ABCMdb

ABCC2 p.Gly699Ala

Predicted by SNAP2:	A: D (91%), C: D (91%), D: D (95%), E: D (95%), F: D (95%), H: D (95%), I: D (95%), K: D (95%), L: D (95%), M: D (95%), N: D (91%), P: D (95%), Q: D (91%), R: D (95%), S: D (91%), T: D (91%), V: D (91%), W: D (95%), Y: D (95%),
Predicted by PROVEAN:	A: D, C: D, D: D, E: D, F: D, H: D, I: D, K: D, L: D, M: D, N: D, P: D, Q: D, R: D, S: D, T: D, V: D, W: D, Y: D,

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[hide] Influence of drug transporters and UGT polymorphis... Ther Drug Monit. 2008 Oct;30(5):559-64. Miura M, Kagaya H, Satoh S, Inoue K, Saito M, Habuchi T, Suzuki T
Influence of drug transporters and UGT polymorphisms on pharmacokinetics of phenolic glucuronide metabolite of mycophenolic acid in Japanese renal transplant recipients.
Ther Drug Monit. 2008 Oct;30(5):559-64., [PMID:18695635]

Abstract [show]
Mycophenolic acid (MPA) is mainly glucuronized by uridine diphosphate-glucuronosyltransferases (UGTs) into the phenolic MPA glucuronide (MPAG). MPAG is excreted by transporters such as organic anion-transporting polypeptide (gene SLCO), multidrug resistance protein 2 (gene ABCC2), breast cancer resistance protein (BCRP, gene ABCG2) or P-glycoprotein (gene ABCB1). This study investigated the association of UGTs, SLCOs, ABCB1, ABCC2, and ABCG2 polymorphisms with MPAG pharmacokinetics in 80 Japanese renal transplant recipients. Eighty recipients were given repeated doses of combination immunosuppressive therapy consisting of mycophenolate mofetil and tacrolimus every 12 hours at a designated time (0900 and 2100). On day 28, after renal transplantation, plasma concentrations of MPA and MPAG were measured by high-performance liquid chromatography. There were no significant differences in the area under the plasma concentration-time curve (AUC) ratio of MPAG/MPA between UGT1A1, UGT1A6, UGT1A7, UGT1A8, and UGT1A9 I399C/T genotypes. On the other hand, the median dose-adjusted AUC0-12 of MPAG in SLCO1B1 1a/1a+1a/1b+1b+1b (n = 53) and 1a/*15 + 1b/*15+*15/*15 (n = 27) were 1549 and 1134 mg.h L g, respectively (P = 0.03004 in multivariate analysis). The median dose-adjusted AUC0-12 of MPAG in SLCO1B3 334T/T+T/G (699G/G+G/A, n = 46) and 334G/G (699A/A, n = 34) was 1191 and 1580 mg.h L g, respectively (P = 0.02792 in multivariate analysis). There were no significant differences in the dose-adjusted AUC0-12 of MPAG between the ABCB1 C3435T and ABCC2 C-24T genotypes. However, the dose-adjusted AUC0-12 of MPAG was significantly lower in recipients with ABCG2 421C/A+A/A (n = 44) than in those with C/C (n = 36) (P = 0.0295). In conclusion, our findings showed that MPAG pharmacokinetics were significantly influenced by SLCO1B1 and SLCO1B3 polymorphisms and not by UGT polymorphisms. BCRP rather than multidrug resistance protein 2 seems to be the transporter associated with biliary excretion of MPAG.

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14 OATPs, encoded by SLCO genes, mediate the transmembrane transport of a wide range of amphiphilic organic compounds.10 The area under the plasma concentration-time curve (AUC)6-12 of an organic anion MPA, which estimates enterohepatic circulation and recirculation of MPA, was greater in SLCO1B3 T334G GG (or G699A AA) carriers than in TT carriers (or G699A GG).11 On the other hand, MRP2/ABCC2 is expressed at the hepatocyte apical membrane, the proximal renal tubular cell luminal membrane, and intestinal epithelial cells.12 Naesens et al13 reported that ABCC2 C-24T polymorphisms are associated with MPA oral clearance. Login to comment

[hide] Impact of genetic polymorphisms of transporters on... Drug Metab Pharmacokinet. 2008;23(4):223-35. Maeda K, Sugiyama Y
Impact of genetic polymorphisms of transporters on the pharmacokinetic, pharmacodynamic and toxicological properties of anionic drugs.
Drug Metab Pharmacokinet. 2008;23(4):223-35., [PMID:18762709]

