ABCMdb

ABCB1 p.Gly1249Ala

Predicted by SNAP2:	A: D (80%), C: D (80%), D: D (91%), E: D (91%), F: D (91%), H: D (85%), I: D (85%), K: D (91%), L: D (91%), M: D (85%), N: D (85%), P: D (91%), Q: D (85%), R: D (91%), S: D (80%), T: D (85%), V: D (85%), W: D (91%), Y: D (91%),
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] Pharmacogenetic characteristics of indinavir, zido... J Acquir Immune Defic Syndr. 2006 Aug 1;42(4):441-9. Anderson PL, Lamba J, Aquilante CL, Schuetz E, Fletcher CV
Pharmacogenetic characteristics of indinavir, zidovudine, and lamivudine therapy in HIV-infected adults: a pilot study.
J Acquir Immune Defic Syndr. 2006 Aug 1;42(4):441-9., 2006-08-01 [PMID:16791115]

Abstract [show]
OBJECTIVE: The aim of the study was to investigate relationships among indinavir, lamivudine-triphosphate, and zidovudine-triphosphate pharmacokinetics and pharmacodynamics with polymorphisms in CYP3A5, MDR1, MRP2, MRP4, BCRP, and UGT1A1 genes. STUDY DESIGN: Retrospective pilot investigation among 33 subjects who participated in a randomized pharmacological study of indinavir, lamivudine, and zidovudine. Subjects were defined as genetic variant carriers or not. Relationships were investigated with multivariable regression. Indinavir clearance was adjusted for African American race; triphosphates for sex; and HIV-response for study arm, drug exposure, and baseline HIV-RNA. RESULTS: Genetically determined CYP3A5 expressors had 44% faster indinavir oral clearance versus nonexpressors (P = 0.002). MRP2-24C/T variant carriers had 24% faster indinavir oral clearance (P = 0.05). Lamivudine-triphosphate concentrations were elevated 20% in MRP4 T4131G variant carriers (P = 0.004). A trend for elevated zidovudine-triphosphates was observed in MRP4 G3724A variant carriers (P = 0.06). The log10 changes in HIV-RNA from baseline to week 52 were -3.7 for MDR1 2677 TT, -3.2 for GT, and -2.2 for GG (P < 0.05). Bilirubin increases were 2-fold higher in UGT1A1 [TA]7/[TA]7 genotypes. No relationships were identified with BCRP. DISCUSSION: Novel relationships were identified among genetic variants in drug transporters and indinavir, lamivudine-triphosphate, and zidovudine-triphosphate concentrations. CYP3A5 expression was associated with faster indinavir oral clearance. These pilot data provide a scientific basis for more rational utilization of antiretroviral drugs.

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46 ABCC2 (MRP2) IDV pharmacokinetics j24 C/T Theoretical altered promoter function with -24 C/T G1249A G1249A associated with saquinavir plasma concentrations in one abstract ABCC4 (MRP4) ZDV-triphosphate and 3TC-triphosphate pharmacokinetics and pharmacodynamics C1612T, G3463A, G3724A, T4131G All SNPs have relatively high probability of altered mRNA splicing and potentially altered MRP4 protein expression based on exonic splicing enhancer analyses for SRp40, SF35, SF2/ASF, and SRp5 proteins. Login to comment
163 IDV is a substrate of MRP2, which lines the bile cannicular cells and the gut epithelia, with the potential consequence of limiting drug absorption and speeding drug elimination.19,20 Genetic variability in MRP2 has been identified, but the influence of common SNPs (frequencies 910%) on protein function is not clear.21 One study of 34 HIV-infected patients treated with other HIV protease inhibitors (saquinavir and lopinavir/ ritonavir) described 3-fold higher saquinavir concentrations in patients with the MRP2 G1249A GG genotype compared with variant carriers (P = 0.009).22 In the present study, MRP2 G1249A variant carrier status was not related with the pharmacokinetics or pharmacodynamics of IDV, whereas variant carrier status at MRP2 C-24T was associated with faster IDV CL/F after adjusting for African American race. Login to comment

[hide] Antiepileptic medication during pregnancy: does fe... Pediatr Res. 2007 Aug;62(2):120-7. Atkinson DE, Brice-Bennett S, D'Souza SW
Antiepileptic medication during pregnancy: does fetal genotype affect outcome?
Pediatr Res. 2007 Aug;62(2):120-7., [PMID:17597651]

Abstract [show]
Congenital abnormalities and impaired development in childhood are attributable to fetal exposure to antiepileptic drugs (AEDs). Pregnancy registries set up to obtain information about the potential risks of fetal exposure to AEDs, in particular major congenital malformations (MCMs), suggest that valproate exposure increases the frequency of congenital malformations more than other AEDs. Furthermore, follow-up studies have drawn attention to cognitive impairments in later childhood after prenatal exposure to valproate. Fetal exposure to AEDs may be influenced by drug transporting proteins in the placenta, including P-glycoprotein (P-gp), multidrug resistance protein (MRP) 1, and breast cancer resistance protein (BCRP). Their location in the syncytiotrophoblast plasma membrane, at the interface of the maternal and fetal circulations, allows these transport proteins to efflux xenobiotics back to the mother and offers the fetus protection from medications taken during pregnancy. Genetic variations in the expression and activity of these transport proteins may influence fetal exposure to AEDs and thus the risk of teratogenicity. Identification of a hierarchy of haplotypes ranging from susceptible to protective of congenital abnormalities could assist genetic counseling, in assessing fetal risks from exposure to AEDs.

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185 Meyer zu Schwabedissen et al. (49) demonstrated that the G1249A polymorphism resulted in a significant decrease in placental MRP2 mRNA expression in preterm placentas. Login to comment

[hide] Lack of association between ABCB1, ABCG2, and ABCC... Epilepsy Res. 2009 Mar;84(1):86-90. Epub 2009 Jan 22. Kim DW, Lee SK, Chu K, Jang IJ, Yu KS, Cho JY, Kim SJ
Lack of association between ABCB1, ABCG2, and ABCC2 genetic polymorphisms and multidrug resistance in partial epilepsy.
Epilepsy Res. 2009 Mar;84(1):86-90. Epub 2009 Jan 22., [PMID:19167193]

Abstract [show]
ATP-binding cassette (ABC) transporters participate in drug disposition and response in various conditions, and many polymorphisms in ABC transporter genes have been recognized in association with altered transporter functions of various drugs. Studies on epilepsy have focused on the C3435T polymorphism of the ABCB1 gene, but other ABC transporters are also thought to be involved in the transport of antiepileptic drugs. We have evaluated the functional polymorphisms of ABCB1, ABCG2, and ABCC2 genes with regard to epilepsy drug response in partial epilepsy, and have investigated the potential of combined effects of polymorphisms in more than one transporter gene. We studied 6 genetic polymorphisms in 3 transporter genes in 193 drug responders and 198 nonresponders. There was no significant difference between the two groups, and we did not observe any combined effects of ABCB1 and ABCG2 genetic polymorphisms. Our study suggests that genetic polymorphisms in ABC transporters may not be significant predictors of drug response in epilepsy patients.

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70 We studied G1249A polymorphism because this polymorphism was strongly associated with higher activity of transporter function (Haenisch et al., 2008). Login to comment
88 Recent studies have failed to show significant interactions between BCRP protein and several AEDs (Cerveny et al., 2006), and association between the drug-resistant epilepsy and variations of ABCC2 gene including G1249A polymorphism (Seo et al., 2008). Login to comment

[hide] Intracellular trafficking of MDR transporters and ... Curr Top Med Chem. 2009;9(2):197-208. Porcelli L, Lemos C, Peters GJ, Paradiso A, Azzariti A
Intracellular trafficking of MDR transporters and relevance of SNPs.
Curr Top Med Chem. 2009;9(2):197-208., [PMID:19200005]

Abstract [show]
Multi-drug resistance (MDR) frequently contributes to the failure of chemotherapeutic treatments in cancer patients. Mechanisms underlying the development of MDR have been extensively studied and are considered multifactorial. Among them, the ATP-Binding Cassette (ABC) family of proteins plays a pivotal role. Processes of cellular distribution and subcellular localization of MDR-ABC proteins are not yet well explored and to enlighten these topics could be crucial to understand cellular drug uptake and retention. In this review, we analysed literature data concerning i) intracellular trafficking of MDR-ABC proteins (BCRP, P-gp and MRP1) and ii) mechanisms altering their cellular localization and trafficking. Moreover, we describe single nucleotide polymorphisms (SNP) that have been reported for some multidrug resistance (MDR) transporters, such as BCRP and P-gp, emphasizing their ability to affect the expression, function and localization of the transporters, with implications on drug resistance phenotypes.

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259 [122] studied the expression and cellular localization of the wild-type and three reported SNP variants of ABCC2 (G1249A (V417I), C2366T (S789F) and G4348A (A1450T)) in LLC-PK1 cells. Login to comment

[hide] Drug transporters in the human blood-placental bar... Br J Pharmacol. 2009 Oct;158(3):665-78. Epub 2009 Sep 25. Vahakangas K, Myllynen P
Drug transporters in the human blood-placental barrier.
Br J Pharmacol. 2009 Oct;158(3):665-78. Epub 2009 Sep 25., [PMID:19788499]

Abstract [show]
Studies on the increasing number of transporters found in the placental barrier are gaining momentum, because of their tissue-specific expression, significance in physiology and disease, and the possible utilization of the emerging knowledge in pharmacology. In the placenta, both syncytiotrophoblast and fetal capillary endothelium express transporters. Fetal exposure is determined by the net effect of combination of transporters, their nature and localization in relation to placental cells and their substrate specificity. Although the significance of placental transporters on human fetal drug exposure is almost an unstudied field so far, their potential use to design drugs that do not cross the placenta is already being pursued. It is thus of interest to review the existing knowledge of human placental transporters. Transporters in all groups which take part in drug transport are found in human placenta. Especially, ATP-binding cassette transporters ABCG2/breast cancer resistance protein, ABCB1/P-glycoprotein and ABCC2/MRP2 are all expressed at the apical surface of syncytiotrophoblast facing maternal blood and are putatively important protective proteins both for placental tissue and the fetus, because they are efflux transporters and their substrates include many drugs and also environmental chemicals. Such protective effect has been shown in animals, but these results cannot be directly extrapolated to humans due to interspecies differences in placental structure and function. Experimental models utilizing human placental tissue, especially human placental perfusion, offer valuable possibilities, which have been insufficiently studied so far.

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99 Table 4 Significance of drug transporter polymorphisms in human placenta Protein Gene polymorphisms Type of study Significance in placenta Reference P-gp/MDR1 G2677A/T (Ala toThr/Ser) T-129C 100 human placentas Less P-gp protein Less P-gp protein 1 P-gp/MDR1 G2677T/A C3435T 73 human placentas from Caucasians No effect on MDR1 mRNA Homozygosity of 3435T and 2677T lead to lower protein levels 2 P-gp/MDR1 C3435T 44 human placentas T allele associated with a higher expression 3 P-gp/MDR1 C3435T and G2677A/T Human placental perfusion No effect on saquinavir transfer 3, 4 P-gp/MDR1 C3435T Human placental perfusion 3435T associated with increased transfer of quetiapine 5 MRP2 G1249A 58 human placentas Reduced expression of MRP2 mRNA in preterm placentas only 6 BCRP G34A (Val12Met) C421A (Gln141Lys) 99 human placentas No effect on protein level Protein decreased 7 References: (1) Tanabe et al. (2001), (2) Hitzl et al. (2004), (3) Rahi et al. (2008), (4) Mölsä et al. (2005), (5) Rahi et al. (2007), (6) Meyer zu Schwabedissen et al. (2005b), (7) Kobayashi et al. (2005). Login to comment
181 Genetic polymorphisms of ABCC2/MRP2 have been found and at least one of them (G1249A) results in lower ABCC2/MRP2 expression. Login to comment

[hide] Polymorphism of the ABC transporter genes, MDR1, M... Pharmacogenetics. 2001 Mar;11(2):175-84. Ito S, Ieiri I, Tanabe M, Suzuki A, Higuchi S, Otsubo K
Polymorphism of the ABC transporter genes, MDR1, MRP1 and MRP2/cMOAT, in healthy Japanese subjects.
Pharmacogenetics. 2001 Mar;11(2):175-84., [PMID:11266082]

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37 Four were associated with an amino acid substitution; G to A transversion at position 1249 (G1249A, Val to Ile at codon 417) in exon 10, C to T at 2302 (C2302T, Arg to Trp at 768) and C to T at 2366 (C2366T, Ser to Phe at 789) in exon 18, and G to A at 4348 (G4348A, Ala to Thr at 1450) in exon 31 (position numbering: Taniguchi et al., 1996; Toh et al., 1999) (Fig. 3). Login to comment
39 The allele frequencies of G1249A, C2302T, C2366T, G4348A and C-24T were 0.125, 0.01, 0.01, 0.01 and 0.188, respectively. Login to comment
81 In the MRP2/cMOAT gene, four missense mutations, G1249A, C2302T, C2366T and G4348A, were observed. Login to comment

[hide] Effects of polymorphisms of MDR1, MRP1, and MRP2 g... Biol Pharm Bull. 2002 Oct;25(10):1356-9. Moriya Y, Nakamura T, Horinouchi M, Sakaeda T, Tamura T, Aoyama N, Shirakawa T, Gotoh A, Fujimoto S, Matsuo M, Kasuga M, Okumura K
Effects of polymorphisms of MDR1, MRP1, and MRP2 genes on their mRNA expression levels in duodenal enterocytes of healthy Japanese subjects.
Biol Pharm Bull. 2002 Oct;25(10):1356-9., [PMID:12392094]

Abstract [show]
In the present study, we examined whether polymorphisms in the ATP-binding cassette (ABC) transporter genes, MDR1, MRP1 and MRP2, were associated with their respective mRNA expression levels in duodenal enterocytes of 13 healthy Japanese volunteers. MDR1 genotypes of T-129C, G2677(A,T) and C3435T, MRP1 genotypes of G128C, C218T, G2168A and G3173A, and MRP2 genotypes of C-24T, G1249A, C2302T, C2366T and G4348A were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) or direct sequencing. Mutations T-129C, G2677(A,T) and C3435T of MDRI gene were found at allele frequencies of 2/26, 16/26 and 12/26, respectively. Mutations G2168A of the MRPI gene and C-24T of the MRP2 gene were also found at allele frequencies of 1/26 and 6/26, respectively, whereas other mutations were not detected in MRP1 and MRP2 genes. The relative concentrations (mean +/- S.E.) of MDR1 mRNA to villin mRNA were 0.38 +/- 0.15, 0.56 +/- 0.14 and 1.13 +/- 0.42 in the subjects with C/C3435, C/T(3435) and T/T(3435), respectively, which supported the lower serum concentrations of digoxin after single oral administration in the subjects with the mutant T-allele at position 3435. Genetic collaboration between positions 3435 and 2677 was suggested, and those in G/G2677, G/(A,T)(2677) and T/(A,T)(2677) were 0.16 +/- 0.05, 1.10 +/- 0.40, and 0.63 +/- 0.16, respectively (p = 0.107). However, there was no remarkable effect of the G2168A of the MRP1 gene or of C-24T of the MRP2 gene on the relative MRP1 or MRP2 mRNA concentrations, respectively.

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0 The small intestine is the primary site of absorption for many drugs administered orally, and P-glycoprotein (MDR1) located in the villus epithelium of the small intestine is considered to play a role in limiting the absorption of xenobiotics.1,2) The extrusive function of the multidrug resistance-associated proteins (MRPs) have also attracted a great deal of attention in the small intestine.3) MDR1, MRP1 and MRP2 have been reported to show genetic polymorphisms,4-8) and their genotypes are thought to be responsible for the inter-individual differences in absorption properties of the drugs that are their substrates.6,9,10) Kim et al. reported that plasma concentration of fexofenadine after single oral administration was lower in subjects homozygous for the mutant allele at exon 26, position 3435 of the MDR1 gene (T/T3435 ), than in those homozygous for the wild-type allele (C/C3435 ).9) We also demonstrated that systemic exposure to digoxin after single oral administration was lower in subjects with the mutation C3435T of the MDR1 gene.10) C3435T is a silent mutation without amino acid substitution, and its effects on phenotype have been discussed from the viewpoint of changes in the level of expression rather than changes in the function of MDR1.6,11) Thus, in the present study, the effects of the MDR1 genotypes of T-129C, G2677(A,T) and C3435T, MRP1 genotypes of G128C, C218T, G2168A and G3173A, and MRP2 genotypes of C-24T, G1249A, C2302T, C2366T and G4348A on their mRNA expression levels were examined in human duodenal enterocytes obtained from 13 healthy male Japanese subjects. Login to comment
14 MDR1 genotypes of T-129C, G2677(A,T) and C3435T, MRP1 genotypes of G128C, C218T, G2168A and G3173A, and MRP2 genotypes of C-24T, G1249A, C2302T, C2366T and G4348A were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) or direct sequencing. Login to comment
28 MDR1, MRP1 and MRP2 Genotyping Genomic DNA was extracted by the method described previously.10) In the present study, the mutation T-129C in the promoter region, 1 missence mutation (G2677(A,T)) and 1 silent mutation (C3435T) in the MDR1 gene, 4 missense mutations (G128C, C218T, G2168A and G3173A) in the MRP1 gene and 4 missense mutations (G1249A, C2302T, C2366T and G4348A) and the mutation C-24T in the 5Ј-flankling region in the MRP2 gene were examined. Login to comment
53 Among the mutations C-24T, G1249A, C2302T, C2366T and G4348A in the MRP2 gene, only C-24T was detected in the 13 subjects in the present study, and 61% (8/13) were homozygous for the wild-type allele (C/C-24 ), 31% (4/13) were compound heterozygotes (C/T-24 ), and only one subject (1/13, 8%) was homozygous for the mutant allele (T/T-24 ) (Table 1). Login to comment

[hide] Association between single nucleotide polymorphism... Anticancer Res. 2006 May-Jun;26(3B):2227-32. Obata H, Yahata T, Quan J, Sekine M, Tanaka K
Association between single nucleotide polymorphisms of drug resistance-associated genes and response to chemotherapy in advanced ovarian cancer.
Anticancer Res. 2006 May-Jun;26(3B):2227-32., [PMID:16821592]

Abstract [show]
BACKGROUND: Single nucleotide polymorphisms (SNPs) may show clinicopathological importance as prognostic markers. This study examined the association of SNPs and the expression of drug resistance-associated markers with response to chemotherapy in advanced ovarian cancer (stages III and IV) patients. MATERIALS AND METHODS: SNPs were analyzed for MDR1, MRP1, MRP2 and LRP in 60 advanced ovarian cancer patients. The protein expression of each factor was analyzed by immunohistochemistry in all patients. RESULTS: As a result of examining the relevance of SNP genotypes to the response to chemotherapy, a significant relevance (p=0.01) was observed regarding MRP1 exon-17 SNP (G2168A) involving amino acid substitution. No significant relationship was observed between protein expression and the response to chemotherapy or disease-free survival time. CONCLUSION: Analysis of drug resistance gene polymorphism appears to be an indicator of the response to chemotherapy in advanced ovarian cancer.

