CYP2C19 genetic variants affect nelfinavir pharmacokinetics and virologic response in HIV-1-infected children receiving highly active antiretroviral therapy.
ABSTRACT The objective of this research was to identify the impact of genetic variants of P-glycoprotein (ABCB1) and cytochrome P450 (CYP) on nelfinavir pharmacokinetics and response to highly active antiretroviral therapy (HAART) in HIV-1-infected children.
HIV-1-infected children (n = 152) from Pediatric AIDS Clinical Trial Group 366 or 377 receiving nelfinavir as a component of HAART were evaluated. Genomic DNA was assayed for ABCB1 and CYP genetic variants using real-time polymerase chain reaction Nelfinavir oral clearance (CL/F), M8 to nelfinavir ratios, CD4 T cells, and HIV-1-RNA were measured during HAART.
Nelfinavir CL/F and M8 to nelfinavir ratios were significantly associated with the CYP2C19-G681A genotypes (P < 0.001). Furthermore, the CYP2C19-G681A genotype was related to virologic responses at week 24 (P = 0.01). A multivariate analysis demonstrated that age (P = 0.03), concomitant protease inhibitor use (P < 0.001), and the CYP2C19-G681A genotype (P < 0.001) remained significant covariates associated with nelfinavir CL/F.
CYP2C19 genotypes altered nelfinavir pharmacokinetics and the virologic response to HAART in HIV-1-infected children. These findings suggest that CYP2C19 genotypes are important determinants of nelfinavir pharmacokinetics and virologic response in HIV-1-infected children.
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ABSTRACT: Significant intra- and interindividual variability has been observed in response to use of pharmacological agents in treatment of HIV infection. Treatment of HIV infection is limited by high rates of adverse drug reactions and development of resistance in a significant proportion of patients as a result of suboptimal drug concentrations. The efficacy of antiretroviral therapy is challenged by the emergence of resistant HIV-1 mutants with reduced susceptibility to antiretroviral drugs. Moreover, pharmacotherapy of patients infected with HIV is challenging because a great number of comorbidities increase polypharmacy and the risk for drug-drug interactions. Drug-metabolizing enzymes and drug transporters regulate drug access to the systemic circulation, target cells, and sanctuary sites. These factors, which determine drug exposure, along with the emergence of mutations conferring resistance to HIV medications, could explain variability in efficacy and adverse drug reactions associated with antiretroviral drugs. In this review, the major factors affecting the disposition of antiretroviral drugs, including key drug-metabolizing enzymes and membrane drug transporters, are outlined. Genetic polymorphisms affecting the activity and/or the expression of cytochromes P450 or UGT isozymes and membrane drug transport proteins are highlighted and include such examples as the association of neurotoxicity with efavirenz, nephrotoxicity with tenofovir, hepatotoxicity with nevirapine, and hyperbilirubinemia with indinavir and atazanavir. Mechanisms of drug resistance conferred by specific viral mutations are also reviewed, with particular attention to replicative viral fitness and transmitted HIV drug resistance with the objectives of providing a better understanding of mechanisms involved in HIV drug resistance and helping health care providers to better manage interpatient variability in drug efficacy and toxicity.Pharmacological reviews 07/2012; 64(3):803-33. · 18.55 Impact Factor
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ABSTRACT: Genetic polymorphism for cytochrome 450 (P450) enzymes leads to interindividual variability in the plasma concentrations of many drugs. In some cases, P450 genotype results in decreased enzyme activity and an increased risk for adverse drug effects. For example, individuals with the CYP2D6 loss-of-function genotype are at increased risk for ventricular arrhythmia if treated with usual does of thioridazine. In other cases, P450 genotype may influence the dose of a drug required to achieve a desired effect. This is the case with warfarin, with lower doses often necessary in carriers of a variant CYP2C9*2 or *3 allele to avoid supratherapeutic anticoagulation. When a prodrug, such as clopidogrel or codeine, must undergo hepatic biotransformation to its active form, a loss-of-function P450 genotype leads to reduced concentrations of the active drug and decreased drug efficacy. In contrast, patients with multiple CYP2D6 gene copies are at risk for opioid-related toxicity if treated with usual doses of codeine-containing analgesics. At least 25 drugs contain information in their US Food and Drug Administration-approved labeling regarding P450 genotype. The CYP2C9, CYP2C19, and CYP2D6 genes are the P450 genes most often cited. To date, integration of P450 genetic information into clinical decision making is limited. However, some institutions are beginning to embrace routine P450 genotyping to assist in the treatment of their patients. Genotyping for P450 variants may carry less risk for discrimination compared with genotyping for disease-associated variants. As such, P450 genotyping is likely to lead the way in the clinical implementation of pharmacogenomics. This review discusses variability in the CYP2C9, CYP2C19, and CYP2D6 genes and the implications of this for drug efficacy and safety.Pharmacogenomics and Personalized Medicine 01/2011; 4:123-36.
