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

被引:3
作者
Liu, Jiawen [1 ]
Zhu, Yongqian [2 ]
Zhang, Jiexiu [1 ]
Wei, Jintao [3 ]
Zheng, Ming [1 ]
Gui, Zeping [4 ]
Chen, Hao [1 ]
Sun, Li [1 ]
Han, Zhijian [1 ]
Tao, Jun [1 ]
Ju, Xiaobin [1 ]
Tan, Ruoyun [1 ]
Gu, Min [1 ,4 ]
Wang, Zijie [1 ]
机构
[1] Nanjing Med Univ, Affiliated Hosp 1, Dept Urol, Nanjing 210029, Peoples R China
[2] Nanjing Med Univ, Affiliated Hosp 1, Dept Med Qual Management, Nanjing 210029, Peoples R China
[3] Zhejiang Univ, Affiliated Hosp 2, Dept Emergency Med, Sch Med, Hangzhou 310003, Peoples R China
[4] Nanjing Med Univ, Affiliated Hosp 2, Dept Urol, Nanjing 210003, Peoples R China
基金
中国国家自然科学基金;
关键词
Kidney transplantation; mycophenolic acid; single nucleotide polymorphism; pharmacokinetic; drug metabolism; next-generation sequencing; LIMITED SAMPLING STRATEGY; KIDNEY-TRANSPLANT; 388A-GREATER-THAN-G POLYMORPHISM; GENETIC POLYMORPHISMS; SLCO1B1-ASTERISK-15; OPPORTUNITIES; PITAVASTATIN; DISPOSITION; UGT2B7;
D O I
10.2174/1389200224666230124121304
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
ObjectiveThis 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 MethodA 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.ResultsA 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 (r(2)=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.ConclusionA 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.
引用
收藏
页码:114 / 123
页数:10
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