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84 Gene Nucleic acid Amino acid Allele frequencies Allele frequencies location change substitution (major alleles) (major alleles) in this study in other subject* MDR1 Promotor 1 T/C - 0.908 - Promotor 2 A-41aG - 0.883 0.927 exon-12 T1236C Gly412Gly 0.633 0.615 exon-26 G/A IIe1144IIe 0.500 - exon-28 A/G - 0.742 - MRP1 exon-8 T825C Val275Val 0.600 0.625 exon-9 T1062C Asn354Asn 0.567 0.646 exon-13 T1684C Leu562Leu 0.750 0.802 exon-16 C2007T Pro669Pro 0.950 0.917 exon-17 G2168A Arg723Gln 0.917 0.927 exon-28 G4002A Ser1334Ser 0.883 0.844 MRP2 Promotor C-24T - 0.867 - exon-10 G1249A Val417IIe 0.925 0.875 exon-28 C3972T IIe1324IIe 0.758 0.781 *Ito S. et al. Login to comment

[hide] Does the A118G polymorphism at the mu-opioid recep... Anesthesiology. 2002 Oct;97(4):814-9. Lotsch J, Zimmermann M, Darimont J, Marx C, Dudziak R, Skarke C, Geisslinger G
Does the A118G polymorphism at the mu-opioid receptor gene protect against morphine-6-glucuronide toxicity?
Anesthesiology. 2002 Oct;97(4):814-9., [PMID:12357145]

Abstract [show]
BACKGROUND: Some, but not all, patients with renal dysfunction suffer from side effects after morphine administration because of accumulation of the active metabolite morphine-6-glucuronide (M6G). The current study aims to identify genetic causes that put patients at risk for, or protect them from, opioid side effects related to high plasma M6G. Candidate genetic causes are the single nucleotide polymorphism (SNP) A118G of the mu-opioid-receptor gene (OPRM1), which has recently been identified to result in decreased potency of M6G, and mutations in the MDR1-gene coding P-glycoprotein, of which morphine and M6G might be a substrate. METHODS: Two men, aged 87 and 65 yr, with renal failure (creatinine clearance of 6 and 9 ml/min) received 30 mg/day oral morphine for pain treatment. Both patients had sufficient analgesia from morphine. However, while one patient tolerated morphine well despite high plasma M6G of 1735 nM, in the patient with M6G plasma concentrations of 941 nM it caused severe sleepiness and drowsiness. Patients were genotyped for known SNPs of the OPRM1 and MDR1 genes. RESULTS: The patient who tolerated morphine well despite high plasma M6G was a homozygous carrier of the mutated G118 allele of the mu-opioid-receptor gene, which has been previously related to decreased M6G potency. In contrast, the patient who suffered from side effects was "wild-type" for this mutation. No other differences were found between the OPRM1 and MDR1 genes. CONCLUSIONS: The authors hypothesize that the A118G single nucleotide polymorphism of the mu-opioid-receptor is among the protective factors against M6G-related opioid toxicity. The observation encourages the search for pharmacogenetic reasons that cause interindividual variability of the clinical effects of morphine.

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106 33 T/T T/T MDR1 2 A61G Asn21Asp 11.2 20.6 9 A/G A/G Forward: 5Ј-AGG AGC AAA GAA GAA GAA CTT TTT TAA ACT GAT C-3Ј 9.3 17.6 8 Reverse: 5Ј-GAT TCC AAA GGC TAG CTT GC-3Ј 5 T307C Phe103Leu 0.6 1.2 9 T/T T/T Forward: 5Ј-GTG GTT GCA CAC AGT CAG CA-3Ј Reverse: 5Ј-GGA GGA TGT CTA ATT ACC TGG TCA-3Ј 11 G1199A Ser400Asn 5.5 11.1 9 G/G G/G Forward: 5Ј-CAG CTA TTC GAA GAG TGG GC-3Ј 6.5 12.9 8 Reverse: 5Ј-CCG TGA GAA AAA AAC TTC AAG G-3Ј 21 G2677T Ala893Ser 41.6 49.2 9 T/T T/T Forward: 5Ј-TGC AGG CTA TAG GTT CCA GG-3Ј 63.9 43.4 8 Reverse: 5Ј-GTT TGA CTC ACC TTC CCA G-3Ј 21 G2677A Ala893Thr 0.9 2 9 NA NA Forward: 5Ј-TGC AGG CTA TAG GTT CCA GG-3Ј Reverse: 5Ј-TTT AGT TTG ACT CAC CTT CCC G-3Ј 26 A3320C Gln1107Pro 0.2 0.4 9 A/A A/A 26 C3396T Ala1132Ala 0.3 0.5 8 C/C C/C Forward: 5Ј-ATC TGT GAA CTC TTG TTT TCA GC-3Ј 26 C3435T Ile1145Ile 50.3 47.7 8 T/T T/T Reverse: 5Ј-TCG ATG AAG GCA TGT ATG TTG-3Ј 53.9 50.5 9 - - MRP2 10 G1249A Val417Ile 12.5 20.8 34 G/G G/G Forward: 5Ј-GGG TCC TAA TTT CAA TCC TTA-3Ј Reverse: 5Ј-TAT TCT TCT GGG TGA CTT TTT-3Ј 18 C2302T Arg768Trp 1 2.1 34 C/C C/C Forward: 5Ј-GGA GTA GTG CTT AAT ATG AAT-3Ј 18 C2366T Ser789Phe 1 2.1 34 C/C C/C Reverse: 5Ј-CCC ACC CCA CCT TTA TAT CTT-3Ј 28 C3972T Ile132Ile 21.9 35.4 34 C/T C/T Forward: 5Ј-TGC TAC CCT TCT CCT GTT CTA-3Ј Reverse: 5Ј-ATC CAG GCC TTC CTT CAC TCC-3Ј 31 G4348A Ala1450Thr 1 2.1 34 G/G G/G Forward: 5Ј-AGG AGC TAA CAC ATG GTT GCT-3Ј Reverse: 5Ј-GGG TTA AGC CAT CCG TGT CAA-3Ј † Sequence is not translated. Login to comment

[hide] Impact of genetic polymorphisms in transmembrane c... Naunyn Schmiedebergs Arch Pharmacol. 2004 Jan;369(1):69-77. Epub 2003 Nov 4. Gerloff T
Impact of genetic polymorphisms in transmembrane carrier-systems on drug and xenobiotic distribution.
Naunyn Schmiedebergs Arch Pharmacol. 2004 Jan;369(1):69-77. Epub 2003 Nov 4., [PMID:14598019]

Abstract [show]
Active transport across biological membranes has become a noticeable factor in the absorption, distribution, and excretion of an increasing number of drugs. Different transmembrane transport systems including organic anion transporters (OATP, solute carrier family SLC21A), organic cation transporters (OCT, SLC22A), dipeptide transporters (PEPT, SLC15A), nucleoside transporters (CNT, SLC28A), monocarboxylate carriers (MCT, SLC2A), and members of the large ATP-binding cassette family (ABC, SLC3A) are involved in drug disposition. Genetic polymorphisms in transport proteins frequently occur and contribute to interindividual differences in the efficacy and safety of pharmatherapy. Currently, the most advanced research has been done on P-glycoprotein (ABCB1, SLC3A1.201.1). Knowledge of this transporter indicates that haplotype analysis rather than association with single nucleotide polymorphisms (SNPs) provides the most appropriate interpretation of pharmacogenetic data from drug transporters. This review gives an overview and update on the pharmacological impact of genetic variants in transmembrane transporters.

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145 Frequently occurring SNPs were C24T (18.8%) of the promoter region and the two exonic SNPs G1249A (12.5%, exon 10) and C3972T (21.9%, exon 28). Login to comment

[hide] CYP2D6 genotype and induction of intestinal drug t... Clin Pharmacol Ther. 2004 Mar;75(3):213-22. Giessmann T, Modess C, Hecker U, Zschiesche M, Dazert P, Kunert-Keil C, Warzok R, Engel G, Weitschies W, Cascorbi I, Kroemer HK, Siegmund W
CYP2D6 genotype and induction of intestinal drug transporters by rifampin predict presystemic clearance of carvedilol in healthy subjects.
Clin Pharmacol Ther. 2004 Mar;75(3):213-22., [PMID:15001973]

Abstract [show]
BACKGROUND: Clinical trials have indicated that the combined beta- and alpha-adrenergic receptor blocker carvedilol improves the survival rate in patients with advanced chronic heart failure. The objective of our study was the identification and quantification of factors that modulate steady-state serum concentrations of carvedilol and its enantiomers and that may influence therapeutic efficacy and safety. METHODS: The influence of genetic variants of cytochrome P450 (CYP) 2D6 and CYP2C9 and of transporter proteins (P-glycoprotein, multidrug resistance protein 2 [MRP2]) on the disposition of carvedilol and its enantiomers after intravenous (5 mg) and long-term oral administration (25 mg for 7 days) was assessed in 12 healthy subjects. The intestinal expression of P-glycoprotein and MRP2 was analyzed by quantitative real-time polymerase chain reaction and immunohistochemical techniques. RESULTS: The area under the serum concentration-time curve (AUC) values of carvedilol were significantly (P <.05) increased in 6 subjects with CYP2D6 deficiency, with effects being more pronounced for R(+)-carvedilol (230 +/- 72.6 ng. h/mL versus 93.9 +/- 64.6 ng. h/mL in extensive metabolizers) than for S(-)-carvedilol (62.9 +/- 21.1 ng. h/mL versus 32.7 +/- 14.5 ng. h/mL). The AUC and fecal excretion of intravenous carvedilol were correlated with the intestinal expression of MDR1 messenger ribonucleic acid (mRNA) (r = -0.67, P =.001; r = 0.83, P =.002) and MRP2 mRNA (r = -0.74, P <.001; r = 0.70, P =.025). Furthermore, we measured the disposition of long-term oral carvedilol after comedication of the pregnane X receptor ligand rifampin (INN, rifampicin) (600 mg, 9 days), which up-regulates both P-glycoprotein and MRP2 but not CYP2D6. Rifampin decreased the AUC of carvedilol to an extent independent of the CYP2D6 genotype (poor metabolizers, 341 +/- 147 ng. h/mL versus 126 +/- 41.7 ng. h/mL; extensive metabolizers, 173 +/- 102 ng. h/mL versus 74 +/- 41.4 ng. h/mL; both P <.05). The AUC was significantly correlated with intestinal expression of MDR1 mRNA (r = -0.671, P =.001) and MRP2 mRNA (r = -0.595, P <.006). CONCLUSIONS: Variable plasma concentrations of carvedilol during long-term administration are predicted by CYP2D6 genotype and intestinal expression of P-glycoprotein and MRP2.

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30 Genotyping of the MRP2 gene identified 9 subjects with CC and 3 with CT of the promoter variant C-24T, 7 subjects with GG and 5 with GA of G1249A, and 6 subjects with CC and 6 with CT of C3972T. Login to comment
58 CYP2D6 was genotyped for the major deficient alleles in white subjects, *3 (2549AϾdel frameshift mutation), *4 (1846GϾA splice-site mutation), *5 (gene deletion), and *6 (1707TϾdel frameshift mutation), as well as for gene duplications (*1xN, *2xN), and MDR1 was genotyped for G2677T/A and C3435T.19-21 MRP2 genotypes C-24T in the promoter region, G1249A in exon 10, and C3972T in exon 28 were determined by use of polymerase chain reaction-based restriction fragment length polymorphism assays by use of BbsI for distinction of C-24T and mismatch primers for G1249A and C3972T, introducing an AclI or BsrDI site in the presence of the mutation. Login to comment
94 The basal expression of P-gp and MRP2 (mRNA and protein levels) in our small number of subjects was not dependent on G2677T/A and C3435T of MDR1 and C-24T, G1249A, and C3972T of the MRP2 gene. Login to comment

[hide] The role of common variation in drug transporter g... Expert Opin Pharmacother. 2005 Jul;6(8):1305-12. Soranzo N, Goldstein DB, Sisodiya SM
The role of common variation in drug transporter genes in refractory epilepsy.
Expert Opin Pharmacother. 2005 Jul;6(8):1305-12., [PMID:16013981]

Abstract [show]
Resistance to antiepileptic drugs (AEDs) is one of the most serious clinical problems in epilepsy, and along with AED teratogenicity, perhaps the major concern of epilepsy pharmacogenetics. Studying the genetics of drug resistance in epilepsy is important, as it may identify or confirm key mechanisms underlying this phenomenon that have real clinical importance; it might also offer insights into its prediction and management. Drug resistance in epilepsy is likely to be multifactorial: overactivity of multi-drug transporters provides one likely underlying mechanism through lowering of AED concentration in the epileptogenic focus. Genetic association studies may provide a tool to assess this 'transporter' hypothesis by determining whether differences between individuals contribute to resistance phenotypes. Most of these studies have investigated one variant in the ABCB1 gene, and have provided, thus far, inconclusive evidence. This review also considers current knowledge of the role of genetic polymorphisms in multi-drug transporters in pharmacoresistant epilepsy, to highlight possible confounding factors affecting the implementation and interpretation of association studies in this field.

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104 Individuals heterozygous at the MRP2 exon 10 G1249A site had higher expression compared with GG homozygotes in DNTs (6.12-fold, p < 0.05) and in PT (2.69-fold, not significant). Login to comment

[hide] MDR1, MRP1 and MRP2 genotypes and in vitro chemose... Kobe J Med Sci. 2004;50(5-6):181-8. Nishioka C, Sakaeda T, Nakamura T, Moriya Y, Okamura N, Tamura T, Nakahara T, Aoyama N, Kamigaki T, Ohno M, Kuroda Y, Kasuga M, Okumura K
MDR1, MRP1 and MRP2 genotypes and in vitro chemosensitivity in Japanese patients with colorectal adenocarcinomas.
Kobe J Med Sci. 2004;50(5-6):181-8., [PMID:16107775]

Abstract [show]
In our previous paper, the chemosensitivity of human colorectal adenocarcinoma was evaluated against 12 anticancer drugs including 5-fluorouracil (5-FU), 7-ethyl-10-hydroxycamptothecin (SN-38), mitomycin C (MMC) and cisplatin (CDDP), and it was found that the anticancer drugs were effective against those with a relatively high growth rate. MMC was effective for those with a relatively high mRNA expression of the multidrug resistance-associated protein 2 (MRP2), whereas no correlation was found for the multidrug resistant transporter MDR1 and MRP1. In this study, 3 genotypes of MDR1, 4 genotypes of MRP1, and 6 genotypes of MRP2 were additionally evaluated, and it was suggested that MDR1 C3435T and MRP2 G1249A were related with the susceptibility to colorectal adenocarcinoma. The chemosensitivity against 5-FU, SN-38, MMC and CDDP was independent of MDR1 C3435T, MRP1 G2168A, and MRP2 C-24T (C3972T), possibly due to no association with the growth rate of and mRNA expression levels of MDR1, MRP1 and MRP2 in the adenocarcinoma, however, MDR1 C3435T tended to be accompanied with a higher expression of MDR1 mRNA.

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4 In this study, 3 genotypes of MDR1, 4 genotypes of MRP1, and 6 genotypes of MRP2 were additionally evaluated, and it was suggested that MDR1 C3435T and MRP2 G1249A were related with the susceptibility to colorectal adenocarcinoma. Login to comment
19 In the present study, the distributions of MDR1 genotypes of T-129C, G2677(A,T) and C3435T, MRP1 genotypes of G128C, C218T, G2168A and G3173A, and MRP2 genotypes of C-24T, G1249A, C2302T, C2366T, C3972T and G4348A were evaluated in Japanese patients with primary colorectal adenocarcinoma, and their effects on the chemosensitivity against 5-FU, SN-38, MMC and CDDP, and also on the growth rate of tumor and mRNA expression levels of MDR1, MRP1 and MRP2 in the adenocarcinoma were examined for future individualization of cancer chemotherapy based on the genotyping of these transporters. Login to comment
37 The polymorphism of T-129C in the promoter region, a missense polymorphism of G2677(A,T), and a silent polymorphism of C3435T in the MDR1 gene, 4 missense polymorphisms of G128C, C218T, G2168A and G3173A in the MRP1 gene, and a polymorphism of C-24T in the 5`-flanking region, 4 missense polymorphisms of G1249A, C2302T, C2366T and G4348A, and a silent polymorphism of C3972T in the MRP2 gene were evaluated by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), and confirmed by direct sequencing. Login to comment
46 Compared with the healthy subjects, T-allele at C3435T of MDR1 was more frequently found in patients with colorectal adenocarcinoma, whereas A-allele at G1249A of MRP2 was found less frequently, although this is from a small number of patients with insufficient statistical power. Login to comment
51 MDR1, MRP1 and MRP2 genotypes in 13 Japanese patients with colorectal adenocarcinomas Genotype Allele Position w/w w/m m/m w m MDR1 T-129C 11 2 0 24 2 G2677(A,T) 3 6 4 12 14 C3435T 3 6 4 12 14 MRP1 G128C 13 0 0 26 0 C218T 13 0 0 26 0 G2168A 10 3 0 23 3 G3173A 13 0 0 26 0 MRP2 C-24T 7 4 2 18 8 G1249A 12 1 0 25 1 C2302T 13 0 0 26 0 C2366T 13 0 0 26 0 C3972T 7 4 2 18 8 G4348A 13 0 0 26 0 The symbols "w" and "m" mean the polymorphisms with higher and lower frequency of allele, respectively. Login to comment
66 In conclusion, MDR1 genotypes of T-129C, G2677(A,T) and C3435T, MRP1 genotypes of G128C, C218T, G2168A and G3173A, and MRP2 genotypes of C-24T, G1249A, C2302T, C2366T, C3972T and G4348A were evaluated in the Japanese patients with primary colorectal adenocarcinoma, and it was suggested that MDR1 C3435T and MRP2 G1249A were related with the susceptibility to colorectal adenocarcinoma. Login to comment

[hide] Sarcomas and pharmacogenetics. Pharmacogenomics. 2005 Sep;6(6):585-601. Biason P, Toffoli G
Sarcomas and pharmacogenetics.
Pharmacogenomics. 2005 Sep;6(6):585-601., [PMID:16142999]

Abstract [show]
Sarcomas are a heterogeneous group of tumors, requiring different chemotherapeutic approaches. Recently, several regimens for metastatic tumors were evaluated with respect to the different responses to conventional chemotherapy of the various histologic subtypes of sarcomas. The impact of pharmacogenetics in the progress of chemotherapy appears to be crucial in defining the clinical response to many drugs, such as anthracycline or alkylating agents, that are widely used in treatment regimens for soft tissue sarcomas (STS) or sarcomas of the bone. Polymorphisms of metabolizing enzymes (e.g., cytochrome P450 and glutathione-S-transferase), transporter proteins (reduced folate carrier and P-glycoprotein) or target proteins (thymidylate synthase, methylenetetrahydrofolate reductase, dihydrofolate reductase, and c-KIT) may be responsible for an altered clinical outcome, in terms of both response and toxicity. The administration of new chemotherapeutic agents, such as imatinib for gastrointestinal tumors (GIST), requires the study of genetic polymorphisms possibly affecting the integrity of the target (c-KIT), which may provide valid information regarding possible developments of therapy. For STS and sarcoma of the bone, the genetic markers, which could be unambiguously predictive of the phenotypic profile of patients, are as yet undetermined.

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56 Gene Polymorphism Molecular effect of polymorphism Drug Effect on chemotherapy Ref. Phase I enzymes CYP2B6 CYP2B6*5 (C1459 T) Decreased enzyme expression Increased activity CPA Increased drug bioactivation [24] CYP2B6*6 (G516T, A785G) [28] CYP2B6*7 (G516T, A785G, C1459T) [24] CYP2C9 CYP2C9*2 (C430T) Decreased enzyme activity CPA Decreased drug bioactivation [31]CYP2C9*3 (A1075C) CYP2C19 CYP2C19*2 (G108620C) Lack of enzyme activity CPA No data available CYP3A4 CYP3A4*1B (A290G) Decreased mRNA expression CPA No data available [39,42] CYP3A5 CYP3A5*3 (A6986G) Lack of enzyme activity CPA No data available [42] CYP3A5*6 (G14690A) CYP2C8 CYP2C8*2 (A805T) Reduced protein activity Paclitaxel Reduced clearance of drug [44]CYP2C8*3 (G416A, A1196G) Reduced protein activity Paclitaxel Defective metabolism Phase II enzymes GST GSTA1*B (C-69T) Reduced enzyme activity CPA Increased survival [46] GSTM1 (null genotype) Complete absence of protein DOX CPA Poorer survival No impact in STS survival [47] [52] GSTT1 (null genotype) Complete absence of protein DOX CPA Increased response No impact in STS survival [49] [52] GSTP1 (A313G) Decreased enzyme activity DOX CPA Cisplatin Longer survival [53] Transporter MDR1 C3435T Decreased protein expression DOX MTX Better clinical response [59] MRP2 C24T Alteration in protein expression MTX Cisplatin No data available [63] G1249A RFC G80A Decreased affinity for MTX MTX Poorer response No correlation with toxicity [68,70] Intracellular target DHFR T91C Increased enzyme activity MTX Resistance to drug [72] MTHFR C677T Reduced enzyme activity MTX Higher toxicity [77] TYMS TSER (*3/*3 repeats) Increased mRNA expression MTX Necessity of higher dose of MTX [75] CPA: Cyclophosphamide; CYP: Cytochrome P450; DHFR: Dihydrofolate reductase; DOX: Doxorubicin; ERCC1: Excision repair cross-complementing rodent repair deficiency, complementation group 1; ET-743: Ecteinascidin-743; GST: Glutathione S-transferase; MDR: Multidrug resistance; MTHFR: Methylenetetrahydrofolate reductase; MTX: Methotrexate; RFC: Replication factor C; TYMS: Thymidylate synthetase; XPD: Xeroderma pigmentosum group D; XRCC1: X-ray repair complementing defective repair in Chinese hamster cells 1. Login to comment
143 Among these, two SNPs are mainly responsive to alterations in protein expression: C24T (promoter region) and G1249A (exon 10) [62]. Login to comment
235 Genetic analyses for MTX response are usually performed in transporter enzymes (RFC G80A, MRP C24T and G1249A) or in target enzymes (DHFR T91C, TSER and MTHFR C677T). Login to comment

[hide] Single nucleotide polymorphisms in human P-glycopr... Expert Opin Drug Deliv. 2006 Jan;3(1):23-35. Dey S
Single nucleotide polymorphisms in human P-glycoprotein: its impact on drug delivery and disposition.
Expert Opin Drug Deliv. 2006 Jan;3(1):23-35., [PMID:16370938]

Abstract [show]
Drug efflux pumps belong to a large family of ATP-binding cassette transporter proteins. These pumps bind their substrate and export it through the membrane using energy derived from ATP hydrolysis. P-glycoprotein, the main efflux pump in this family, is expressed not only in tumour cells but also in normal tissues with excretory function (liver, kidney and the intestine). It has a broad specificity of substrates and plays an important role in drug delivery and disposition. Recently, genetic screening of P-glycoprotein has yielded multiple single nucleotide polymorphisms, which seem to alter transporter function and expression. This review discusses the various polymorphisms of this gene and its impact on drug disposition and diseases.

