women's Interagency HIV Study: an observational cohort brings clinical sciences to the bench. Clin Diagn Lab Immunol 2005; 12: 1013–1019.

  33. 33.

    , , , , , et al. Nonnucleoside reverse transcriptase inhibitor pharmacokinetics in a large unselected cohort of HIV-infected women. J Acquir Immune Defic Syndr 2009; 50: 482–491.

  34. 34.

    , , , , , et al. A single-nucleotide polymorphism in CYP2B6 leads to >3-fold increases in efavirenz concentrations in plasma and hair among HIV-infected women. J Infect Dis 2012; 206: 1453–1461.

  35. 35.

    , , , . The simultaneous assay of tenofovir and emtricitabine in plasma using LC/MS/MS and isotopically labeled internal standards. J Chromatogr B Anal Technol Biomed Life Sci 2009; 877: 1907–1914.

  36. 36.

    , , , , . A panel of ancestry informative markers for estimating individual biogeographical ancestry and admixture from four continents: utility and applications. Hum Mutat 2008; 29: 648–658.

  37. 37.

    , , , , . Snagger: a user-friendly program for incorporating additional information for tagSNP selection. BMC Bioinformatics 2008; 9: 1–13.

  38. 38.

    , , , , , et al. Associations between CYP2B6 polymorphisms and pharmacokinetics after a single dose of nevirapine or efavirenz in African americans. J Infect Dis 2009; 199: 872–880.

  39. 39.

    , . A comparison of numerical integrating algorithms by trapezoidal, Lagrange, and spline approximation. J Pharmacokinet Biopharm 1978; 6: 79–98.

  40. 40.

    , , , , . Pharmacokinetics and dosing recommendations of tenofovir disoproxil fumarate in hepatic or renal impairment. Clin Pharmacokinet 2006; 45: 1115–1124.

  41. 41.

    , , , , , et al. Pharmacokinetics of antiretroviral regimens containing tenofovir disoproxil fumarate and atazanavir-ritonavir in adolescents and young adults with human immunodeficiency virus infection. Antimicrob Agents Chemother 2008; 52: 631–637.

  42. 42.

    , , , , , et al. Tenofovir plasma concentrations related to estimated glomerular filtration rate changes in first-line regimens in African HIV-infected patients: ANRS 12115 DAYANA substudy. J Antimicrob Chemother 2015; 70: 1517–1521.

  43. 43.

    , , , , , . Tenofovir-induced renal toxicity in 324 HIV-infected, antiretroviral-naïve patients. Scand J Infect Dis 2011; 43: 656–660.

  44. 44.

    , , , , , et al. A pharmacogenetic candidate gene study of tenofovir-associated Fanconi syndrome. Pharmacogenet Genomics 2015; 25: 82–92.

  45. 45.

    , , , , , et al. A Single-Nucleotide Polymorphism in ABCC4 Is Associated with Tenofovir-Related Beta2-Microglobulinuria in Thai Patients with HIV-1 Infection. PLoS ONE 2016; 11: e0147724.

  46. 46.

    , , , , . ABCC2*1C and plasma tenofovir concentration are correlated to decreased glomerular filtration rate in patients receiving a tenofovir-containing antiretroviral regimen. J Antimicrob Chemother 2014; 69: 2195–2201.

  47. 47.

    , , , , , et al. Tenofovir-induced renal tubular dysfunction in vertically HIV-infected patients associated with polymorphisms in ABCC2, ABCC4 and ABCC10 genes. Pediatr Infect Dis J 2013; 32: e403–e405.

  48. 48.

    , , , , , et al. Common polymorphisms influencing serum uric acid levels contribute to susceptibility to gout, but not to coronary artery disease. PLoS ONE 2009; 4: e7729.

  49. 49.

    , , , , , . Identification of a urate transporter, ABCG2, with a common functional polymorphism causing gout. Proc Natl Acad Sci USA 2009; 106: 10338–10342.

  50. 50.

    , , , , , et al. Association of three genetic loci with uric acid concentration and risk of gout: a genome-wide association study. Lancet 2008; 372: 1953–1961.

  51. 51.

    , , , , , et al. Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations. PLoS Genet 2009; 5: e1000504.

  52. 52.

    , , , , , et al. Association of functional polymorphism rs2231142 (Q141K) in the ABCG2 gene with serum uric acid and gout in 4 US populations: the PAGE Study. Am J Epidemiol 2013; 177: 923–932.

  53. 53.

    , , . ABCG2: structure, function and role in drug response. Expert Opin Drug Metab Toxicol 2008; 4: 1–15.

  54. 54.