Abstract [show]
As the importance of drug transporters in the clinical pharmacokinetics of drugs is recognized, genetic polymorphisms of drug transporters have emerged as one of the determinant factors to produce the inter-individual variability of pharmacokinetics. Many clinical studies have shown the influence of genetic polymorphisms of drug transporters on the pharmacokinetics and subsequent pharmacological and toxicological effects of drugs. The functional change in a transporter in clearance organs such as liver and kidney affects the drug concentration in the blood circulation, while that in the pharmacological or toxicological target can alter the local concentration at the target sites without changing its plasma concentration. As for the transporters for organic anions, some single nucleotide polymorphisms (SNPs) or haplotypes occurring with high frequency in organic anion transporting polypeptide (OATP) 1B1, multidrug resistance 1 (MDR1), and breast cancer resistance protein (BCRP) have been extensively investigated in both human clinical studies and in vitro functional assays. We introduce some examples showing the relationship between haplotypes in transporters and pharmacokinetics and pharmacological effects of drugs. We also discuss how to predict the effect of functional changes in drug transporters caused by genetic polymorphisms on the pharmacokinetics of drugs from in vitro data.

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124 T334G (Ser112Ala) and G669A (Met233Ile) are observed frequently in OATP1B3 gene in all ethnic populations, and these two SNPs are tightly linked to each other.23) T334G mutation in OATP1B3 was reported to increase in the plasma AUC (6-12 hr after oral administration) of mycophenolic acid, suggesting that this mutation decreased the transport function of OATP1B3.62) However, the 1/Tmax value in the erythromycin breath test was significantly higher in subjects with T334G, indicating that T334G accelerates the metabolism of erythromycin, which is inconsistent with the clinical study mentioned above.63) On the other hand, T334G and G699A in OATP1B3 did not affect the pharmacokinetics of paclitaxel, docetaxel, telmisartan, which are substrates of OATP1B3.64-66) Very recently, Kiyotani et al. have shown that SNPs in the non-coding region of OATP1B3 and MRP2 are associated with the frequency of docetaxel-induced severe neutropenia in cancer patients with the use of a data-mining approach from ``Biobank Japan'' (http://www.biobankjp.org/), which possesses genome and serum samples from more than 200,000 patients with clinical information.67) This novel approach enables genome-wide searches to find the unknown causal genes for the modification of drug responses. Login to comment

[hide] Xenobiotic, bile acid, and cholesterol transporter... Pharmacol Rev. 2010 Mar;62(1):1-96. Epub 2010 Jan 26. Klaassen CD, Aleksunes LM
Xenobiotic, bile acid, and cholesterol transporters: function and regulation.
Pharmacol Rev. 2010 Mar;62(1):1-96. Epub 2010 Jan 26., [PMID:20103563]

Abstract [show]
Transporters influence the disposition of chemicals within the body by participating in absorption, distribution, and elimination. Transporters of the solute carrier family (SLC) comprise a variety of proteins, including organic cation transporters (OCT) 1 to 3, organic cation/carnitine transporters (OCTN) 1 to 3, organic anion transporters (OAT) 1 to 7, various organic anion transporting polypeptide isoforms, sodium taurocholate cotransporting polypeptide, apical sodium-dependent bile acid transporter, peptide transporters (PEPT) 1 and 2, concentrative nucleoside transporters (CNT) 1 to 3, equilibrative nucleoside transporter (ENT) 1 to 3, and multidrug and toxin extrusion transporters (MATE) 1 and 2, which mediate the uptake (except MATEs) of organic anions and cations as well as peptides and nucleosides. Efflux transporters of the ATP-binding cassette superfamily, such as ATP-binding cassette transporter A1 (ABCA1), multidrug resistance proteins (MDR) 1 and 2, bile salt export pump, multidrug resistance-associated proteins (MRP) 1 to 9, breast cancer resistance protein, and ATP-binding cassette subfamily G members 5 and 8, are responsible for the unidirectional export of endogenous and exogenous substances. Other efflux transporters [ATPase copper-transporting beta polypeptide (ATP7B) and ATPase class I type 8B member 1 (ATP8B1) as well as organic solute transporters (OST) alpha and beta] also play major roles in the transport of some endogenous chemicals across biological membranes. This review article provides a comprehensive overview of these transporters (both rodent and human) with regard to tissue distribution, subcellular localization, and substrate preferences. Because uptake and efflux transporters are expressed in multiple cell types, the roles of transporters in a variety of tissues, including the liver, kidneys, intestine, brain, heart, placenta, mammary glands, immune cells, and testes are discussed. Attention is also placed upon a variety of regulatory factors that influence transporter expression and function, including transcriptional activation and post-translational modifications as well as subcellular trafficking. Sex differences, ontogeny, and pharmacological and toxicological regulation of transporters are also addressed. Transporters are important transmembrane proteins that mediate the cellular entry and exit of a wide range of substrates throughout the body and thereby play important roles in human physiology, pharmacology, pathology, and toxicology.