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179 Among them, C24T (promoter region), G1249A (exon 10) and C3972T (exon 28) are most frequently observed [80]. Login to comment
180 The SNP associated with G1249A also changes the amino acid residue from Val to Ile (Val417Ile); however, C3972T is a 'silent mutation` with no change in amino acid sequence. Login to comment

[hide] Influence of polymorphisms of ABCB1 and ABCC2 on m... Pharmacogenomics J. 2007 Feb;7(1):56-65. Epub 2006 Jun 20. Haenisch S, Zimmermann U, Dazert E, Wruck CJ, Dazert P, Siegmund W, Kroemer HK, Warzok RW, Cascorbi I
Influence of polymorphisms of ABCB1 and ABCC2 on mRNA and protein expression in normal and cancerous kidney cortex.
Pharmacogenomics J. 2007 Feb;7(1):56-65. Epub 2006 Jun 20., [PMID:16788565]

Abstract [show]
There is increasing evidence that polymorphisms of the adenosine 5' triphosphate membrane transporters ABCB1 (P-glycoprotein, MDR1) may affect expression and function, whereas less information is available about the impact of ABCC2 (multidrug resistance-associated protein (MRP2)) single-nucleotide polymorphisms . Particularly, their role in human kidney for drug elimination and in the etiology of renal cell carcinoma is poorly understood. ABCB1 and ABCC2 mRNA and protein expression levels were determined by real-time polymerase chain reaction or immunohistochemistry in kidney cancer and adjacent unaffected cortex tissue of 82 nephrectomized renal cell cancer (RCC) patients (63 clear-cell RCC (CCRCC), 19 non-CCRCC). The DNA of all patients was genotyped for ABCB1 -2352G>A, -692T>C, 2677G>T/A (Ala893Ser/Thr), and 3435C>T, and ABCC2 -24C>T, 1249G>A (Val417Ile) and 3972C>T. ABCB1 and ABCC2 were less expressed in CCRCC than in normal cortex on mRNA as well as on protein level. Although the overall genotype frequency distribution did not differ between the patients and a matched control group, ABCB1 2677T/A and 3435T genotypes were associated with higher (P=0.02 and P=0.04) and ABCC2 -24 T with lower mRNA levels in normal tissues (0.03). The expression of ABCB1 and ABCC2 was not related to genetic variants in RCC tissue. In a reporter gene assay in HepG2 cells, the ABCC2 -24T construct showed an 18.7% reduced activity (P=0.003). In conclusion, ABCB1 and ABCC2 genotypes modulate the expression in the unaffected renal cortex of RCC patients, possibly contributing to inter-individual differences in drug and xenobiotics elimination. Their role in RCC cancer susceptibility or chemotherapy resistance needs further elucidation.

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52 The wild-type (ABCC2-C) and the variant (ABCC2-T) fragment were ligated into the pGL3 basic vector (Promega, Mannheim, Germany) being in-frame of the translation Table 1 Primers and restriction endonucleases used for genotyping of novel ABCB1 (MDR1) and ABCC2 (MRP2) variants and primers and fluorescent probes used for cDNA real-time quantification Gene SNP Name of primer Primer sequence Restriction enzyme Fragment length (bp) mut/wt ABCB1 T-692C MDR1-692f 50 -CTA GAG AGG TGC AAC GGA AAG MspA1I 32 117 208 MDR1-692r 50 -TAG TAG CTC CCA GCT TTG CG 117 240 G-2352A MDR1-2352f 50 -TTT ACC TGA TGC TCA AGA TTG TAG MboI 179 MDR1 -2352r* 50 - TCA CTT TTG TTT TGC TTT GTT GCT TGA T 144 35 ABCB1 mdr1 forward 50 -TTC GCA ACC CCA AGA TCC TC mdr1 reverse 50 -ACA ATG GTG GTC CGA CCT TT Probe 50 -6FAM-ATC CAG AGC CAC CTG AAC CAC TGC T XT p ABCC2 C-24T MRP2-Pro 50 -TAA ATG GTT GGG ATG AAA GG BbsI 301 MRP2-ProR2 50 -GCT TTA GAC CAA TTG CAC ATC 188 113 G1249A MRP2-10* 50 -AAC TTG GCC AGG AAG GAG TAC AAC AclI 260 MRP2-10R 50 -CTG GGT GAC TTT TTC TTT ACC TGA ATG 236 24 C3972T MRP2-28 50 -AAC TTA CTT CTC ATC TTG TCT CCT TGC BsrDI 156 28 MRP2-28R* 50 -CTC CAC CTA CCT TCT CCA TGC TAG 184 ABCC2 mrp2 forward 50 -CTG GGA ACA TGA TTC GGA AGC mrp2 reverse 50 -GAG GAT TTC CCA GAG CCG AC Probe 50 -6FAM-CAG TCC GAG ATG TGA ACC TGG ACA T XT p Abbreviations: MDR1, multidrug resistance protein 1; MRP2, multidrug resistance-associated protein. Login to comment
103 The difference, however, was statistically not significant (P ¼ 0.134), but there were increased mRNA expression levels among ABCB1 H1/H4 (P ¼ 0.044) and ABCB1 H2/H4 (P ¼ 0.01) (Mann-Whitney Table 2 Allele frequencies and frequencies of genotypes in 82 patients and in 164 controls Location Allele Allele frequency Genotype Frequency of genotypes Odds ratio P-value RCC Controls RCC controls 95% CI MDR1 G 99.4 99.1 GG 98.8 98.2 0.66 (0.03-7.29) 0.72 G-2352A A 0.6 0.9 GA 1.2 1.8 AA 0.0 0.0 T-692C T 98.0 97.0 TT 96.3 93.3 0.53 (0.11-2.12) 0.33 C 2.0 3.0 TC 3.7 6.7 CC 0.0 0.0 G2677T/A G 58.5 54.3 GG 35.4 32.3 0.87 (0.48-1.59) 0.63 T 39.6 43.6 GT 42.7 41.5 A 1.8 2.1 TT 18.3 22.0 GA 3.7 2.4 TA 0.0 1.8 AA 0.0 0.0 C3435T C 42.7 46.3 CC 18.3 22.6 1.3 (0.64-2.69) 0.44 T 57.3 53.7 CT 48.8 47.6 TT 32.9 29.9 MRP2 C 78 81.4 CC 64.6 68.9 1.21 (0.67-2.20) 0.50 C-24T T 22 18.6 CT 26.8 25.0 TT 8.5 6.1 G1249A G 83.5 77.8 GG 67.1 61.6 0.79 (0.43-1.43) 0.40 A 16.5 22.2 GA 32.9 32.3 AA 0.0 6.1 C3972T C 62.8 69.2 CC 41.5 51.2 1.48 (0.84-2.62) 0.15 T 37.2 30.8 CT 42.7 36.0 TT 15.9 12.8 Abbreviations: MDR1, multidrug resistance protein 1; MRP2, multidrug resistance-associated protein; RCC, renal cell carcinoma. Login to comment
121 Table 3 Frequencies of ABCB1 and ABCC2 haplotypes in RCC patients and controls estimated with the EH program26 ABCB1 haplotype G2677T/ A C3435T Frequency RCC Controls 1 G C 40.9 38.8 2 G T 17.7 15.5 3 T C 0.0 6.1 4 T T 39.6 37.5 5 A C 1.8 1.5 6 A T 0.0 0.6 w2 ¼ 11.63, d.f. ¼ 5, P ¼ 0.04 ABCC2 haplotype C-24T G1249A C3972T Frequency RCC Controls 1 C G C 45.8 47.0 2 T G C 0.0 1.4 3 C A C 16.4 20.8 4 T A C 0.0 0.0 5 C G T 15.8 12.2 6 T G T 22.0 17.2 7 C A T 0.0 1.4 8 T A T 0.0 0.0 w2 ¼ 8.55, d.f. ¼ 5, P ¼ 0.128 Twelve square w2 test was conducted to compare differences between haplotype frequencies of RCC and controls. Login to comment

[hide] Pharmacogenetics of HIV therapy. Pharmacogenet Genomics. 2006 Oct;16(10):693-703. Owen A, Pirmohamed M, Khoo SH, Back DJ
Pharmacogenetics of HIV therapy.
Pharmacogenet Genomics. 2006 Oct;16(10):693-703., [PMID:17001288]

Abstract [show]
Drug treatment in HIV disease is characterized by variable responses, in terms of both efficacy and toxicity. Both genetic and environmental factors are important determinants of this variability, although the relative contributions are unclear and likely to vary with different drugs. Many of the antiretrovirals are metabolized by polymorphically expressed enzymes (cytochrome P450, CYP450; glucuronyl transferase, GT) and/or transported by drug transporters (ABC and SLC families). Initial studies of antiretroviral efficacy have therefore focused on these genes. For example, it has recently been shown that a CYP2B6 genetic variant predicts higher plasma efavirenz exposure and possibly increased central nervous system toxicity. A large number of studies on ABCB1 genetics with antiretrovirals have also been undertaken; however, as in other therapeutic areas, the data have been contradictory, and currently, no firm conclusions can be reached on the effect of ABCB1 variability as a determinant of efficacy. Indeed, this highlights the need for validation of initial association studies in pharmacogenetic research. By contrast, the clearest association between genetic variants and response relates to the hypersensitivity reaction that occurs with abacavir. The identification that the major histocompatibility complex haplotype 57.1 acts as a strong genetic predisposing factor can be regarded as a prime example of how fundamental research can be translated into a pharmacogenetic test. Nevirapine hypersensitivity has also been related to an HLA gene (HLA-DRB1*0101) but the predictive value does not appear to be sufficient to implement in clinical practice. Much more work needs to be done to define the genetic factors determining response to antiretroviral agents. These studies need to be sufficiently powered and utilize a modern genotyping strategy. Most importantly, the phenotype needs to be carefully characterized. We also need to disseminate this information: a pivotal resource for this can be found at www.HIV-pharmacogenomics.org.

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171 Pharmacogenetics of HIV therapy Owen et al. 699 Table 1 Polymorphisms that have been studied within the context of metabolism, transport and toxicity (but not progression and response) along with the reference ID (where available), the genotypic consequence and the observed phenotype for antiretroviral drugs Gene SNP (haplotype) Reference SNP Genotypic consequence Phenotypic consequence Confirmation CYP3A4 A - 392G (CYP3A4*1B) rs2740574 Promoter; altered expression No effect on nelfinavir or efavirenz Yes for nelfinavir; controversial for efavirenz T878C (CYP3A4*18) rs4986909 L293P; altered activity No effect on efavirenz No CYP3A5 A6986G (CYP3A5*3) rs776746 Splice defect No effect on nelfinavir, saquinavir or efavirenz AUC but altered urinary metabolic ratio of saquinavir Yes for efavirenz G14690A (CYP3A5*6) rs10264272 Splice defect No effect on nelfinavir or efavirenz Yes CYP2C19 G681A (CYP2C19*2) rs4244285 Truncated protein Higher nelfinavir AUC and trend toward decreased virological failure; no effect on efavirenz Yes for efavirenz; controversial for nelfinavir CYP2D6 A2549del (CYP2D6*3) NT21914757 Frameshift Trend to higher plasma levels of nelfinavir and efavirenz No G1846A (CYP2D6*4) rs3892097 Splice defect Trend to higher plasma levels of nelfinavir and efavirenz No T1707del (CYP2D6*6) rs5030655 Frameshift Higher plasma nelfinavir concentrations No CYP2B6 G516 T (CYP2B6*6, *7, *9, *13, *19 and *20) rs3745274 Q172H Higher plasma and intracellular efavirenz AUCs and increased neurotoxicity Yes, numerous studies C1459T (CYP2B6*5 and *7) rs3211371 R487C No effect on nelfinavir or efavirenz No ABCB1 IVS1 - 80delG rs3214119 N/A No influence on cellular nelfinavir No A61G rs9282564 N21D No influence on cellular nelfinavir No TAG1 rs3789243 N/A No influence on cellular nelfinavir No G1199A rs2229109 S400N No influence on cellular nelfinavir No TAG5 rs1128503 N/A No influence on cellular nelfinavir No TAG6 rs2235046 N/A No influence on cellular nelfinavir No IVS21 + T49C rs2032583 N/A No influence on cellular nelfinavir No C3435T rs1045642 Synonymous Some evidence of an influence on plasma and intracellular nelfinavir; decreased efavirenz plasma concentrations; currently under debate; increase in HDL cholesterol with efavirenz Controversial G2677T rs2032582 Ala893Ser No effect on efavirenz, ritonavir, nelfinavir, indinavir or viral decay and CD4 count Yes IVS26 + T59G rs2235047 N/A No influence on cellular nelfinavir No IVS26 + T80C rs2235048 N/A Increased intracellular nelfinavir concentrations No TAG11 rs1186746 N/A No influence on cellular nelfinavir No TAG12 rs1186745 N/A No influence on cellular nelfinavir No ABCC1 G816A P272P No influence on cellular nelfinavir No T825C rs246221 V275V No influence on cellular nelfinavir No T1062C rs35587 Synonymous No influence on cellular nelfinavir No IVS9 + A8G rs35588 N/A No influence on cellular nelfinavir No IVS10 + C64T N/A No influence on cellular nelfinavir No ABCC2 C - 24T rs717620 N/A No influence on cellular nelfinavir No G1249A rs2273697 V417I No influence on cellular nelfinavir No C1436G Synonymous No influence on cellular nelfinavir No IVS16 - G47A N/A No influence on cellular nelfinavir No T3563A rs8187694 V1188E No influence on cellular nelfinavir No C4488T rs8187707 Synonymous No influence on cellular nelfinavir No IVS31 + G12A rs8187708 N/A No influence on cellular nelfinavir No IVS31 + C74T N/A No influence on cellular nelfinavir No G4544A rs8187710 C1515Y No influence on cellular nelfinavir No G + 259T N/A No influence on cellular nelfinavir No ABCG2 - 19571_ - 19568delT- CAC rs4148162 Deletion No influence on cellular nelfinavir No A-19541G N/A No influence on cellular nelfinavir No G34A rs2231137 V12M No influence on cellular nelfinavir No IVS2 + 35G rs4148152 N/A No influence on cellular nelfinavir No C421A rs2231142 Q141K No influence on cellular nelfinavir No APOCIII C-482T Pending Promoter Hyperlipidaemia in presence of ritonavir Yes T-455C Pending Promoter Hyperlipidaemia in presence of ritonavir Yes C3238G rs5128 30 UTR variant Hyperlipidaemia in presence of ritonavir Yes APOE 2060T/2198T (APOEe2) rs429358 R112C/R158C Hyperlipidaemia in presence of ritonavir Yes 2060T/2198C (APOEe3) rs7412 R112C/R158R Hyperlipidaemia in presence of ritonavir Yes TNFa G - 238A rs361525 Promoter Rapid development of lipoatrophy Controversial SPINK-1 C112T rs17107315 N34S Associated with risk of pancreatitis Yes, in general population CFTR G1717 - 1A Splice defect Associated with risk of pancreatitis Yes, in general population IVS8 5T Splice defect Associated with risk of pancreatitis Yes, in general population HLA-B HLA-B*57.1 N/A Abacavir hypersensitivity Yes, but not in all populations HLA-DR HLA-DRB1*0101 N/A Nevirapine hypersensitivity No HSPA1L C2437T rs2227956 M493T Abacavir hypersensitivity No UGT1A1 A(TA)7TAA, - 43_ - 42in- sTA (UGT1A1*28) rs8175347 Promoter; insertion at TATA box Gilberts syndrome, hyperbilirubinaemia in presence of atazanavir and indinavir but not saquinavir Yes MT-CO1 C7028T Synonymous Haplogroup T associated with greater incidence of peripheral neuropathy No 700 Pharmacogenetics and Genomics 2006, Vol 16 No The NNRTI nevirapine can also cause a hypersensitivity syndrome characterized by a rash with systemic symptoms; occasionally liver injury may be part of the clinical picture, or alternatively, may actually be the only manifestation. 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[hide] The emerging importance of transporter proteins in... Drug Metab Rev. 2007;39(4):723-46. Wang JS, Newport DJ, Stowe ZN, Donovan JL, Pennell PB, DeVane CL
The emerging importance of transporter proteins in the psychopharmacological treatment of the pregnant patient.
Drug Metab Rev. 2007;39(4):723-46., [PMID:18058331]

Abstract [show]
P-glycoprotein, breast cancer resistance protein, and multidrug resistance proteins have physiological functions in placental tissue. Several antidepressants, antipsychotics, and anti-epileptic drugs have been found to be substrates of P-glycoprotein and other transporters. The extent that drugs pass through the placental barrier is likely influenced by drug transporters. The rational choice of psychoactive drugs to treat mental illness in women of child-bearing age should incorporate knowledge of both drug disposition as well as expected pharmacologic effects. This review summarizes the current data on drug transporters in the placental passage of medications, with a focus on medications used in clinical psychopharmacology.

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115 One study of 58 human placenta samples found a significant influence of the MRP2 G1249A missense mutation on mRNA associated with a lower expression in pre-term samples. Login to comment

[hide] Role of the multidrug transporter proteins ABCB1 a... Drug Metab Dispos. 2008 Apr;36(4):740-4. Epub 2008 Jan 14. May K, Minarikova V, Linnemann K, Zygmunt M, Kroemer HK, Fusch C, Siegmund W
Role of the multidrug transporter proteins ABCB1 and ABCC2 in the diaplacental transport of talinolol in the term human placenta.
Drug Metab Dispos. 2008 Apr;36(4):740-4. Epub 2008 Jan 14., [PMID:18195111]

Abstract [show]
Placental syncytiotrophoblasts are known to express the efflux transporter proteins P-glycoprotein (ABCB1) and multidrug resistance-associated protein 2 (ABCC2), which are supposed to be a functional part of the human placental barrier. With advancing gestational age, expression of ABCB1 decreases progressively, whereas ABCC2 is more expressed. To evaluate to which extent they contribute to placental barrier function at term, permeability of talinolol, a substrate of both carriers, was measured using a validated human placenta perfusion model. We identified in randomized, crossover experiments a unidirectional transfer of talinolol in the fetomaternal direction because the maternofetal transfer was significantly lower (0.663 +/- 0.188 versus 0.394 +/- 0.067 relative to creatinine permeability, p = 0.012). Maternofetal permeability was increased by the ABCC2 inhibitor probenecid (0.59 +/- 0.15 versus 0.68 +/- 0.13, p = 0.028) and the nonspecific inhibitor verapamil (0.53 +/- 0.09 versus 0.66 +/- 0.16, p = 0.028) but was not influenced by the ABCB1 inhibitor valspodar (PSC833) (0.48 +/- 0.11 versus 0.46 +/- 0.09, p = 0.345). Genetic polymorphisms of ABCB1 and ABCC2 lacked significant influence on expression of the carriers and permeability of talinolol, respectively. In conclusion, maternofetal transfer of talinolol is restricted by a unidirectional process that is influenced by inhibitors of ABCC2.

