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. Author manuscript; available in PMC: 2021 Dec 1.
Published in final edited form as: Infect Genet Evol. 2021 Apr 8;92:104856. doi: 10.1016/j.meegid.2021.104856

Pharmacogenetic predictors of nevirapine pharmacokinetics in Ghanaian children living with HIV with or without TB coinfection

Taimour Langaee a, Mohammad H Al-Shaer b, Yan Gong a, Elizabeth Lima a,c, Sampson Antwi d,e, Anthony Enimil d,e, Albert Dompreh f, Hongmei Yang g, Wael A Alghamdi h, Lubbe Wiesner i, Charles A Peloquin b, Awewura Kwara j,*
PMCID: PMC8636019  NIHMSID: NIHMS1757755  PMID: 33839311

Abstract

Nevirapine (NVP) is a non-nucleoside reverse transcriptase inhibitor that is used in the treatment of human immunodeficiency virus (HIV) infection in children younger than 3 years old. Identifying genetic predictors of NVP pharmacokinetics (PK) in young children is important because inter-individual variability in NVP concentrations contributes to variable treatment response and the information may be used to individualize dosing decisions. We examined the relationship between genetic variations in relevant drug disposition genes and NVP PK parameters in Ghanaian children living with HIV eligible to initiate NVP-based antiretroviral therapy. Participants received NVP plus zidovudine and lamivudine or abacavir and lamivudine twice daily, and those with tuberculosis (TB) coinfection received concurrent anti-TB therapy with NVP. Pharmacokinetic sampling was performed after at least 4 weeks of antiretroviral therapy. Nevirapine minimum concentration (Cmin), area under the concentration-time curve from time 0 to 12 h (AUC0–12h) and apparent clearance (CL/F) were calculated using non-compartmental analysis using Phoenix v8.0 software. Genotyping for CYP2B6, CYP2A6, CYP3A5, ABCB1, NR1I2, and NR1I3 single nucleotide polymorphism (SNPs) was performed by TaqMan® allelic discrimination method. The median (range) NVP dose received was 10 (7–14) mg/kg. Of the 53 participants, the median (range) Cmin was 3.3 (0.0–14.0) mg/L and AUC0–12h was 56.0 (16.7–202.6) mg.hr/L. Using step-wise regression, CYP2B6 rs3745274 and NR1I2 rs6785049 SNPs were independent as well as joint predictors of NVP AUC0–12h, Cmin, and CL/F. We concluded that genotyping for CYP2B6 rs3745274, and the NR1I2 rs6785049 G > A SNP (which encodes the transcriptional factor, pregnane X receptor), could improve prediction of NVP PK for individualized therapy.

Keywords: Nevirapine, Pharmacokinetics, CYP2B6, CYP3A4, Nuclear receptors, Single nucleotide polymorphism

1. Introduction

Nevirapine (NVP), a non-nucleoside reverse transcriptase inhibitor (NNRTI) is an essential component of alternative first-line antiretroviral therapy (ART) regimen for neonates and children younger than 3 years who are living with human immunodeficiency virus (HIV) in resource-limited settings (WHO, 2019). The efficacy of NVP-based ART in children living with HIV is highly variable, with high rates of virological failure reported (Barlow-Mosha et al., 2016; Bienczak et al., 2017b; Bitwale et al., 2021; Lowenthal et al., 2013). Nevirapine minimum concentrations (Cmin) < 3 mg/L has been associated with poor virological suppression in studies in adults (de Vries-Sluijs et al., 2003; Veldkamp et al., 2001). A relationship between NVP Cmin and virological response is also reported in children (Bienczak et al., 2017b) suggesting that NVP concentrations influence clinical outcomes. There is a high interindividual variability in NVP plasma concentrations after the fixed standard dosing for children (Bienczak et al., 2017a; Dross et al., 2014; Ellis et al., 2007; Fillekes et al., 2012; Nikanjam et al., 2012; Swaminathan et al., 2011). As NVP concentrations outside its narrow therapeutic window of >3 to 8 mg/L could contribute to the risk of adverse effects or virological failure (de Vries-Sluijs et al., 2003), identifying predictors of NVP pharmacokinetics (PK) could inform strategies to individualized therapy. There is even greater variability in NVP concentrations during coadministration with rifampin-containing TB therapy in children with HIV/TB co-infection, which may suggest there is interindividual differences in responsiveness to drug-drug interactions (Enimil et al., 2019; Oudijk et al., 2012).