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6427 Nucleotide Change Amino Acid Change In Vitro Function Protein Expression/Localization SLCO1A2 OATP1A2 T38C I13T 1↔ Normal A382T N128Y ↔ N.D. A404T N135I 2↔ N.D. C502T R168C 2 N.D. A516C E172D 2 Intracellular G559A A187T 2 Normal A833- Asn278STOP 2 N.D. C2003G T668S ↔ Intracellular SLCO1B1 OATP1B1 T217C F73L 2 Intracellular T245C V82A 2 Intracellular A388G N130D 2↔ Normal A452G N151S N.D. N.D. C463A P155T ↔ Normal A467G E156G 2 Normal T521C V174A 2 Intracellular/normal T578G L193R 2 Intracellular C1007G P336R N.D. N.D. T1058C I353T 2 Intracellular A1294G N432D 2↔ Normal A1385G D462G ↔ Normal G1454T C485F N.D. N.D. G1463C G488A 2 Intracellular T1628G L543W N.D. N.D. A1964G D655G 2↔ Normal A2000G E667G 2↔ Normal SLCO1B3 OATP1B3 T334G S112A 1↔ Normal G699A M233I ↔ Normal G1564T G522C 2↔ Reduced G1748A G583E 2↔ Reduced 2, reduced function; 1, increased function; ↔, no change in function; N.D. not determined. ions. Login to comment
6426 Nucleotide Change Amino Acid Change In Vitro Function Protein Expression/Localization SLCO1A2 OATP1A2 T38C I13T 1࢒ Normal A382T N128Y ࢒ N.D. A404T N135I 2࢒ N.D. C502T R168C 2 N.D. A516C E172D 2 Intracellular G559A A187T 2 Normal A833- Asn278STOP 2 N.D. C2003G T668S ࢒ Intracellular SLCO1B1 OATP1B1 T217C F73L 2 Intracellular T245C V82A 2 Intracellular A388G N130D 2࢒ Normal A452G N151S N.D. N.D. C463A P155T ࢒ Normal A467G E156G 2 Normal T521C V174A 2 Intracellular/normal T578G L193R 2 Intracellular C1007G P336R N.D. N.D. T1058C I353T 2 Intracellular A1294G N432D 2࢒ Normal A1385G D462G ࢒ Normal G1454T C485F N.D. N.D. G1463C G488A 2 Intracellular T1628G L543W N.D. N.D. A1964G D655G 2࢒ Normal A2000G E667G 2࢒ Normal SLCO1B3 OATP1B3 T334G S112A 1࢒ Normal G699A M233I ࢒ Normal G1564T G522C 2࢒ Reduced G1748A G583E 2࢒ Reduced 2, reduced function; 1, increased function; ࢒, no change in function; N.D. not determined. ions. Login to comment

[hide] Clinical impact of polymorphisms of transport prot... Transplant Proc. 2009 Jun;41(5):1441-55. Rosso Felipe C, de Sandes TV, Sampaio EL, Park SI, Silva HT Jr, Medina Pestana JO
Clinical impact of polymorphisms of transport proteins and enzymes involved in the metabolism of immunosuppressive drugs.
Transplant Proc. 2009 Jun;41(5):1441-55., [PMID:19545654]

Abstract [show]
Individualization of immunosuppressive therapy after solid organ transplantation is a goal that has been pursued for a long time. Nevertheless, in clinical practice, we are still stratifying patients in subgroups in which risk is assessed using demographic information and population analysis. Then, a combination of immunosuppressive drugs is chosen and doses are individualized to compensate for intra- and interindividual variabilities in drug pharmacokinetics, to obtain similar plasma/blood concentrations that are believed to be therapeutic, again based on data derived from population analysis. One step further in this strategy is to recognize, before initiation of immunotherapy, those patients at higher risk to be either under- or overexposed to currently used immunosuppressive drugs. Several studies have been undertaken to correlate single nucleotide polymorphisms in genes encoding transport proteins and metabolizing enzymes involved in the disposition of immunosuppressive drugs. Overall, the results from these studies have been mixed. The causes of these sometimes conflicting results include methodologic, genetic, or nongenetic factors. The degree of linkage disequilibrium, the measure of nonrandom associations between polymorphisms at different loci, not necessarily on the same chromosome, is perhaps the main genetic factor. The influence of the environment, physiology (such as kidney and liver functions), disease state, use of multidrug regimens, and inherent drug-to-drug interactions are present nongenetic factors. Moreover, it is also important to increase our knowledge of the genetic factors involved in the variabilities observed in drug responses of pharmacodynamics. True individualized therapy, with the ability to improve health outcomes of each transplant recipient, will depend on our knowledge of the genetic factors involved in immunological response and drug pharmacokinetics and pharmacodynamics.