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ABSTRACT: Introduction: Human ATP-binding cassette (ABC) transporters act as translocators of numerous substrates across extracellular and intracellular membranes, thereby contributing to bioavailability and consequently therapy response. Genetic polymorphisms are considered as critical determinants of expression level or activity and subsequently response to selected drugs.Areas covered: Here the influence of polymorphisms of the prominent ABC transporters P-glycoprotein (MDR1, ABCB1), breast cancer resistance protein (BCRP, ABCG2) and the multidrug resistance-associated protein (MRP) 2 (ABCC2) as well as MRP3 (ABCC3) on the pharmacokinetic of drugs and associated consequences on therapy response and clinical outcome is discussed.Expert opinion: ABC transporter genetic variants were assumed to affect interindividual differences in pharmacokinetics and subsequently clinical response. However, decades of medical research have not yielded in distinct and unconfined reproducible outcomes. Despite some unique results, the majority were inconsistent and dependent on the analyzed cohort or study design. Therefore, variability of bioavailability and drug response may be attributed only by a small amount to polymorphisms in transporter genes, whereas transcriptional regulation or post-transcriptional modification seems to be more critical. In our opinion, currently identified genetic variants of ABC efflux transporters can give some hints on the role of transporters at interfaces but are less suitable as biomarkers to predict therapeutic outcome.Expert Opinion on Drug Metabolism & Toxicology 08/2014; · 2.93 Impact Factor
CYP2C19 Genetic Variants Affect Nelfinavir and M8 Pharmacokinetics and Virologic Response in HIV-1 Infected Children Receiving HAART
Akihiko Saitoh,1Elizabeth Sarles,1Edmund Capparelli,1Francesca Aweeka,2Andrea Kovacs,3Sandra Burchett,4Andrew Wiznia,5Sharon Nachman,6Terence Fenton,7Stephen A. Spector1
1Pediatric Infectious Diseases, University of California, San Diego, La Jolla, CA, 2University of California, San Francisco, CA, 3University of Southern California, Los Angeles, CA, 4Harvard Medical School, Boston, MA, 5Jacobi Medical Center, Bronx, NY,
6State University of New York at Stony Brook Health Science Center, Stony Brook, NY, 7Harvard School of Public Health, Boston, MA
9500 Gilman Dr. La Jolla, CA
Tel. (858) 534-7258
Fax. (858) 534-7411
Abstract - - revised
Protease inhibitors (PIs) are known to be a substrate of P-glycoprotein, which has an important role transporting PIs from
intracellular space to extracellular space in various tissues including intestinal epithelial cells, liver, kidney, and lymphocytes.
After absorption from gastrointestinal tract, they are metabolized by hepatic cytochrome P450 (CYP), mainly by CYP3A4 and
CYP2C19. In particular, nelfinavir (NFV) is metabolized into the active metabolite hydroxyl-tert-butylamide (M8) by the
CYP2C19 enzyme, and subsequently NFV and M8 are metabolized by CYP3A4. Several pharmacogenetic studies have
shown that single nucleotide polymorphisms (SNPs) in ATP-binding cassette, sub-family B, member 1 ABCB1 (previously
called multi-drug resistance 1, MDR1) and CYP can influence the activity and bioavailability of NFV.
