ABCMdb

ABCB1 p.Ser893Ala

ClinVar:	c.2677T>G , p.Ser893Ala N , Benign c.2677T>A , p.Ser893Thr N , Benign
Predicted by SNAP2:	A: N (72%), C: N (53%), D: D (80%), E: D (80%), F: D (91%), G: D (71%), H: D (75%), I: D (66%), K: D (80%), L: D (71%), M: D (91%), N: D (91%), P: D (75%), Q: D (75%), R: D (80%), T: D (59%), V: N (53%), W: D (80%), Y: D (75%),
Predicted by PROVEAN:	A: N, C: N, D: D, E: N, F: D, G: N, H: D, I: D, K: N, L: N, M: N, N: D, P: N, Q: N, R: N, T: N, V: N, W: D, Y: D,

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[hide] Clinical pharmacogenetics and potential applicatio... Curr Drug Metab. 2008 Oct;9(8):738-84. Zhou SF, Di YM, Chan E, Du YM, Chow VD, Xue CC, Lai X, Wang JC, Li CG, Tian M, Duan W
Clinical pharmacogenetics and potential application in personalized medicine.
Curr Drug Metab. 2008 Oct;9(8):738-84., [PMID:18855611]

Abstract [show]
The current 'fixed-dosage strategy' approach to medicine, means there is much inter-individual variation in drug response. Pharmacogenetics is the study of how inter-individual variations in the DNA sequence of specific genes affect drug responses. This article will highlight current pharmacogenetic knowledge on important drug metabolizing enzymes, drug transporters and drug targets to understand interindividual variability in drug clearance and responses in clinical practice and potential use in personalized medicine. Polymorphisms in the cytochrome P450 (CYP) family may have had the most impact on the fate of pharmaceutical drugs. CYP2D6, CYP2C19 and CYP2C9 gene polymorphisms and gene duplications account for the most frequent variations in phase I metabolism of drugs since nearly 80% of drugs in use today are metabolised by these enzymes. Approximately 5% of Europeans and 1% of Asians lack CYP2D6 activity, and these individuals are known as poor metabolizers. CYP2C9 is another clinically significant drug metabolising enzyme that demonstrates genetic variants. Studies into CYP2C9 polymorphism have highlighted the importance of the CYP2C9*2 and CYP2C9*3 alleles. Extensive polymorphism also occurs in a majority of Phase II drug metabolizing enzymes. One of the most important polymorphisms is thiopurine S-methyl transferases (TPMT) that catalyzes the S-methylation of thiopurine drugs. With respect to drug transport polymorphism, the most extensively studied drug transporter is P-glycoprotein (P-gp/MDR1), but the current data on the clinical impact is limited. Polymorphisms in drug transporters may change drug's distribution, excretion and response. Recent advances in molecular research have revealed many of the genes that encode drug targets demonstrate genetic polymorphism. These variations, in many cases, have altered the targets sensitivity to the specific drug molecule and thus have a profound effect on drug efficacy and toxicity. For example, the beta (2)-adrenoreceptor, which is encoded by the ADRB2 gene, illustrates a clinically significant genetic variation in drug targets. The variable number tandem repeat polymorphisms in serotonin transporter (SERT/SLC6A4) gene are associated with response to antidepressants. The distribution of the common variant alleles of genes that encode drug metabolizing enzymes, drug transporters and drug targets has been found to vary among different populations. The promise of pharmacogenetics lies in its potential to identify the right drug at the right dose for the right individual. Drugs with a narrow therapeutic index are thought to benefit more from pharmacogenetic studies. For example, warfarin serves as a good practical example of how pharmacogenetics can be utilized prior to commencement of therapy in order to achieve maximum efficacy and minimum toxicity. As such, pharmacogenetics has the potential to achieve optimal quality use of medicines, and to improve the efficacy and safety of both prospective and licensed drugs.

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532 Nucleotide change rs number Amino acid change 49T>C rs28381804 F17L 61A>G rs61615398; rs9282564 N21D 131A>G rs1202183 N44S 178A>C rs41315618 I60L 239C>A rs9282565 A80E 266T>C Rs35810889 M89T 431T>C rs61607171 I144T 502G>A rs61122623 V168I 548A>G rs60419673 N183S 554G>T rs1128501 G185V 781A>G rs36008564 I261V 1199G>A rs2229109 S400N 1696G>A rs28381902 E566K 1777C>T rs28381914 R593C 1778G>A rs56107566 R593H 1795G>A rs2235036 A599T 1837G>T rs57001392 D613Y 1985T>G rs61762047 L662R 2005C>T rs35023033 R669C 2207A>T rs41316450 I736K 2398G>A rs41305517 D800N 2401G>A rs2235039 V801M 2485A>G rs2032581 I829V 2506A>G rs28381967 I836V 2547A>G rs36105130 I849M 2677T>A/G rs2032582 S893A/T 2975G>A rs56849127 S992N 3151C>G rs28401798 P1051A 3188G>C rs2707944 G1063A 3262G>A rs57521326 D1088N 3295A>G rs41309225 K1099E 3320A>C rs55852620 Q1107P 3322T>C rs35730308 W1108R 3410G>T rs41309228 S1137I 3421T>A rs2229107 S1141T 3502A>G rs59241388 K1168E 3669A>T rs41309231 E1223D 3751G>A rs28364274 V1251I 3767C>A r35721439 T1256K Data are from NCBI dbSNP (access date: 2 August 2008). 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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56 In addition to T1236C, T to G transversion at position 2677, which is a missense mutation (Ser to Ala at codon 893), was reported as a natural mutation. Login to comment

[hide] The effects of the human MDR1 genotype on the expr... Clin Pharmacol Ther. 2002 Nov;72(5):572-83. Siegmund W, Ludwig K, Giessmann T, Dazert P, Schroeder E, Sperker B, Warzok R, Kroemer HK, Cascorbi I
The effects of the human MDR1 genotype on the expression of duodenal P-glycoprotein and disposition of the probe drug talinolol.
Clin Pharmacol Ther. 2002 Nov;72(5):572-83., [PMID:12426521]

Abstract [show]
BACKGROUND AND OBJECTIVES: A single-nucleotide polymorphism (SNP) of the human multidrug-resistance gene in wobble position of exon 26 reportedly predicts expression and function of P-glycoprotein in human enterocytes and lymphocytes. Several other allelic variants of MDR1 have been identified, some of which lead to amino acid exchange with as yet unknown functional relevance. METHODS: In healthy white volunteers, we investigated the influence of the hereditary variants C3435T in exon 26 and G2677T/A (Ala893Ser/Thr) in exon 21 and the influence of 7 frequent or putative functional SNPs on duodenal MDR1 messenger ribonucleic acid (n = 32) and immunoreactive P-glycoprotein (n = 37) expression. Moreover, the disposition of the probe drug talinolol was evaluated in 55 subjects after oral administration (100 mg) and in 23 subjects after intravenous administration(30 mg). RESULTS: Duodenal MDR1 messenger ribonucleic acid and P-glycoprotein, as assessed by real-time polymerase chain reaction (TaqMan) and immunostaining, were not influenced by any MDR1 polymorphism studied. Talinolol disposition was not affected by the exon 26 mutation C3435T. In carriers of the TT/TA variants of G2677T/A, the area under the serum concentration-time curve values of oral talinolol were slightly but significantly elevated compared with those in carriers of at least 1 wild-type allele (P <.05, Kruskal-Wallis test; P =.014, Mann-Whitney U test). However, multiple comparisons with combinations of putative functional SNPs did not confirm a significant influence of the MDR1 genotype on talinolol disposition. CONCLUSIONS: We did not identify any influence of MDR1 genotypes on duodenal expression of P-glycoprotein and disposition of talinolol in humans.

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97 In fact, substitution of alanine for serine at position 893 of AdrR MCF-7 cells resulted in a different multidrug-resistance pattern.37 In our study both variants in cDNA position 2677 changed neither duodenal MDR1 mRNA expression nor duodenal content of P-glycoprotein. Login to comment

[hide] An association study of 43 SNPs in 16 candidate ge... Pharmacogenomics J. 2005;5(6):352-8. Thompson JF, Man M, Johnson KJ, Wood LS, Lira ME, Lloyd DB, Banerjee P, Milos PM, Myrand SP, Paulauskis J, Milad MA, Sasiela WJ
An association study of 43 SNPs in 16 candidate genes with atorvastatin response.
Pharmacogenomics J. 2005;5(6):352-8., [PMID:16103896]

Abstract [show]
Variation in individual response to statin therapy has been widely studied for a potential genetic component. Multiple genes have been identified as potential modulators of statin response, but few study findings have replicated. To further examine these associations, 2735 individuals on statin therapy, half on atorvastatin and the other half divided among fluvastatin, lovastatin, pravastatin and simvastatin were genotyped for 43 SNPs in 16 genes that have been implicated in statin response. Associations with low-density lipoprotein cholesterol (LDL-C) lowering, total cholesterol lowering, HDL-C elevation and triglyceride lowering were examined. The only significant associations with LDL-C lowering were found with apoE2 in which carriers of the rare allele who took atorvastatin lowered their LDL-C by 3.5% more than those homozygous for the common allele and with rs2032582 (S893A in ABCB1) in which the two groups of homozygotes differed by 3% in LDL-C lowering. These genetic effects were smaller than those observed with the demographic variables of age and gender. The magnitude of all the differences found is sufficiently small that genetic data from these genes should not influence clinical decisions on statin administration.