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198 In one study including 87 Japanese kidney transplant recipients, carriers of the SNP (T334G or G699A) of one OATP transport member (SLCO1 B3), which have increased uptake transport activity, showed higher dose-adjusted MPA exposure compared with wild-type carriers. Login to comment

[hide] Monitoring of mycophenolic acid predose concentrat... Ther Drug Monit. 2011 Jun;33(3):295-302. Miura M, Niioka T, Kato S, Kagaya H, Saito M, Habuchi T, Satoh S
Monitoring of mycophenolic acid predose concentrations in the maintenance phase more than one year after renal transplantation.
Ther Drug Monit. 2011 Jun;33(3):295-302., [PMID:21572388]

Abstract [show]
BACKGROUND: Routine therapeutic drug monitoring of mycophenolic acid (MPA) is generally performed using the area under the concentration-time curve from 0 to 12 hours (AUC0-12) with recommended values between 30 and 60 mug.h/mL. OBJECTIVE: The aim of this study was to examine whether the monitoring of the MPA predose concentration (C0) in patients who are stable for >1 year after renal transplantation was practical and to determine factors that cause MPA C0 variability among patients. METHODS: Eighty-six Japanese patients who had undergone renal transplantation and were taking tacrolimus and who had their MPA C0 analyzed >6 times by high-performance liquid chromatography for >1 year posttransplantation were enrolled. RESULTS: Recipients with MPA AUC0-12 levels<30 mug.h/mL on day 28 and 1 year after transplantation had an MPA C0 of <2.0 mug/mL, with a sensitivity of 90.9% and a specificity of 70.7%. There was no significant difference in the mean dose-adjusted MPA C0>1 year after transplantation between subjects with either the UGT (1A1, 1A9, and 2B7) or drug transporter (SLCO1B3, ABCC2, and ABCG2) genotypes. However, in a multiple regression analysis, the dose-adjusted mean MPA C0>1 year after transplantation was significantly associated with age (P=0.0035), creatinine clearance (P=0.0001), and the dose-adjusted MPA AUC0-12 at 1 year (P=0.0147). CONCLUSIONS: To keep the MPA AUC0-12>30 mug.h/mL, the plasma threshold for maintaining the MPA C0 with tacrolimus should be set >2.0 mug/mL as determined by high-performance liquid chromatography. For patients who are stable for >1 year after transplantation, continued monitoring of the MPA C0 using the same samples used to monitor the tacrolimus C0 and the additional assessment of the MPA AUC0-12 at the 1-year time point seem to be a viable option. If a change of the mycophenolate mofetil dose seems necessary based on the routine MPA C0 information, the determination of MPA AUC0-12 using a limited sampling strategy is recommended.

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34 procedure as previously described.16,17 UGT1A9 I399C/T (relative to the end of UGT1A9 exon 1) was genotyped by direct sequencing with a PCR procedure as previously described.18 A genotyping procedure to identify the SLCO1B1 1a, 1b, and *15 alleles was performed using the PCR-RFLP method of Nozawa et al19 Genotyping procedures identifying each allele of the SLCO1B3 gene (T334G and G699A) used the PCR-RFLP method described by Tsujimoto et al20 Genotyping procedures identifying the C and T alleles in exon 1 of ABCC2 (C-24T) were performed by combining 2 PCR-RFLP methods described by Rau et al21 The ABCG2 C421A polymorphism was genotyped by the PCR-RFLP method of Kobayashi et al22 All the frequencies for the different analyzed loci were in Hardy-Weinberg equilibrium. Login to comment

[hide] Influence of SLCO1B1, 1B3, 2B1 and ABCC2 genetic p... Eur J Clin Pharmacol. 2007 Dec;63(12):1161-9. Epub 2007 Sep 29. Miura M, Satoh S, Inoue K, Kagaya H, Saito M, Inoue T, Suzuki T, Habuchi T
Influence of SLCO1B1, 1B3, 2B1 and ABCC2 genetic polymorphisms on mycophenolic acid pharmacokinetics in Japanese renal transplant recipients.
Eur J Clin Pharmacol. 2007 Dec;63(12):1161-9. Epub 2007 Sep 29., [PMID:17906856]