We previously reported that genetic variants in ABCB1 gene encoding for P-glycoprotein was responsible for variability in
NFV pharmacokinetics (PK) and virologic responses to HAART in children. However, the study was limited because of the
small number of children with the ABCB1-3435-T/T genotype and their different background characteristics. Therefore, to
expand the number of subjects with the ABCB1-3435-T/T genotype, we included the subjects who received NFV as a
component of HAART from two PACTG cohorts including 366 and 377 to investigate the association between ABCB1
genotypes and NFV PK. We also investigated the association between NFV PK and SNPs in CYP2C19 and CYP3A4 which
could be responsible for determining the NFV PK and their clinical response.
Subjects and Methods
Subjects and Methods
Objective: Nelfinavir (NFV) is transported via P-glycoprotein, metabolized to active metabolite (M8) by cytochrome
P450 (CYP) 2C19, and subsequently metabolized by CYP3A4. This research investigated the association between
genetic variants of P-glycoprotein (ABCB1) and CYP on NFV pharmacokinetics (PK) and the response to HAART in
HIV-1 infected children.
Methods: We evaluated 152 HIV-1 infected children from PACTG 366 and 377 receiving NFV as a component of
HAART. Genomic DNA from peripheral blood mononuclear cells was evaluated for ABCB1 and CYP genetic
variants using real-time PCR. Intensive (70%) and sparse (30%) PK were used to calculate NFV oral clearance
(CL/F/m2) and M8 levels. CD4+ T-cell and HIV-1 RNA were measured during HAART.
Results: The NFV CL/F in children with the CYP2C19-681-G/G (wild type, 58.7 L/hr/m2, n=102) was higher than
for those with the G/A (heterozygous variant, 38.0 L/hr/m2, n=42, P=0.001) and A/A (homozygous variant, 31.2
L/hr/m2, n=8, P=0.02). In contrast, the ratio of M8 to NFV was higher in children with the CYP2C19-681-A/A than
for those with the G/A (P=0.003) and G/G (P<0.001). Furthermore, the children with the CYP2C19-681-G/A or A/A
achieving HIV-1 RNA <400 copies/mL (68%) was higher than those with the G/G (46%) at week 24 (P=0.01). The
ABCB1-C3435T genotype was associated with the NFV CL/F (P=0.03) by univariate analyses, but not by
multivariate analyses (P=0.13).
Conclusions: The CYP2C19 genetic variants impacted on NFV PK and the virologic response to HAART in HIV-1
infected children. These findings suggest that CYP2C19 genetic variants are the important determinant in NFV PK
and virologic response in HIV-1 infected children.
Although the ABCB1-C3435T genotype affected NFV PK and virologic response to HAART in HIV-1 infected children by univariate analyses, in multivariate analyses the CYP2C19-
G681A genotype, age, and concomitant RTV use were the only determinants found to significantly affect NFV PK in HIV-1 infected children.
These findings suggest that the CYP2C19-G681A is the most important pharmacogenetic determinant for NFV PK and virologic responses in children who receive HAART containing
To investigate the impact of the ABCB1 and CYP genotypes on NFV PK and clinical response to NFV containing HAART
regimens in HIV-1 infected children.
Subjects (Table 1)
The subjects were selected from the whole study population because they satisfied the following criteria: i) received NFV as a
component of HAART for >24 weeks with reported excellent compliance to HAART, ii) virologic and immunologic data were
available at baseline, weeks 12 and 24, iii) PK data for NFV were available at week 4. Concomitant antiretrovirals included
nevirapine (NVP) (n = 89, 59%), ritonavir (RTV) (n = 69, 45%), and nucleoside reverse transcriptase inhibitors (NRTIs) (n = 152,
106 children (70%): intensive PK collected over 8 hr at week 4 of treatment, 46 subjects (30%): sparse PK. Oral clearance (CL/F)
was determined as dose/area under the curve (AUC0-tau) and was adjusted to body surface area (CL/F/m2). The M8: NFV ratios
were calculated based on each M8 and NFV value and averaged in subjects with the intensive PK data. For children with the
sparse data, the ratio was calculated based on a set of M8 and NFV value at a single visit. When the M8 level was <50 ng/mL,
such numbers were imputed to 50 ng/mL.