    , , , . Interactions of tenofovir and tenofovir disoproxil fumarate with drug efflux transporters ABCB1, ABCG2, and ABCC2; role in transport across the placenta. AIDS 2014; 28: 9–17.

  55. 55.

    , , , , , et al. Marked intraindividual variability in antiretroviral concentrations may limit the utility of therapeutic drug monitoring. Clin Infect Dis 2006; 42: 1189–1196.

Download references

Acknowledgements

We thank the Women's Interagency HIV Study (WIHS) participants who contributed data to this study. Data were collected by the WIHS Collaborative Study Group with centers (Principal Investigators at the time of data collection) at New York City/Bronx Consortium (KA); Brooklyn, New York (Howard Minkoff, MD); Washington DC, Metropolitan Consortium (MAY); The Connie Wofsy Study Consortium of Northern California (RMG, Phyllis Tien and BEA); Los Angeles County/Southern California Consortium (Alexandra Levine, MD); Chicago Consortium (MC); and Data Coordinating Center (SJG). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the US National Institutes of Health. WIHS (Principal Investigators): UAB-MS WIHS (Michael Saag, Mirjam-Colette Kempf and Deborah Konkle-Parker), U01-AI-103401; Atlanta WIHS (Ighovwerha Ofotokun and Gina Wingood), U01-AI-103408; Bronx WIHS (KA), U01-AI-035004; Brooklyn WIHS (Howard Minkoff and Deborah Gustafson), U01-AI-031834; Chicago WIHS (MC and Audrey French), U01-AI-034993; Metropolitan Washington WIHS (MAY and Seble Kassaye), U01-AI-034994; Miami WIHS (Margaret Fischl and Lisa Metsch), U01-AI-103397; UNC WIHS (Adaora Adimora), U01-AI-103390; Connie Wofsy Women’s HIV Study, Northern California (RMG, BEA and Phyllis Tien), U01-AI-034989; WIHS Data Management and Analysis Center (SJG and Elizabeth Golub), U01-AI-042590; Southern California WIHS (Joel Milam), U01-HD-032632 (WIHS I – WIHS IV). The WIHS is funded primarily by the National Institute of Allergy and Infectious Diseases (NIAID), with additional co-funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Cancer Institute (NCI), the National Institute on Drug Abuse (NIDA) and the National Institute on Mental Health (NIMH). Targeted supplemental funding for specific projects is also provided by the National Institute of Dental and Craniofacial Research (NIDCR), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute on Deafness and other Communication Disorders (NIDCD) and the NIH Office of Research on Women’s Health. WIHS data collection is also supported by UL1-TR000004 (UCSF CTSA) and UL1-TR000454 (Atlanta CTSA). SMB is supported by the UCSF Traineeship in AIDS Prevention Studies (US National Institutes of Health (NIH) T32 MH-19105). This research was also supported by a grant from the National Institutes of Health, University of California, San Francisco-Gladstone Institute of Virology and Immunology Center for AIDS Research, P30-AI027763.

Author information

Affiliations

  1. Department of Medicine, University of California, San Francisco, San Francisco, CA, USA

    • S M Baxi
    •  & R M Greenblatt
  2. School of Public Health, University of California, Berkeley, Berkeley, CA, USA

    • S M Baxi
  3. Department of Clinical Pharmacy, University of California, San Francisco, San Francisco, CA, USA

    • R M Greenblatt
    •  & B E Aouizerat
  4. Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA

    • R M Greenblatt
    •  & P Bacchetti
  5. CORE Center, Division of Infectious Diseases, John H. Stroger Jr. Hospital of Cook County, Chicago, IL, USA

    • M Cohen
  6. Division of Infectious Diseases, State University of New York, Downstate Medical Center, Brooklyn, NY, USA

    • J A DeHovitz
  7. Departments of Medicine and Obstetrics and Gynecology and Women’s Health, Albert Einstein College of Medicine, Bronx, NY, USA

    • K Anastos
  8. Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

    • S J Gange
  9. Department of Medicine, Georgetown University Medical Center, Washington, DC, USA

    • M A Young
  10. Bluestone Center for Clinical Research, College of Dentistry, New York University, New York, NY, USA

    • B E Aouizerat
  11. Department of Oral and Maxillofacial Surgery, College of Dentistry, New York University, New York, NY, USA

    • B E Aouizerat

Authors

  1. Search for S M Baxi in:

  2. Search for R M Greenblatt in:

  3. Search for P Bacchetti in:

  4. Search for M Cohen in:

  5. Search for J A DeHovitz in:

  6. Search for K Anastos in:

  7. Search for S J Gange in:

  8. Search for M A Young in:

  9. Search for B E Aouizerat in:

Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to B E Aouizerat.

Supplementary information