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5 The only significant associations with LDL-C lowering were found with apoE2 in which carriers of the rare allele who took atorvastatin lowered their LDL-C by 3.5% more than those homozygous for the common allele and with rs2032582 (S893A in ABCB1) in which the two groups of homozygotes differed by 3% in LDL-C lowering. Login to comment
57 N ¼ 160 Cauc. N ¼ 2454 Hisp. N ¼ 85 Best P Statin Ref. ABC B1 rs2229109 7 86 824 460 Ser400Asn 0 1.2 3.8 1.8 rs2032582 7 86 805 269 Ser893Ala 40.0 89.4 56.7 60.2 rs17149694 7 86 783 310 Ser1141Thr 0 6.2 0.02 0.6 rs1045642 7 86 783 296 Ile1145Ile 50.0 79.0 48.7 50.0 0.023 Atorva 9 ABC G5 rs6720173 2 43 952 052 Gln604Glu 20.8 33.1 16.8 32.5 ABC G8 rs11887534 2 43 977 898 Asp19His 1.4 3.9 5.4 6.6 0.036 Atorva 17 rs4148211 2 43 983 394 Tyr54Cys 29.2 23.1 37.4 32.5 rs4148217 2 44 011 334 Thr400Lys 10.0 24.0 18.1 30.1 rs6544718 2 44 016 576 Val632Ala 6.9 5.9 21.8 18.7 ACE rs4331 17 58 917 784 Ala157Ala 72.2 43.2 43.8 53.0 0.005 Fluva 18 rs4341 17 58 919 722 72.2 43.8 44.0 51.9 0.005 Fluva 18 Apo AI rs670 11 116 213 623 Promoter G/A 20.8 14.4 16.4 21.1 HDLC Prava 19 ApoE rs429358 19 50 103 781 E4 (Cys130Arg) 8.3 29.0 17.7 17.7 0.043 Lova 20 rs7412 19 50 103 919 E2 (Cys176Arg) 2.8 5.0 3.7 1.2 0.01 Atorva 21 19 50 106 239 SNP17 5.6 13.5 7.3 2.4 5 CETP rs1800775 16 55 552 735 CÀ629A 51.6 57.3 48.2 48.1 HDLC Atorva 22 rs708272 16 55 553 789 TaqIB 46.8 25.7 42 42.5 HDLC Atorva 22 Cyp3A4 rs4986910 7 99 003 175 Met445Thr 0 0.9 0.8 0 0.05 Atorva 23 rs2740574 7 99 026 747 AÀ392G 4.7 56.2 3.9 11.4 0.038 Atorva 23 Cyp3A5 rs776746 7 98 915 190 *3 40.6 64.2 7.4 27.2 0.026 24 rs10264272 7 98 907 486 *6, Lys208Lys 1.6 8.7 0.07 3.2 Cyp7A1 rs3808607 8 59 575 478 33.3 56.8 39.3 31.9 0.001 Atorva 25 FDFT1 rs2686196 8 11 697 311 0 0.6 1.4 0.6 HMGCR 5 74 681 677 Asn204Ser 0.0 0.0 0.2 0.0 rs5908 5 74 687 955 Val638Ser 0.0 0.3 1.7 1.2 rs2303151 5 74 691 457 11.1 2.9 4.9 4.8 5 74 691 504 SNP29 0.0 8.5 2.8 2.9 0.003 Prava 5 LDLR rs5925 19 11 091 881 Val653Val, AvaII 40.3 23.1 47.0 56.7 0.05 Fluva 26 rs688 19 11 088 602 Asn591Asn, HincII 36.1 13.0 46.8 46.3 LIPC rs1800588 15 56 510 967 CÀ514T 40.3 49.1 23.1 45.7 0.01 Prava 27 LPL rs1801177 8 19 849 988 Asp9Asn 0 3.9 1.3 1.2 rs268 8 19 857 809 Asn291Ser 0 0.3 1.7 0.6 rs328 8 19 864 004 Ser447X 11.1 8.2 11.2 9.1 OATP C 12 21 185 236 CÀ540T 5.6 3.8 5.0 10.8 12 21 216 983 *2, Phe73Leu 0 0 0.04 0 rs2291073 12 21 217 081 25.0 52.4 8.3 10.0 rs4149036 12 21 219 007 31.9 49.4 21.0 20.5 rs2306283 12 21 221 005 Asn130Asp, *1b 61.1 74.4 40.6 40.9 PK Prava 28 rs11045819 12 21 221 080 Pro155Thr, *4 2.8 9.7 15.8 8.5 rs4149056 12 21 222 816 Val174Ala, *5 8.3 3.8 16.0 14.5 PK Prava 28 12 21 250 200 Gly488Ala, *9 0 5.0 0 0 rs4149080 12 21 268 826 29.2 15.4 17.4 15.2 12 21 283 243 Leu643Phe 1.4 5.3 5.8 3.7 The genes and SNPs examined are listed in columns 1 and 2 with dbSNP identifiers, if available. Login to comment

[hide] Substrate-dependent effects of human ABCB1 coding ... J Pharmacol Exp Ther. 2008 May;325(2):435-42. Epub 2008 Feb 20. Gow JM, Hodges LM, Chinn LW, Kroetz DL
Substrate-dependent effects of human ABCB1 coding polymorphisms.
J Pharmacol Exp Ther. 2008 May;325(2):435-42. Epub 2008 Feb 20., [PMID:18287207]

Abstract [show]
One of the many obstacles to effective drug treatment is the efflux transporter P-glycoprotein (P-gp), which can restrict the plasma and intracellular concentrations of numerous xenobiotics. Variable drug response to P-gp substrates suggests that genetic differences in ABCB1 may affect P-gp transport. The current study examined how ABCB1 variants alter the P-gp-mediated transport of probe substrates in vitro. Nonsynonymous ABCB1 variants and haplotypes with an allele frequency >/=2% were transiently expressed in HEK293T cells, and the transport of calcein acetoxymethyl ester and 4,4-difluoro-4-bora-3a,4a-diaza-s-indacene (BODIPY-FL)-paclitaxel was measured in the absence or presence of the P-gp inhibitor cyclosporin A. The A893S, A893T, and V1251I variants and the N21D/1236C>T/A893S/3435C>T haplotype altered intracellular accumulation compared with reference P-gp in a substrate-dependent manner. It is interesting that certain variants showed altered sensitivity to cyclosporin A inhibition that was also substrate-specific. These functional data demonstrate that nonsynonymous polymorphisms in ABCB1 may selectively alter P-gp transport and drug-drug interactions in a substrate- and inhibitor-dependent manner.

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21 The majority of pharmacogenetic studies for P-gp have focused on two polymorphisms, the synonymous 3435CϾT variation and the nonsynonymous 2677GϾT (S893A) variation (Schwab et al., 2003; Marzolini et al., 2004; Pauli-Magnus and Kroetz, 2004; Salama et al., 2006; Schaefer et al., 2006). Login to comment

[hide] Genetic mutations that prevent pain: implications ... Pharmacogenomics. 2008 Feb;9(2):179-94. Oertel B, Lotsch J
Genetic mutations that prevent pain: implications for future pain medication.
Pharmacogenomics. 2008 Feb;9(2):179-94., [PMID:18370847]

Abstract [show]
Part of the interindividual variability in pain therapy has been associated with genetic polymorphisms. Several genetic variants prevent or at least decrease pain in their carriers as compared with carriers of the respective wild-type or common alleles by impeding the generation, transmission and processing of nociceptive information or by increasing the local availability of active analgesics or their pharmacodynamic effects. Complete prevention of pain has so far been seen in six distinct rare hereditary syndromes, namely the 'channelopathy-associated insensitivity to pain', caused by 13 currently identified variants in the SCN9A gene coding for the alpha-subunit of the voltage-gated sodium channel, and five maladies belonging to the hereditary sensory and autonomic neuropathy (HSAN) I-V syndromes, caused by various mutations in several genes. Reduced pain in the average population has been associated with frequent variants in the micro-opioid receptor gene (OPRM1), catechol-O-methyltransferase gene (COMT), guanosine triphosphate cyclohydrolase 1/dopa-responsive dystonia gene (GCH1), transient receptor potential cation channel, subfamily V, member 1 gene (TRPV1) or the melanocortin-1 receptor gene (MC1R). Duplications/amplifications of the cytochrome P450 2D6 (CYP2D6) gene leading to increased enzyme function may cause intense opioid effects of codeine up to toxicity. The COMT V158M variant has been associated with decreased morphine requirements for analgesia. Inactivating MC1R variants have been associated with increased opioid analgesia of the micro-opioid receptor agonist morphine-6-glucuronide and, in women only, of kappa-opioid agonists. Finally, variants in the P-glycoprotein gene (ABCB1) conferring decreased transporter function have been associated with increased respiratory depressive effects of fentanyl. In summary, a finite number of genetic variants that prevent pain by decreasing nociception or increasing analgesia have been identified. Given the complex biological and psychological nature of pain, we will see in the near future how much of the interindividual variance in pain and analgesia is due to identifiable genetic causes, and to what extent genetics enters clinical pain therapy.

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159 Protein Chromosome Gene Gene position Variant as given in respective publications (reference ID if available) Transcriptional effect Minorallele frequency (%) Ref. MC1R 16q24.3 MC1R Exon 1 451C>T (rs1805007) Arg151-to-Cys (R151C) 2 [78] Exon 1 478C>T (rs1805008) Arg160-to-Trp (R160W) 2 Exon 1 880G>C (rs1805009) Asp294-to-His (D294H) - - 29insA - 2 Exon 1 178G>T (rs1805005) Val60-to-Leu (V60L) - Exon 1 252C>A (rs1805006) Asp84-to-Glu (D84E) - Exon 1 274G>A (rs2228479) Val92-to-Met (V92M) - Exon 1 488G>A (rs885479) Arg163-to-Gln (R163Q) - COMT 22q11.21 COMT Exon 4 472G>A (rs4680) Val158-to-Met (V158M) - [110] CYP2D6 22q13.1 CYP2D6 Exon 5 *3 2549A>del 260X [111] 2 [92] Exon 4 *4 1846G>A 182X [111] 20.7 - *5 chromosomal gene deleted - 2 Exon 3 *6 1707T>del (rs5030655) Trp152-to-Ter (W152X) 0.9 Exon 6 *7 2935A>C (rs5030867) His324-to-Pro (H324P) 0.1 Exon 3 *8 1758G>T 169X [111] 0 - Gene duplication/amplification - 2 Exon 5 *9 2613-5delAGA (rs28371720) Lys281-to-del (K281del) 1.8 Exon 1 *10 100C>T,188C>T (rs1065852) Pro34-to-Ser (P34S) 1.5 Intron 6 *41 2988G>A (rs28371725) - 8.4 [112] ABCB1 7q21.1 ABCB1 Exon 12 1236C>T (rs1128503) Gly412-to-Gly (G412G) 44 [113] Exon 22 2677G>T/A (rs2032582) Ser893-toAla/Thr (S893A/T) 42(T), 0.5(A) Exon 27 3435C>T (rs1045642) Ile1145-to-Ile (I1145I) 50 Variants increasing the metabolism of prodrugs into active analgesics Cytochrome P450 2D6 gene Codeine has a 200-times lower affinity at µ-opioid receptors than morphine [89], and therefore its clinical effects largely depend upon its O-demethylation to morphine [9,10], which is mediated by CYP 2D6 [90], although some of its clinical effects appear to persist independently of morphine formation. Login to comment

[hide] ABCB1 (MDR1) genetic variants are associated with ... Hum Mol Genet. 2008 Jul 15;17(14):2219-27. Epub 2008 Apr 17. Levran O, O'Hara K, Peles E, Li D, Barral S, Ray B, Borg L, Ott J, Adelson M, Kreek MJ
ABCB1 (MDR1) genetic variants are associated with methadone doses required for effective treatment of heroin dependence.
Hum Mol Genet. 2008 Jul 15;17(14):2219-27. Epub 2008 Apr 17., 2008-07-15 [PMID:18424454]

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Methadone is a mu-opioid receptor agonist used for treating opiate dependence. The range of effective methadone doses is broad. Part of the large inter-individual variability in efficacy may be accounted for by genetic factors. Methadone is a substrate of the transporter P-glycoprotein (P-gp) 170 that is encoded by the ABCB1 (MDR1) gene. Thus, P-gp variants may play a role in methadone absorption and distribution. We assessed the association between ABCB1 polymorphisms and methadone dose requirements in 98 methadone-maintained patients. The stabilizing methadone doses were normally distributed with a mean and median dose of 160 mg/day (range 30-280 mg/day). Statistical analysis showed significant difference in genotype frequencies between the 'higher' (>150 mg/day) and 'lower' (< or =150 mg/day) methadone dose groups for single nucleotide polymorphism (SNP) 1236C>T (rs1128503) (experiment-wise P = 0.0325). Furthermore, individuals bearing the 3-locus genotype pattern TT-TT-TT (rs1045642, rs2032582 and rs1128503) have an approximately 5-fold chance of requiring the 'higher' methadone dose, while individuals heterozygous for these three SNPs have an approximately 3-fold chance of stabilizing at the 'lower' methadone dose (point-wise P-value = 0.026). These data suggest that specific ABCB1 variants may have clinical relevance by influencing the methadone dose required to prevent withdrawal symptoms and relapse in this population.