Nevirapine undergoes metabolism by hepatic CYP3A and CYP2B6 enzymes to form 2- and 12-hydroxy nevirapine and 3- and 8-hydroxy nevirapine, respectively (Mo et al., 2009; Riska et al., 1999). While several studies have identified a strong association between CYP2B6 516TT genotype status and reduced NVP clearance or high plasma exposure in adults (Bertrand et al., 2012; Heil et al., 2012; Penzak et al., 2007; Ramachandran et al., 2009; Rotger et al., 2005; Vardhanabhuti et al., 2013), few studies have replicated these finding in children (Bienczak et al., 2017a; Saitoh et al., 2007). Not only is the pharmacogenetics of NVP PK understudied in children, a model that included several genetic factors in one study found that CYP2B6 genetic variation, including 516 G > T single nucleotide polymorphism (SNP) explained only 11% of interindividual variability in NVP clearance (Bertrand et al., 2012). To identify other genetic factors associated with interindividual variability in NVP PK beyond that due to CYP2B6 516G > T SNP in children, we examined the relationship between NVP PK and SNPs in CYP2B6, CYP3A5, CYP2A6, ABCB1, as well as the nuclear receptors, NR1I2 and NR1I3 in Ghanaian children living with HIV with and without tuberculosis (TB) coinfection.

2. Materials and methods

2.1. Study population

A PK/pharmacogenetics study was performed at Komfo Anokye Teaching Hospital (KATH) in Ghana between October 2012 and November 2017. Participants were enrolled if they were aged 3 to 35 months old or weighed <10 kg, ART-naïve and eligible to initiate NVP-based ART. Children with acute illness other than malnutrition or had opportunistic infections other than TB were excluded. The Institutional Review Boards of Kwame Nkrumah University of Science and Technology, Kumasi Ghana (reference # CHRPE/AP/107/11), Lifespan Hospitals in Providence, Rhode Island (CMTT/Proj # 204412 Pedi Cat B), and University of Florida, Gainesville (IRB # IRB201601266) reviewed and approved the study. All parents/guardians provided written informed consent. This study was registered with ClinicalTrials.gov (NCT01699633).

Patients received NVP (200 mg/m2 once daily for 14 days then twice daily) plus zidovudine and lamivudine or abacavir and lamivudine twice daily. In addition, children with TB coinfection received concurrent therapy with rifampin, isoniazid, pyrazinamide, and ethambutol for 2 months then rifampin and isoniazid for 4 months according to the currently recommended dosages (WHO, 2014).

2.2. Pharmacokinetic analysis

Pharmacokinetic sampling (PK1) was performed after at least 4 weeks of ART in all participants. At the time of PK1, the children with TB coinfection were all receiving concurrent 4-drug antituberculosis (anti-TB) therapy. In addition, PK sampling was repeated after at least 4 weeks off anti-TB therapy (PK2). Participants were fasting for 2 h in case of non-breastfed children, while children exclusively on breastfeeding were fed as needed during the study. Blood samples were collected once at 0, 2, 6, and 12 h after NVP dose, centrifuged at 3000g for 10 min, and stored at −80 °C. Nevirapine concentration was measured using a validated liquid chromatography with tandem mass spectrometry assay at the University of Cape Town as previously described (Enimil et al., 2019). The assay was validated over the concentration range of 0.0195 μg/mL to 20 μg/mL. The accuracy (%Nom) and precision (%CV) statistics of the lower limit of quantification, low, medium, and high quality controls were between 90.8% and 100.8%, and below 9.3% for nevirapine during inter- and intra-day validation. The laboratory participated in the Clinical Pharmacology Quality Assurance (CPQA) external QC program under a contract with the Division of AIDS of the National Institute of Allergy and Infectious Diseases. This assay was CPQA approved. Minimum concentration (Cmin), area under the concentration-time curve from time 0 to 12 h (AUC0–12h), and apparent clearance (CL/F) were calculated using non-compartmental analysis on Phoenix v8.0 (Phoenix Software; Pharsight Corporation, Mountain View, CA).