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126 There is evidence from literature that the genetic polymorphisms ABCB1 G2677T and C3435T and ABCC2 G1249A are associated with altered expression of the transporters in the human placenta (Hitzl et al., 2004; Meyer zu Schwabedissen et al., 2005). Login to comment

[hide] ABCC2 haplotype is not associated with drug-resist... J Pharm Pharmacol. 2008 May;60(5):631-5. Seo T, Ishitsu T, Oniki K, Abe T, Shuto T, Nakagawa K
ABCC2 haplotype is not associated with drug-resistant epilepsy.
J Pharm Pharmacol. 2008 May;60(5):631-5., [PMID:18416940]

Abstract [show]
Several studies have investigated the association between the ABCB1 polymorphism and drug-resistant epilepsy. However, the effect of ABCC2 polymorphisms on anti-epileptic drug (AED) responsiveness remains unknown. The ABCC2 polymorphisms have been genotyped in 279 Japanese epileptic patients treated with AEDs. The association between the AED responsiveness and the polymorphisms was estimated by a haplotype-based analysis. No genotype or haplotype was associated with drug-resistant epilepsy. On the other hand, the delGCGC haplotype at G-1774delG, C-24T, G1249A and C3972T was over represented among the epileptic patients with a complication of mental retardation in comparison with those without (32.4% vs 22.0%; P=0.009); and the G-1774delG allele was also associated with mental retardation (P=0.03). No association between the ABCC2 genotypes or haplotypes, and the responsiveness of AEDs was observed, although this finding was inconclusive because of the small sample size.

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5 On the other hand, the delGCGC haplotype at G-1774delG, C-24T, G1249A and C3972T was over represented among the epileptic patients with a complication of mental retardation in comparison with those without (32.4% vs 22.0%; P=0.009); and the G-1774delG allele was also associated with mental retardation (P=0.03). Login to comment
12 Therefore a linkage disequilibrium analysis was performed to investigate the association between the ABCC2 genotypes of G-1774delG, C-24T, G1249A and C3972T or these haplotypes and clarify the responsiveness to the AED therapy among epileptic patients. Login to comment
34 ABCC2 polymorphisms at C-24T (rs717620), G1249A (rs2273697) and C3972T (rs3740066) were determined by polymerase chain reaction (PCR)-restriction fragment length polymorphism as reported by Naesens et al (2006) and Rau et al (2006). Login to comment
45 On the other hand, a significant linkage disequilibrium was detected among G-1774delG, C-24T, G1249A and C3972T (each ⏐D`⏐ > 0.75; P < 0.0001). Login to comment
56 In this study, the ABCC2 genotypes or haplotypes did not have any impact on the responsiveness to AEDs, while significant associations between mental retardation and the G-1774delG polymorphism or delGCGC haplotype at G-1774delG, C-24T, G1249A and C3972T were observed. Login to comment
67 Responsive (n = 146) Resistant (n = 133) P value Male 79 (54.1%) 77 (57.9%) 0.55 Age (years) 20.7 ± 11.0 21.1 ± 9.1 0.69 Body weight (kg) 49.1 ± 18.5 46.4 ± 20.4 0.25 Onset of epilepsy (years) 5.8 ± 5.0 3.7 ± 4.6 <0.001 Duration of therapy (years) 8.7 ± 4.4 9.6 ± 4.5 0.09 Mental retardation 72(49.3%) 113 (85.0%) <0.001 Seizure typea Partial 95(65.1%) 95(71.4%) 0.38 Generalized 47(32.2%) 33(24.8%) Aetiology Idiopathic 42(28.8%) 8(6.0%) <0.001 Cryptogenic 66(45.2%) 50(37.6%) Symptomatic 38(26.0%) 75(56.4%) Prescribed AEDsb Carbamazepine 64(43.8%) 76(57.1%) 0.031 Phenytoin 6(4.1%) 19(14.3%) 0.003 Phenobarbital 14(9.6%) 24(18.0%) 0.054 Valproic acid 38(26.0%) 47(35.3%) 0.12 Zonisamide 12(8.2%) 22(16.5%) 0.043 Clobazam 17 (11.6%) 44(33.1%) < 0.001 Table 2 Frequency of ABCC2 genotypes and haplotypes in drug-responsive and -resistant epilepsy a P values were determined by Fisher`s exact test for genotype frequencies and 10 000 permutation test for haplotype frequencies. b Haplotype configuration was defined as G-1774delG, C-24T, G1249A and C3972T. Login to comment
69 Variant Responsive (n = 146) Resistant (n = 133) P valuea G-1774delG G/G 77(58.8%) 54(41.2%) 0.08 G/delG 58(45.0%) 71(55.0%) delG/delG 11(57.9%) 8(42.1%) C-24T C/C 93(53.1%) 82(46.9%) 0.81 C/T 47(50.0%) 47(50.0%) T/T 6(60.0%) 4(40.0%) G1249A G/G 104(50.5%) 102(49.5%) 0.25 G/A 35(54.7%) 29(45.3%) A/A 7(77.8%) 2(22.2%) C3972T C/C 89(52.0%) 82(48.0%) 0.66 C/T 48(51.1%) 46(48.9%) T/T 9(64.3%) 5(35.7%) Haplotypesb GCGC 33.2% 32.3% 0.83 delGCGC 25.5% 32.7% 0.049 GTGT 17.7% 18.8% 0.73 GCAC 16.2% 12.0% 0.19 Otherc 7.4% 4.2% - 634 Takayuki Seo et al (2007b) indicated that substrate recognition or transport efficacy by efflux transporters differed between man and mouse for certain AEDs. Login to comment
74 A significant linkage was found among the C-24T, G1249A and C3972T polymorphisms of ABCC2, and the genotypes and haplotypes were reported to influence the expression of ABCC2 mRNA or protein, dispositions of the substrates, and adverse reactions (Naesens et al 2006; Rau et al 2006; de Jong et al 2007; Haenisch et al 2007). Login to comment
95 Table 3 Frequency of ABCC2 genotypes and haplotypes in mental retardation and non-mental retardation groups a P values were determined by Fisher`s exact test for genotype frequencies and 10000 permutation test for haplotype frequencies. b delG carriers vs non-carriers, P = 0.03. c Haplotype configuration was defined as G-1774delG, C-24T, G1249A and C3972T. Login to comment
97 Variant Non-mental retardation (n = 94) Mental retardation (n = 185) P valuea G-1774delGb G/G 53(40.5%) 78(59.5%) 0.08 G/delG 36(27.9%) 93(72.1%) delG/delG 5(26.3%) 14(73.7%) C-24T C/C 58(33.1%) 117(66.9%) 0.55 C/T 31(33.0%) 63(67.0%) T/T 5(50.0%) 5(50.0%) G1249A G/G 66(32.0%) 140(68.0%) 0.54 G/A 25(39.1%) 39(60.9%) A/A 3(33.3%) 6(66.7%) C3972T C/C 58(33.9%) 113(66.1%) 0.13 C/T 28(29.8%) 66(70.2%) T/T 8(57.1%) 6(42.9%) Haplotypesc GCGC 35.5% 31.4% 0.34 delGCGC 22.0% 32.4% 0.009 GTGT 17.9% 18.3% 1.00 GCAC 15.2% 13.8% 0.61 Otherd 9.4% 4.1% - 635 Conclusion This study showed that ABCC2 polymorphisms may not have influenced the AED responsiveness. Login to comment

[hide] Concentration-dependent effects and intracellular ... J Antimicrob Chemother. 2010 May;65(5):906-16. Epub 2010 Mar 17. Janneh O, Bray PG, Jones E, Wyen C, Chiba P, Back DJ, Khoo SH
Concentration-dependent effects and intracellular accumulation of HIV protease inhibitors in cultured CD4 T cells and primary human lymphocytes.
J Antimicrob Chemother. 2010 May;65(5):906-16. Epub 2010 Mar 17., [PMID:20237075]

Abstract [show]
BACKGROUND: The intracellular and plasma concentrations of HIV protease inhibitors (HPIs) vary widely in vivo. It is unclear whether there is a concentration-dependent effect of HPIs such that at increasing concentration they may either block their own efflux (leading to 'autoboosting') or influx (leading to saturability/decreased intracellular accumulation). METHOD: The effects of various concentrations (0-30 microM) of lopinavir, saquinavir, ritonavir and atazanavir on the accumulation of [(14)C]lopinavir, [(3)H]saquinavir, [(3)H]ritonavir and [(3)H]atazanavir, respectively, were investigated in CEM(parental), CEM(VBL) [P-glycoprotein (ABCB1) overexpressing], CEM(E1000) (MRP1 overexpressing) and in peripheral blood mononuclear cells (PBMCs). We also investigated the effects of inhibitors of ABCB1/ABCG2 (tariquidar), ABCC (MK571) and ABCC1/2 (frusemide), singly and in combination with HPIs, on cellular accumulation. RESULTS: In all the cell lines, with increasing concentration of lopinavir, saquinavir and ritonavir, there was a significant increase in the cellular accumulation of [(14)C]lopinavir, [(3)H]saquinavir and [(3)H]ritonavir. Tariquidar, MK571 and frusemide (alone and in combination with lopinavir, saquinavir and ritonavir) significantly increased the accumulation of [(14)C]lopinavir, [(3)H]saquinavir and [(3)H]ritonavir. Ritonavir (alone or in combination with tariquidar) decreased the intracellular accumulation of [(3)H]ritonavir in PBMCs. Atazanavir decreased the accumulation of [(3)H]atazanavir in a concentration-dependent manner in all of the cells tested. CONCLUSIONS: There are complex and variable drug-specific rather than class-specific effects of the HPIs on their own accumulation.

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21 For example, despite some of the HPIs, e.g. lopinavir, being a substrate for ABCB1 and ABCC,12,19 an earlier retrospective study of HIV-infected patients under antiretroviral therapy found no influence of the ABCB1 C3435T polymorphism on the plasma and peripheral blood mononuclear cell (PBMC) levels of lopinavir (or the non-nucleoside reverse transcriptase inhibitor, efavirenz)20,21 even though polymorphisms at the ABCB1 C3435T and G2677T/ A, MRP1 (ABCC1) C218T and G2168A and MRP2 (ABCC2) G1249A have been associated with alterations in ABCB1, ABCC1 and ABCC2 activity.22 - 26 However, some studies found no association between the concentrations of saquinavir (alone or when boosted with ritonavir), atazanavir or lopinavir and polymorphisms in ABCB1 C3435T and G2677T/A.27,28 Furthermore, recent studies on three common exonic ABCB1 polymorphisms, C1236T, G2677T/A and C3435T, showed that these are poor predictors of the concentrations of lopinavir and ritonavir in saliva, semen and plasma.29 However, there is evidence of some association between G4544A polymorphism in ABCC2 and higher accumulation of lopinavir in PBMCs of HIV-treated patients.21 Similar studies on 74 HIV-infected patients showed significantly higher plasma levels of atazanavir in patients with genotype CC than those with CT or TT for polymorphism at the ABCB1 C3435T.30 Studies in cultured cells showed that the permeability of amprenavir, indinavir, lopinavir and ritonavir was greater in ABCB1 (G1199A) cells than in ABCB1 wt cells, suggesting that ABCB1 G1199A polymorphism may impact on the systemic bioavailability of HPIs.12 Clearly if inter-individual differences in the bioavailability of HPIs is caused by genetic variants of ABCB1, ABCC1 and ABCC2, this may have a profound effect on the pharmacokinetics and pharmacodynamics of substrate drugs. Login to comment
120 This is because being efficient inhibitors, substrates and inducers of some drug efflux proteins and drug metabolizing enzymes,9,46,47,51-53,60-65 there is a complex interaction between HPIs and drug efflux/influx transporters and enzymes, especially if the patients are on other medications.66-69 Indeed alterations in ABCB1 and ABCC2 activity have been associated with single nucleotide polymorphisms in ABCB1 (C3435T and G2677T/A), ABCC1 and ABCC2 (G1249A).22-26 While some studies showed no association between the exposure of HPIs and polymorphisms in ABCB1 C3435T, C1236T and G2677T/A,27 -29 some in vitro and in vivo studies found some association between G4544A and G1199A polymorphisms in ABCC2 and ABCB1, respectively and higher accumulation of some HPIs,12,21,30 suggesting that these polymorphisms may impact on the systemic bioavailability of various HPIs that are substrates of ABCB1 and ABCC2. 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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207 Influence of Genetic Polymorphisms of Drug Transporters and Metabolizing Enzymes on Mycophenolic Acid Pharmacokinetics Population Investigated Polymorphisms Findings References 95 de novo kidney transplant recipients receiving MMF/TAC/ steroids UGT1A9 C-2152T, T-275A - 86 MRP2C-24T, C3972T (CC, CT, TT) Lower MPA AUC0-12* MRP2 G-1549A, G-1023A, A-1019G, G1249A - 95 de novo kidney transplant recipients receiving MMF/TAC/ steroids UGT1A9 T-275A, C-2152T Lower MPA C0 and AUC0-12 95 40 renal transplant recipients receiving MMF/CSA UGT1A9 C-440T, T-331C Lower/higher MPA AUC0-12 96 (Caucasian) ABCC2-C-24T, G1249A - 80 renal transplant recipients receiving MMF/TAC UGT1A7 (*1/*1, *1/*2, *1/*3, *2/*3, *3/*3) No difference in MPA AUC0-12 98 (Japanese) UGT1A9 intronic 1399 (CC, CT, TT) 92 renal transplant recipients receiving MMF/SRL UGT2B7 G-842A (GG, GA, AA) Higher Acyl-MPA AUC0-9 † 99 (n ϭ 40), TAC/MMF (n ϭ 24), CsA/ MMF, (n ϭ 28) 72 renal transplant recipients receiving MMF/TAC UGT1A8 (*1/*1, *1/*2, *2/*2) No difference in MPA AUC0-12 100 (Japanese) 87 renal transplant recipients receiving MMF/TAC OATP/SLCO1B1 (*1/*1, *1/*3, *3/*3) No difference in MPA AUC0-12 103 (Japanese) ABCC2 C-24T (CC, CT, TT) No difference in MPA AUC0-12 MMF, mycophenolate mofetil; TAC, tacrolimus; CsA, cyclosporine; SRL, sirolimus; MPA, mycophenolic acid; AUC, area under the concentration-time curve; C0, trough concentrations; -, no effect. Login to comment
206 Influence of Genetic Polymorphisms of Drug Transporters and Metabolizing Enzymes on Mycophenolic Acid Pharmacokinetics Population Investigated Polymorphisms Findings References 95 de novo kidney transplant recipients receiving MMF/TAC/ steroids UGT1A9 C-2152T, T-275A - 86 MRP2C-24T, C3972T (CC, CT, TT) Lower MPA AUC0-12* MRP2 G-1549A, G-1023A, A-1019G, G1249A - 95 de novo kidney transplant recipients receiving MMF/TAC/ steroids UGT1A9 T-275A, C-2152T Lower MPA C0 and AUC0-12 95 40 renal transplant recipients receiving MMF/CSA UGT1A9 C-440T, T-331C Lower/higher MPA AUC0-12 96 (Caucasian) ABCC2-C-24T, G1249A - 80 renal transplant recipients receiving MMF/TAC UGT1A7 (*1/*1, *1/*2, *1/*3, *2/*3, *3/*3) No difference in MPA AUC0-12 98 (Japanese) UGT1A9 intronic 1399 (CC, CT, TT) 92 renal transplant recipients receiving MMF/SRL UGT2B7 G-842A (GG, GA, AA) Higher Acyl-MPA AUC0-9 ߤ 99 (n afd; 40), TAC/MMF (n afd; 24), CsA/ MMF, (n afd; 28) 72 renal transplant recipients receiving MMF/TAC UGT1A8 (*1/*1, *1/*2, *2/*2) No difference in MPA AUC0-12 100 (Japanese) 87 renal transplant recipients receiving MMF/TAC OATP/SLCO1B1 (*1/*1, *1/*3, *3/*3) No difference in MPA AUC0-12 103 (Japanese) ABCC2 C-24T (CC, CT, TT) No difference in MPA AUC0-12 MMF, mycophenolate mofetil; TAC, tacrolimus; CsA, cyclosporine; SRL, sirolimus; MPA, mycophenolic acid; AUC, area under the concentration-time curve; C0, trough concentrations; -, no effect. Login to comment

[hide] ABCB1 C3435T genetic polymorphism on population ph... Clin Ther. 2012 Aug;34(8):1816-26. Epub 2012 Jul 13. Kim IW, Yun HY, Choi B, Han N, Park SY, Lee ES, Oh JM
ABCB1 C3435T genetic polymorphism on population pharmacokinetics of methotrexate after hematopoietic stem cell transplantation in Korean patients: a prospective analysis.
Clin Ther. 2012 Aug;34(8):1816-26. Epub 2012 Jul 13., [PMID:22796246]

Abstract [show]
BACKGROUND: Methotrexate (MTX) is often used to prevent graft-versus-host disease (GVHD) after allogeneic hematopoietic stem cell transplantation (HSCT). However, MTX has great pharmacokinetic variability and its use can result in fatal complications and/or infections after HSCT. OBJECTIVES: The purposes of this study were to build a population pharmacokinetic model of MTX treatment in Korean patients who have undergone HSCT and to identify covariates, including genetic polymorphisms, that affect the pharmacokinetic properties of MTX. METHODS: Clinical characteristics and MTX concentration data for 20 post-HSCT patients were collected. For each patient, ABCB1, ABCC2, ATIC, GGH, MTHFR, and TYMS genotyping was performed. Population pharmacokinetic analysis was performed using the NONMEM program. Analysis of MTX pharmacokinetic properties was accomplished using a 2-compartment pharmacokinetic model that incorporated first-order conditional estimation methods with interaction. The effects of a variety of demographic and genetic factors on MTX disposition were investigated. RESULTS: The study population consisted of 12 men (60%) and 8 women (40%). Median age and body weight were 28 years (range, 18-49 years) and 55.6 kg (range, 44.8-80.8 kg), respectively. Within the study population, the estimated mean MTX clearance (CL) was 7.08 L/h, whereas the mean central compartment volume (V(1)) of MTX distribution was 19.4 L. MTX CL was significantly affected by glomerular filtration rate (GFR), penicillin use, and the ABCB1 3435 genotype. Interindividual variabilities for CL and V(1) were 21.6% and 73.3%. A 10-mL/min GFR increase was associated with a 32% increase in mean MTX CL, whereas penicillin use was associated with a decrease in MTX CL of 61%. MTX CL was significantly greater (by approximately 21%) in patients with the ABCB1 3435 CC and CT genotype than in those with the ABCB1 3435 TT genotype (P < 0.001). CONCLUSIONS: There was great interindividual variation in MTX pharmacokinetic properties in patients who had undergone HSCT. GFR, concurrent penicillin use, and the presence of the ABCB1 3435 C<T genotypes significantly affected MTX CL. The MTX population pharmacokinetic model developed here may provide useful information for individualizing MTX therapy after HSCT.