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62 SNP rs2032582 (2677G/T/A) is non-synonymous (Ser893Ala/Thr), SNPs rs1045642 (3435C.T) and rs1128503 (1236C.T) are synonymous and the other six SNPs are intronic. Login to comment
89 ABCB1 single nucleotide polymorphisms (SNPs) analyzed in this study No. SNP Alleles Positiona Amino acid change Exon/intron (i) MAFb Map positionc HWE P-valued 1 rs1045642 C/T 3435 Ile1145Ile 26 0.45 86976581 0.8 2 rs6949448 A/G i25 0.43 86979750 0.7 3 rs2235067 G/A i22 0.07 86987858 0.8 4 rs2032583 C/T i21 0.08 86998497 0.8 5 rs2032582 G/T (A) 2677 Ser893Ala (Thr) 21 0.43 (0.02) 86998554 0.7 6 rs1922242 A/T i16 0.50 87011603 0.3 7 rs1128503 C/T 1236 Gly412Gly 12 0.42 87017537 0.6 8 rs2520464 A/G i4 0.45 87039022 0.6 9 rs3789243 C/T i3 0.49 87058822 0.4 HWE, Hardy-Weinberg equilibrium. Login to comment

[hide] Prediction of irinotecan and 5-fluorouracil toxici... Pharmacogenomics J. 2011 Feb;11(1):61-71. Epub 2010 Feb 23. Glimelius B, Garmo H, Berglund A, Fredriksson LA, Berglund M, Kohnke H, Bystrom P, Sorbye H, Wadelius M
Prediction of irinotecan and 5-fluorouracil toxicity and response in patients with advanced colorectal cancer.
Pharmacogenomics J. 2011 Feb;11(1):61-71. Epub 2010 Feb 23., [PMID:20177420]

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Irinotecan and 5-fluorouracil (5-FU) are used to treat metastatic colorectal cancer. Irinotecan's active metabolite is inactivated by UDP-glucuronosyltransferase 1A1 (UGT1A1), which is deficient in Gilbert's syndrome. Irinotecan and metabolites are transported by P-glycoprotein, encoded by ABCB1. 5-FU targets folate metabolism through inhibition of thymidylate synthase (TYMS). Methylenetetrahydrofolate reductase (MTHFR) generates active folate necessary for haematopoiesis. We retrospectively genotyped 140 Swedish and Norwegian irinotecan and 5-FU-treated colorectal cancer patients from the Nordic VI clinical trial for selected variants of UGT1A1, ABCB1, TYMS and MTHFR. We found an increased risk of clinically relevant early toxicity in patients carrying the ABCB1 3435 T/T genotype, Odds ratio (OR)=3.79 (95% confidence interval (CI)=1.09-13.2), and in patients carrying the UGT1A1(*)28/(*)28 genotype, OR=4.43 (95% CI=1.30-15.2). Patients with UGT1A1(*)28/(*)28 had an especially high risk of neutropenia, OR=6.87 (95% CI=1.70-27.7). Patients who had reacted with toxicity during the first two cycles were in total treated with fewer cycles (P<0.001), and less often responded to treatment (P<0.001). Genetic variation in ABCB1 was associated with both early toxicity and lower response to treatment. Carriers of the ABCB1 1236T-2677T-3435T haplotype responded to treatment less frequently (43 vs 67%, P=0.027), and survived shorter time, OR=1.56 (95% CI=1.01-2.45).

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63 Genotyping of ABCB1 c.2677G4T/A (rs2032582), which leads to a change in amino acid 893 from serine to alanine or threonine, was performed according to Saito et al.44 Allelic discrimination of the synonymous ABCB1 polymorphisms c.1236C4T (rs1128503) and c.3435C4T (rs1045642) was performed using TaqMan SNP Genotyping Assay kits containing primers and probes (C__7586662_10 and C__7586657_1, Applied Biosystems). Login to comment

[hide] Very important pharmacogene summary: ABCB1 (MDR1, ... Pharmacogenet Genomics. 2011 Mar;21(3):152-61. Hodges LM, Markova SM, Chinn LW, Gow JM, Kroetz DL, Klein TE, Altman RB
Very important pharmacogene summary: ABCB1 (MDR1, P-glycoprotein).
Pharmacogenet Genomics. 2011 Mar;21(3):152-61., [PMID:20216335]

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106 The three most common SNPs in the protein coding region are rs1128503 (1236T > C, Gly412Gly), rs2032582 (2677T > G/A, Ser893Ala/Thr), and rs1045642 (3435T > C, Ile1145Ile) [125], according to the National Center for Biotechnology Information build 130 of dbSNP. Login to comment
111 Rs2032582 (2677T > G/A, mRNA 3095T > G/A, Ser893Ala/Thr) The triallelic SNP, rs2032582 (2677T > G/A, Ser893Ala/ Thr), has been well studied because it is a common amino acid change in P-gp. Login to comment

[hide] Temozolomide-induced severe myelosuppression: anal... Anticancer Drugs. 2011 Jan;22(1):104-10. Sylvester RK, Steen P, Tate JM, Mehta M, Petrich RJ, Berg A, Kolesar J
Temozolomide-induced severe myelosuppression: analysis of clinically associated polymorphisms in two patients.
Anticancer Drugs. 2011 Jan;22(1):104-10., [PMID:20938339]

Abstract [show]
Genotyping of putative determinants of temozolomide (TMZ)-induced life-threatening bone marrow suppression was performed in two patients with glioma treated with adjuvant TMZ and radiation therapy. DNA was extracted from the patients' mononuclear cells and genotyping of O-methylguanine-DNA-methyltransferase (MGMT), multidrug resistance (MDR1; also known as ABCB1), NQO1, and GSTP1 genes and analysis for the epigenetic silencing of specific MGMT gene promoters were carried out to evaluate the possible genetic determinants of increased risk of severe TMZ-induced myelosuppression. Although both patients were heterozygous for all ABCB1 single nucleotide polymorphisms and for rs12917 and rs1803965 in the MGMT gene, patient 1 was heterozygous for rs1695 in GSTP1 and rs2308327 in the MGMT gene. This patient also exhibited GG genotype for the MGMT single nucleotide polymorphisms, rs2308321, which is noteworthy for its 0.7% frequency globally. Epigenetic silencing of MGMT gene was not detected in either patient. Two single nucleotide polymorphisms identified in patient 1 (missense I143V and K178R polymorphisms; rs2308321 and rs2308327, respectively) have recently been shown to correlate with an increased risk of severe TMZ-induced myelosuppression. The polymorphisms identified in patient 2 have not been associated with an increased risk of severe TMZ-induced myelosuppression. Genotyping analyses of larger patient populations administered TMZ are required to validate the genetic determinants of severe TMZ-induced myelosuppression.

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101 Although both patients were Table 1 Summary of genotyping results of the selected SNPsa SNP Case 1 Case 2 Genotype with increased riskb SNP typec Frequency in Caucasiand,e ABCB1 rs1045642 CT CT - Synonymous CC: 0.15, CT: 0.63, TT: 0.22 rs1128503 CT CT - Synonymous CC: 0.35, CT: 0.52, TT: 0.13 rs2032582 GT GT - missense (S893A) GG: 0.32, GT: 0.56, TT: 0.12 GSTP1 rs1695 AG AA AA missense (I105V) AA: 0.33, AG: 0.55, GG: 0.12 MGMT rs12917 CT CT - missense (L84F) CC: 0.78, CT: 0.20, TT: 0.02 rs1803965 GA GA - Synonymous GG: 0.85, GA: 0.14, AA: 0.02 rs2282164 CC CC - missense (W65C) CC 1.00, CG and GG are < 0.001 rs2308318 GG GG - missense (G160R) GG 1.00, AG is 0.007 globally, AA: 0.00 rs2308321 GG AA AG or GG missense (I143V) AA: 0.65, AG: 0.35; GG: 0.007 globally rs2308322 GG GG - missense (P58S) GG, 1.00, GA is 0.003 globally, AA 0.00 rs2308327 AG AA AG or GG missense (K178R) AA: 0.98, AG: 0.02, GG: 0.00 NQO1 rs1800566 GG GG GG missense (P187S) GG: 0.60, AG: 0.37, AA: 0.03 ABCB1, ATB-binding cassette subfamily B member 1; GSTP1, glutathione S-transferases pi 1; MGMT, O6 -methylguanine-DNA-methyltransferase; NQO1, NAD(P)H dehydrogenase (quinone) family; SNPs, single nucleotide polymorphisms; a Bold lettering denotes SNPs, which were found to be non-wild-type for the indicated patient. Login to comment

[hide] Xenobiotic metabolizing and transporter genes: gen... Pharmacogenomics. 2010 Dec;11(12):1725-31. Gasso P, Mas S, Alvarez S, Trias G, Bioque M, Oliveira C, Bernardo M, Lafuente A
Xenobiotic metabolizing and transporter genes: gene-gene interactions in schizophrenia and related disorders.
Pharmacogenomics. 2010 Dec;11(12):1725-31., [PMID:21142916]

Abstract [show]
AIMS: In this study we explored possible epistasis between CYP2D6 (*3, *4, *5, *6 and *1xN), CYP3A5 (*3), CYP1A2 (*1C and *1F) and ABCB1 (G2677T) in schizophrenia and related disorders. MATERIALS & METHODS: A total of 344 patients diagnosed with schizophrenia and related disorders, and 484 healthy controls participated in the present study. We analyzed gene-gene interactions by multifactor dimensionality reduction. RESULTS: A four-way model including ABCB1 G2677T, CYP3A5*3, CYP1A2*1F and CYP2D6*4 variants had the best overall performances (accuracy: 0.573) and a crossvalidation consistency of 10/10 (permutation testing p < 0.004). CONCLUSION: Our results suggest a significant involvement of CYPs and transporters in brain metabolism and homeostasis, and provide evidence of gene-gene interactions among xenobiotic metabolizing and transporter genes in the context of schizophrenia.