2.3. Genotyping

Genotyping for CYP2B6 (rs3745274, rs3211371, rs4803419, rs28399499), CYP2A6 (rs28399433), CYP3A5 (rs10264272, rS776746), ABCB1 (rs1045642), NR1I2 (rs2472677, rs6785049, rS3732356), and NR1I3 (rS2307424, rs2502815, rs3003596), SNPs was performed by TaqMan® allelic discrimination using the fluorescence-based TaqMan® Quant Studio Real-Time PCR System (Life Technologies/Fisher Scientific, Foster City, CA). The PCR primers and probes for TaqMan® assays were purchased from Applied Biosystems/Fisher Scientific (Life Technologies/Fisher Scientific, Foster City, California, USA). The genotyping for SNP assays was performed and analyzed according to the manufacturer’s recommendations (Life Technologies/Fisher Scientific, Foster City, CA). For primary analyses, we performed genotyping of polymorphisms (CYP2B6 516G > T and 983 T > C) known for associations with NVP PK (Bienczak et al., 2017a). A more extensive genotyping in CYP2B6, as well as selected SNPs in CYP2A6, CYP3A4/5, PXR, CAR, ABCB1, NR1I3 and NR1I2 was performed for exploratory analyses to find novel genotype-phenotype associations. However, three SNPs (CYP2B6 rS28399499, CYP2A6 rS28399433, NR1I2 rS3732356) which deviated from the Hardy Weinberg Equilibrium (HWE) were removed from the final analysis.

2.4. Statistical analysis

Categorical data were presented as counts and percentages, while continuous data as medians (ranges) or means (standard deviations) as appropriate. Association between NVP PK parameters and each studied SNP was investigated using unadjusted and adjusted linear regression analyses. Step-wise regression was performed to evaluate the contribution of multiple SNPs and covariates associated with each PK parameter using P-value < 0.2 for inclusion and >0.05 for exclusion, while age, sex, nucleoside reverse transcriptase (NRTI) backbone, and TB co-infection were forced into the model. An additive mode of inheritance was used in analyses and the genotypes were coded as 0, 1, and 2. When appropriate, the combined effect of multiple SNPs on an individual level was also evaluated. Statistical analyses were performed using SAS v9.4 or JMP Pro v15.0 (SAS Institute, Cary, NC). A P-value < 0.05 was considered statistically significant.

3. Results

Of 60 eligible participants who completed PK1 sampling, seven were excluded from the final analysis because of the following reasons: six participants had two NVP peak concentrations with the second peak occurring at 12 h post-dose, and one had very low concentrations throughout the sampling period suspicious for poor medication adherence. Of the 53 participants in the study, the median (range) age and weight were 1.6 (0.3–3.6) years and 8.3 (4.5–12.5) kg, 31 (58%) were male, and 23 (43%) had TB co-infection. The median (range) NVP dose received was 10 (7–14) mg/kg. The median (range) Cmin was 3.3 (0.0–14.0) mg/L, AUC0–12 56.0 (16.7–202.6) mg.hr/L, and CL/F 1.4 (0.4–4.3) L/h.

The SNPs included in our analyses and minor allele frequency is shown in Table 1. In the univariate regression analysis, CYP2B6 516G > T SNP was the only predictor of NVP AUC0–12h, Cmin and CL/F in both the unadjusted and adjusted analyses while NR1I2 rs6785049 G > A SNP was a predictor of NVP AUC0–12h and Cmin and showed a trend towards association with CL/F (Table 1).

Table 1.

Minor allele frequency of the studied SNPs and the P-values for the single-SNP analysis in unadjusted and adjusted regression models.