Abstract [show]
OBJECTIVE: We investigated the association between mycophenolic acid (MPA) pharmacokinetics and organic anion-transporting polypeptide (OATP/SLCO)1B1, 1B3, 2B1 and multidrug resistance-association protein 2 (MRP2/ABCC2) genetic polymorphisms and diarrhea. METHODS: Eighty-seven renal allograft recipients were given repeated doses of mycophenolate mofetil every 12 h at a designated time (09:00 and 21:00). The pharmacokinetics of MPA were analyzed on day 28 posttransplantation. RESULTS: The dose-adjusted area under the cuve (AUC)(6-12) of MPA, an estimate of enterohepatic recirculation, was greater in SLCO1B3 T334G GG (or G699A AA) carriers than in TT carriers (or G699A GG) (40 vs. 25 ng h/mL per milligram, respectively, P = 0.0497). None of the polymorphism of SLCO1B1, SLCO2B1, or ABCC2 C-24T were associated with MPA pharmacokinetics or diarrhea. However, the oral clearance of MPA in recipients having both the SLCO1B3 T334G GG genotype and the ABCC2 C-24T T allele was significantly lower than in patients having both the SLCO1B3 T334G TT and ABCC2 C-24T CC genotypes (0.15 vs. 0.18 L/h per kilogram, respectively, P = 0.0010). CONCLUSIONS: MPA excretion into bile in patients with SLCO1B3 T334G GG (or G699A AA) was higher than in those with T334G TT (or G699A GG), probably resulting in a higher AUC(6-12) value of MPA. MPA uptake into hepatocytes and excretion into bile at first pass may be greater in SLCO1B3 T334G GG carriers than in TT carriers. In addition, the ABCC2 C-24T polymorphism also seems to be associated with enhanced enterohepatic circulation of MPA. The SLCO1B3 and ABCC2 transporters rather than uridine diphosphate-glucuronosyltransferase (UGT) may partly affect interindividual variety in plasma MPA concentration.