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26 Regarding ABCB1, although several exon polymorphisms have been identified, G2677T is a missense mutation (amino acid change Ser893Ala), whereas others such as C3435T are synonymous variants. Login to comment

[hide] An update on ABCB1 pharmacogenetics: insights from... Pharmacogenomics J. 2011 Oct;11(5):315-25. doi: 10.1038/tpj.2011.16. Epub 2011 May 31. Wolf SJ, Bachtiar M, Wang J, Sim TS, Chong SS, Lee CG
An update on ABCB1 pharmacogenetics: insights from a 3D model into the location and evolutionary conservation of residues corresponding to SNPs associated with drug pharmacokinetics.
Pharmacogenomics J. 2011 Oct;11(5):315-25. doi: 10.1038/tpj.2011.16. Epub 2011 May 31., [PMID:21625253]

Abstract [show]
The human ABCB1 protein, (P-glycoprotein or MDR1) is a membrane-bound glycoprotein that harnesses the energy of ATP hydrolysis to drive the unidirectional transport of substrates from the cytoplasm to the extracellular space. As a large range of therapeutic agents are known substrates of ABCB1 protein, its role in the onset of multidrug resistance has been the focus of much research. This role has been of particular interest in the field of pharmacogenomics where genetic variation within the ABCB1 gene, particularly in the form of single nucleotide polymorphisms (SNPs), is believed to contribute to inter-individual variation in ABCB1 function and drug response. In this review we provide an update on the influence of coding region SNPs within the ABCB1 gene on drug pharmacokinetics. By utilizing the crystal structure of the mouse ABCB1 homolog (Abcb1a), which is 87% homologous to the human sequence, we accompany this discussion with a graphical representation of residue location for amino acids corresponding to human ABCB1 coding region SNPs. Also, an assessment of residue conservation, which is calculated following multiple sequence alignment of 11 confirmed sequences of ABCB1 homologs, is presented and discussed. Superimposing a 'heat map' of residue homology to the Abcb1a crystal structure has permitted additional insights into both the conservation of individual residues and the conservation of their immediate surroundings. Such graphical representation of residue location and conservation supplements this update of ABCB1 pharmacogenetics to help clarify the often confounding reports on the influence of ABCB1 polymorphisms on drug pharmacokinetics and response.

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85 This non-synonymous SNP confers one of two amino-acid substitutions at position 893 (Ser893Ala/Thr). Login to comment
90 Many contradictory results are reported and as such no definitive conclusion has been Figure 3 Location and conservation of (a) E13/1236C4T (G412G), (b) E22/2677G4T/A (S893A/T) and (c) E27/3435C4T (I1145I). Login to comment
151 Of the remaining 10 previously associated SNPs, which can be mapped to the 3D structure, none reside in the substrate-binding region highlighted by Aller et al.12 Only one SNP, E8/554G4T (G185) (#ns7) resides within the membrane whereas another SNP (E22/2677G4T/A (S893A/ T) (#ns22)) resides in the region between the membrane and the cytosolic N-terminal NBD in the crystal structure, although this residue is part of TM10 (Figure 2). Login to comment

[hide] Efflux and uptake transporters as determinants of ... Expert Opin Drug Metab Toxicol. 2010 May;6(5):621-32. Rodrigues AC
Efflux and uptake transporters as determinants of statin response.
Expert Opin Drug Metab Toxicol. 2010 May;6(5):621-32., [PMID:20367534]

Abstract [show]
IMPORTANCE OF THE FIELD: The important role of drug transporters in drug absorption and disposition has been well documented. Statins are subjected to active transport of membrane proteins of the superfamilies ATP-binding cassette and solute carrier, and there is limited understanding of the mechanisms by which differences in transporter expression and activity contributes to variability of pharmacokinetics (PKs)/pharmacodynamics (PDs) of statins. AREAS COVERED IN THIS REVIEW: This review aims to discuss the roles of drug transporters in the PKs and PDs of statins, and in drug interactions with statins. WHAT THE READER WILL GAIN: A comprehensive summary of the literature on this subject including in vitro and in vivo observations. TAKE HOME MESSAGE: In vivo and in vitro studies have shown that efflux and uptake transporters modulate the PKs/PDs of statins. Until now organic anion transporting polypeptides (OATP)1B1 variants have been considered major factors in limiting the uptake of statins and increasing statin exposure, and, consequently, increasing risk of myopathy. Further studies in pharmacogenetics and in vitro models to assess statin disposition and toxicity are required to understand the contribution of others transporters, such as multidrug resistance-associated protein (MRP)1, MRP2, breast cancer resistance protein, OATP2B1, OAT1B3 and OATP1A2, in interindividual variability to statins efficacy and safety.

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98 The ACCESS study showed an association between G2677T (S893A) single nucleotide polymorphism (SNP) and changes on LDL and total cholesterol after atorvastatin treatment [41]. Login to comment

[hide] MDR1 gene polymorphisms may be associated with Beh... Gene. 2012 Sep 1;505(2):333-9. doi: 10.1016/j.gene.2012.05.040. Epub 2012 Jun 15. Rustemoglu A, Gul U, Gumus-Akay G, Gonul M, Yigit S, Bozkurt N, Karadag A, Piskin E, Sunguroglu A, Kadikiran A
MDR1 gene polymorphisms may be associated with Behcet's disease and its colchicum treatment response.
Gene. 2012 Sep 1;505(2):333-9. doi: 10.1016/j.gene.2012.05.040. Epub 2012 Jun 15., [PMID:22705826]

Abstract [show]
Behcet's disease (BD) is a chronic multisystem disorder. Infectious agents, immune system mechanisms, and genetic factors are implicated in the etiopathogenesis of BD, which remains to be explained. The human MDR1 (ABCB1) gene encoder P-glycoprotein (P-gp) plays a key role in drug disposition, serves as a protective mechanism against xenobiotics, and provides additional protection for the brain, testis, and fetus. We investigated the genotype and haplotype distributions of three MDR1 gene polymorphisms (C1236T, G2677T/A, and C3435T) in 104 BD patients and 130 control subjects. The genotyping analysis was performed by using PCR-RFLP methods. No statistically significant differences were found for the genotypic and allelic distributions of three individual single nucleotide polymorphisms (SNPs) in the MDR1 gene between BD patients and control subjects in this study (p>0.05). However, combined genotype and haplotype frequencies have found statistically significant differences between BD and control subjects for some combinations (p<0.05). The CC-GG binary genotype for C1236T-G2677T/A loci couple in particular may have a high degree of predisposition to BD (p=0.009; OR, 3.03; 95% CI, 1.41-6.54). Furthermore, significant differences between colchicine-responsive and -nonresponsive groups were found. Genotypic and allelic distributions of C3435T and G2677T/A loci, as well as their genotype and haplotype combinations, were found to have statistically significant differences (p<0.05). The TT genotype for the C3435T locus (p=0.001; OR, 6.59; 95% CI, 1.86-23.30) and T allele (p=0.009; OR, 2.09; 95% CI, 1.18-3.70) plays a substantial role in the colchicine response. Our study showed that MDR1 genes and their polymorphisms may affect a patient's BD susceptibility and colchicine response.

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104 Position Exon Amino acid change Allele BD (N=210) Control (N=260) P Genotype BD (105) Control (130) n F n F N p for HWE N p for HWE 1236 (rs1128503) 12 G412G C 109 0.524 121 0.465 0.3964 CC 33 0.0771 27 0.7270 CT 43 67 T 101 0.476 139 0.535 TT 29 36 2677 (rs2032582) 21 S893A/T G 104 0.495 124 0.477 0.5676 GG 26 0.9214 29 0.7323 GT 45 61 T 94 0.448 123 0.473 TT 22 27 A 12 0.057 13 0.050 TA 5 8 GA 7 5 3435 (rs1045642) 26 I1145I C 103 0.490 124 0.477 0.8739 CC 26 0.8449 33 0.2232 CT 51 58 T 107 0.510 136 0.523 TT 28 39 BD-Behcet's disease; n-number of alleles; N-number of subjects; F-frequency of alleles; HWE-Hardy-Weinberg equilibrium. Login to comment
103 Position Exon Amino acid change Allele BD (N=210) Control (N=260) P Genotype BD (105) Control (130) n F n F N p for HWE N p for HWE 1236 (rs1128503) 12 G412G C 109 0.524 121 0.465 0.3964 CC 33 0.0771 27 0.7270 CT 43 67 T 101 0.476 139 0.535 TT 29 36 2677 (rs2032582) 21 S893A/T G 104 0.495 124 0.477 0.5676 GG 26 0.9214 29 0.7323 GT 45 61 T 94 0.448 123 0.473 TT 22 27 A 12 0.057 13 0.050 TA 5 8 GA 7 5 3435 (rs1045642) 26 I1145I C 103 0.490 124 0.477 0.8739 CC 26 0.8449 33 0.2232 CT 51 58 T 107 0.510 136 0.523 TT 28 39 BD-Behcet's disease; n-number of alleles; N-number of subjects; F-frequency of alleles; HWE-Hardy-Weinberg equilibrium. Login to comment

[hide] Genetic variability in drug transport, metabolism ... BMC Pharmacol Toxicol. 2015 Feb 27;16:2. doi: 10.1186/s40360-015-0001-5. Lambrechts S, Lambrechts D, Despierre E, Van Nieuwenhuysen E, Smeets D, Debruyne PR, Renard V, Vroman P, Luyten D, Neven P, Amant F, Leunen K, Vergote I
Genetic variability in drug transport, metabolism or DNA repair affecting toxicity of chemotherapy in ovarian cancer.
BMC Pharmacol Toxicol. 2015 Feb 27;16:2. doi: 10.1186/s40360-015-0001-5., [PMID:25881102]

