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      Impact of the CYP3A5, CYP3A4, COMT, IL-10 and POR Genetic Polymorphisms on Tacrolimus Metabolism in Chinese Renal Transplant Recipients

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          Abstract

          Tacrolimus is a widely used immunosuppressive drug for preventing the rejection of solid organ transplants. The efficacy of tacrolimus shows considerable variability, which might be related to genetic variation among recipients. We conducted a retrospective study of 240 Chinese renal transplant recipients receiving tacrolimus as immunosuppressive drug. The retrospective data of all patients were collected for 40 days after transplantation. Seventeen SNPs of CYP3A5, CYP3A4, COMT, IL-10 and POR were identified by the SNaPshot assay. Tacrolimus blood concentrations were obtained on days 1–3, days 6–8 and days 12–14 after transplantation, as well as during the period of the predefined therapeutic concentration range. Kruskal–Wallis test was used to examine the effect of genetic variation on the tacrolimus concentration/dose ratio ( C 0/ D) at different time points. Chi-square test was used to compare the proportions of patients who achieved the target C 0 range in the different genotypic groups at weeks 1, 2, 3 and 4 after transplantation. After correction for multiple testing, there was a significant association of C 0/ D with CY P3A5*3, CYP3A4*1G and CYP3A4 rs4646437 T>C at different time points after transplantation. The proportion of patients in the IL-10 rs1800871-TT group who achieved the target C 0 range was greater ( p = 0.004) compared to the IL-10 rs1800871-CT and IL-10 rs1800871-CC groups at week 3 after transplantation. CYP3A5*3, CYP3A4 *1G, CYP3A4 rs4646437 T>C and IL-10 rs1800871 C>T might be potential polymorphisms affecting the interindividual variability in tacrolimus metabolism among Chinese renal transplant recipients.

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          Optimization of initial tacrolimus dose using pharmacogenetic testing.

          Retrospective studies have demonstrated that patients who are expressors of cytochrome P4503A5 (CYP3A5) require a higher tacrolimus dose to achieve a therapeutic trough concentration (C(0)). The aim of this study was to evaluate this effect prospectively by pretransplantation adaptation. We randomly assigned 280 renal transplant recipients to receive tacrolimus either according to CYP3A5 genotype or according to the standard daily regimen. The primary end point was the proportion of patients within the targeted C(0). Secondary end points included the number of dose modifications and the delay in achieving the targeted C(0). In the group receiving the adapted dose, a higher proportion of patients had values within the targeted C(0) at day 3 after initiation of tacrolimus (43.2% vs. 29.1%; P = 0.03); they required fewer dose modifications, and the targeted C(0) was achieved by 75% of these patients more rapidly. The clinical end points were similar in the two groups. Pharmacogenetic adaptation of the daily dose of tacrolimus is associated with improved achievement of the target C(0). Whether this improvement will affect clinical outcomes requires further evaluation.
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            A new functional CYP3A4 intron 6 polymorphism significantly affects tacrolimus pharmacokinetics in kidney transplant recipients.

            Tacrolimus (Tac) is a potent immunosuppressant with considerable toxicity. Tac pharmacokinetics varies between individuals and thus complicates its use in preventing rejection after kidney transplantation. This variability might be caused by genetic polymorphisms in metabolizing enzymes. We used TaqMan analyses to evaluate the impact of a newly discovered CYP3A4 (cytochrome P450, family 3, subfamily A, polypeptide 4) single-nucleotide polymorphism (SNP) (rs35599367C>T; CYP3A4*22) on Tac pharmacokinetics in 185 renal transplant recipients who participated in an international randomized controlled clinical trial (fixed-dose, concentration-controlled study). The overall mean daily-dose requirement to reach the same predose Tac blood concentration was 33% lower for carriers of the T variant allele than for rs35599367CC patients (95% CI, -46% to -20%; P = 0.018). When combined with the *3 genotype of the CYP3A5 (cytochrome P450, family 3, subfamily A, polypeptide 5) gene, the rs35599367C>T SNP was also associated with a risk of supratherapeutic Tac concentrations (>15 μg/L) during the first 3 days after surgery, with an odds ratio of 8.7 for carriers of the CYP3A4 T allele plus CYP3A5*3/*3 (P = 0.027) and 4.2 for the CYP3A4 CC homozygotes plus CYP3A5*3/*3 (P = 0.002), compared with CYP3A4 CC homozygotes having 1 or 2 CYP3A5*1 alleles. The overall increase in the Tac dose-adjusted trough blood concentration was +179% for carriers of the CYP3A4 T allele with CYP3A5*3/*3 (P T polymorphism is associated with a significantly altered Tac metabolism and therefore increases the risk of supratherapeutic Tac concentrations early after transplantation. Analysis of this CYP3A4*22 SNP may help in identifying patients at risk of Tac overexposure.
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              Novel polymorphisms associated with tacrolimus trough concentrations: results from a multicenter kidney transplant consortium.