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128 Minor Allele Frequency P* ABCB1 G2677T/A rs2032582 0.488 0.293 ABCB1 C3435T rs1045642 0.615 0.575 ABCC2 C-24T rs717620 0.439 0.909 ABCC2 G1249A rs2273697 0.139 0.717 ATIC C347G rs2372536 0.349 0.987 GGH C-401T rs3758149 0.375 0.371 MTHFR C677T rs1801133 0.495 0.964 MTHFR A1298C rs1801131 0.180 0.619 TYMS TSER 2R/3R rs699517 0.399 0.585 *Derived from ␹2 test (Hardy-Weinberg equilibrium). Login to comment
125 Minor Allele Frequency P* ABCB1 G2677T/A rs2032582 0.488 0.293 ABCB1 C3435T rs1045642 0.615 0.575 ABCC2 C-24T rs717620 0.439 0.909 ABCC2 G1249A rs2273697 0.139 0.717 ATIC C347G rs2372536 0.349 0.987 GGH C-401T rs3758149 0.375 0.371 MTHFR C677T rs1801133 0.495 0.964 MTHFR A1298C rs1801131 0.180 0.619 TYMS TSER 2R/3R rs699517 0.399 0.585 *Derived from ই2 test (Hardy-Weinberg equilibrium). Login to comment

[hide] Common variants in ABCB1, ABCC2 and ABCG2 genes an... Gynecol Oncol. 2012 Mar;124(3):575-81. Epub 2011 Nov 21. Tian C, Ambrosone CB, Darcy KM, Krivak TC, Armstrong DK, Bookman MA, Davis W, Zhao H, Moysich K, Gallion H, DeLoia JA
Common variants in ABCB1, ABCC2 and ABCG2 genes and clinical outcomes among women with advanced stage ovarian cancer treated with platinum and taxane-based chemotherapy: a Gynecologic Oncology Group study.
Gynecol Oncol. 2012 Mar;124(3):575-81. Epub 2011 Nov 21., [PMID:22112610]

Abstract [show]
PURPOSE: Efflux transporters of the ATP-binding cassette (ABC) family are major determinants of chemoresistance in tumor cells. This study examined associations between functional variants in ABCB1, ABCC2 and ABCG2 genes and clinical outcomes in patients with epithelial ovarian/primary peritoneal cancer (EOC/PPC) following platinum and taxane-based chemotherapy. METHODS: Sequenom iPLEXTMGOLD Assay and MALDI-TOF platform were used to genotype the non-synonymous G2677T/A (rs2032582; encoding Ala893Ser/Thr) and synonymous C3435T (rs1045642; encoding Ile1145Ile) variants in ABCB1, the non-synonymous G1249A variant in ABCC2 (rs2273697; encoding Val417Ile), and the non-synonymous C421A variant in ABCG2 (rs2231142; encoding Q141K, Gln141Lys) in normal DNA from up to 511 women in Gynecologic Oncology Group (GOG) phase III trials, GOG-172 or GOG-182. Progression-free survival (PFS) and overall survival (OS) were analyzed in relation to genetic polymorphisms using Kaplan-Meier and Cox proportional hazards model. RESULTS: The C421A variant (CA+AA versus CC) in ABCG2 was associated with a 6-month longer median PFS (22.7 versus 16.8 months, p=0.041). In multivariate analysis, patients with variant genotypes were at a reduced risk of disease progression (hazard ratio [HR]=0.75, 95% confidence interval [CI]=0.59-0.96, p=0.022). The association between C421A and OS was not statistically significant (HR=0.88, 95% CI=0.67-1.15, p=0.356). None of the other variants measured in either ABCB1 or ABCC2 was associated with PFS or OS. CONCLUSION: The C421A variant in ABCG2, previously shown to be associated with enhanced protein degradation and drug sensitivity, was associated with longer PFS in advanced stage EOC/PPC patents treated with platinum+taxane-based chemotherapy. This finding requires further validation.

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4 Sequenom iPLEXTMGOLD Assay and MALDI-TOF platform were used to genotype the non-synonymous G2677T/A (rs2032582; encoding Ala893Ser/Thr) and synonymous C3435T (rs1045642; encoding Ile1145Ile) variants in ABCB1, the non-synonymous G1249A variant in ABCC2 (rs2273697; encoding Val417Ile), and the non-synonymous C421A variant in ABCG2 (rs2231142; encoding Q141K, Gln141Lys) in normal DNA from up to 511 women in Gynecologic Oncology Group (GOG) phase III trials, GOG-172 or GOG-182. Login to comment
57 Sequenom iPLEXTMGOLD Assay and MALDI-TOF platform were used to genotype the G2677T/ A (rs2032582) and C3435T (rs1045642) polymorphisms in ABCB1, the G1249A polymorphism in ABCC2 (rs2273697), and the C421A polymorphism in ABCG2 (rs2231142) in normal DNA as described previously [28]. Login to comment
84 (%) PFS OS HR 95% CI P value HR 95% CI P value ABCB1 (G2677T/A) GG 165 (32.7) Referent Referent GT+GA 259 (51.4) 0.98 0.79-1.22 0.856 0.88 0.69-1.11 0.271 TT+TA 80 (15.9) 1.02 0.76-1.38 0.877 0.93 0.67-1.29 0.663 GT+G A+TT+TA 339 (67.3) 0.99 0.81-1.22 0.924 0.89 0.71-1.11 0.299 ABCB1 (C3435T) CC 127 (25.8) Referent Referent CT 266 (54.1) 1.11 0.88-1.40 0.399 1.00 0.77-1.30 0.981 TT 99 (20.1) 0.98 0.73-1.32 0.908 0.88 0.64-1.23 0.454 CT+TT 365 (74.2) 1.07 0.86-1.34 0.550 0.97 0.76-1.24 0.803 ABCC2 (G1249A) GG 313 (61.7) Referent Referent GA 167 (32.9) 0.98 0.80-1.20 0.839 0.89 0.71-1.12 0.318 AA 27 (5.3) 1.62 1.06-2.48 0.025 0.86 0.52-1.44 0.572 GA+AA 194 (38.2) 1.04 0.86-1.27 0.692 0.89 0.71-1.11 0.281 ABCG2 (C421A) CC 404 (79.8) Referent Referent CA+AA 102 (20.2) 0.75 0.59-0.96 0.022 0.88 0.67-1.15 0.356 Hazard ratio (HR) with 95% confidence interval (CI) estimated from Cox model adjusted for cell type, stage/residual disease status, and treatment regimen. Login to comment
89 ABCC2 Polymorphism The G1249A polymorphism in ABCC2 was not associated with patient characteristics including race (data not shown). Login to comment
92 The G1249A variant in ABCC2 was not associated with OS (Table 2). Login to comment
103 Kaplan-Meier estimates of progression-free survival (PFS) by the G2677T/A polymorphorism in ABCB1 (a), the C3435T polymorphorism in ABCB1 (b), or the G1249A polymorphorism in ABCC2 (c). Login to comment
143 The G1249A polymorphism encodes Val417Ile, and one study reported that this polymorphism was associated with a higher activity of the intestinal transporter [50]. Login to comment
144 Our study did not demonstrate that the GA+AA genotypes vs GG genotype in the ABGCC2 G1249A polymorphism was associated with worse PFS or OS. Login to comment
146 The G1249A polymorphism was also studied in the ovarian cancer SCOTROC1 trial and found no association with PFS [47]. Login to comment
148 In summary, the present study analyzed common polymorphisms in ABCB1 (G2677T/A; C3435T), ABCC2 (G1249A) and ABCG2 (C421A) in relation to PFS and OS. Login to comment

[hide] Multidrug resistance protein 2 genetic polymorphis... Transplantation. 2006 Oct 27;82(8):1074-84. Naesens M, Kuypers DR, Verbeke K, Vanrenterghem Y
Multidrug resistance protein 2 genetic polymorphisms influence mycophenolic acid exposure in renal allograft recipients.
Transplantation. 2006 Oct 27;82(8):1074-84., [PMID:17060857]

Abstract [show]
BACKGROUND: Mycophenolic acid (MPA) is glucuronidated by uridine diphosphate-glucuronosyltransferases (UGTs) to its pharmacologically inactive 7-O-glucuronide metabolite (MPAG). MPAG is excreted into the bile via the multidrug resistance-associated protein 2 (MRP2/ABCC2), which is essential for enterohepatic (re)circulation (EHC) of MPA(G). METHODS: The objective of this study was to determine the relationship between single nucleotide polymorphisms (SNPs) in the MRP2 (G-1549A, G-1023A, A-1019G, C-24, G1249A, C3972T and G4544A) and UGT1A9 (C-2152T, T-275AandT98C) genes and MPA pharmacokinetics in 95 renal allograft recipients at days 7, 42, 90, and 360 after transplantation. In addition to mycophenolate mofetil, all patients received tacrolimus and corticosteroids as immunosuppression. RESULTS: At day seven after transplantation, in the absence of the MRP2 C-24T SNP, mild liver dysfunction was associated with significantly lower MPA dose-interval exposure and higher MPA oral clearance, while liver dysfunction did not affect MPA pharmacokinetics in patients with the MRP2 C-24T variant. A similar effect is noted for the C-3972T variant, which is in linkage disequilibrium with C-24T. At later time points after transplantation the MRP2 C-24T SNP was associated with significantly higher dose-corrected MPA trough levels. Patients with the MRP2 C-24T variant had significantly more diarrhea in the first year after transplantation. CONCLUSIONS: The MRP2 C-24T and C-3972T polymorphisms protect renal transplant recipients from a decrease in MPA exposure associated with mild liver dysfunction. Furthermore, this study suggests that the C-24T SNP is associated with a lower oral clearance of MPA in steady-state conditions.

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45 The similarly frequent G1249A (exon 10) variant of MRP2 (allelic frequency 12.5-22%), which leads to an amino acid alteration from Val to Ile at position 417, has been associated with a reduced expression of MRP2 in preterm placentas (37). Login to comment
82 150 ␮L of GeneAmp௡ 10ϫ PCR buffer and GeneAmp MgCl2 (Applied Biosystems) were added to the PCR mixture, to a MgCl2 concentration of 1.5 mmol/L for C-24T and G1249A and of 2.0 mmol/L for the other MRP2 SNPs. Login to comment
83 Then 10 ␮L of PCR mixture was added to 5 ␮L of 10 ng/␮L DNA to a final PCR reaction volume of 15 ␮L. PCR conditions were as follows: 12 min at 95°C; 35 cycles of 30 sec at 93°C, 35 sec at 55°C, 30 sec at 72°C; and finally five min at 72°C for the C-24TSNP and 12 min at 95°C. Annealing temperature was respectively 56°C, 60°C, 60°C, 63°C, 58°C, and 58°C for the G-1549A, G-1023A, A-1019G, G1249A, C3972T and G4544A SNP. Login to comment
89 Primers and restriction enzymes used for restriction fragment length polymorphism analysis of MRP2 and UGT1A9 single nucleotide polymorphisms Gene Polymorphism Primers Restriction enzymes MRP2 A-1549G FW 5Ј tgacttgtgaagttgattcagttg 3Ј AccI REV 5Ј aactgatgaagagttaatatccacag 3Ј G-1023A FW 5Ј agcaatttaagtgacagtacaaaagg 3Ј StyI REV 5Ј gtctcaaactccaggcttcaacaatcat 3Ј A-1019G FW 5Ј agcaatttaagtgacagtacaaaagg 3Ј BstF5I REV 5Ј gtctcaaactccaggcttcaacaatcat 3Ј C-24T FW 5Ј ctgttccactttctttgatga 3Ј BbsI REV 5Ј tcttgttggtgaccaccctaa 3Ј G1249A FW 5Ј gggcaaagaagtgtgtggat 3Ј NcoI REV 5Ј acatcaggttcactgtttctccca 3Ј C3972T FW 5Ј aacttacttctcatcttgtctccttgc 3Ј ClaI REV 5Ј ctccacctaccttctccatgctatc 3Ј G4544A FW 5Ј gtaaaacgacggccagtggcctagacttgagatgctgct 3Ј RsAI REV 5Ј aacagctatgaccatgttcacttatccttttttaaaacgtaca 3Ј UGT1A9 C-2152T FW 5Ј ttgagacagagtcgtgctgttt 3Ј MseI REV 5Ј aggtcaaggtgggcgtatc 3Ј T-275A FW 5Ј tcagtgctaagggccttgtt 3Ј XbaI REV 5Ј cctgtgctgcaatgttaagtcta 3Ј T98C FW 5Ј gttctctgatggcttgcaca 3Ј StyI REV 5Ј atgccccctgagaatgagtt 3Ј were compared by the chi-square test for association. Login to comment
107 Testing the influence of the G-1549A, G-1023A, A-1019G, G1249A and G4544A SNP on dose-corrected MPA pharmacokinetics, no significant effect was noted at seven days after transplantation. Login to comment
125 Also similarly to the C-24T SNP, there was no differential effect of liver dysfunction on MPA exposure parameters in patients carrying the C3972T SNP (nϭ49) (MPA AUC0-12/dose 73.9Ϯ50.8 vs. 73.9Ϯ27.6 mg.hr/L.g;PϭNS).Therewerenodifferentialeffectsoftheother MRP2 SNPs (G-1549A, G-1023A, A-1019G, G1249A, G4544A) on MPA pharmacokinetics in patients with or without liver dysfunction (data not shown). Login to comment
137 The other MRP2 SNPs (G-1549A, G-1023A, A-1019 and G1249A) were not associated with differences in MPA pharmacokinetics at these later time points. Login to comment

[hide] Variable expression of MRP2 (ABCC2) in human place... Drug Metab Dispos. 2005 Jul;33(7):896-904. Epub 2005 Apr 8. Meyer zu Schwabedissen HE, Jedlitschky G, Gratz M, Haenisch S, Linnemann K, Fusch C, Cascorbi I, Kroemer HK
Variable expression of MRP2 (ABCC2) in human placenta: influence of gestational age and cellular differentiation.
Drug Metab Dispos. 2005 Jul;33(7):896-904. Epub 2005 Apr 8., [PMID:15821043]

Abstract [show]
MRP2 (ABCC2) is an ATP-binding cassette (ABC)-type membrane protein involved in transport of conjugates of various drugs and endogenous compounds. MRP2 has been localized to the apical membrane of syncytiotrophoblasts and is assumed to be involved in diaplacental transfer of the above substances. It has been shown that both genetic and environmental factors can influence MRP2 expression. We therefore investigated whether gestational age, cellular differentiation, and genetic polymorphisms influence expression and localization of MRP2 in 58 human placenta samples. We detected a significant increase of transporter-mRNA with gestational age by quantitative real-time polymerase chain reaction (MRP2 mRNA/18S rRNA ratio x 1000 +/- S.D.; 0.43 +/- 0.13 in early preterms versus 1.18 +/- 0.44 in late preterms versus 2.1 +/- 0.63 in terms; p < 0.05). MRP2 protein followed the mRNA amount as shown by Western blotting (mean relative band intensity +/- S.D.; 0.56 +/- 0.1 versus 0.7 +/- 0.18 versus 0.92 +/- 0.19; early preterms versus terms p < 0.05). In cultured cytotrophoblasts, MRP2 expression increased with differentiation to syncytiotrophoblasts, with a peak on day 2 (MRP2 mRNA/18S rRNA ratio x 1000 +/- S.D.; 0.06 +/- 0.01 versus 0.88 +/- 0.27 versus 0.24 +/- 0.02 on days 0, 2, and 4). Moreover, we studied the effect of single nucleotide polymorphisms (C-24T; G1249A, and C3972T) in the MRP2 gene on placental expression. One of these polymorphisms (G1249A) resulted in a significantly reduced expression of MRP2 mRNA in preterms. In summary, the expression of MRP2 in human placenta is influenced by gestational age, cellular differentiation, and genetic factors.

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288 In the present paper, we studied the effect of three single nucleotide polymorphisms on the mRNA expression in human placenta, namely, the C-24T, G1249A, and C3972T. Login to comment
293 We found, however, a significant influence of the G1249A missense mutation on mRNA level in the present study. Login to comment

[hide] Single nucleotide polymorphisms in multidrug resis... Adv Drug Deliv Rev. 2002 Nov 18;54(10):1311-31. Suzuki H, Sugiyama Y
Single nucleotide polymorphisms in multidrug resistance associated protein 2 (MRP2/ABCC2): its impact on drug disposition.
Adv Drug Deliv Rev. 2002 Nov 18;54(10):1311-31., [PMID:12406647]

Abstract [show]
Multidrug resistance associated protein 2 (MRP2/ABCC2), expressed on the bile canalicular membrane, plays an important role in the biliary excretion of various kinds of substrates. In addition, MRP2 is also expressed on the apical membrane of epithelial cells such as enterocytes. It is possible that the inter-individual difference in the function of MRP2 affects the drug disposition. In the present article, we will summarize the physiological and pharmacological role of MRP2, particularly focusing on the factors affecting its transport function such as single nucleotide polymorphisms and/or the induction/down regulation of this transporter. Mutations found in patients suffering from the Dubin-Johnson syndrome, along with the amino acid residues which are involved in supporting the transport activity of MRP2, are also summarized.

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134 G1249A is to the PDZ-interacting domain characterized by the associated with amino acid alterations from Val to Ile carboxy-terminal amino acid sequence Ser/Thr-Xat 417, whereas C3972T is the 'silent` mutation at hydrophobic residue, where X represents any amino 1324 (Ile1324Ile) (Fig. 3) [118]. Login to comment
145 The frequently observed SNPs in Japanese amino acid sequence in this region may be involved subjects (C-24T, G1249A and C3972T) were also in the apical targeting, stabilization, and/or in main- found very often in the established cell lines. Login to comment
152 Therefore, it is possible that some SNP them, C-24T (promoter), G1249A (exon 10) and mutations observed at a lower frequency are associ- Fig. 3. Login to comment

[hide] Signatures of recent positive selection at the ATP... Hum Mol Genet. 2007 Jun 1;16(11):1367-80. Epub 2007 Apr 5. Wang Z, Wang J, Tantoso E, Wang B, Tai AY, Ooi LL, Chong SS, Lee CG
Signatures of recent positive selection at the ATP-binding cassette drug transporter superfamily gene loci.
Hum Mol Genet. 2007 Jun 1;16(11):1367-80. Epub 2007 Apr 5., [PMID:17412754]

Abstract [show]
Members of the ATP-binding cassette (ABC) superfamily of transporters have been implicated as major players in drug response. Single nucleotide polymorphisms (SNPs) in the ABC transporter genes may account for variation in drug response between individuals. Given the abundance of SNPs within the human genome, identification of functionally important SNPs is difficult. Here, we utilized signatures of recent positive selection (RPS) to identify SNPs in ABC genes that have potential functional significance by using the long-range-haplotype test to search for signatures of RPS at 18 ABC genes involved in drug transport. From the genotype data of these 18 ABC genes in four populations extracted from the HapMap database, at least one SNP in each of these genes displayed genomic signatures of RPS in at least one population. However, only 13 SNPs in 10 ABC genes from three populations retained statistical significance after Type I error reduction. The functional significance of six of these RPS SNPs, including those that failed multiple testing correction (MTC), has been reported previously. We experimentally confirmed a functional effect for two SNPs, including one that failed to show evidence of RPS after MTC. These observations suggest that Type I error reduction may inadvertently increase Type II error. Although the remaining positively selected SNPs have yet to be functionally validated, our study illustrates the feasibility of using this strategy to identify SNPs within 'adaptive' genes that may confer functional effect, prior to testing their roles in individual/population drug response variation or in complex disease susceptibility.