Abstract [show]
BACKGROUND: This study aimed to determine whether single nucleotide polymorphisms (SNPs) in genes involved in DNA repair or metabolism of taxanes or platinum could predict toxicity or response to first-line chemotherapy in ovarian cancer. METHODS: Twenty-six selected SNPs in 18 genes were genotyped in 322 patients treated with first-line paclitaxel-carboplatin or carboplatin mono-therapy. Genotypes were correlated with toxicity events (anemia, neutropenia, thrombocytopenia, febrile neutropenia, neurotoxicity), use of growth factors and survival. RESULTS: The risk of anemia was increased for variant alleles of rs1128503 (ABCB1, C > T; p = 0.023, OR = 1.71, 95% CI = 1.07-2.71), rs363717 (ABCA1, A > G; p = 0.002, OR = 2.08, 95% CI = 1.32-3.27) and rs11615 (ERCC1, T > C; p = 0.031, OR = 1.61, 95% CI = 1.04-2.50), while it was decreased for variant alleles of rs12762549 (ABCC2, C > G; p = 0.004, OR = 0.51, 95% CI = 0.33-0.81). Likewise, increased risk of thrombocytopenia was associated with rs4986910 (CYP3A4, T > C; p = 0.025, OR = 4.99, 95% CI = 1.22-20.31). No significant correlations were found for neurotoxicity. Variant alleles of rs2073337 (ABCC2, A > G; p = 0.039, OR = 0.60, 95% CI = 0.37-0.98), rs1695 (ABCC1, A > G; p = 0.017, OR = 0.55, 95% CI 0.33-0.90) and rs1799793 (ERCC2, G > A; p = 0.042, OR = 0.63, 95% CI 0.41-0.98) associated with the use of colony stimulating factors (CSF), while rs2074087 (ABCC1, G > C; p = 0.011, OR = 2.09, 95% CI 1.18-3.68) correlated with use of erythropoiesis stimulating agents (ESAs). Homozygous carriers of the rs1799793 (ERCC2, G > A) G-allele had a prolonged platinum-free interval (p = 0.016). CONCLUSIONS: Our data reveal significant correlations between genetic variants of transport, hepatic metabolism, platinum related detoxification or DNA damage repair and toxicity or outcome in ovarian cancer.

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111 The following 7 genetic variants failed genotyping: rs2032582 (Ser893Ala in ABCB1), rs2273697 (Val417Ile in ABCC2), rs1058930 (Ile194Met in CYP2C8), rs11572080 (Arg69Lyes in CYP2C8), rs10509681 (Lys329Arg in CYP2C8), rs12721627 (Thr185Ser in CYP3A4), rs25487 (Gln398Arg in XRCC1). Login to comment

[hide] Drug-induced trafficking of p-glycoprotein in huma... PLoS One. 2014 Feb 4;9(2):e88154. doi: 10.1371/journal.pone.0088154. eCollection 2014. Noack A, Noack S, Hoffmann A, Maalouf K, Buettner M, Couraud PO, Romero IA, Weksler B, Alms D, Romermann K, Naim HY, Loscher W
Drug-induced trafficking of p-glycoprotein in human brain capillary endothelial cells as demonstrated by exposure to mitomycin C.
PLoS One. 2014 Feb 4;9(2):e88154. doi: 10.1371/journal.pone.0088154. eCollection 2014., [PMID:24505408]

Abstract [show]
P-glycoprotein (Pgp; ABCB1/MDR1) is a major efflux transporter at the blood-brain barrier (BBB), restricting the penetration of various compounds. In other tissues, trafficking of Pgp from subcellular stores to the cell surface has been demonstrated and may constitute a rapid way of the cell to respond to toxic compounds by functional membrane insertion of the transporter. It is not known whether drug-induced Pgp trafficking also occurs in brain capillary endothelial cells that form the BBB. In this study, trafficking of Pgp was investigated in human brain capillary endothelial cells (hCMEC/D3) that were stably transfected with a doxycycline-inducible MDR1-EGFP fusion plasmid. In the presence of doxycycline, these cells exhibited a 15-fold increase in Pgp-EGFP fusion protein expression, which was associated with an increased efflux of the Pgp substrate rhodamine 123 (Rho123). The chemotherapeutic agent mitomycin C (MMC) was used to study drug-induced trafficking of Pgp. Confocal fluorescence microscopy of single hCMEC/D3-MDR1-EGFP cells revealed that Pgp redistribution from intracellular pools to the cell surface occurred within 2 h of MMC exposure. Pgp-EGFP exhibited a punctuate pattern at the cell surface compatible with concentrated regions of the fusion protein in membrane microdomains, i.e., lipid rafts, which was confirmed by Western blot analysis of biotinylated cell surface proteins in Lubrol-resistant membranes. MMC exposure also increased the functionality of Pgp as assessed in three functional assays with Pgp substrates (Rho123, eFluxx-ID Gold, calcein-AM). However, this increase occurred with some delay after the increased Pgp expression and coincided with the release of Pgp from the Lubrol-resistant membrane complexes. Disrupting rafts by depleting the membrane of cholesterol increased the functionality of Pgp. Our data present the first direct evidence of drug-induced Pgp trafficking at the human BBB and indicate that Pgp has to be released from lipid rafts to gain its full functionality.

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126 In the MDR1 sequence of this construct we identified three of the most common single nucleotide polymorphisms, T1236C (Gly412Gly), T2677G (Ser893Ala) and T3435C (Ile1145Ile), which have been described in MDR1 of humans [24]. Login to comment

[hide] CYP2C9, VKORC1, CYP4F2, ABCB1 and F5 variants: inf... Pharmacol Rep. 2014 Apr;66(2):243-9. doi: 10.1016/j.pharep.2013.09.006. Epub 2014 Mar 3. Nahar R, Saxena R, Deb R, Parakh R, Shad S, Sethi PK, Takkar P, Verma IC
CYP2C9, VKORC1, CYP4F2, ABCB1 and F5 variants: influence on quality of long-term anticoagulation.
Pharmacol Rep. 2014 Apr;66(2):243-9. doi: 10.1016/j.pharep.2013.09.006. Epub 2014 Mar 3., [PMID:24911077]

Abstract [show]
AIMS: The study aims to evaluate the impact of genetic, demographic and clinical data on various measures of outcome of anticoagulation quality in patients. PATIENTS AND METHODS: The study consisted of 310 patients receiving long-term oral anticoagulation therapy in our hospital. Apart from demographic and clinical variables, 21 SNPs (in 7 genes) were analyzed and compared with the outcomes of anticoagulation therapy. Various outcomes that were measured are; supra therapeutic INRs (INR >3, >6), anticoagulation stabilization, time taken to stabilize and proportion of INRs within (2-3), above (>3) and below (<2) therapeutic range. RESULTS: Supra therapeutic INRs were influenced by CYP2C9*2, *3, CYP4F2 rs2108622, VKORC1-1639G>A, 1173C>T, rs55894764 along with concomitant drugs, smoking, body weight and height. Persistently fluctuating INRs/absolute instability correlated with VKORC1-1639G>A, gender, height and body mass index. The time taken to stabilize was associated with CYP4F2 rs2108622, CYP2C9*14, smoking, clinical indication and concomitant drugs. The overall distribution of INR was influenced by variants in CYP4F2 rs2108622, CYP2C9*3, rs9332230, VKORC1 1173C>T, -1639G>A, rs55894764, ABCB1 rs2032582, rs1128503, rs1045642 and F5 rs6025, age, smoking and concomitant drugs. CONCLUSIONS: Knowledge of factors influencing the quality of long term anticoagulation can help clinicians to customize therapy either by dose variation, therapy with alternate choice of drug, concurrent heparin therapy and/or frequent INR monitoring.

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34 Nine variants in CYP2C9 (*2/rs1799853/430C>T/p.Cys144Arg in exon 3; *3/rs1057910/c.1075A>C/p.Ileu359Leu in exon 7; rs9332120, c.331+73T>C in intron 2; rs9332230, c.1291+53A>T in intron 8; rs2298037, c.1291+147C>T in intron 8; *14/rs72558189, c.374G>A/p.Arg125His in exon 2; rs9332172, c.820-73A>G in intron 5; rs1057911, c.1425A>T/p.Gly475Gly in exon 9; and c.610A>C, *57/p.Asn204His in exon 4), four variants in VKORC1 (1639G>A/g.3588G>A/rs9923231 in upstream promoter region; rs9934438, c.1173C>T in intron 2; rs7294, c.516G>A/ 3730G>A in 30 UTR and rs55894764/c.36G>A/p.Arg12Arg in exon 1), CYP4F2 rs2108622 (c.1297G>A/p.Val433Met in exon 11), three common polymorphisms in the MDR1/ABCB1 gene (rs1128503/ c.1236T>C/p.Gly412Gly in exon 12; rs2032582/c.2677T>G/A/ p.Ser893Ala/Thr in exon 21 and rs1045642/c.3435C>T/ p.Ile1145Ile in exon 26), APOE isoforms (e2, e3, e4 distinguished by two non synonymous polymorphisms; rs7212 and rs229358), factor V Leiden variant in F5 (rs6025/1691G>A/p.Arg506Gln) and prothrombin variant in F2 (rs1799963/20210G>A in 30 UTR) were genotyped. Login to comment

[hide] Resistance and intolerance to statins. Nutr Metab Cardiovasc Dis. 2014 Oct;24(10):1057-66. doi: 10.1016/j.numecd.2014.05.009. Epub 2014 Jun 6. Reiner Z
Resistance and intolerance to statins.
Nutr Metab Cardiovasc Dis. 2014 Oct;24(10):1057-66. doi: 10.1016/j.numecd.2014.05.009. Epub 2014 Jun 6., [PMID:24996502]

Abstract [show]
BACKGROUND AND AIMS: Many patients treated with statins are considered statin-resistant because they fail to achieve adequate reduction of low density lipoprotein cholesterol (LDL-C) levels. Some patients are statin-intolerant because they are unable to tolerate statin therapy at all or to tolerate a full therapeutic statin dose because of adverse effects, particularly myopathy and increased activity of liver enzymes. RESULTS: The resistance to statins has been associated with polymorphisms in the 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMG-CoA-R), P-glycoprotein (Pg-P/ABCB1), breast cancer resistance protein (BCRP/ABCG2), multidrug resistance-associated proteins (MRP1/ABCC1 and MRP2/ABCC2), organic anion transporting polypeptides (OATP), RHOA, Nieman-Pick C1-like1 protein (NPC1L1), farnesoid X receptor (FXR), cholesterol 7alpha-hydroxylase (CYP7A1), Apolipoprotein E (ApoE), proprotein convertase subtilisin/kexin type 9 (PCSK9), low density lipoprotein receptor (LDLR), lipoprotein (a) (LPA), cholesteryl ester transfer protein (CETP), and tumor necrosis factor alpha (TNF-alpha) genes. However, currently, there is still not enough evidence to advocate pharmacogenetic testing before initiating statin therapy. Patients with inflammatory states and HIV infection also have diminished LDL-C lowering as a response to statin treatment. Pseudo-resistance due to nonadherence or non-persistence in real-life circumstances is probably the main cause of insufficient LDL-C response to statin treatment. CONCLUSIONS: If a patient is really statin-resistant or statin-intolerant, several other treatment possibilities are nowadays available: ezetimibe alone or in combination with bile acid sequestrants, and possibly in the near future mipomersen, lomitapide, or monoclonal antibodies against PCSK9.