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3 Results The dose-adjusted area under the cuve (AUC)6-12 of MPA, an estimate of enterohepatic recirculation, was greater in SLCO1B3 T334G GG (or G699A AA) carriers than in TT carriers (or G699A GG) (40 vs. 25 ng·h/mL per milligram, respectively, P=0.0497). Login to comment
6 Conclusions MPA excretion into bile in patients with SLCO1B3 T334G GG (or G699A AA) was higher than in those with T334G TT (or G699A GG), probably resulting in a higher AUC6-12 value of MPA. Login to comment
36 The SLCO1B3 G699A A allele increases uptake transport activity in vitro [20]. Login to comment
54 Diagnosis of gastrointestinal side effects of MMF MMF-related gastrointestinal side effects, such as diarrhea, nausea, vomiting, or abdominal pain, were defined by the absence of any other demonstrable etiology and improve- Table 2 Pharmacokinetic parameters of mycophenolic acid (MPA) and tacrolimus in the SLCO1B1 genotype groups Genotype group *1a/*1a *1a/*1b *1b/*1b *1a/*15 *1b/*15 *15/*15 ANOVA P Patient numbers (%) 6 (7) 35 (40) 17 (20) 8 (12) 19 (9) 2 (2) Patients with diarrhea (%) 1 (17) 10 (29) 4 (24) 1 (13) 8 (42) 0 Prednisolone (mg/kg) 0.20±0.04 0.20±0.06 0.19±0.04 0.16±0.04 0.20±0.03 0.21±0.08 0.4825 MPA MMF single dose (mg) 750±158 786±162 838±152 875±189 794±159 1000±0 0.2953 Dose-adjusted Cmax (μg/mL/g) 15.2±5.6 18.0±5.5 15.1±7.4 19.1±7.5 19.5±9.9 6.7±1.7 0.1175 Dose-adjusted C0 (μg/mL/g) 6.0±2.2 5.4±3.6 4.2±2.7 4.8±3.0 5.4±3.0 3.7±1.0 0.7278 CL/F (L/hr/kg) 0.16±0.05 0.16±0.06 0.23±0.27 0.12±0.02 0.15±0.07 0.34±0.03 0.1413 AUC0-12/D (μg·h/mL/g) 103±38 95±31 89±51 99±20 106±45 37±2 0.2543 AUC0-6/D (μg·h/mL/g) 64±27 59±17 57±36 63±17 66±29 21±1 0.2735 AUC6-12/D (μg·h/mL/g) 40±12 36±28 32±19 36±11 40±22 16±0.2 0.7484 AUC6-12/AUC0-12 (%) 40±6.9 35±13 36±13 36±9 37±11 44±1 0.8775 Tacrolimus Single dose (mg/kg) 0.08±0.02 0.10±0.05 0.09±0.04 0.09±0.04 0.10±0.05 0.15±0 0.4080 Dose-adjusted C0 (μg/ml/mg/kg) 0.16±0.06 0.15±0.08 0.15±0.07 0.19±0.11 0.13±0.06 0.08±0.01 0.3492 AUC0-12/D (μg·h/ml/mg/kg) 2.67±0.90 2.34±1.07 2.38±1.05 2.63±1.49 1.94±0.82 1.51±0.15 0.4080 Values are shown as the mean ± SD. There were no significant differences in MPA pharmacokinetics between SLCO1B1*1a/*1a and *1b/*1b, *1a/*1a and *1a/*15, and *1b/*1b and *1b/*15 Cmax maximum plasma concentration, CL/F apparent oral clearance, AUC0-12, AUC0-6, and AUC6-12, area under the plasma concentration-time curve from 0 to 12 h, 0 to 6 h, and 6 to 12 h, respectively, D single dose, ANOVA analysis of variance Table 3 Pharmacokinetic parameters of mycophenolic acid (MPA) and tacrolimus in the SLCO1B3 T334G and G699A genotype groups Genotype group T334G T/T T/G G/G ANOVA P values G699A G/G G/A A/A Patient numbers (%) 10 (12) 40 (45) 37 (43) Patients with diarrhea (%) 4 (40) 8 (20) 12 (32) Prednisolone (mg/kg) 0.19±0.03 0.19±0.05 0.20±0.04 0.7317 MPA Single dose (mg) 750±189 827±142 804±178 0.4315 Dose-adjusted Cmax (μg/mL/g) 19.6±12.6 16.3±6.4 17.9±6.6 0.4107 Dose-adjusted C0 (μg/mL/g) 4.5±1.4 4.8±3.2 5.6±3.3 0.4028 CL/F (L/h/kg) 0.18±0.07 0.16±0.07 0.18±0.19 0.8127 AUC0-12/D (μg·h/mL/g) 85±37 90±35 104±43 0.2333 AUC0-6/D (μg·h/mL/g) 60±29 57±22 64±28 0.4921 AUC6-12/D (μg·h/mL/g) 25±10 34±17 40±28* 0.1684 AUC6-12/AUC0-12 (%) 31±8 37±9 37±14 0.3615 Tacrolimus Single dose (mg/kg) 0.09±0.03 0.09±0.04 0.10±0.06 0.4414 Dose-adjusted C0 (μg/ml/mg/kg) 0.16±0.09 0.15±0.08 0.14±0.06 0.6178 AUC0-12/D (μg·h/ml/mg/kg) 2.42±0.90 2.31±1.13 2.24±1.01 0.8875 Values are shown as the mean ± SD Cmax maximum plasma concentration, CL/F apparent oral clearance, AUC0-12, AUC0-6, and AUC6-12 area under the plasma concentration-time curve from 0 to 12 h, 0 to 6 h, and 6 to 12 h, respectively, D single dose, ANOVA analysis of variance *P<0.05 compared with the SLCO1B3 T334G TT (or OATP1B3 G699A GG) ment or resolution of symptoms by reduction of the dose of MMF alone. Login to comment