Gene
 SNP
 rs number
 MAF
 AUC0–12
 Cmin
 CL/F
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
CYP2B6 516G > T (Q172H) rs3745274 0.50 0.01 0.005 0.027 0.02 0.039 0.02
CYP2B6 15582C > T rs4803419 0.07 0.34 0.37 0.32 0.36 0.12 0.11
CYP2B6 1459C > T rs3211371 0.02 0.59 0.91 0.64 0.91 0.87 0.82
CYP3A5 * 3 6986A > G rs776746 0.14 0.14 0.16 0.15 0.15 0.35 0.53
CYP3A5 * 6 14690G > A rs10264272 0.18 0.39 0.08 0.31 0.08 0.25 0.06
ABCB1 3435C > T rs1045642 0.16 0.63 0.52 0.62 0.55 0.39 0.25
NR1I2 C > T rs2472677 0.39 0.96 0.82 0.98 0.77 0.82 0.79
NR1I2 G > A rs6785049 0.02 0.026 0.005 0.026 0.008 0.07 0.009
NR1I3 G > A rs2307424 0.07 0.31 0.41 0.29 0.38 0.13 0.21
NR1I3 G > A rs2502815 0.36 0.75 0.84 0.79 0.86 0.41 0.69
NR1I3 A > G rs3003596 0.45 0.30 0.30 0.29 0.28 0.33 0.29
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SNP, single nucleotide polymorphism; MAF, minor allele frequency; AUC0–12h, area under the concentration-time curve from times 0 to 12 h; CL/F, apparent clearance; Cmin, minimum concentration; SNP, single nucleotide polymorphism; Adjusted analyses adjusted for age, gender, TB, and NVP dose received.

*

Significant P-values are shown in bold.

In the stepwise regression analysis in which the regression model was adjusted for age, gender, NRTI backbone, and TB coinfection status, CYP2B6 516G > T rS3745274 and NR1I2 rS6785049 G > A SNPs were independently associated with AUC0–12h, Cmin, and CL/F (Table 2). The final models explained 37%, 29% of variability in AUC0–12h, Cmin, and CL/F, respectively. Fig. 1 shows the concentration versus time profile for CYP2B6 rs3745274 and NR1I2 rs6785049 stratified by genotype. Genotype-dependent differences for CYP2B6 rs3745274 was seen as early as 2-h post-dose while that for NR1I2 was only significant at the 6 and 12-h post-dose (Fig. 1). Nevirapine AUC0–12h stratified by combined CYP2B6 rs3745274 and NR1I2 rs6785049 SNPs are shown in Fig. 2. The combined CYP2B6 516GT/NR1I2 rs6785049 GA genotype was associated with a slow metabolizer phenotype (Fig. 2). The two participants with CYP2B6 516GT/NR1I2 rs6785049 GA genotype and high NVP exposure had TB co-infection and were receiving concurrent rifampin-containing anti-TB therapy at the time of PK sampling. As shown in Fig. 3, the two participants with NR1I2 variant had paradoxically reduced CL/F while on (PK1) compared to off rifampin-containing anti-TB therapy (PK2). In contrasts, all those with NR1I2 wild type (GG) except one had an increase in CL/F on anti-TB therapy, consistent with induction of clearance (Fig. 3).

Table 2.

Parameter estimates and P-values for the significant SNPs tested together in the adjusted regression model.

Covariates AUC0–12
 Cmin
 CL/F
Beta P Cumulative R2 Beta P Cumulative R2 Beta P Cumulative R2
Age 11.4 0.10 0.01 0.7 0.17 0.01 −0.1 0.63 <0.01
Sex (female) −2.7 0.61 0.02 −0.1 0.74 0.02 0.1 0.36 <0.01
NRTI backbone# −0.7 0.87 0.02 −0.1 0.79 0.02 −0.1 0.51 0.01
TB coinfection* −14.4 0.0076 0.06 −0.9 0.034 0.04 0.4 0.003 0.09
CYP2B6 rs3745274 −27.9 0.0011 0.21 −1.8 0.0072 0.15 0.5 0.007 0.19
NR1I2 rs6785049 90.8 0.0019 0.37 6.4 0.0046 0.29 −1.7 0.0091 0.31
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AUC0–12, area under the concentration-time curve from times 0 to 12 h; CL/F, apparent clearance; Cmin, minimum concentration; SNP, single nucleotide polymorphism.