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66 The ACCESS trial also showed an association between G2677T (S893A) SNP and changes of total cholesterol as well as LDL-C plasma concentration after atorvastatin treatment [11]. Login to comment

[hide] Genetic polymorphisms and gene-dosage effect in ov... J Exp Clin Cancer Res. 2015 Jan 16;34:2. doi: 10.1186/s13046-015-0124-y. Tecza K, Pamula-Pilat J, Kolosza Z, Radlak N, Grzybowska E
Genetic polymorphisms and gene-dosage effect in ovarian cancer risk and response to paclitaxel/cisplatin chemotherapy.
J Exp Clin Cancer Res. 2015 Jan 16;34:2. doi: 10.1186/s13046-015-0124-y., [PMID:25591549]

Abstract [show]
BACKGROUND: Ovarian malignancies are often diagnosed in advanced stage and at the same time resistance to treatment, both intrinsic and developed during treatment, is sometimes observed. These facts underscore the need for new markers of ovarian cancer risk, as well as markers of treatment effectiveness. METHODS: In this study we genotyped 225 ovarian cancer patients, 64 breast and ovarian cancer patients and 348 healthy controls. In total, 12 polymorphic variants and 2 deletions in PGR, ABCB1, ABCG2, GSTT1, GSTM1, GSTP1, ATM, TP53 and ATP7B genes were analyzed using ASA-PCR, RFLP-PCR, multiplex-PCR and sequencing. RESULTS: Ten genetic polymorphisms were significantly associated with the risk of developing ovarian carcinoma in at least one of the groups under study. Impact of PGR gene polymorphisms on ovarian cancer risk was specific only for the group of the BRCA1 mutation carriers (in presence of p.Val660Leu variant- OR 2,82; p = 0,010), which confirms the difference in modulation of ovarian cancer risk between sporadic and hereditary malignancies, including the breast-ovarian cancer group (as a cancer-prone group). The analyses showed also the importance of ATP7B gene in ovarian carcinogenesis, both studied variants of which significantly modulated the ovarian cancer risk in all groups excluding the group with BRCA1 mutation. Cumulative risk analysis revealed 3 unfavorable variants that increased significantly the risk of developing ovarian cancer (p.Ile1145 = ABCB1+ p.Asp1853Asn ATM+ p.Ser406Ala ATP7B- OR 7,47; p = 0,002) and significantly modified the progression free survival (PFS) of the patients, and also two favorable genotypes which protected against ovarian cancer (p.Arg952Lys ATP7B+ p.Arg72Pro TP53- OR 0,50; p = 0,008). PFS analysis for carriers of favorable versus unfavorable genotypes emphasized the impact of the regulation of cell cycle (p.Asp1853Asn ATM) and active transport of xenobiotics (p.Ser894Ala/Thr ABCB1) on the risk of disease progression (HR 3,81; p = 0,010) after paclitaxel/cisplatin chemotherapy. CONCLUSIONS: The unfavorable genetic variants could facilitate carcinogenic process and once their carriers developed malignancy, their chances of survival were smaller. Our analyses also showed a strong gene-dosage effect with the decrease of progression-free survival for the carriers of two unfavorable genetic factors.