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96 Ala rs497692 G - - LRH - 0.55 0.95 1.25 ABCC1 50 FR/G-260C 50 FR - rs504348 G - - LRH - - - - ABCC2 E1/C-24T Exon 1 - rs717620 T - - LRH - 20.54 2 1.14 21.46 E10/G1249A Exon 10 Val/Ile rs2273697 A - - LRH - 20.20 2 1.67 -1.32 I19/C-2133T Intron 19 - rs2002042 T - - - LRH 20.80 1.02 2 1.36 I23/G-752A Intron 23 - rs7898096 A - - - MTC - - 2 1.36 E25/G3542T Exon 25 Arg/Leu rs8187692 T - - - MTC 0.22 - 2 2.64 I26/T154C Intron 26 - rs3758395 C LRH - - - 2 1.24 20.57 20.36 I29/A154G Intron 29 - rs3740065 G LRH - - - 2.09 - 0.24 ABCC3 I1/C-3695G Intron 1 - rs719717 C MTC - - - 1.81 0.36 0.52 I30/A-1022C Intron 30 - rs3785911 C MTC - - - 0.96 0.71 0.29 ABCC4 I4/C4542Tc Intron 4 - rs17189481 T - - LRH - - - - ABCC5 I17/T20G Intron 17 - rs4148584 G LRH - - - 2 1.59 20.59 0.83 ABCC6 I30/A-31G Intron 30 - rs212097 A - - LRH - 0.76 0.17 1.02 ABCC7 I10/G377T Intron 10 - rs10487371 T - - - MTC - - 2 3.43 ABCC8 I16/A2575G Intron 16 - rs2237984 G MTC - - - 2.07 1.44 0.27 ABCC9 I27/C-1020G Intron 27 - rs704176 C - - - MTC 0.39 0.09 2.51 I37/C533G Intron 37 - rs829060 C - - - MTC 20.63 20.16 2 2.68 ABCC10 I1/G7A Intron 1 - rs9394952 A MTC - - - 0.90 1.24 1.19 ABCC11 I1/T1541G Intron 1 - rs13332304 T - - LRH LRH - - - I14/A473C Intron14 - rs7206909 A - - LRH LRH - 0.91 1.15 E19/C2436T Exon 19 Phe/Phe rs11866251 C - - MTC - - 1.37 1.15 I23/T-570C Intron 23 - rs11861031 T - - - LRH - 0.54 1.05 ABCC12 I2/C759A Intron 2 - rs8049005 C - - LRH - - 1.19 - ABCC13 50 FR/A-59G 50 FR - rs2822520 G LRH - - - 2 0.36 22.14 20.18 I1/A953C Intron 1 - rs2822522 C LRH - - - 2 1.21 20.90 21.04 ABCG2 E5/C421A Exon 5 Gln/Lys rs2231142 A MTC - - - 2 1.34 20.08 - a LRH represents SNPs that passed the modified long-range-haplotype test only if not corrected for multiple testing; MTC represents SNPs that passed both the modified LRH test and subsequent multiple test correction. Login to comment
192 Two ABCC2 SNPs (e1/C-24T and e10/G1249A) that exhibited RPS when Type I error reduction was not performed (Table 2) have been previously examined in some studies. Login to comment
196 The exonic SNP e10/G1249A, which involves a conservative amino acid change (V471I), was reported to result in decreased ABCC2 mRNA expression in preterm babies (56). Login to comment

[hide] Impact of ABCC2, ABCG2 and SLCO1B1 polymorphisms o... Drug Metab Pharmacokinet. 2012 Sep 25. Oh ES, Kim CO, Cho SK, Park MS, Chung JY
Impact of ABCC2, ABCG2 and SLCO1B1 polymorphisms on the pharmacokinetics of pitavastatin in humans.
Drug Metab Pharmacokinet. 2012 Sep 25., [PMID:23007012]

Abstract [show]
Pitavastatin, a 3-hydroxyl-3-methylglutaryl-coenzyme A reductase inhibitor is distributed to the liver, a target organ of action and excreted mainly into the bile. To investigate the impact of influx (OATP1B1) and efflux (MRP2, BCRP) transporter alleles on its disposition, the pharmacokinetic (PK) parameters were compared among the following groups: SLCO1B1 (*15 carrier and non-carrier), ABCC2 (G1249A, C3972T, C-24T, G1549A, and G1774T), and ABCG2 (C421A) single nucleotide polymorphisms in 45 healthy Korean volunteers. Pitavastatin AUC(last) was higher in individuals carrying the SLCO1B1*15 allele than those not carrying it (144.1+/- 55.3 vs. 84.7 +/- 25.7 hng/mL [mean +/- SD], p= 0.002). The AUC(last) varied significantly according to the ABCC2 C-24T allele (103.4 +/- 42.2, 80.2 +/- 23.8, and 39.0 hng/mL in CC, CT and TT, respectively; p= 0.027). Other SNPs of ABCC2 and ABCG2 were not significant. The effect of these transporters and body weight on the AUC(last) and C(max) were tested, and only SLCO1B1 and ABCC2 C-24T genotypes were significant factors by analysis of covariance. These variants accounted for almost 50% of the variation in AUC(last) and C(max) of pitavastatin. Therefore, ABCC2 C-24T was significantly associated with pitavastatin human PK when the known effect of SLCO1B1*15 was also considered.

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100 The insignificant results of G1249A, C3972T, and G1549A associated with pitavastatin PK could be introduced by the same reason. Login to comment
106 The C-24T polymorphism is located in the 5`-untranslated region (UTR),36) but this variant combined with the G1549A decreased MRP2 promoter activity by 39% in a functional molecular study.20) In a recent report, the genetic variants C-24T, G1249A, and C3972T appeared to influence transport capacity as a haplotype,37) and C3972T is highly linked with C-24T in all ethnic populations.6) Even though G1249A, C3927T, and G1549A did not influence the PK of pitavastatin in our results (Table1), 1249AA group showed about 2.5-fold higher Cmax and systemic exposure compared to the GG or GA. Login to comment

[hide] Gene polymorphisms of ABC transporters are associa... Arch Med Sci. 2012 Sep 8;8(4):659-71. doi: 10.5114/aoms.2012.30290. Zhai X, Wang H, Zhu X, Miao H, Qian X, Li J, Gao Y, Lu F, Wu Y
Gene polymorphisms of ABC transporters are associated with clinical outcomes in children with acute lymphoblastic leukemia.
Arch Med Sci. 2012 Sep 8;8(4):659-71. doi: 10.5114/aoms.2012.30290., [PMID:23056078]

Abstract [show]
INTRODUCTION: Genetic variability affects clinical outcome in pediatric acute lymphocytic leukemia (ALL) patients. Evaluating gene polymorphisms in ABC transporters could help identify relapse risk and predict outcome. MATERIAL AND METHODS: The SNaPshot SNP technique was used to analyze single-nucleotide polymorphisms (SNPs) in the multidrug transporter 1 (MDR1), multidrug resistance associated proteins (MRP1, MRP2) and breast cancer resistance protein (BCRP) genes of 82 pediatric ALL patients. The association between the SNPs with risk of all events and death as well as with survival was evaluated by the univariate Cox proportional hazard model. RESULTS: The BCRP G34A SNP was the only SNP significantly associated with ALL. Risk factors included pre-treatment WBC counts and post-treatment peripheral and bone marrow leukemic cell counts. We found no association between MDR1 SNPs with these factors. The BCRP C421A C/A and C/C genotypes were significantly associated with low pre-treatment WBC counts while MRP2 G1249A G/G was significantly associated with low levels of post-treatment peripheral and bone marrow leukemic cells. A combination of C1236T, G1249A and/or G34A SNPs was significantly associated with lower EFS and OS. CONCLUSIONS: Polymorphisms associated with risk of ALL and clinical outcome may be potential biomarkers to predict clinical outcome and improve prognosis in childhood ALL.

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7 The BCRP C421A C/A and C/C genotypes were significantly associated with low pre-treatment WBC counts while MRP2 G1249A G/G was significantly associated with low levels of post-treatment peripheral and bone marrow leukemic cells. Login to comment
8 A combination of C1236T, G1249A and/or G34A SNPs was significantly associated with lower EFS and OS. Login to comment
91 Primer sequences (5'-3') used for PCR Mutation PCR primers Exon MDR1 C3435T F gagcccatcctgtttgactgc 26 rs1045642 R tgtatgttggcctcctttgctg MDR1 G2677T/A F cccatcattgcaatagcaggagt 21 rs2032582 R gcatgaaaaagattgctttgagga MDR1 C1236T F tcagttcctatatcctgtgtctgtgaa 12 rs1128503 R ccacagccactgtttccaacc MRP1 T825C F gtggtagggggctgcatctct 8 rs246221 R aagcctccacctcctcattcg MRP2 C24T F ccagcatgattcctggactgc 1 rs717620 R cgattaaatggttgggatgaaagg MRP2 G1249A F tggctttgtccatgggtccta 10 rs2273697 R gggcatccacagacatcaggt MRP2 C3972T F cactccacctaccttctccatgc 28 rs3740066 R ccagtttaacaactaccaagtgcggta BCRP C421A F gttgtgatgggcactctgacg 5 rs2231142 R tgaccctgttaatccgttcgttt BCRP G34A F ccagatgtcttccagtaatgtcgaa 2 rs2231137 R cgacaaggtagaaagccactcttca leukemia Table III. Login to comment
92 Frequency of SNPs in the patient and control groups Variable Healthy control ALL Value of p (n = 93) (n = 82) T825C exon 8a C/C 21 (24.4%) 24 (32.0%) 0.409 C/T 47 (54.7%) 33 (44.0%) T/T 18 (20.9%) 18 (24.0%) Value of p for HWE 0.382 0.322 C3435T exon 26 C/C 40 (43.0%) 39 (47.6%) 0.775 C/T 40 (43.0%) 34 (41.5%) T/T 13 (14.0%) 9 (11.0%) Value of p for HWE 0.559 0.700 G2677T exon 21a A/A 7 (7.5%) 5 (6.2%) 0.630 G/A 13 (14.0%) 13 (16.0%) G/G 18 (19.4%) 14 (17.3%) G/T 28 (30.1%) 25 (30.9%) T/A 7 (7.5%) 12 (14.8%) T/T 20 (21.5%) 12 (14.8%) Value of p for HWE 0.016 0.883 C1236T exon 12 C/C 18 (19.4%) 16 (19.5%) 0.289 C/T 32 (34.4%) 37 (45.1%) T/T 43 (46.2%) 29 (35.4%) Value of p for HWE 0.013 0.501 C421A exon 5 A/A 8 (8.6%) 8 (9.8%) 0.733 C/A 42 (45.2%) 41 (50.0%) C/C 43 (46.2%) 33 (40.2%) Value of p for HWE 0.614 0.353 G34A exon 2 A/A 11 (11.8%) 4 (4.9%) 0.043* G/A 46 (49.5%) 32 (39.0%) G/G 36 (38.7%) 46 (56.1%) Value of p for HWE 0.523 0.599 C24T exon 1 T/T 6 (6.5%) 3 (3.7%) 0.418 C/T 27 (29.0%) 31 (37.8%) C/C 60 (64.5%) 48 (58.5%) Value of p for HWE 0.232 0.458 G1249A exon 10 A/A 1 (1.1%) 2 (2.4%) 0.823 G/A 17 (18.3%) 15 (18.3%) G/G 75 (80.6%) 65 (79.3%) Value of p for HWE 0.973 0.332 C3972T exon 28 T/T 6 (6.5%) 3 (3.7%) 0.141 C/T 29 (31.2%) 37 (45.1%) C/C 58 (62.4%) 42 (51.2%) Value of p for HWE 0.371 0.132 aThere were 14 values missing (7 for each group) in T825C exon 8, and one value missing in G2677T exon 21 in the patient group. Login to comment
99 Patients with the MRP2 G1249A polymorphism of the A/A genotype had a significantly higher risk of all events and a significantly higher risk of death compared to those with the G/G genotype (hazard ratios of 8.27, p = 0.006, and 13.07, p = 0.001, respectively) (Table IV). Login to comment
100 Effect of SNP combinations on EFS and OS Based on our data showing a significantly higher risk of all events and death in 1) children with MDR1 G2677 T/A (G/G, G/A or A/A genotypes); 2) children with MDR1 C1236T of the C/C genotype; 3) children with MRP-2 G1249A of the A/A genotype; and 4) the association of BCRP G34A of the A/A genotype with ALL, we evaluated the effect of different combinations of these 4 polymorphisms on event-free survival (EFS) and overall survival (OS). Login to comment
109 The MRP2 G1249A SNP was significantly associated with post-treatment peripheral leukemic cell counts and bone marrow leukemic cell counts. Login to comment
112 G2677T/A exon21 G/G+G/A+A/A 3.15 (1.16, 8.57) 0.025* 2.62 (0.85, 8.07) 0.093 G/T+T/T +T/A - - C1236T exon 12 T/T - - C/T 3.04 (0.81, 11.35) 0.099 1.81 (0.45, 7.29) 0.406 C/C 4.63 (1.08, 19.80) 0.039* 3.47 (0.76, 15.76) 0.108 C421A exon 5 C/C - - C/A 0.68 (0.25, 1.89) 0.460 0.97 (0.30, 3.20) 0.963 A/A 1.05 (0.22, 4.96) 0.949 1.71 (0.33, 8.85) 0.520 G34A exon 2 G/G - - G/A 0.86 (0.31, 2.44) 0.781 1.10 (0.33, 3.63) 0.879 A/A 4.19 (0.89, 19.63) 0.069 4.80 (0.96, 23.99) 0.056 C24T exon 1 C/C - - C/T 1.30 (0.50, 3.36) 0.592 0.61 (0.19, 2.00) 0.419 T/T NA NA G1249A exon 10 G/G - - G/A NA NA A/A 8.27 (1.82, 37.59) 0.006* 13.07 (2.68, 63.64) 0.001* C3972T exon 28 C/C - - C/T 0.94 (0.36, 2.43) 0.894 0.45 (0.14, 1.47) 0.188 T/T NA NA Post-treatment characteristics D8 peripheral ≤ 1000 - - leukemic cells [/μl] > 1000 3.30 (0.75, 14.54) 0.115 5.12 (1.11, 23.49) 0.036* D15 bone marrow < 5 - - leukemic cells [%] 5-25 1.76 (0.48, 6.44) 0.390 1.76 (0.36, 8.52) 0.482 > 25 3.57 (1.12, 11.38) 0.032* 5.20 (1.52, 17.82) 0.009* D33 bone marrow < 5 - - leukemic cells [%] 5-25 27.17 (2.82, 261.57) 0.004* 41.55 (3.76, 459.28) 0.002* > 25 3.03 (0.38, 23.90) 0.293 4.11 (0.51, 33.27) 0.185 Variable Risk of all events Risk of death HR (95% CI) Value of p HR (95% CI) Value of p NA - the corresponding odds ratio was not applicable due to zero or small count. Login to comment
114 Both children with G1249A in A/A had over 25% bone marrow leukemic cells on day 15 after treatment. Login to comment
115 Four of the 15 children (26.7%) with G1249A in G/A had over 5% bone marrow leukemic cells on day 15 after treatment, while only 12 of the 65 (18.5%) children with the G/G genotype had over 5% bone marrow leukemic cells on day 15 after treatment (p = 0.023). Login to comment
124 However, the BCRP C421A C/A and C/C genotypes were significantly associated with low pre-treatment WBC counts (< 20 × 109/l), while the MRP2 G1249A G/G genotype was significantly associated with low levels of post-treatment day 8 peripheral leukemic cells and day 15 and day 33 bone marrow leukemic cells. Login to comment
126 Importantly, our data also suggest that a combination of MDR1 C1236T, MRP2 G1249A and/or BCRP G34A SNPs was significantly associated with lower EFS and OS. Login to comment
147 To the best of our knowledge, we are the first to analyze combinations of SNPs and to show that a combination of MDR1 (C1236T), MRP2 (G1249A) and/or the BRCP (G34A) SNPs was associated with a significantly lower EFS and OS in pediatric ALL patients. Login to comment
156 We would like to evaluate the association between the MDR1 C1236T, MRP2 G1249A and/or BCRP G34A SNPs and response to specific chemotherapy regimens in our pediatric ALL patient population. Login to comment
90 Primer sequences (5'-3') used for PCR Mutation PCR primers Exon MDR1 C3435T F gagcccatcctgtttgactgc 26 rs1045642 R tgtatgttggcctcctttgctg MDR1 G2677T/A F cccatcattgcaatagcaggagt 21 rs2032582 R gcatgaaaaagattgctttgagga MDR1 C1236T F tcagttcctatatcctgtgtctgtgaa 12 rs1128503 R ccacagccactgtttccaacc MRP1 T825C F gtggtagggggctgcatctct 8 rs246221 R aagcctccacctcctcattcg MRP2 C24T F ccagcatgattcctggactgc 1 rs717620 R cgattaaatggttgggatgaaagg MRP2 G1249A F tggctttgtccatgggtccta 10 rs2273697 R gggcatccacagacatcaggt MRP2 C3972T F cactccacctaccttctccatgc 28 rs3740066 R ccagtttaacaactaccaagtgcggta BCRP C421A F gttgtgatgggcactctgacg 5 rs2231142 R tgaccctgttaatccgttcgttt BCRP G34A F ccagatgtcttccagtaatgtcgaa 2 rs2231137 R cgacaaggtagaaagccactcttca Table III. Login to comment
98 Patients with the MRP2 G1249A polymorphism of the A/A genotype had a significantly higher risk of all events and a significantly higher risk of death compared to those with the G/G genotype (hazard ratios of 8.27, p = 0.006, and 13.07, p = 0.001, respectively) (Table IV). Login to comment
108 The MRP2 G1249A SNP was significantly associated with post-treatment peripheral leukemic cell counts and bone marrow leukemic cell counts. Login to comment
111 G2677T/A exon21 G/G+G/A+A/A 3.15 (1.16, 8.57) 0.025* 2.62 (0.85, 8.07) 0.093 G/T+T/T +T/A - - C1236T exon 12 T/T - - C/T 3.04 (0.81, 11.35) 0.099 1.81 (0.45, 7.29) 0.406 C/C 4.63 (1.08, 19.80) 0.039* 3.47 (0.76, 15.76) 0.108 C421A exon 5 C/C - - C/A 0.68 (0.25, 1.89) 0.460 0.97 (0.30, 3.20) 0.963 A/A 1.05 (0.22, 4.96) 0.949 1.71 (0.33, 8.85) 0.520 G34A exon 2 G/G - - G/A 0.86 (0.31, 2.44) 0.781 1.10 (0.33, 3.63) 0.879 A/A 4.19 (0.89, 19.63) 0.069 4.80 (0.96, 23.99) 0.056 C24T exon 1 C/C - - C/T 1.30 (0.50, 3.36) 0.592 0.61 (0.19, 2.00) 0.419 T/T NA NA G1249A exon 10 G/G - - G/A NA NA A/A 8.27 (1.82, 37.59) 0.006* 13.07 (2.68, 63.64) 0.001* C3972T exon 28 C/C - - C/T 0.94 (0.36, 2.43) 0.894 0.45 (0.14, 1.47) 0.188 T/T NA NA Post-treatment characteristics D8 peripheral ࣘ 1000 - - leukemic cells [/bc;l] > 1000 3.30 (0.75, 14.54) 0.115 5.12 (1.11, 23.49) 0.036* D15 bone marrow < 5 - - leukemic cells [%] 5-25 1.76 (0.48, 6.44) 0.390 1.76 (0.36, 8.52) 0.482 > 25 3.57 (1.12, 11.38) 0.032* 5.20 (1.52, 17.82) 0.009* D33 bone marrow < 5 - - leukemic cells [%] 5-25 27.17 (2.82, 261.57) 0.004* 41.55 (3.76, 459.28) 0.002* > 25 3.03 (0.38, 23.90) 0.293 4.11 (0.51, 33.27) 0.185 Variable Risk of all events Risk of death HR (95% CI) Value of p HR (95% CI) Value of p NA - the corresponding odds ratio was not applicable due to zero or small count. Login to comment
127 Table VII. The associations between MRP2 SNPs: C24T exon 1, G1249A exon 10, and C3972T exon 28 and pre-treatment WBC counts in day 8 peripheral leukemic cells and in day 15 and day 33 bone marrow leukemic cells Variable C24T exon 1 Value of p G1249A exon 10 Value of p C3972T exon 28 Value of p T/T C/T C/C A/A G/A G/G T/T C/T C/C Pretreatment < 20 1 (33.3%) 20 (64.5%) 33 (68.8%) 0.265 1 (50.0%) 13 (86.7%) 40 (61.5%) 0.109 1 (33.3%) 24 (64.9%) 29 (69.0%) 0.386 WBC [10 9 /l] 20-100 1 (33.3%) 10 (32.3%) 11 (22.9%) 0 (0.0%) 2 (13.3%) 20 (30.8%) 1 (33.3%) 11 (29.7%) 10 (23.8%) > 100 1 (33.3%) 1 (3.2%) 4 (8.3%) 1 (50.0%) 0 (0.0%) 5 (7.7%) 1 (33.3%) 2 (5.4%) 3 (7.1%) Post-treatment D8 peripheral ࣘ 1000 3 (100.0%) 31 (100.0%) 44 (91.7%) 0.270 0 (0.0%) 13 (86.7%) 65 (100.0%) < 0.001 3 (100.0%) 37 (100.0%) 38 (90.5%) 0.243 leukemic cells [/bc;l] > 1000 0 (0.0%) 0 (0.0%) 4 (8.3%) 2 (100.0%) 2 (13.3%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 4 (9.5%) D15 bone marrow < 5 3 (100.0%) 24 (77.4%) 37 (77.1%) 0.845 0 (0.0%) 11 (73.3%) 53 (81.5%) 0.023 3 (100.0%) 30 (81.1%) 31 (73.8%) 0.782 leukemic cells [%] 5-25 0 (0.0%) 3 (9.7%) 7 (14.6%) 0 (0.0%) 3 (20.0%) 7 (10.8%) 0 (0.0%) 3 (8.1%) 7 (16.7%) > 25 0 (0.0%) 4 (12.9%) 4 (8.3%) 2 (100.0%) 1 (6.7%) 5 (7.7%) 0 (0.0%) 4 (10.8%) 4 (9.5%) D33 bone marrow < 5 3 (100.0%) 30 (96.8%) 47 (97.9%) 0.660 1 (50.0%) 15 (100.0%) 64 (98.5%) 0.048 3 (100.0%) 36 (97.3%) 41 (97.6%) 0.741 leukemic cells (%) 5-25 0 (0.0%) 0 (0.0%) 1 (2.1%) 1 (50.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (2.4%) > 25 0 (0.0%) 1 (3.2%) 0 (0.0%) 0 (0.0%) 0 (0.0%) 1 (1.5%) 0 (0.0%) 1 (2.7%) 0 (0.0%) Gene expression profiles have been shown to correlate with morphology, immunophenotype and response to therapy and drug resistance in childhood ALL patients [5, 31].The genetic polymorphisms in MDR1 are thought to influence the expression levels of the P-gp protein, thereby influencing the development of ALL [32]. Login to comment

[hide] Validation of in vitro cell models used in drug me... Toxicol Appl Pharmacol. 2006 Feb 15;211(1):1-10. Epub 2005 Jun 21. Brandon EF, Bosch TM, Deenen MJ, Levink R, van der Wal E, van Meerveld JB, Bijl M, Beijnen JH, Schellens JH, Meijerman I
Validation of in vitro cell models used in drug metabolism and transport studies; genotyping of cytochrome P450, phase II enzymes and drug transporter polymorphisms in the human hepatoma (HepG2), ovarian carcinoma (IGROV-1) and colon carcinoma (CaCo-2, LS180) cell lines.
Toxicol Appl Pharmacol. 2006 Feb 15;211(1):1-10. Epub 2005 Jun 21., [PMID:15975613]

Abstract [show]
Human cell lines are often used for in vitro biotransformation and transport studies of drugs. In vivo, genetic polymorphisms have been identified in drug-metabolizing enzymes and ABC-drug transporters leading to altered enzyme activity, or a change in the inducibility of these enzymes. These genetic polymorphisms could also influence the outcome of studies using human cell lines. Therefore, the aim of our study was to pharmacogenotype four cell lines frequently used in drug metabolism and transport studies, HepG2, IGROV-1, CaCo-2 and LS180, for genetic polymorphisms in biotransformation enzymes and drug transporters. The results indicate that, despite the presence of some genetic polymorphisms, no real effects influencing the activity of metabolizing enzymes or drug transporters in the investigated cell lines are expected. However, this characterization will be an aid in the interpretation of the results of biotransformation and transport studies using these in vitro cell models.