#

Nucleoside reverse transcriptase inhibitor backbone (abacavir + lamivudine vs. zidovudine + lamivudine).

*

TB coinfection on isoniazid, rifampin, pyrazinamide and ethambutol.

Fig. 1.

Fig. 1.

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Mean (standard error) nevirapine concentration versus time profile stratified by genotype for the significant single nucleotide polymorphisms in the multivariate model. P values are for comparison of mean concentrations by genotype at each timed sample point.

Fig. 2.

Fig. 2.

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Boxplot of nevirapine AUC0–12 h stratified by combined CYP2B6 rs3745274 and NR1I2 rs6785049.

Fig. 3.

Fig. 3.

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Nevirapine CL/F and AUC0–12h on and off antituberculosis therapy in 14 TB/HIV co-infected children with paired samples. Both participants with NR1I2 variant had paradoxically reduced CL/F on anti-TB therapy while only 1 of the 12 with wild type reduced CL/F on anti-TB therapy.

4. Discussion

In this study, we investigated the association between genetic variations in drug metabolizing enzymes, nuclear receptors, and ABCB1 transporter and NVP PK in children living with HIV with and without TB coinfection. The main finding is that CYP2B6 516G > T and NR1I2 rs6785049 genotypes were independent, as well as joint predictors of NVP PK after adjusting for age, sex, NRTI backbone, NVP dose and anti-TB therapy in the children with TB coinfection. In our adjusted regression model analysis that included significant SNPs from the univariate analysis, CYP2B6 516G > T and NR1I2 rs6785049 G > A SNPs were found to be joint predictors of NVP AUC0–12h and Cmin, and CL/F. The other genetic factors included in the analysis did not appear to influence NVP PK in our study population. Consistent with our previous observation in this cohort (Enimil et al., 2019), concurrent anti-TB therapy in the children with TB/HIV coinfection was a significant joint predictor of NVP PK with CYP2B6 516G > T and NR1I2 rs6785049 G > A SNPs.

The association of CYP2B6 516G > T and NVP PK has been well-recognized in studies in diverse adult populations (Bertrand et al., 2012; Brown et al., 2012; Heil et al., 2012; Mahungu et al., 2009; Penzak et al., 2007; Ramachandran et al., 2009; Rotger et al., 2005; Vardhanabhuti et al., 2013). While less studied in children, one study demonstrated the association between the CYP2B6 516TT genotype and reduced NVP clearance or high plasma exposure (Saitoh et al., 2007), while another study found the combined effect of CYP2B6 516G > T/983 T > C genotype to be the main predictor of NVP clearance in African children (Bienczak et al., 2017a). The association between CYP2B6 516G > T SNP and NVP PK is not surprising as NVP is metabolized in part by the CYP2B6 enzyme (Mo et al., 2009; Riska et al., 1999) and the CYP2B6*6 allele harboring the SNPs C.516G > T [Q172H] and C.785A > G [K262R] was significantly associated with a pronounced decrease in CYP2B6 expression and activity (Desta et al., 2007).