              The CYP4503A5*1 genotype is associated with lower tacrolimus concentrations. Although its effect is important, it incompletely explains the variability in tacrolimus concentrations and has a relatively low minor allele frequency in whites relative to African Americans (AA). We studied clinical and recipient genetic correlates of dose-normalized tacrolimus troughs (n=12,277) in the first 6 months posttransplant using a customized single-nucleotide polymorphism chip with 2722 variants in a large, ethnically diverse (144 AA and 551 non-AA) adult kidney transplant population through a seven-center consortium. During the 6-month study, AAs had consistently lower median (interquartile range) troughs than non-AAs, 6.2 (4.4-8.4) ng/mL vs. 8.3 (6.4-10.4) ng/mL (P<0.0001), despite 60% higher daily doses, 8 (5-10) mg vs. 5 (4-7) mg (P<0.0001). The median tacrolimus trough concentration in week 1 posttransplant was particularly low in AAs (2.1 [1.2-3.5] ng/mL) compared with non-AAs (5.0 [3.1-8.2] ng/mL) (P<0.0001), despite similar initial doses. In single-variant analysis, CYP3A5*3 (rs776746) was the top variant (P=2.4×10) associated with troughs. After adjustment for CYP3A5*3, clinical factors and race, 35 additional variants were identified (P<0.01, not significant at false discovery rate 20%). In the final multivariant, regression models beginning with these variants and clinical factors, seven variants were identified in the non-AA and seven variants in the AA group towards the first trough concentrations. Rs776746 (CYP3A5), rs2239393 (COMT) and diabetes were the only factors common in both populations. We identified variants beyond CYP3A5*3, which may further explain pharmacokinetic variability of tacrolimus and demonstrated that important variants differ by race.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                21 January 2014
                : 9
                : 1
                : e86206
                Affiliations
                [1 ]Department of Surgery, Nanfang Hospital, Southern Medical University, Guangzhou, PR China
                [2 ]Department of Medical Genetics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, PR China
                [3 ]Department of Clinical Laboratory, Nanfang Hospital, Southern Medical University, Guangzhou, PR China
                [4 ]College of Pharmacy, University of Cincinnati Academic Health Centre, Cincinnati, Ohio, United States of America
                [5 ]Department of Pharmacy, Nanfang Hospital, Southern Medical University, Guangzhou, PR China
                [6 ]Department of Biostatistics, School of Public Health and Tropical Medicine, Southern Medical University, Guangzhou, PR China
                Universite de Montreal, Canada
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: L. Li. Performed the experiments: C-JL W-ML H-XJ PZ. Analyzed the data: L. Li L. Lin Z-YZ Y-JZ X-HT LZ. Contributed reagents/materials/analysis tools: C-JL. Wrote the paper: L. Li C-JL.

                Article
                PONE-D-13-19899
                10.1371/journal.pone.0086206
                3897654
                24465960
                705ca1cf-bade-4373-becb-78e97bfcacd2
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 14 May 2013
                : 9 December 2013
                Page count
                Pages: 9
                Funding
                This work was funded by a programme grant from the National Natural Science Fund of China to Liang Li (NSFC, No. 81101328), the Pearl River Young Talents of Science and Technology in Guangzhou to Liang Li (No. 2013J2200050), the Natural Science Fund of Guangdong to Liang Li (No. S2012040007745), the Research Fund for the President of Nanfang Hospital to Chuan-Jiang Li. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biotechnology
                Pharmacogenomics
                Computational Biology
                Genomics
                Pharmacogenomics
                Population Genetics
                Genetic Polymorphism
                Evolutionary Biology
                Population Genetics
                Genetic Polymorphism
                Genetics
                Population Genetics
                Genetic Polymorphism
                Genomics
                Genomic Medicine
                Pharmacogenomics
                Pharmacogenomics
                Population Biology
                Population Genetics
                Genetic Polymorphism
                Medicine
                Clinical Genetics
                Drugs and Devices
                Pharmacoepidemiology
                Pharmacogenetics
                Epidemiology
                Pharmacoepidemiology
                Nephrology
                Renal Transplantation

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