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61 Genotyping of polymorphic variants in PGR (rs10895068 and p.Val660Leu), ABCB1 (p.Ile1145 = and p.Ser893Ala/ Trp), ABCG2 (p.Gln141Lys), ATM (p.Asp1853Asn), TP53 (p.Arg72Pro), GSTP1 (p.Ile105Val) genes, as well as detection of GSTT1/M1 gene deletions, were performed as described previously [9-17]. Login to comment
101 The polymorphisms, which in univariate analysis were modulating ovarian cancer risk, were included in the Table 2 Case-control analyses of ovarian and breast and ovarian cancer risk Ovarian cancer all patients Ovarian cancer BRCA1- Ovarian cancer BRCA1+ Breast and ovarian cancer Gene polymorphism Genotype Controls n(%) n(%) OR (&#b1;95% CI) p n(%) OR (&#b1;95% CI) p n(%) OR (&#b1;95% CI) p n(%) OR (&#b1;95% CI) p PGR p.Val660Leu rs1042838 GG 239 (69.3) 143 (63.9) 1(ref) 131 (66.5) 1(ref) 12 (44.4) 1(ref) 46 (75.4) 1 (ref) GT 95 (27.5) 74 (33.0) 1.03 (0.90-1.88) 0.160 60 (30.5) 1.15 (0.78-1.70) 0.473 14 (51.9) 2.94 (1.31-6.58) 0.009 14 (23.0) 0.77 (0.40-1.46) 0.416 TT 11 (3.2) 7 (3.1) 1.06 (0.40-2.81) 0.901 6 (3.0) 1.00 (0.36-2.75) 0.993 1 (3.70) 1.81 (0.22-15.20) 0.584 1 (1.6) 0.47 (0.06-3.75) 0.478 GT + TT 106 (30.7) 81 (36.1) 1.20 (0.88-1.63) 0.249 66 (33.5) 1.14 (0.78-1.65) 0.504 15 (55.6) 2.82 (1.28-6.23) 0.010 15 (24.6) 0.74 (0.39-1.38) 0.336 ABCB1 p.Ser893Ala p.Ser893Thr rs2032582 GG 117 (33.7) 65 (29.0) 1(ref) 56 (28.4) 1(ref) 9 (33.4) 1(ref) 16 (26.2) 1 (ref) GT 156 (45.0) 115 (51.4) 1.33 (0.90-1.95) 0.152 104 (52.8) 1.39 (0.93-2.09) 0.108 11 (40.7) 0.92 (0.37-2.28) 0.852 33 (54.1) 1.55 (0.71-2.94) 0.184 TT 60 (17.3) 37 (16.5) 1.11 (0.67-1.85) 0.688 32 (16.3) 1.11 (0.65-1.90) 0.691 5 (18.5) 1.08 (0.35-3.38) 0.890 9 (14.8) 1.10 (0.46-2.63) 0.836 GA 9 (2.6) 2 (0.9) 0.40 (0.08-1.91) 0.250 2 (1.0) 0.46 (0.10-2.24) 0.337 - - - 2 (3.3) 1.63 (0.32-8.31) 0.557 TA 5 (1.4) 5 (2.2) 1.80 (0.50-6.45) 0.367 3 (1.5) 1.25 (0.29-5.49) 0.763 2 (7.4) 5.20 (0.87-31.18) 0.069 1 (1.6) 1.46 (0.16-13.6) 0.736 AA - - - - - - - - - - - - - GG + GT + GA 282 (81.3) 182 (81.3) 1 (ref) 162 (82.2) 1 (ref) 20 (74.1) 1 (ref) 51 (83.6) 1 (ref) TT + TA 65 (18.7) 42 (18.7) 1.00 (0.92-1.09) 1.000 35 (17.8) 0.94 (0.60-1.48) 0.780 7 (25.9) 1.52 (0.61-3.76) 0.364 10 (16.4) 0.85 (0.41-1.77) 0.664 ABCB1 p.Ile1145= rs1045642 CC 83 (24.0) 44 (19.6) 1(ref) 35 (17.8) 1(ref) 9 (33.3) 1(ref) 16 (26.2) 1 (ref) CT 162 (47.0) 122 (54.5) 1.42 (0.92-2.19) 0.113 112 (56.8) 1.64 (1.03-2.60) 0.036 10 (37.1) 0.57 (0.22-1.46) 0.239 26 (42.6) 0.83 (0.42-1.64) 0.596 TT 100 (29.0) 58 (25.9) 1.09 (0.67-1.78) 0.718 50 (25.4) 1.18 (0.70-2.00) 0.522 8 (29.6) 0.74 (0.27-2.00) 0.549 19 (31.2) 0.98 (0.48-2.04) 0.969 CT + TT 262 (76.0) 180 (80.4) 1.02 (0.81-1.30) 0.827 162 (82.2) 1.47 (0.94-2.28) 0.089 18 (66.7) 0.63 (0.27-1.46) 0.285 45 (73.8) 0.89 (0.48-1.66) 0.716 ABCG2 p. Gln141Lys rs2231142 CC 276 (80.2) 191 (86.4) 1 (ref) 167 (85.6) 1 (ref) 24 (92.3) 1 (ref) 56 (87.5) 1 (ref) CA 68 (19.8) 30 (13.6) 0.64 (0.40-1.02) 0.059 28 (14.4) 0.68 (0.42-1.10) 0.116 2 (7.7) 0.34 (0.08-0.47) 0.147 8 (12.5) 0.58 (0.26-1.28) 0.175 ATM p. Asp1853Asn rs1801516 GG 254 (75.8) 153 (68.6) 1 (ref) 134 (68.4) 1 (ref) 19 (70.4) 1 (ref) 45 (70.3) 1 (ref) GA 76 (22.7) 64 (28.7) 1.40 (0.95-2.06) 0.091 57 (29.1) 1.42 (0.95-2.13) 0.083 7 (25.9) 1.23 (0.50-3.05) 0.651 15 (23.4) 1.11 (0.59-2.11) 0.740 AA 5 (1.5) 6 (2.7) 1.99 (0.60-6.66) 0.262 5 (2.5) 1.90 (0.54-6.69) 0.319 1 (3.7) 2.67 (0.39-24.29) 0.380 4 (6.3) 4.52 (1.16-17.56) 0.029 GA + AA 81 (24.2) 70 (31.4) 1.43 (0.98-2.09) 0.061 62 (31.6) 1.45 (0.98-2.15) 0.062 8 (29.6) 1.32 (0.73-2.40) 0.352 19 (29.7) 1.32 (0.56-3.14) 0.528 TP53 p.Arg72Pro rs1042522 GG 167 (49.0) 130 (57.8) 1 (ref) 115 (58.1) 1 (ref) 15 (55.6) 1 (ref) 29 (48.3) 1 (ref) GC 150 (44.0) 79 (35.1) 0.68 (0.47-0.97) 0.031 70 (35.3) 0.68 (0.47-0.98) 0.039 9 (33.3) 0.67 (0.28-1.57) 0.355 29 (48.3) 1.11 (0.64-1.95) 0.707 CC 24 (7.0) 16 (7.1) 0.86 (0.44-1.68) 0.652 13 (6.6) 0.79 (0.39-1.61) 0.511 3 (11.1) 1.39 (0.38-5.16) 0.621 2 (3.3) 0.48 (0.11-2.14) 0.336 GC + CC 174 (51.0) 95 (42.2) 0.80 (0.61-1.05) 0.104 83 (41.9) 0.69 (0.49-0.99) 0.042 12 (44.4) 0.77 (0.35-1.69) 0.511 31 (51.67) 1.03 (0.59-1.78) 0.927 ATP7B p.Ser406Ala rs1801243 TT 103 (30.8) 41 (19.0) 1 (ref) 35 (18.5) 1 (ref) 6 (22.2) 1 (ref) 13 (20.3) 1 (ref) TG 157 (47.0) 113 (52.3) 1.81 (1.17-2.80) 0.008 100 (52.9) 1.87 (1.18-2.97) 0.007 13 (48.2) 1.42 (0.52-3.88) 0.490 32 (50.0) 1.61 (0.81-3.23) 0.174 GG 74 (22.2) 62 (28.7) 2.10 (1.28-3.46) 0.003 54 (28.6) 2.15 (1.27-3.62) 0.004 8 (29.6) 1.86 (0.61-5.61) 0.270 19 (29.7) 2.03 (0.94-4.40) 0.069 TG + GG 231 (69.2) 175 (81.0) 1.90 (1.26-2.88) 0.002 154 (81.5) 1.96 (1.27-3.03) 0.002 21 (77.8) 1.56 (0.61-3.99) 0.352 51 (79.7) 1.75 (0.91-3.36) 0.093 Table 2 Case-control analyses of ovarian and breast and ovarian cancer risk (Continued) ATP7B p.Arg952Lys rs732774 AA 103 (30.7) 86 (38.9) 1 (ref) 76 (39.2) 1 (ref) 10 (37.0) 1 (ref) 25 (39.7) 1 (ref) AG 159 (47.5) 96 (43.4) 0.72 (0.49-1.06) 0.096 82 (42.3) 0.70 (0.47-1.04) 0.078 14 (51.9) 0.91 (0.39-2.11) 0.821 31 (49.2) 0.80 (0.45-1.44) 0.471 GG 73 (21.8) 39 (17.7) 0.64 (0.39-1.04) 0.070 36 (18.5) 0.67 (0.41-1.10) 0.112 3 (11.1) 0.42 (0.11-1.61) 0.203 7 (11.1) 0.40 (0.16-0.97) 0.041 AG + GG 232 (69.3) 135 (61.1) 0.70 (0.49-1.00) 0.047 118 (60.8) 0.69 (0.48-1.00) 0.049 17 (63.0) 0.75 (0.33-1.71) 0.499 38 (60.3) 0.67 (0.39-1.18) 0.165 GST T1/M1 Gene deletions wt/wt 118 (34.6) 82 (36.8) 1(ref) 72 (36.7) 1(ref) 10 (37.0) 1(ref) 20 (31.3) 1(ref) wt/null 49 (14.4) 18 (8.1) 0.53 (0.29-0.98) 0.040 17 (8.7) 0.57 (0.30-1.07) 0.076 1 (3.7) 0.24 (0.03-1.96) 0.180 6 (9.4) 0.72 (0.27-1.92) 0.512 null/wt 138 (40.5) 95 (42.6) 0.99 (0.64-1.54) 0.967 82 (41.8) 0.97 (0.65-0.47) 0.90 13 (48.2) 1.11 (0.47-2.64) 0.810 31 (48.4) 1.32 (0.72-2.45) 0.368 null/null 36 (10.5) 28 (12.5) 1.12 (0.63-1.98) 0.698 25 (12.8) 1.14 (0.63-2.06) 0.667 3 (11.1) 0.98 (0.24-4.04) 0.982 7 (10.9) 1.14 (0.45-2.95) 0.774 GSTP1 p.Ile105Val rs1695 AA 151 (45.2) 104 (46.4) 1 (ref) 93 (47.2) 1 (ref) 11 (40.7) 1 (ref) 32 (52.4) 1 (ref) AG 162 (48.5) 95 (42.4) 0.85 (0.60-1.22) 0.376 84 (42.6) 0.84 (0.58-1.22) 0.361 11 (40.7) 0.93 (0.39-2.22) 0.873 36 (36.1) 0.64 (0.36-1.15) 0.137 GG 21 (6.3) 25 (11.2) 1.73 (0.92-3.26) 0.090 20 (10.2) 1.54 (0.79-3.01) 0.199 5 (18.6) 3.27 (1.03-10.42) 0.044 7 (11.5) 1.57 (0.61-4.03) 0.342 AG + GG 183 (54.8) 120 (53.6) 0.95 (0.68-1.34) 0.776 104 (52.8) 0.92 (0.65-1.32) 0.656 16 (49.3) 1.20 (0.54-2.67) 0.653 43 (47.6) 0.75 (0.43-1.29) 0.296 Statistically significant analyses are in bold. groups of risk reductors (favorable genotypes) or risk enhancers (unfavorable genotypes). 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111 Higher risk of disease progression was associated with presence of genotypes lacking a major p.Ser893Ala/Trp polymorphism (HR 2.14; 95% CI 1.07-4.28; p = 0.031) in the G allele of ABCB1 and with the presence of major homozygote GG of p.Asp1853Asn in the ATM gene (HR 2.32; 95% CI 1.06-5.10; p = 0.036) (Table 4). Login to comment
127 Similar results were also obtained for the rare heterozygotes TA of p. Ser893Ala/Trp polymorphism in ABCB1 gene. Login to comment
130 A. overall survival and risk of death for TP53 p.Arg72Pro; B. overall survival and risk of death for PGR p.Val660Leu; C. progression-free survival and cumulative risk of progression for unfavorable PFS factors (ATM p.Asp1853Asn GG genotype and ABCB1 p.Ser893Ala/Trp TT + TA genotypes group). Login to comment
131 Table 4 Progression-free survival/multivariate analysis/ Factor Variant Cases n (%) HR (&#b1;95% CI) P Histotype Non-serous 57 (44.2) 1 (ref) Serous 72 (55.8) 5.04 (2.05-12.37) 0.0004 FIGO 1 + 2 58 (46.0) 1 (ref) 3 + 4 68 (54.0) 2.19 (1.03-4.64) 0.041 ABCB1 p.Ser893Ala p.Ser893Thr rs2032582 Common allele carriers (GG + GT + GA) 101 (80.2) 1 (ref) Rare genotypes (AT + TT) 25 (19.8) 2.14 (1.07-4.28) 0.031 ATM p.Asp1853Asn rs1801516 Rare allele carriers (GA + AA) 87 (61.0) 1 (ref) Common homozygote (GG) 39 (39.0) 2.32 (1.06-5.10) 0.036 Statistically significant analyses are in bold. relevant compounds. Login to comment
167 As for the survival analyses, it was evident that accumulation of relatively weak genetic variants (ABCB1 p.Ser893Ala/ Trp and ATM p.Asp1853Asn) may significantly enhance the risk of progression after paclitaksel/cisplatin treatment. Login to comment
169 It should be noted that in recent large study performed on over four thousand invasive ovarian cancer patients the p.Ser893Ala/Trp polymorphism had no impact on patients` survival [21]. Login to comment

[hide] Genetic polymorphisms of the multidrug resistance ... Tumour Biol. 2015 Aug;36(9):7007-15. doi: 10.1007/s13277-015-3407-1. Epub 2015 Apr 12. Wang ZC, Liu LZ, Liu XY, Hu JJ, Wu YN, Shi JY, Yang LX, Duan M, Wang XY, Zhou J, Fan J, Gao Q
Genetic polymorphisms of the multidrug resistance 1 gene MDR1 and the risk of hepatocellular carcinoma.
Tumour Biol. 2015 Aug;36(9):7007-15. doi: 10.1007/s13277-015-3407-1. Epub 2015 Apr 12., [PMID:25861753]

Abstract [show]
A possible association between multiple drug resistance 1 gene (MDR1) polymorphisms and the risk of developing hepatocellular carcinoma (HCC) is currently under debate, and evidence from various epidemiological studies has yielded controversial results. To derive a more precise estimation of the association between MDR1 polymorphisms and HCC risk, the present meta-analysis was performed. A total of 8 studies containing 11 cohorts with 4407 cases and 4436 controls were included by systematic literature search of EMBASE, PubMed, Web of Science, and CNKI. All polymorphisms were classified as mutant/wild-type alleles. In particular, the variation type, functional impact, and protein domain location of the polymorphisms were assessed and used as stratified indicators. The pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated to evaluate the association. Overall, our results suggested that the mutant alleles of the MDR1 gene were associated with a significantly increased risk for HCC under all genetic models (allelic model: OR = 1.28, 95 % CI = 1.20-1.36, P < 0.001; dominant model: OR = 1.27, 95 % CI = 1.16-1.38, P < 0.001; recessive model: OR = 1.59, 95 % CI = 1.36-1.85, P < 0.001). Furthermore, increased risks for HCC were also revealed in stratified analyses by ethnicity, sample size, and quality scores of cohorts as well as variation type, functional impact, and protein domain location of polymorphisms. In conclusion, the present meta-analysis suggested that the presence of MDR1 mutant alleles might be a risk factor for HCC.

