Influence of SLCO1B1 Polymorphisms on the Pharmacokinetics of Mycophenolic Acid in Renal Transplant Recipients.

IF 2.1 4区 医学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Jiawen Liu, Yongqian Zhu, Jiexiu Zhang, Jintao Wei, Ming Zheng, Zeping Gui, Hao Chen, Li Sun, Zhijian Han, Jun Tao, Xiaobin Ju, Ruoyun Tan, Min Gu, Zijie Wang
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引用次数: 1

Abstract

Objective: This study was designed to analyze the correlation between single nucleotide polymorphisms (SNP) related to drug metabolism and pharmacokinetics of mycophenolic acid (MPA) during long-term follow-up.

Materials and method: A retrospective cohort study involving 71 renal transplant recipients was designed. Blood samples were collected to extract total DNAs, followed by target sequencing based on next-generation sequencing technology. The MPA area under the curve (AUC) was calculated according to the formula established in our center. The general linear model and linear regression model were used to analyze the association between SNPs and MPA AUC.

Results: A total of 689 SNPs were detected in our study, and 90 tagger SNPs were selected after quality control and linkage disequilibrium analysis. The general linear model analysis showed that 9 SNPs significantly influenced MPA AUC. A forward linear regression was conducted, and the model with the highest identical degree (r2=0.55) included 4 SNPs (SLCO1B1: rs4149036 [P < 0.0001], ABCC2: rs3824610 [P = 0.005], POR: rs4732514 [P = 0.006], ABCC2: rs4148395 [P = 0.007]) and 6 clinical factors (age [P < 0.0001], gender [P < 0.0001], the incident of acute rejection (AR) [P = 0.001], albumin [P < 0.0001], duration after renal transplantation [P = 0.01], lymphocyte numbers [P = 0.026]). The most relevant SNP to MPA AUC in this model was rs4149036. The subgroup analysis showed that rs4149036 had a significant influence on MPA AUC in the older group (P = 0.02), high-albumin group (P = 0.01), male group (P = 0.046), and both within-36-month group (P = 0.029) and after-36-month group (P = 0.041). The systematic review included 4 studies, and 2 of them showed that the mutation in SLCO1B1 resulted in lower MPA AUC, which was contrary to our study.

Conclusion: A total of 4 SNPs (rs4149036, rs3824610, rs4148395, and rs4732514) were identified to be significantly correlated with MPA AUC. Rs4149036, located in SLCO1B1, was suggested to be the most relevant SNP to MPA AUC, which had a stronger influence on recipients who were elder, male, or with high serum albumin. Furthermore, 6 clinical factors, including age, gender, occurrence of acute rejection, serum albumin, time from kidney transplantation, and blood lymphocyte numbers, were found to affect the concentration of MPA.

SLCO1B1多态性对肾移植受者霉酚酸药代动力学的影响
目的:本研究旨在分析长期随访中与药物代谢相关的单核苷酸多态性(SNP)与霉酚酸(MPA)药代动力学的相关性。材料和方法:对71例肾移植受者进行回顾性队列研究。采集血样提取总dna,然后基于下一代测序技术进行目标测序。曲线下MPA面积(AUC)根据本中心建立的公式计算。采用一般线性模型和线性回归模型分析snp与MPA AUC的关系。结果:本研究共检测到689个snp,经质量控制和连锁不平衡分析筛选出90个标记snp。一般线性模型分析显示,9个snp对MPA AUC有显著影响。对4个snp (SLCO1B1: rs4149036 [P < 0.0001]、ABCC2: rs3824610 [P = 0.005]、POR: rs4732514 [P = 0.006]、ABCC2: rs4148395 [P = 0.007])和6个临床因素(年龄[P < 0.0001]、性别[P < 0.0001]、急性排斥反应(AR)发生率[P = 0.001]、白蛋白[P < 0.0001]、肾移植术后持续时间[P = 0.01]、淋巴细胞数量[P = 0.026])进行正线性回归,模型一致性最高(r2=0.55)。该模型中与MPA AUC最相关的SNP为rs4149036。亚组分析显示,rs4149036对老年组(P = 0.02)、高白蛋白组(P = 0.01)、男性组(P = 0.046)、36月龄组(P = 0.029)和36月龄组(P = 0.041)的MPA AUC均有显著影响。系统综述纳入4项研究,其中2项研究显示SLCO1B1突变导致MPA AUC降低,这与我们的研究相反。结论:共鉴定出4个snp (rs4149036、rs3824610、rs4148395、rs4732514)与MPA AUC显著相关。位于SLCO1B1的Rs4149036被认为是与MPA AUC最相关的SNP,对老年人、男性或血清白蛋白高的受体有更大的影响。此外,年龄、性别、急性排斥反应的发生、血清白蛋白、肾移植时间、血淋巴细胞数量等6个临床因素影响MPA浓度。
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来源期刊
Current drug metabolism
Current drug metabolism 医学-生化与分子生物学
CiteScore
4.30
自引率
4.30%
发文量
81
审稿时长
4-8 weeks
期刊介绍: Current Drug Metabolism aims to cover all the latest and outstanding developments in drug metabolism, pharmacokinetics, and drug disposition. The journal serves as an international forum for the publication of full-length/mini review, research articles and guest edited issues in drug metabolism. Current Drug Metabolism is an essential journal for academic, clinical, government and pharmaceutical scientists who wish to be kept informed and up-to-date with the most important developments. The journal covers the following general topic areas: pharmaceutics, pharmacokinetics, toxicology, and most importantly drug metabolism. More specifically, in vitro and in vivo drug metabolism of phase I and phase II enzymes or metabolic pathways; drug-drug interactions and enzyme kinetics; pharmacokinetics, pharmacokinetic-pharmacodynamic modeling, and toxicokinetics; interspecies differences in metabolism or pharmacokinetics, species scaling and extrapolations; drug transporters; target organ toxicity and interindividual variability in drug exposure-response; extrahepatic metabolism; bioactivation, reactive metabolites, and developments for the identification of drug metabolites. Preclinical and clinical reviews describing the drug metabolism and pharmacokinetics of marketed drugs or drug classes.
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