Plasma HIV-1 RNA quantitation
Plasma HIV-1 RNA was quantified using the Roche Amplicor HIV-1 Monitor assay (Roche Molecular Systems, Alameda, CA) with
a detection limit of 400 copies/mL of HIV-1 RNA.
Amplification and detection of polymorphisms in ABCB1 and CYP genes by real-time PCR
Genomic DNA was extracted from PBMC using the QIAamp DNA Blood Mini Kits (Qiagen, Valencia, CA). Previously developed
fluorescence assays were used for analyzing the ABCB1-C3435T (rs1045642) and CYP3A4-A392G (rs2740574). For the
ABCB1-G2677T (rs2032582) genotype, and CYP2C19C*2-G681A (rs4244285) and CYP2C19*3-G636A (rs28399504) genotypes,
previously reported real-time PCR assays were used. In addition, novel fluorescent assays were developed to detect the
ABCB1-C1236T (rs1128503) and ABCB1-G1199A (rs2229109) genotypes using real-time PCR.
The Kruskal-Wallis test: comparisons among three genotypes or ≥3 categorical groups. The Wilcoxon sum rank test:
comparisons between 2 groups (numericals). The Chi-square and Fisher’s Exact Tests: pairwise comparisons (categoricals).
Table 1. Subjects from PACTG 366 and 377
Table 2. Baseline characteristics of 126 children based on the ABCB1 and CYP2C19 genotypes
Antiretroviral therapy during the study
Previous antiretroviral experience
366 40 (26%)
d4T + 3TC, or d4T
77, (51%)23 (15%) +c
--d4T + 3TC --
Nelfinavir: a: 25 mg/kg/dose if ≤ 30kg; 1000 mg if 30-37 kg; 1250 mg if >37kg every 8 hrs, b: 25 mg/kg/dose if ≤ 30kg; 1000 mg
if 30-37 kg; 1250 mg if >37kg every 12 hrs, c: 50-55 mg/kg every 12 hrs with a maximum of 4,000 mg/day
Nevirapine: 120 mg/m2/day X 14 days, and 120 mg/m2/dose twice a day thereafter.
Ritonavir: 350 mg/m2/dose every 12 hours for PACTG 366 and 400 mg/m2/dose every 12 hrs for PACTG 377.
d4T (stavudine): 1 mg/kg/dose every 12 hrs if <30 kg, 30 mg every 12 hrs if ≥30 kg - <60 kg, 40 mg every 12 hrs if ≥60 kg
3TC (lamivudine): 4 mg/kg/dose, every 12 hrs
0.65 4.44 (0.74) 4.62 (0.64)4.54 (0.70)0.114.47 (0.67)4.46 (0.61)4.68 (0.75)4.56 (0.68) Mean HIV-1 RNA (log10 copies/mL) (SD)
0.85 22 (6-40)25 (19-31)23 (16-32)0.0229 (21-11)26 (18-35)21 (14-28) 24 (16-32)Baseline CD4+ % (%) [median, (IQR)]
1 (13)10 (24)18 (18)4 (21)12 (18) 13 (20)29 (19)Ritonavir + Nevirapine
3 (38)14 (33)43 (42)10 (53)23 (34) 27 (42)60 (40)Nevirapine
2 (25)9 (21)29 (28)3 (16)19 (28) 18 (28)40 (26)Ritonavir
0.632 (25)9 (21)12 (12) 0.55 2 (11)14 (21)7 (11)23 (15)
Concomitant ARVs No
0.82 7.9 (5.9-10.7)7.1 (3.9-9.4)7.1 (3.5-10.1)0.937.2 (4.2-11.3)6.9 (3.8-9.4)7.3 (3.7-9.4) 7.1 (3.8-9.6)Mean age (years), [median, (IQR)]
4 (50)20 (48)49 (48)7 (37)33 (49)33 (51)73 (48) Female
0.994 (50)22 (52)53 (52)0.5612 (63)35 (51) 32 (49)79 (52)
Sex, n (%)
n = 8, (%)n = 42, (%)n = 102, (%)n = 19, (%)n = 68, (%) n = 65, (%)n = 152, (%)
Figure 1. Children with the ABCB1-3435-C/C genotype
showed higher oral clearance rates for nelfinavir
compared to children with the ABCB1-C3435T variants.