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80 Positions in different coding Table 1 Characteristics of the studies and cohorts included in the meta-analysis Name of studies Country Ethnicity Type of case/control Genotyping method Quality scores Age Male/female ratio Variant site Genotype frequency of case/control HWE Case Control Case Control 1/1 1/2 2/2 Mean SD Mean SD Chen Y [29] China Chinese HCC a /HP PCR-RFLP 6 55.8 14.7 54.5 13.9 91/9 90/10 2677G>T/A 18/19 56/53 26/28 0.492 Minoru F-1 [30] Japan Japanese HCC b /HP PCR-SSCP 8 70 7 - - 43/15 61 2677G>T/A 12/16 29/30 17/15 0.900 Minoru F-2 [30] Japan Japanese HCC b /HP PCR-SSCP 8 70 7 - - 43/15 61 3435C>T 16/14 29/39 13/8 0.023 Ren YQ [31] China Chinese HCC a /HP CRS-PCR 7 58.7 11.3 55.8 15.6 512/177 499/181 4125A>C 299/312 289/303 101/65 0.487 Gao J-1 [32] China Chinese HCC a /HP CRS-PCR 7 57.9 13.7 53.5 14.9 278/75 269/66 335T>C 141/172 150/128 62/35 0.132 Gao J-2 [32] China Chinese HCC a /HP CRS-PCR 7 57.9 13.7 53.5 14.9 278/75 269/66 3073A>C 116/155 158/139 79/41 0.261 Rui J [33] China Chinese HCC a /HP MALDI-TOF-MS 8 46 - 48 - 95/14 90/19 1236C>T 19/22 54/48 36/39 0.310 Yang D-1 [34] China Chinese HCC a /HP CRS-PCR 8 59.2 14.3 58.3 15.3 418/287 429/297 159G>T 312/342 298/308 95/76 0.591 Yang D-2 [34] China Chinese HCC a /HP CRS-PCR 8 59.2 14.3 58.3 15.3 418/287 429/297 1465C>T 294/367 306/292 105/67 0.420 Li XF [35] China Chinese HCC a /HP CRS-PCR 8 58.6 14.5 59.1 13.5 409/236 445/213 3751G>A 283/325 271/286 91/47 0.136 Wan YY [36] China Chinese HCC a /HP CRS-PCR 8 57.7 13.2 58.6 14.2 399/233 435/210 1564A>T 278/311 266/276 88/58 0.772 Total 4407 4436 1788/2055 1906/1902 713/479 1/1, 1/2, and 2/2 represent wild homozygous genotype, wild/mutant heterozygous genotype, and mutant homozygous genotype, respectively HCC hepatocellular carcinoma, HP healthy people, CHC chronic hepatitis C, CHB chronic hepatitis B, B-^ unclear, PCR-RFLP polymerase chain reaction-restriction fragment length polymorphism, PCR-SSCP polymerase chain reaction-single-strand conformation polymorphism, CRS-PCR created restriction site-polymerase chain reaction, MALDI-TOF-MS matrix-assisted laser desorption ionization timeof-flight mass spectrometry a Hepatitis B-related HCC b Hepatitis C-related HCC Table 2 Characteristics of the MDR1 polymorphisms included in the meta-analysis Studies Polymorphism site Exon location Variation type A.A. alteration FI a FI score a Feature key P. location description b P. function description b Chen Y [29] 2677G>T/A Exon 21 Nonsynonymous S893A Neutral -0.98 Topological domain Cytoplasmic ABC transmembrane type 1 S893T Low 1.66 Topological domain Cytoplasmic ABC transmembrane type 1 Minoru F-1 [30] 2677G>T/A Exon 21 Nonsynonymous S893A Neutral -0.98 Topological domain Cytoplasmic ABC transmembrane type 1 S893T Low 1.66 Topological domain Cytoplasmic ABC transmembrane type 1 Minoru F-2 [30] 3435C>T Exon 26 Synonymous - - - Topological domain Cytoplasmic ABC transporter Ren YQ [31] 4125A>C Exon 28 Nonsynonymous E1211A Low 1.805 Topological domain Cytoplasmic ABC transporter Gao J-1 [32] 335T>C 5'-UTR Noncoding - - - - - - Gao J-2 [32] 3073A>C Exon 22 Nonsynonymous L860F Medium 2.715 Transmembrane Helical ABC transmembrane type 1 Rui J [33] 1236C>T Exon 12 Synonymous - - - Topological domain Cytoplasmic ABC transporter Yang D-1 [34] 159G>T Exon 5 Synonymous - - - Transmembrane Helical ABC transmembrane type 1 Yang D-2 [34] 1465C>T Exon 14 Nonsynonymous R489C Medium 1.97 Topological domain Cytoplasmic ABC transporter Li XF [35] 3751G>A Exon 28 Nonsynonymous V1251I Neutral -0.365 Topological domain Cytoplasmic ABC transporter Wan YY [36] 1564A>T Exon 15 Nonsynonymous T522S Low 1.42 Topological domain Cytoplasmic ABC transporter A.A. amino acid, FI functional impact, ABC ATP-binding cassette a The functional impact is evaluated using online MutationAssessor.org b Location of SNP in the protein structure is assessed by Uniprot.org online service sequence subgroup analyses revealed that cytoplasmic polymorphisms correlated with a significantly higher HCC risk (cytoplasmic subgroup: OR=1.28, 95 % CI 1.19-1.37; P<0.00001), whereas transmembrane polymorphisms exhibited site-specific results (Gao J-2, 2013: OR=1.65, 95 % CI 1.32-2.05, P<0.0001; Yang D-1, 2013: OR=1.65, 95 % CI 0.98-1.33, P=0.10). Login to comment

[hide] Drug Transporter Genetic Variants Are Not Associat... PLoS One. 2015 Nov 4;10(11):e0141931. doi: 10.1371/journal.pone.0141931. eCollection 2015. Nishijima T, Hayashida T, Kurosawa T, Tanaka N, Oka S, Gatanaga H
Drug Transporter Genetic Variants Are Not Associated with TDF-Related Renal Dysfunction in Patients with HIV-1 Infection: A Pharmacogenetic Study.
PLoS One. 2015 Nov 4;10(11):e0141931. doi: 10.1371/journal.pone.0141931. eCollection 2015., [PMID:26535588]

Abstract [show]
OBJECTIVE: To investigate whether single nucleotide polymorphisms (SNP) of drug transporter proteins for TDF is a risk factor for TDF-related renal function decrement. METHODS: This study investigated the association between 3 SNPs (ABCC2-24, 1249, and ABCB1 2677), which are shown to be associated with TDF-induced tubulopathy, and clinically important renal outcomes (>10ml/min/1.73m2 decrement in eGFR relative to baseline, >25% decrement in eGFR, and eGFR <60ml/min/1.73m2) in 703 HIV-1-infected Japanese patients who initiated TDF-containing antiretroviral therapy (ART). Genotyping was performed by allelic discrimination using TaqMan 5'-nuclease assays. RESULTS: 95% of the study patients were males and 66% were treatment-naive, with median CD4 count of 249/mul, median baseline eGFR of 96ml/min/1.73m2 (IQR 84.6-109.2), and median exposure to TDF of 3.66 years (IQR 1.93-5.59). The frequencies of genotypes at -24, 1249 of ABCC2, and 2677 of ABCB1 were neither different between patients with decrement in eGFR of >10ml/min/1.73m2 and those without such decrement (ABCC2: -24, p = 0.53, 1249, p = 0.68; ABCB1: 2677, p = 0.74), nor between those without and with the other two renal outcomes (>25% decrement: ABCC2: -24, p = 0.83, 1249, p = 0.97, ABCB1: 2677, p = 0.40; eGFR <60ml/min/1.73m2: ABCC2: -24, p = 0.51, 1249, p = 0.81, ABCB1: 2677, p = 0.94). Logistic regression analysis showed that the risk genotype of the three SNPs were not associated with any of the three renal outcomes, respectively. Logistic regression model that applied either dominant, recessive, or additive model yielded the same results. CONCLUSIONS: SNPs of the drug transporters for TDF are not associated with clinically important renal outcomes in patients who initiated TDF-containing ART.

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97 >10 ml/min/1.73 m2 decrement in eGFR from baseline >25% decrement in eGFR from baseline eGFR <60 ml/min/1.73 m2 Amino acid >10 ml/min/ 1.73 m2 decrement (n = 624) No decrement (n = 79) P value* >25% decrement (n = 119) No decrement (n = 584) P value* <60 ml/ min/1.73 m2 (n = 126) No decrement (n = 577) P value* ABCC2 (MRP2) -24 C!T, rs717620 C/C 382 (61) 51 (65) 76 (64) 357 (61) 83 (66) 350 (61) C/T 215 (35) 27 (34) 0.53 38 (32) 204 (35) 0.83 38 (30) 204 (35) 0.51 T/T 27 (4) 1 (1) 5 (4) 23 (4) 5 (4) 23 (4) 1249 G!A, rs2273697 Val417Ile G/G 483 (78) 61 (77) 93 (78) 451 (77) 100 (79) 444 (77) A/G 132 (21) 16 (20) 0.68 24 (20) 124 (21) 0.97 24 (19) 124 (21) 0.81 A/A 9 (1) 2 (3) 2 (2) 9 (2) 2 (2) 9 (2) ABCB1 (P-glycoprotein) 2677T!A/ G, rs2032582 A: Ser893Thr G: Ser893Ala T/T 112 (18) 13 (16) 19 (16) 106 (18) 21 (17) 104 (18) T/A 77 (12) 13 (16) 22 (18) 68 (11) 18 (14) 72 (12) G/G 122 (20) 13 (16) 0.74 20 (17) 115 (20) 0.40 21 (17) 114 (20) 0.94 G/T 195 (31) 29 (37) 39 (33) 185 (32) 41 (32) 183 (32) G/A 96 (15) 9 (12) 17 (14) 88 (15) 20 (16) 85 (15) A/A 22 (4) 2 (3) 2 (2) 22 (4) 5 (4) 19 (3) *By use of Fisher`s exact test for 2&#d7;3 table (2&#d7;6 table for rs2032582). Login to comment
102 >10 ml/min/1.73 m2 decrement in eGFR from baseline >25% decrement in eGFR from baseline eGFR <60 ml/min/1.73 m2 Amino acid >10 ml/min/ 1.73 m2 decrement (n = 624) No decrement (n = 79) P value* >25% decrement (n = 119) No decrement (n = 584) P value* <60 ml/ min/1.73 m2 (n = 126) No decrement (n = 577) P value* ABCC2 (MRP2) -24 C!T, rs717620 C/C 302 (62) 131 (61) 79 (64) 354 (61) 38 (66) 395 (61) C/T 166 (34) 76 (36) 0.59 39 (31) 203 (35) 0.62 18 (31) 224 (35) 0.91 T/T 22 (4) 6 (3) 6 (5) 22 (4) 2 (3) 26 (4) 1249 G!A, rs2273697 Val417Ile G/G 386 (79) 158 (74) 98 (79) 446 (77) 45 (78) 499 (77) A/G 95 (19) 53 (25) 0.20 24 (19) 124 (21) 0.86 12 (21) 136 (21) 1.00 A/A 9 (2) 2 (1) 2 (2) 9 (2) 1 (1) 10 (2) ABCB1 (P-glycoprotein) 2677T!A/ G, rs2032582 A: Ser893Thr G: Ser893Ala T/T 83 (17) 42 (20) 19 (15) 106 (18) 9 (15) 116 (18) T/A 62 (13) 28 (13) 24 (19) 66 (11) 8 (14) 82 (13) G/G 95 (19) 40 (19) 0.95 21 (17) 114 (20) 0.22 12 (21) 123 (19) 0.76 G/T 157 (32) 67 (31) 41 (33) 183 (32) 15 (26) 209 (32) G/A 75 (15) 30 (14) 17 (14) 88 (15) 12 (21) 93 (14) A/A 18 (4) 6 (3) 2 (2) 22 (4) 2 (3) 22 (4) *By use of Fisher`s exact test for 2&#d7;3 table (2&#d7;6 table for rs2032582). Login to comment