To the best of our knowledge, this is the first report of an association of NR1I2 rs6785049 G > A SNP with NVP PK and would warrant confirmation in further studies. The mechanism by which genetic variation in NR1I2 variant may lead to reduced NVP clearance and increased plasma exposure is unknown. Interestingly, rifampin-containing anti-TB therapy did not increase NVP CL/F in the two participants with the NR1I2 variant, which may suggest that the variants are less susceptible to induction compared to wild type (Fig. 3). The nuclear receptor NR1I2 regulates the transcription levels of CYP3A5 and ABCB1 (Tompkins and Wallace, 2007), while NR1I3 tend to regulate CYP2B6 (Sueyoshi et al., 1999). Genetic polymorphisms of NR1I2 can alter the induction of CYP3A4 and CYP2B6 promoter activity, potentially influencing the bioavailability and/or toxicity of antiretroviral drugs (Svard et al., 2010). In the study by Bertrand et al., 2012, in the HIV-infected Cambodians, no consistent associations were found between NR1I2 gene variants and steady-state NVP clearance but the study did not include NR1I2 rS6785049 G > A SNP. Interestingly, NR1I2 rs6785049 SNP was associated with temsirolimus (a prodrug and CYP3A4 substrate) PK, a high risk of severe sirolimus toxicities in patients receiving the drug for bladder cancer treatment (Mbatchi et al., 2017). These findings suggest that effects of NR1I2 rs6785049 G > A SNP is functional and may be mediated through CYP3A4 activity. Thus this SNP should be included in studies examining the pharmacogenetics of CYP3A4 substrates with narrow therapeutic index. Whether the associations of NR1I2 rs6785049 G > A SNP with NVP PK in the young children in our study (who may have immature enzyme systems) can be generalized to adults is unknown and should be further investigated. Although developmental expression of CYP enzymes is a key factor in determining PK status, the maturation of CYP3A4 appear to occur within the first year of life (Hakkola et al., 1998).

Of the two functional SNPs of CYP3A5 in our study, there was a trend towards a significant relationship between CYP3A5*6 and NVP PK in the univariate analysis (Table 1). The functional CYP3A5*3 did not appear to influence NVP PK in our study, which is consistent with the finding of other studies that included CYP3A5*3 (Heil et al., 2012; Penzak et al., 2007). However, one study that enrolled children and adults living with HIV found CYP3A5*3 to be associated with a 31% decreased NVP AUC after controlling for CYP2B6 and age (Brown et al., 2012).

We also found that CYP2B6 516G > T SNP was common in the Ghanaian population with a MAF of 50%, while NR1I2 rs6785049 G > A was rare, with MAF only 2%. Although NR1I2 rs6785049 GA variant was rare, it was associated with the high median NVP concentrations at all sampling points (Fig. 1) and identified patients with CYP2B6 516G > T intermediate metabolizers who were slow metabolizers of NVP (Fig. 2). Thus, our finding suggest that genotyping for CYP2B6 516G > T SNP would identify children at risk of high NVP exposure and the addition of NR1I2 rs6785049 genotyping would identify other persons with unexplained high NVP exposure.

Our study has some limitations. We had planned to include CYP2B6 983 T > C SNP (rs28399499) in our analysis given its known effect on function of CYP2B6. However, given that the genotype distribution did not meet criteria for HWE, it was excluded from the analysis. In addition, our overall sample size was small, which may have limited our ability to detect small genotype effects.

5. Conclusions

Despite the small sample size and the low MAF of NR1I2 rs6785049 SNP in our population, our findings suggest that NR1I2 rs6785049 SNP genotyping along with CYP2B6 SNPs may improve prediction of risk for high NVP concentrations. It is also interesting that NR1I2 rs6785049 variants were not susceptible to the induction effect of rifampin-containing ant-TB therapy. Further studies especially in populations with higher MAF of NR1I2 rs6785049 SNP are required to confirm our findings as well as identify the mechanism for the SNP effect.

Acknowledgements

We thank the study participants and the supportive staff of the TB and HIV clinics at KATH who helped with patient enrolment.

Funding

This work was supported primarily by the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health [grant number HD071779]. The University of Cape Town (UCT) Clinical PK Laboratory was supported in part via the Adult Clinical Trial Group (ACTG), by the National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health under award numbers UM1 AI068634, UM1 AI068636, as well as Infant Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT), funding provided by National Institute of Allergy and Infectious Diseases (U01 AI068632), The Eunice Kennedy Shriver National Institute of Child Health and Human Development, and National Institute of Mental Health grant AI068632. Dr. Yang utilized core services and support from the University of Rochester Center for AIDS Research (CFAR), an NIH-funded program (P30 AI078498). Dr. Kwara received additional support from the Gatorade Trust through funds distributed by the University of Florida Department of Medicine. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Competing interests statement

All authors have no competing interests to declare.

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