Figure 2. Children with the CYP2C19-681-G/G genotype
show higher oral clearance rates for nelfinavir compared
to children with the CYP2C19-G681A variants.
Figure 3. Association between the CYP2C19-G681A
genotype and the M8: NFV ratio.
Table 3. Frequency of genetic polymorphisms evaluated in
(n = 4)
0 (0.0) 0 (0.0)31 (33.7)31 (20.4)G/G
3 (12.5)7 (24.2)50 (54.3)61 (40.1) A/G
21 (87.5)25 (75.8)11 (12.0)60 (39.5) A/A
1 (4.2)0 (0.0) 6 (6.5)8 (5.3) A/A
5 (20.8)8 (25.0)28 (30.4)42 (27.6)G/A
18 (75.0)24 (75.0) 58 (63.0)
2 (8.3)1 (3.1) 3 (3.3)6 (3.9)G/A
22 (91.7)31 (96.9) 89 (96.7)
5 (20.8)8 (25.0)5 (5.4) 18 (11.8)T/T
15 (62.5)15 (46.9)33 (35.9) 66 (43.4)C/T
4 (16.7)9 (28.1) 55 (59.8)68 (44.7)C/C
7 (29.2)9 (28.1)1 (1.0)17 (11.1) A/A
13 (54.2)10 (31.2)
23 (25.0)49 (32.2)G/A
4 (16.7)13 (40.6)68 (73.9)86 (56.6)G/G
4 (16.7) 7 (21.2)7 (7.6) 19 (12.5)T/T
17 (70.8)14 (43.5)35 (38.0) 68 (44.7) C/T
3 (12.5)11 (36.4)50 (54.3)65 (42.7)C/C
n, (%)n, (%)n, (%)n, (%)
(n = 24) (n = 32)(n = 92)(n = 152)
Table 4. Multivariate analysis for NFV oral clearance
CovariatesRegression Coefficient ±± S.E. P-value
Race/ethnicity (AA) 11.506 ± 6.273 0.069
Concomitant PIs (RTV) -20.102 ± 5.487 < 0.001
CYP2C19-G681A (G/A or A/A) -22.683 ± 5.980 < 0.001
ABCB1-C3435T (C/T or T/T) -3.163 ± 6.160 0.608
CYP3A4-G392A (A/A) 6.385 ± 7.809 0.415
72.379 ± 8.728 < 0.001
-1.507 ± 0.705 0.034
Virologic response during HAART in children with ABCB1
and CYP genotypes.
At week 24, the percentage of subjects with the ABCB1-3435-
C/T or T/T genotype reached undetectable plasma HIV-1
RNA (60%, 52 of 87) was higher than subjects with the
ABCB1-3435-C/C genotype (45%, 36 of 65) (P = 0.01).
Similarly, the percentage of subjects with the CYP2C19-681-
G/T or T/T genotype reached undetectable plasma HIV-1
RNA (68%, 34 of 50) was higher than those with the
CYP2C19-681-G/G genotype (46%, 47 of 102) (P = 0.01).
Immunologic response during HAART in children with the
ABCB1 and CYP genotypes.
Changes in CD4+ T-cell percentage from baseline to weeks
24 were not different among the three genotypes in ABCB1-
C3435T (P = 0.08, P = 0.21, respectively), or CYP2C19-
G681A (P = 0.50, P = 0.44, respectively).