75 Results Association of SLCO1B1 polymorphisms with MPA pharmacokinetics The SLCO1B1*1a/*1a, *1a/*1b, *1b/*1b, *1a/*15, *1b/ *15, and *15/*15 genotypes were detected in 6 (7%), 35 0 5 10 15 20 MPA plasma concentration (µg/mL) 0 2 4 6 8 10 12 Time (h) 334G/G (699A/A) 334T/G (699G/A) 334T/T (699G/G) Fig. 1 Mean ± SD of the plasma concentration-time profiles of mycophenolic acid (MPA) in recipients having SLCO1B3 T334G TT genotype (G699A GG) (open circles), TG (GA) (open square), and GG (AA) (solid circles) carriers 0 50 100 150 AUC ( µ g h/mL/g) AUC6-12/D AUC0-6 /D AUC0-12/D 334G/G (699A/A) 334T/G (699G/A) 334T/T (699G/G) Fig. 2 The area under the plasma concentration-time curve from 0 to 12 h (AUC0-12) (open column), the partial AUC from 0 to 6 h (AUC0-6) (gray column), and from 6 to 12 h (AUC6-12) (solid column). Login to comment
81 Association of SLCO1B3 polymorphisms with MPA pharmacokinetics The SLCO1B3 T334G TT, TG, and GG (G699A GG, GA and AA) genotypes were detected in 10 (12%), 40 (45%) and 37 (43%) patients, respectively, and the genotype distribution was in Hardy-Weinberg equilibrium [22]. Login to comment
82 The SLCO1B3 T334G and G699A showed complete linkage disequilibrium (Table 3). Login to comment
86 However, the dose-adjusted AUC6-12 of MPA was significantly greater in SLCO1B3 T334G GG (G699A GG) genotype carriers than in TT (G699A AA) genotype carriers (40 vs. 25 μg·h/ml per gram, P=0.0497) (Fig. 2). Login to comment
97 Table 5 Pharmacokinetic parameters of mycophenolic acid (MPA) and tacrolimus in the ABCC2 C-24T genotype groups Genotype group C/C C/T T/T ANOVA P value CT+T/T P value vs. C/C Patient numbers (%) 47 (53) 37 (42) 4 (5) 41 Patients with diarrhea (%) 13 (28) 11 (30) 0 (0) Prednisolone (mg/kg) 0.20±0.05 0.18±0.03* 0.23±0.08 0.0683 MPA Single dose (mg) 783±174 847±150 750±0 0.1608 838±145 0.1247 Dose-adjusted Cmax (μg/mL/g) 16.9±6.4 18.3±8.4 14.1±6.4 0.4744 17.9±8.3 0.5569 Dose-adjusted C0 (μg/mL/g) 5.0±2.8 5.1±3.2 6.2±5.9 0.7806 5.2±3.4 0.7868 CL/F (L/h/kg) 0.19±0.17 0.16±0.07 0.19±0.07 0.8127 0.16±0.07 0.3656 AUC0-12/D (μg·h/mL/g) 94±37 98±42 85±34 0.7752 97±41 0.7321 AUC0-6/D (μg·h/mL/g) 61±24 60±28 51±20 0.7690 59±27 0.8181 AUC6-12/D (μg·h/mL/g) 34±18 38±28 34±15 0.6640 38±27 0.3940 AUC6-12/AUC0-12 (%) 35±9 37±14 40±5 0.4927 38±14 0.2734 Tacrolimus Single dose (mg/kg) 0.10±0.04 0.09±0.05 0.11±0.05 0.6992 0.09±0.05 0.6473 Dose-adjusted C0 (μg/ml/mg/kg) 0.14±0.08 0.16±0.08 0.11±0.04 0.3699 0.15±0.08 0.5262 AUC0-12/D (μg·h/ml/mg/kg) 2.26±1.03 2.42±1.09 1.46±0.51 0.2114 2.32±1.08 0.7941 Values are shown as the mean ± SD. There were no significant difference in MPA pharmacokinetics between ABCC2 -24C/C and other genotype groups Cmax maximum plasma concentration, CL/F apparent oral clearance, AUC0-12, AUC0-6, and AUC6-12 area under the plasma concentration-time curve from 0 to 12 h, 0 to 6 h, and 6 to 12 h, respectively, D single dose, ANOVA analysis of variance Table 6 Pharmacokinetic parameters of mycophenolic acid (MPA) in the SLCO1B3 T334G (G699A) and ABCC2 C-24T genotype groups Genotype group T334G (G699A) TT (GG) TG (GA) GG (AA) ANOVA P value ABCC2 C-24T C/C C/T+T/T C/C C/T+T/T C/C C/T+T/T C/C C/T+T/T Patient numbers 5 5 21 19 20 17 MPA Single dose (mg) 750±177 750±204 813±160 842±124 763±190 853±155 Dose-adjusted Cmax (μg/mL/g) 15.3±1.7 25.0± 18.7 16.3±6.7 16.4±6.1 18.0±6.7 17.8±6.6 0.5877 0.1711 Dose-adjusted C0 (μg/mL/g) 4.5±1.6 4.5±1.4 5.0±3.1 4.6±3.3 5.2±2.8 6.2±3.8 0.8794 0.3533 CL/F (L/h/kg) 0.18± 0.02 0.18±0.11 0.17± 0.07 0.16± 0.07 0.21± 0.25 0.15±0.06 * 0.7531 0.8215 AUC0-12/D (μg·h/mL/g) 75±18 98±53 89±30 92±39 105±45 102±41 0.1962 0.7655 AUC0-6/D (μg·h/mL/g) 53±12 69±43 54±17 59±26 69±30 58±25 0.1284 0.7558 AUC6-12/D (μg·h/mL/g) 23±8 29±12 34±18 33±17 36±19 45±36 0.3351 0.3481 AUC6-12/AUC0-12 (%) 30±6 33±9 38±10 36±9 34±9 41±18 0.1538 0.3798 Values are shown as the mean ± SD Cmax maximum plasma concentration, CL/F apparent oral clearance, AUC0-12, AUC0-6, and AUC6-12 area under the plasma concentration-time curve from 0 to 12 h, 0 to 6 h, and 6 to 12 h, respectively, D, single dose. Login to comment
99 Combination of SLCO1B3 T334G and ABCC2 C-24T polymorphisms The pharmacokinetic parameters of MPA as they relate to ABCC2 C-24T polymorphisms in the three different SLCO1B3 T334G (G699A) genotype groups are shown in Table 6. Login to comment
103 The SLCO1B3 T334G GG (or G699A AA) genotypes, which are in linkage disequilibrium, increased the dose-adjusted AUC6-12 of MPA compared with those in SLCO1B3 T334G TT (or G699A GG). Login to comment
151 In conclusion, this study showed that the SLCO1B3 T334G (or G699A) polymorphism was associated with the MPA AUC6-12. Login to comment