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215 DJS W H H W G1249A ? Login to comment
212 DJS W H H W G1249A ? Login to comment

[hide] MDR-1 and MRP2 Gene Polymorphisms in Mexican Epile... Front Neurol. 2014 Oct 9;5:184. doi: 10.3389/fneur.2014.00184. eCollection 2014. Escalante-Santiago D, Feria-Romero IA, Ribas-Aparicio RM, Rayo-Mares D, Fagiolino P, Vazquez M, Escamilla-Nunez C, Grijalva-Otero I, Lopez-Garcia MA, Orozco-Suarez S
MDR-1 and MRP2 Gene Polymorphisms in Mexican Epileptic Pediatric Patients with Complex Partial Seizures.
Front Neurol. 2014 Oct 9;5:184. doi: 10.3389/fneur.2014.00184. eCollection 2014., [PMID:25346718]

Abstract [show]
Although the Pgp efflux transport protein is overexpressed in resected tissue of patients with epilepsy, the presence of polymorphisms in MDR1/ABCB1 and MRP2/ABCC2 in patients with antiepileptic-drugs resistant epilepsy (ADR) is controversial. The aim of this study was to perform an exploratory study to identify nucleotide changes and search new and reported mutations in patients with ADR and patients with good response (CTR) to antiepileptic drugs (AEDs) in a rigorously selected population. We analyzed 22 samples In Material and Methods, from drug-resistant patients with epilepsy and 7 samples from patients with good response to AEDs. Genomic DNA was obtained from leukocytes. Eleven exons in both genes were genotyped. The concentration of drugs in saliva and plasma was determined. The concentration of valproic acid in saliva was lower in ADR than in CRT. In ABCB1, five reported SNPs and five unreported nucleotide changes were identified; rs2229109 (GA) and rs2032582 (AT and AG) were found only in the ADR. Of six SNPs associated with the ABCC2 that were found in the study population, rs3740066 (TT) and 66744T > A (TG) were found only in the ADR. The strongest risk factor in the ABCB1 gene was identified as the TA genotype of rs2032582, whereas for the ABCC2 gene the strongest risk factor was the T allele of rs3740066. The screening of SNPs in ACBC1 and ABCC2 indicates that the Mexican patients with epilepsy in this study display frequently reported ABCC1 polymorphisms; however, in the study subjects with a higher risk factor for drug resistance, new nucleotide changes were found in the ABCC2 gene. Thus, the population of Mexican patients with AED-resistant epilepsy (ADR) used in this study exhibits genetic variability with respect to those reported in other study populations; however, it is necessary to explore this polymorphism in a larger population of patients with ADR.

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27 The MRP2 transporter protein recognizes CBZ, LTG, and FBM; its most relevant polymorphisms are rs2273697 (G1249A) and rs3740066 (C3972T). Login to comment

[hide] Fetal polymorphisms at the ABCB1-transporter gene ... Eur J Hum Genet. 2013 Dec;21(12):1436-41. doi: 10.1038/ejhg.2013.25. Epub 2013 Feb 27. Omoumi A, Wang Z, Yeow V, Wu-Chou YH, Chen PK, Ruczinski I, Cheng J, Cheah FS, Lee CG, Beaty TH, Chong SS
Fetal polymorphisms at the ABCB1-transporter gene locus are associated with susceptibility to non-syndromic oral cleft malformations.
Eur J Hum Genet. 2013 Dec;21(12):1436-41. doi: 10.1038/ejhg.2013.25. Epub 2013 Feb 27., [PMID:23443032]

Abstract [show]
ATP-binding cassette (ABC) proteins in the placenta regulate fetal exposure to xenobiotics. We hypothesized that functional polymorphisms in ABC genes influence risk for non-syndromic oral clefts (NSOC). Both family-based and case-control studies were undertaken to evaluate the association of nine potentially functional single-nucleotide polymorphisms within four ABC genes with risk of NSOC. Peripheral blood DNA from a total of 150 NSOC case-parent trios from Singapore and Taiwan were genotyped, as was cord blood DNA from 189 normal Chinese neonates used as controls. In trios, significant association was observed between the ABCB1 single-nucleotide polymorphisms and NSOC (P<0.05). Only ABCB1 rs1128503 retained significant association after Bonferroni correction (odds ratio (OR)=2.04; 95% confidence interval (CI)=1.42-2.98), while rs2032582 and rs1045642 showed nominal significance. Association with rs1128503 was replicated in a case-control analysis comparing NSOC probands with controls (OR=1.58; 95% CI=1.12-2.23). A comparison between the mothers of probands and controls showed no evidence of association, suggesting NSOC risk is determined by fetal and not maternal ABCB1 genotype. The two studies produced a combined OR of 1.79 (95% CI=1.38-2.30). The T-allele at rs1128503 was associated with higher risk. This study thus provides evidence that potentially functional polymorphisms in fetal ABCB1 modulate risk for NSOC, presumably through suboptimal exclusion of xenobiotics at the fetal-maternal interface.

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49 Description Association with function or disease phenotype Reference numbers e12/C1236T rs1128503 G412G Increased exposure to irinotecan in cancer patients Altered ABCB1 expression in 3t3 isogenic fibroblasts Lower ABCB1 expression 36 33 34 ABCB1 e21/G2677T e21/G2677A rs2032582 A893S A893T Less placental trophoblast ABCB1 expression in T and A carriers 29 e26/C3435T rs1045642 I1145I Alteration in the rate of translation Lower ABCB1 expression Affects mRNA stability 37 34 38 ABCC1 5`FR/G-260C rs504348 50 UTR Evidence of recent positive selection in European-Americans 39 ABCC2 e1/C-24T rs717620 24C4T Influenced ABCC2 mRNA expression in normal kidney cortex and liver samples but not placenta Evidence of recent positive selection 22,30,39 39 e10/G1249A rs2273697 V471I Decreased ABCC2 mRNA levels in preterm placentas Evidence of recent positive selection 22 39 ABCG2 e5/C421A rs2231142 Q141K Reduced ABCG2 activity Decreased ABCG2 protein level in placenta Evidence of recent positive selection Substrate recognition and/or transport of drugs 40 41 39 42 e2/G34A rs2231137 V12M Reduced ABCG2 activity Substrate recognition and/or transport of drugs 40 42 I9/T-357C rs2054576 Intron Alteration of pre-mRNA splicing 43 volume of 10ml containing 1 ng of genomic DNA, 5 ml 2 PCR master mix buffer (Qiagen), and 0.5 mM of each primer (information of PCR primers are available in Supplementary Table S3). Login to comment
73 n1 n2 Not-transmitted Observed Correcteda OR 95% CI ABCB1 e12/C1236T rs1128503 150 108 T: 92/45 C: 45/92 5.1 10-5 4.6 104 2.04 1.45-2.99 e21/G2677T e21/G2677A rs2032582 150 111 G: 78/91 T: 96/64 A: 23/42 0.008 0.072 1.50b 1.08-2.09 e26/C3435T rs1045642 150 110 C: 56/87 T: 87/56 0.009 0.081 1.55 1.10-2.21 ABCC1 5`FR/G-260C rs504348 150 7 G: 03/04 C: 04/03 0.705 1.33 0.23-9.10 ABCC2 e1/C-24T rs717620 150 76 C: 41/50 T: 50/41 0.345 1.24 0.811.93 e10/G1249A rs2273697 150 53 G: 34/22 A: 22/34 0.107 1.55 0.88-2.77 e5/C421A rs2231142 150 110 C: 70/62 A: 62/70 0.486 1.13 0.79-1.62 ABCG2 e2/G34A rs2231137 150 105 G: 54/71 A: 71/54 0.127 1.32 0.91-1.91 I9/T-357C rs2054576 150 91 T: 59/51 C: 51/59 0.445 1.16 0.78-1.72 Abbreviations: CI, confidence Interval; OR, odds ratio; n1, number of family samples which were successfully genotyped; n2, number families with at least one heterozygote parent. Login to comment

[hide] Population pharmacokinetics analysis of cyclophosp... Eur J Clin Pharmacol. 2013 Aug;69(8):1543-51. doi: 10.1007/s00228-013-1507-7. Epub 2013 Apr 16. Kim IW, Yun HY, Choi B, Han N, Kim MG, Park S, Oh JM
Population pharmacokinetics analysis of cyclophosphamide with genetic effects in patients undergoing hematopoietic stem cell transplantation.
Eur J Clin Pharmacol. 2013 Aug;69(8):1543-51. doi: 10.1007/s00228-013-1507-7. Epub 2013 Apr 16., [PMID:23588565]

Abstract [show]
PURPOSE: To build a population pharmacokinetic (PK) model of cyclophosphamide (CY) and its metabolite, 4-hydroxycyclophosphamide (HCY), in patients undergoing allogeneic haematopoietic stem cell transplantation (HSCT) and to identify covariates, including genetic polymorphisms, which affect CY and HCY PK parameters. METHOD: The study cohort comprised 21 patients undergoing HSCT who received CY intravenously between 2009 and 2011. Clinical characteristics and CY and HCY concentration data were collected for all patients, and ABCB1, ABCC2, GSTA1, GSTM1, GSTP1, GSTT1, CYP2B6, CYP2C19, and CYP3A5 genotyping was performed. A hypothetical enzyme compartment was conducted using the NONMEM program. RESULTS: A population PK analysis showed that the ABCC2 1249 genotype and aspartate aminotransferase levels significantly affected non-induced clearance (CL UI) and induced clearance (CL I) of CY, respectively. The final estimate of the mean CL UI and CL I of CY was 15.5 and 0.683 L/h, respectively, and the mean volume of distribution (V 1) of CY was 88.0 L. The inter-individual variability for CL UI, CL I, and V 1 of CY was 52.8, 200, and 18.0 %, respectively. Additionally, the CL UI of CY was significantly decreased to approximately 51 % in patients with the 1249 GA heterozygous genotype compared to those with the 1249 GG wild-type genotype (p < 0.05). There were only three heterozygous GA variants of ABCC2 1249 in the study patients. CONCLUSIONS: The population PK model developed in this study implies an influence of genetic factors on the clearance of CY. Clearance was moderately reduced in patients with the ABCC2 1249GA heterozygous genotype.

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143 We found that CLUI was associated with the ABCC2 G1249A genotype. ABCC2 has been reported to mediate biliary transport of 4-glutathionylcyclophosphamide [42] but has not been reported to transport CY itself. Login to comment
145 In another study, patients carrying the heterozygous variant alleles of ABCC2 G1249A exhibited higher exposure of acyl mycophenolate phenolic glucuronide than those with the wild-type genotype [43]. Login to comment
177 We demonstrated that carriers of at least one ABCC2 G1249A allele had a decreased CLUI. Login to comment

[hide] Linkage disequilibrium between polymorphisms of AB... PLoS One. 2013 May 23;8(5):e64827. doi: 10.1371/journal.pone.0064827. Print 2013. Subenthiran S, Abdullah NR, Joseph JP, Muniandy PK, Mok BT, Kee CC, Ismail Z, Mohamed Z
Linkage disequilibrium between polymorphisms of ABCB1 and ABCC2 to predict the treatment outcome of Malaysians with complex partial seizures on treatment with carbamazepine mono-therapy at the Kuala Lumpur Hospital.
PLoS One. 2013 May 23;8(5):e64827. doi: 10.1371/journal.pone.0064827. Print 2013., [PMID:23717663]

Abstract [show]
PURPOSE: Carbamazepine (CBZ) is used as the first line of treatment of Complex Partial Seizures (CPS) in the Epilepsy Clinic, Neurology Department of Kuala Lumpur Hospital (KLH). More than 30% of the patients remain drug resistant to CBZ mono-therapy. CBZ is transported by the P-glycoprotein (P-gp). The P-gp encoded by the ABCB1 and ABCC2 genes are expressed in drug resistant patients with epilepsy. A few studies have shown significant association between CBZ resistant epilepsy and Linkage Disequilibrium (LD) with adjacent polymorphisms of these genes. Our study is aimed at determining the correlation between patients' response to CBZ mono-therapy to Single Nucleotide Polymorphisms G2677T and C3435T of the ABCB1 gene as well as G1249A and -24C>T of the ABCC2 gene. METHOD: 314 patients with CPS were recruited from the Neurology Department of the KLH based on stringent inclusion and exclusion criteria, of whom 152 were responders and the other 162 were non-responders. DNA was extracted from their blood samples and Taqman technology for allelic discrimination was performed. Results were described as genotype frequencies. The SHEsis analysis platform was used to calculate linkage disequilibrium index and infer haplotype frequencies. Haploview was used to do permutation test to obtain a corrected p-value. RESULTS: Resistance to treatment with CBZ mono-therapy was significantly associated with the 2677TT and the 3435TT genotypes while it was not significantly associated with the G1249A and -24C>T polymorphisms. The GCGC haplotype combination of the 2677G>T, 3435C>T, 1249G>A and -24C>T respectively was found to be extremely significant (p = 1.10e-20) with good drug response to CBZ mono-therapy. CONCLUSION: Linkage disequilibrium between the 2677G>T, 3435C>T, 1249G>A and -24C>T SNPs may be used as a reliable screening marker to determine the treatment outcome of CBZ mono-therapy with CPS irrespective of race or gender.

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5 Our study is aimed at determining the correlation between patients` response to CBZ mono-therapy to Single Nucleotide Polymorphisms G2677T and C3435T of the ABCB1 gene as well as G1249A and 224C.T of the ABCC2 gene. Login to comment
11 Results: Resistance to treatment with CBZ mono-therapy was significantly associated with the 2677TT and the 3435TT genotypes while it was not significantly associated with the G1249A and 224C.T polymorphisms. Login to comment
136 Genotype frequency (%) *Permuted *Permuted SNP / Genotype Responder Non-responder x2 p ABCB1/ C3435T C/C 35(0.22) 51(0.34) 12.06 0.007 T/T 68(0.42) 36(0.24) C/T 59(0.36) 65(0.43) ABCB1/ G2677T G/G 59(0.36) 144(0.75) 61.70 ,0.001 T/T 57(0.35) 25(0.16) G/T 46(0.28) 13(0.09) ABCC2/ G1249A G/G 120(0.74) 124(0.82) 2.23 0.511 A/A 0(0.00) 1(0.01) G/A 42(0.26) 27(0.18) ABCC2/ 224C.T C/C 110(0.68) 102(0.67) 0.14 0.986 T/T 4(0.03) 6(0.04) C/T 48(0.30) 44(0.29) *1000 permutation applied. Login to comment
140 We found no correlation between the G1249A of the ABCC2 gene and the outcome of treatment of patients with CPS on CBZ monotherapy. This is similar to the findings of the study conducted on German patients [30] and Chinese patients [31]. Login to comment

[hide] Polymorphism of ORM1 is associated with the pharma... PLoS One. 2013 Aug 5;8(8):e70341. doi: 10.1371/journal.pone.0070341. Print 2013. Chen WQ, Shu Y, Li Q, Xu LY, Roederer MW, Fan L, Wu LX, He FZ, Luo JQ, Tan ZR, He YJ, Zhou HH, Chen X, Zhang W
Polymorphism of ORM1 is associated with the pharmacokinetics of telmisartan.
PLoS One. 2013 Aug 5;8(8):e70341. doi: 10.1371/journal.pone.0070341. Print 2013., [PMID:23940561]

Abstract [show]
BACKGROUND: The pharmacokinetics (PKs) and pharmacodynamics (PDs) of telmisartan varies among the individuals, and the main causes remain unknown. The aim of this study was to evaluate the impact of ORM1, as well as ABCC2, ABCB1, ABCG2 and SLCO1B3 polymorphisms, on the disposition of the drug and BP change after taking 40 mg telmisartan in 48 healthy Chinese males. METHOD: A total of 48 healthy males were included in this trial. Every volunteer ingested a single dose of 40 mg telmisartan, and the plasma drug concentration and blood pressure (BP) were measured up to 48 h. RESULT: In this study, the area under the plasma concentration-time curve (AUC) in the heterozygotes of ORM1 113AG was higher than that in the wild-type homozygotes, AUC(0-48) (113AA vs. 113AG, 1,549.18+/-859.84 ng.h/ml vs. 2,313.54+/-1,257.71 ng.h/ml, P = 0.033), AUC(0-infinity) (113AA vs. 113AG, 1,753.13+/-1,060.60 ng.h/ml vs. 2,686.90+/-1,401.87 ng.h/ml, P = 0.016), and the change(%) of the diastolic blood pressure (DBP) from the baseline BP value also showed a significant difference between the ORM1 113AG and 113AA genotypes at 5 h after taking telmisartan (P = 0.026). This study also showed that the allele of ABCC2 C3972T would affected the disposition of telmsiartan and the DBP change significantly after taking the drug. However, the common SNPs of ABCG2 C421, ABCB1 C3435T, and SLCO1B3 T334G showed no impacts on the PKs of telmisartan or BP change(%) in our trial. CONCLUSION: The ORM1 A113G polymorphism was associated with the PKs variability after taking telmsiartan, as well as ABCC2 C3972T. The heterozygotes of ORM1 113AG showed a larger AUC and a notable BP change(%) from the baseline compared with the wild-type. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR-TNC-10000898.