[hide] Mycophenolic acid-related diarrhea is not associat... Pharmacogenet Genomics. 2012 Jun;22(6):399-407. doi: 10.1097/FPC.0b013e32834a8650. Bouamar R, Hesselink DA, van Schaik RH, Weimar W, van der Heiden IP, de Fijter JW, Kuypers DR, van Gelder T
Mycophenolic acid-related diarrhea is not associated with polymorphisms in SLCO1B nor with ABCB1 in renal transplant recipients.
Pharmacogenet Genomics. 2012 Jun;22(6):399-407. doi: 10.1097/FPC.0b013e32834a8650., [PMID:21878834]

Abstract [show]
OBJECTIVE: We investigated the association between genetic polymorphisms in ABCB1 and SLCO1B and mycophenolic acid (MPA) pharmacokinetics, and MPA-related diarrhea and leukopenia in 338 kidney transplant recipients. METHODS: A total of 338 patients participating in an international, randomized-controlled clinical trial were genotyped for ABCB1 and SLCO1B. Patients were all treated with mycophenolate mofetil and either cyclosporine or tacrolimus. MPA-area under the curve (AUCs), MPA-glucuronide AUCs and acylglucuronide-AUCs were measured on days 3 and 10, and months 1, 3, 6, and 12 after kidney transplantation. RESULTS: The risk of developing diarrhea was 1.8-fold higher in patients cotreated with tacrolimus compared with patients cotreated with cyclosporine (95% confidence interval: 1.03-3.13; P=0.038). ABCB1 and SLCO1B SNPs were not associated with dose-adjusted exposure to MPA, MPA-glucuronide, nor acylglucuronide-MPA nor with the incidence of diarrhea or leukopenia. CONCLUSION: Genotyping for ABCB1 or SLCO1B pretransplantation is unlikely to be of clinical value for individualization of MPA therapy.

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165 For example, recently, Liu Table 5 Dose-adjusted mycophenolic acid-area under the curve in patients using cyclosporine as comedication according to ABCB1 and SLCO genotypes Dose-adjusted MPA-AUC (mg.h/l) ± SD n (%) Day 3 Day 10 Month 1 Month 3 Month 6 Month 12 ABCB1 1236C > T CC 55 (33) 31 ± 10 29 ± 13 34 ± 12 41 ± 15 48 ± 14 46 ± 16 CT 84 (51) 31 ± 10 31 ± 12 34 ± 17 44 ± 23 49 ± 24 48 ± 21 TT 27 (16) 36 ± 16 30 ± 10 32 ± 11 41 ± 16 46 ± 14 45 ± 16 2677G > T/A GG 53 (31) 32 ± 10 30 ± 14 35 ± 13 43 ± 17 50 ± 15 45 ± 16 GT/TT 111 (65) 32 ± 12 31 ± 12 33 ± 16 43 ± 21 48 ± 21 48 ± 19 GA 6 (4) 30 ± 5 23 ± 3 27 ± 9 25 ± 10 35 ± 5 49 ± 10 3435C > T CC 36 (22) 32 ± 8 28 ± 9 32 ± 10 41 ± 15 48 ± 15 43 ± 16 CT 90 (54) 31 ± 11 30 ± 12 35 ± 17 43 ± 23 48 ± 22 47 ± 18 TT 40 (24) 33 ± 14 33 ± 14 33 ± 11 43 ± 16 48 ± 17 49 ± 20 SLCO1B1 T521C CC 8 (5) 38 ± 15 29 ± 8 37 ± 24 47 ± 19 54 ± 10 45 ± 13 TC 49 (29) 31 ± 12 29 ± 12 33 ± 19 43 ± 29 50 ± 25 50 ± 26 TT 110 (66) 32 ± 10 31 ± 13 34 ± 12 42 ± 15 47 ± 17 47 ± 17 A388G AA 48 (29) 30 ± 9 27 ± 8 30 ± 12 36 ± 12 42 ± 15 45 ± 16 AG 67 (40) 33 ± 13 32 ± 14 35 ± 17 44 ± 17 49 ± 16 48 ± 17 GG 46 (27) 32 ± 9 32 ± 13 35 ± 15 45 ± 25 51 ± 24 45 ± 20 SLCO1B3 T344G GG 111 (66) 31 ± 10 29 ± 12 33 ± 15 41 ± 17 45 ± 18 49 ± 21 GT 51 (31) 33 ± 13 33 ± 13 36 ± 14 48 ± 26 56 ± 22 46 ± 17 TT 5 (3) 37 ± 14 33 ± 8 26 ± 9 39 ± 17 52 ± 5 43 ± 14 G699A AA 110 (66) 31 ± 10 29 ± 12 33 ± 15 41 ± 17 45 ± 18a 48 ± 19 GA 50 (30) 33 ± 14 33 ± 13 37 ± 14 49 ± 26 56 ± 22 46 ± 17 GG 5 (3) 37 ± 14 33 ± 8 26 ± 9 39 ± 17 52 ± 5 43 ± 14 MPA-AUC, mycophenolic acid-area under the curve; SD, standard deviation. a Significant (P < 0.05). Login to comment