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39 ABCC2 was highly polymorphic, and it was reported that three common SNPs C-24T, G1249A and C3972T [19,25] were in linkage disequilibrium and likes to decrease the transporter function probably by a posttranscriptional modification on transporter protein expression [19,20]. Login to comment
77 The genotypes of ABCC2 C3972T, ABCC2 G1249A, and, SLCO1B3 T334G were determined by a PCR-RFLP procedure as described in previous reports. Login to comment
79 The primers for ABCC2 G1249A were 59-GGGCAAAGAAGTGTGTGGAT-39 (Forward) and 59-TGGGATTACAAGCACCATCA-39 (Reversed) and the endonuclease enzyme was NcoI. Login to comment
81 The Linkage Disequilibrium Analysis The linkage disequilibrium analysis of the ABCC2 variants (C-24T, G1249A and C3972T) was constructed using the online software SHEsis (http://analysis2.bio-x.cn/my Analysis.php). Login to comment
107 The linkage disequilibrium among the ABCC2 single nucleotide polymorphisms (SNPs) was analyzed, and the results showed that the alleles of ABCC2 C3972T was mostly in a linkage with ABCC2 C-24T (D9 = 0.997, r2 = 0.031), and the D9 value was 0.793 and r2 = 0.606 when the analysis tested between the SNPs of ABCC2 G1249A and C-24T. Login to comment
123 In this study, the polymorphisms of ABCC2(G1249A), ABCB1 (C3435T), SLCO1B3 (T334G) and ABCG2 (C421A) had no significant influence on the PKs of telmisartan and the BP change(%) from the baseline after taking telmisartan (Table 3, 4, 5). Login to comment
139 Nucleotide substitution Location Amino Acids MAFa (CHB) MAFa (ASW) MAFa (CEU) MAFb (CHB) ORM1 rs17650 A113G Exon Gln/Arg 0.275[37] N/A N/A 0.208 ABCC2 rs717620 C-24T 59UTR - 0.201 0.035 0.181 0.281 rs3740066 C3972T Exon Ile/Ile 0.267 0.331 N/A 0.250 rs2273697 G1249A Exon Val/Ile 0.106 0.243 0.132 0.083 ABCB1 rs1045642 C3435T Exon Ile/Ile 0.374 0.205 0.571 0.375 SLCO1B3 rs4149117 T334G Exon Ala/Ser 0.266 0.518 0.143 0.354 ABCG2 rs2231142 C421A Exon Gln/Lys 0.292 0.044 0.111 0.219 a data published on hapmap; b, data calculated in this study, N = 48; N/A, no data found in hapmap. Login to comment
153 On the one hand, as ABCC2 C-24T, C3972T, and G1249A SNPs were in a strong linkage disequilibrium, thus the other two SNPs might interfere with C3972T to affect the variability of PKs/PDs. Login to comment
177 Gene SNPs Genotype AUC(0-48)(ng?h/ml) AUC(0-') (ng?h/ml) Cmax(ng/ml) CL/F(l/h) T1/2 (h) ORM1 A113G AA (28) 1,549.186859.84 1,753.1361,060.60 246.876156.93 32.38621.43 15.6365.09 AG (20) 2,313.5461,257.71 2,686.9061,401.87 293.006184.06 18.6368.74 20.01612.81 P VALUE 0.033* 0.016* 0.289 0.355 0.113 ABCC2 C3972T CC (26) 1,871.186817.89 2,090.836952.69 313.326172.05 18.80610.32 15.8364.11 CT (20) 1,289.896506.60 1,526.476626.97 176.486106.47 10.5966.39 20.09613.27 TT (2) 1,973.906135.44 2,057.50697.27 548.22612.93 32.8960.78 12.2663.11 P VALUE 0.031* 0.105 0.001** 0.001** 0.321 CC vs. CT 0.035* 0.105 0.005** 0.008** 0.476 CC vs.TT 0.896 0.964 0.243 0.083 0.237 CT vs. TT 0.311 0.526 0.014* 0.004** 0.147 ABCC2 C-24T CC (24) 1,809.426843.05 2,017.046976.09 306.166182.01 18.37610.92 15.6164.19 CT (21) 1,348.936525.05 1,588.646637.52 191.526112.96 25.10610.75 19.98612.95 TT (3) 2,214.176427.04 2,411.886617.65 467.576139.99 17.2463.89 14.6264.65 P VALUE 0.060 0.161 0.008** 0.005** 0.523 ABCC2 G1249A GG(41) 1597.796667.24 1832.016790.09 256.456156.87 15.3969.41 18.0169.84 GA(6)+AA(1) 1998.4461108.08 1232.576992.12 355.016236.12 21.30614.17 14.0964.01 P VALUE 0.285 0.417 0.296 0.296 0.614 ABCG2 C421A CC (30) 1,579.226713.71 1,800.866797.05 258.146165.95 15.4969.96 17.69610.97 CA (15) 1,679.296719.04 1,840.076798.27 297.906170.29 17.87610.22 16.34611.36 AA (3) 1,943.436921.94 2,459.6861,394.14 186.586133.13 19.5768.94 20.7565.44 P Value 0.669 0.573 0.481 0.540 0.265 ABCB1 C3435T CC (20) 1,606.836646.33 1,791.716814.66 237.236126.55 14.2367.59 15.4865.05 CT (20) 1,673.536789.53 1,920.076849.29 291.526206.17 17.49612.37 18.95612.29 TT (8) 1,598.626913.64 1,846.3061,026.48 274.706165.31 16.4869.92 18.6768.88 P VALUE 0.587 0.317 0.951 0.984 0.076 SLCO1B3 T334G GG (18) 1,702.256740.60 1,877.336806.34 298.076204.22 17.88612.25 15.9064.08 GT (26) 1,574.476755.06 1,829.076896.92 232.816132.75 13.9767.97 18.56611.78 TT (4) 1,704.896797.20 1,914.586939.86 338.566196.27 25.38613.32 17.3168.43 P VALUE 0.793 0.929 0.424 0.307 0.994 Data were shown as mean6SD; *P,0.05; **P,0.01. Login to comment
181 SBP change (%) from the baseline DBP change (%) from the baseline Mauchly`s Time Time*genotype genotype Mauchly`s Time Time*genotype genotype ORM1 A113G 0.004 0.000 0.748 0.770 0.000 0.000 0.258 0.096 ABCC2 C3972T 0.006 0.000 0.262 0.162 0.000 0.000 0.067 0.018* ABCC2 G1249A 0.005 0.000 0.795 0.370 0.000 0.030 0.975 0.144 SLCO1B3 T334G 0.001 0.000 0.842 0.995 0.000 0.000 0.431 0.634 ABCG2 C421A 0.001 0.000 0.300 0.255 0.000 0.000 0.451 0.896 ABCB1 C3435T 0.001 0.000 0.369 0.375 0.000 0.000 0.372 0.241 *P,0.05; ORM1, orosomucoid 1; ABCC2, ATP-binding cassette, sub-family C, member 2; SBP, systolic blood pressure; DBP, diastolic blood pressure; Time, the time point in this study including 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 24, 48 h after taking telmisartan. Login to comment
185 As shown in Table 2, the MAF of ABCC2 C3972T and G1249A, ABCB1 C3435T, SLCO1B3 T334G almost be similar in three main populations. Login to comment

[hide] Interactions between meat intake and genetic varia... Genes Nutr. 2015 Jan;10(1):448. doi: 10.1007/s12263-014-0448-9. Epub 2014 Dec 10. Andersen V, Vogel U
Interactions between meat intake and genetic variation in relation to colorectal cancer.
Genes Nutr. 2015 Jan;10(1):448. doi: 10.1007/s12263-014-0448-9. Epub 2014 Dec 10., [PMID:25491747]

Abstract [show]
Meat intake is associated with the risk of colorectal cancer. The objective of this systematic review was to evaluate interactions between meat intake and genetic variation in order to identify biological pathways involved in meat carcinogenesis. We performed a literature search of PubMed and Embase using "interaction", "meat", "polymorphisms", and "colorectal cancer", and data on meat-gene interactions were extracted. The studies were divided according to whether information on meat intake was collected prospectively or retrospectively. In prospective studies, interactions between meat intake and polymorphisms in PTGS2 (encoding COX-2), ABCB1, IL10, NFKB1, MSH3, XPC (P int = 0.006, 0.01, 0.04, 0.03, 0.002, 0.01, respectively), but not IL1B, HMOX1, ABCC2, ABCG2, NR1I2 (encoding PXR), NR1H2 (encoding LXR), NAT1, NAT2, MSH6, or MLH1 in relation to CRC were found. Interaction between a polymorphism in XPC and meat was found in one prospective and one case-control study; however, the directions of the risk estimates were opposite. Thus, none of the findings were replicated. The results from this systematic review suggest that genetic variation in the inflammatory response and DNA repair pathway is involved in meat-related colorectal carcinogenesis, whereas no support for the involvement of heme and iron from meat or cooking mutagens was found. Further studies assessing interactions between meat intake and genetic variation in relation to CRC in large well-characterised prospective cohorts with relevant meat exposure are warranted.

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60 PRISMA 2009 Flow Diagram Records idenfied through database search (n = 239 ) Screening Included Eligibility Idenficaon Addional records idenfied through other sources (n = 19 ) Records aer removal of duplicates (n = 239 ) Records screened (n = 239) Records excluded (n = 193) Full-text arcles assessed for eligibility (n = 46) Full-text arcles excluded, for various reasons (n = 13) Studies included in qualitave synthesis (n = 33) Fig. 2 Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram of the retrieved studies Table 1 Interactions between meat intake and polymorphisms in relation to the risk of colorectal cancer in prospective cohorts Gene rs-number d N cases N sub-cohort IRR/OR (95 % CI) a P int b Comments c First author Year References Cooking carcinogens and mutagens NAT1 Slow 120 123 4 Chen 1998 Chen et al. (1998) NAT*10 allele Rapid 92 98 0.19 4 Chen et al. (1998) NAT2 Slow 131 125 4 Chen et al. (1998) Rapid 81 96 0.56 4 Chen et al. (1998) NAT2 Slow 107 267 5 Chan 2005 Chan et al. (2005) Rapid 76 476 0.07 5 Chan et al. (2005) NAT1 Slow 0.99 (0.94-1.04) 2, 3, 6 Sorensen 2008 Sorensen et al. (2008) Fast 0.98 (0.90-1.05) [0.40 2, 3, 6 Sorensen et al. (2008) NAT2 Slow 1.00 (0.95-1.06) 2, 3, 6 Sorensen et al. (2008) Fast 0.96 (0.90-1.03) [0.40 2, 3, 6 Sorensen et al. (2008) NAT1 No*10 362 527 7 Nothlings 2009 Nothlings et al. (2009) *10 482 818 0.77 7 Nothlings et al. (2009) NAT2 Slow/med 750 1149 7 Nothlings et al. (2009) Rapid 242 344 0.44 7 Nothlings et al. (2009) NAT1 No*10 362 527 8 Nothlings et al. (2009) *10 482 818 0.93 8 Nothlings et al. (2009) NAT2 Slow/med 750 1,149 8 Nothlings et al. (2009) Rapid 242 344 0.13 8 Nothlings et al. (2009) AHR rs2066853 364 394 0.07 12 Gilsing 2012 Gilsing et al. (2012) UGT1A rs6714486 364 394 0.06 12 Gilsing et al. (2012) rs17868299 364 394 0.05 12 Gilsing et al. (2012) UGT1A rs2011404 364 394 0.08 12 Gilsing et al. (2012) CYP2E1 rs915908 364 394 0.05 12 Gilsing et al. (2012) UGT1A rs6717546 364 394 0.04 12 Gilsing et al. (2012) UGT1A rs12466997 364 394 0.08 12 Gilsing et al. (2012) Arachidonic acid pathway PTGS2 (COX-2) rs689566 A-1195G AA-AG 900 1,686 1.02 (0.98-1.05) 1, 2, 3 Andersen 2013 Andersen et al. (2013b) GG 47 61 1.06 (0.87-1.29) 0.54 1, 2, 3 Andersen et al. (2013b) rs20417 G-765C GG 701 1,256 0.99 (0.95-1.03) 1, 2, 3 Andersen et al. (2013b) GC-CC 235 478 1.08 (1.01-1.15) 0.006 1, 2, 3 Andersen et al. (2013b) rs5275 T8473C TT 430 720 1.04 (0.99-1.09) 1, 2, 3 Andersen et al. (2013b) TC-CC 501 1,018 1.01 (0.96-1.05) 0.29 1, 2, 3 Andersen et al. (2013b) Transport proteins Table 1 continued Gene rs-number d N cases N sub-cohort IRR/OR (95 % CI) a P int b Comments c First author Year References ABCB1 (MDR1) rs1045642 3435 CC 73 118 1.08 (1.00-1.16) 1, 2, 3 Andersen 2009 Andersen et al. (2009) CT-TT 286 647 1.00 (0.95-1.06) 0.02 1, 2, 3 Andersen et al. (2009) rs3789243 Intron 3 GG 81 224 0.95 (0.89-1.02) 1, 2, 3 Andersen et al. (2009) GA-AA 278 541 1.03 (0.98-1.09) 0.01 1, 2, 3 Andersen et al. (2009) ABCG2 (BCRP) rs2231142 C421A CC 296 592 1.02 (0.97-1.08) 1, 2, 3 Andersen et al. (2009) CA-AA 63 173 0.99 (0.91-1.08) 0.40 1, 2, 3 Andersen et al. (2009) ABCC2 (MRP2) rs717620 C-24T CC 260 508 1.02 (0.97-1.07) 1, 2, 3 Andersen 2012 Andersen et al. (2012b) CT-TT 129 280 1.03 (0.95-1.12) 0.72 1, 2, 3 Andersen et al. (2012b) rs2273697 G1249A GG 238 480 1.05 (0.99-1.11) 1, 2, 3 Andersen et al. (2012b) AG-AA 151 308 0.98 (0.91-1.05) 0.10 1, 2, 3 Andersen et al. (2012b) rs3740066 C3972T CC 143 301 1.01 (0.96-1.08) 1, 2, 3 Andersen et al. (2012b) CT-TT 246 487 1.03 (0.97-1.10) 0.69 1, 2, 3 Andersen et al. (2012b) Cytokines IL10 rs1800872 C-592A CC 238 470 1.02 (0.97-1.07) 1, 2, 3, 9 Andersen 2012 Andersen et al. (2012b) AC-AA 140 305 1.02 (0.95-1.11) 0.92 1, 2, 3, 9 Andersen et al. (2012b) rs3024505 CC 268 553 1.02 (0.96-1.08) 1, 2, 3, 9 Andersen et al. (2012b) CT-TT 110 222 1.03 (0.96-1.10) 0.78 1, 2, 3, 9 Andersen et al. (2012b) IL10 rs1800872 C-592A CC 596 1072 1.02 (0.98-1.06) 1, 2, 3 Andersen 2013 Andersen et al. (2013b) AC-AA 353 676 1.00 (0.95-1.06) 0.46 1, 2, 3 Andersen et al. (2013b) rs3024505 CC 648 1,200 1.00 (0.96-1.04) 1, 2, 3 Andersen et al. (2013b) CT-TT 297 565 1.06 (1.00-1.11) 0.04 1, 2, 3 Andersen et al. (2013b) IL1B rs4848306 C-3737T CC 336 560 1.01 (0.96-1.07) 1, 2, 3 Andersen et al. (2013b) CT-TT 605 1,186 1.02 (0.98-1.06) 0.65 1, 2, 3 Andersen et al. (2013b) rs1143623 G-1464C GG 454 925 1.02 (0.97-1.06) 1, 2, 3 Andersen et al. (2013b) GC-CC 492 824 1.02 (0.97-1.07) 0.94 1, 2, 3 Andersen et al. (2013b) rs1143627 T-31C TT 389 773 1.00 (0.96-1.05) 1, 2, 3 Andersen et al. (2013b) TC-CC 557 983 1.03 (0.98-1.07) 0.40 1, 2, 3 Andersen et al. (2013b) Transcription factors NFKB1 rs28362491 -94 ins/del II 122 307 0.96 (0.90-1.04) 1, 2, 3 Andersen 2010 Andersen et al. (2010) ID-DD 261 456 1.03 (0.97-1.08) 0.03 1, 2, 3 Andersen et al. (2010) NR1I2 (PXR) rs1523127 A-24381C AA 131 261 1.04 (0.97-1.12) 1, 2, 3 Andersen et al. (2010) AC-CC 252 502 1.01 (0.95-1.06) 0.20 1, 2, 3 Andersen et al. (2010) rs2276707 C8055T CC 237 448 1.02 (0.96-1.08) 1, 2, 3 Andersen et al. (2010) CT-TT 146 315 1.01 (0.95-1.08) 0.74 1, 2, 3 Andersen et al. (2010) rs6785049 A7635G AA 137 264 1.01 (0.95-1.07) 1, 2, 3 Andersen et al. (2010) Table 1 continued Gene rs-number d N cases N sub-cohort IRR/OR (95 % CI) a P int b Comments c First author Year References AG-GG 246 499 1.02 (0.96-1.08) 0.60 1, 2, 3 Andersen et al. (2010) NR1H2 (LXR) rs1405655 CC 40 76 1.01 (0.93-1.10) 1, 2, 3 Andersen et al. (2010) CT-TT 343 687 1.02 (0.96-1.07) 0.94 1, 2, 3 Andersen et al. (2010) rs2695121 TT 117 227 1.03 (0.96-1.11) 1, 2, 3 Andersen et al. (2010) CT-CC 266 536 1.01 (0.96-1.07) 0.43 1, 2, 3 Andersen et al. (2010) Heme oxygenase Andersen et al. (2011a) HMOX1 (HO-1) rs2071746 A-413T AA 118 260 1.00 (0.93-1.08) 1, 2, 3 Andersen 2011 Andersen et al. (2011a, b) AT-TT 265 503 1.02 (0.97-1.08) 0.55 1, 2, 3 Andersen et al. (2011a, b) DNA repair MSH3 rs184967 R940Q RR 127 8, 10 Berndt 2007 Berndt et al. (2007) RQ-QQ 65 0.08 8, 10 Berndt et al. (2007) MSH3 rs26279 T1036A TT 85 8, 10 Berndt et al. (2007) TA-AA 102 0.002 8, 10 Berndt et al. (2007) MSH6 rs1042821 G39E GG 118 8, 10 Berndt et al. (2007) GE-EE 54 0.29 8, 10 Berndt et al. (2007) MLH1 rs1799977 I219V II 84 8, 10 Berndt et al. (2007) IV-VV 101 0.40 8, 10 Berndt et al. (2007) XPC Rs2228001 d Lys939Gln AA 141 307 1.17 (0.71-1.92) 7, 11 Hansen 2007 Hansen et al. (2007) AC 204 392 1.11 (0.70-1.75) 7, 11 Hansen et al. (2007) CC 50 98 3.70 (1.70-8.04) 0.01 7, 11 Hansen et al. (2007) XPA A23G GG 176 339 1.30 (0.78-2.17) 7, 11 Hansen et al. (2007) AG 187 359 1.41 (0.87-2.26) 7, 11 Hansen et al. (2007) AA 31 90 0.76 (0.34-1.66) 0.37 7, 11 Hansen et al. (2007) ERCC2 (XPD) Rs1799793 d Asp312Asn GG 159 333 1.25 (0.69-2.26) 7, 11 Hansen et al. (2007) AG 191 354 1.25 (0.83-1.87) 7, 11 Hansen et al. (2007) AA 46 108 1.22 (0.61-2.45) 1.00 7, 11 Hansen et al. (2007) XPC Rs2228001 d Lys939Gln AA 141 307 0.63 (0.23-1.69) 8, 11 Hansen et al. (2007) AC 204 392 0.94 (0.41-2.15) 8, 11 Hansen et al. (2007) CC 50 98 3.78 (0.64-22.29) 0.20 8, 11 Hansen et al. (2007) XPA A23G GG 176 339 0.58 (0.23-1.48) 8, 11 Hansen et al. (2007) AG 187 359 1.87 (0.73-4.83) 8, 11 Hansen et al. (2007) AA 31 90 0.31 (0.06-1.64) 0.06 8, 11 Hansen et al. (2007) Data from (Chen et al. 1998; Tiemersma et al. 2002; Sorensen et al. 2008; Chan et al. 2011) have been presented in a previous review (Andersen et al. 2013a, b). Login to comment