Evidence map›Paper›PMID 40761401›Full record

ArticleFrontiers in pharmacology2025

Clinical significance and gene prediction of a novel classification system based on tacrolimus concentration-to-dose ratio in the early post-liver transplant period.

Junwei Fan, Peihao Wen, Liyun Yuan, Yan Xia, Shijie Hu, Xiaoqing Zhang, Zhihai Peng

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Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Junwei FanDepartment of General Surgery, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, China.
Peihao Wen *Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Liyun Yuan *CAS Key Laboratory of Computational Biology, Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
Yan XiaDepartment of General Surgery, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, China.
Shijie HuDepartment of General Surgery, Shidong Hospital Affiliated to University of Shanghai for Science and Technology, Shanghai, China.
Xiaoqing ZhangDepartment of Pharmacy, The International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Zhihai PengDepartment of General Surgery, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Classification system of tacrolimus elimination and its clinical significance has not been well described in liver transplantation. This study aimed to present a novel tacrolimus clearance clinical-FIS (Fast-Intermediate-Slow) classification and its gene prediction system. Methods: Patients from 3 transplant centers were enrolled in this study. All recipients and their corresponding donor livers from center 1 were genotyped using an Affymetrix DMET Plus microarray, and association analysis was performed using trough blood concentration/weight-adjusted-dose ratios (CDR, (ng/mL)/(mg/kg)). The candidate-associated loci were then sequenced in center 2 and center 3 patients for verification. Results: A clinical classification based on tacrolimus CDR can effectively divide liver transplantation patients into fast elimination (FE), intermediate elimination (IE), and slow elimination (SE) groups, which we called the clinical-FIS classification. Trough blood concentrations in the clinical-SE group during the early postoperative period were higher than those in the clinical-FE and clinical-IE groups, which could lead to delayed recovery of liver (P = 0.0373) and kidney function (P = 0.0135) and a higher infection rate (P = 0.0086). The prediction accuracy of the current CPIC (Clinical Pharmacogenetics Implementation Consortium)-EIP metabolizer classification based on recipient CYP3A5 rs776746 genotype for clinical-FIS classification was only 35.56%. A newly established genetic-EIP classification including major effect genetic factors (donor and recipient CYP3A5 rs776746) and minor effect genetic factors (recipient SULT1E1 rs3775770 and donor SLC7A8 rs7141505) showed 73.2% overall consistency with the former clinical FIS classification. Conclusion: Our study presented a novel tacrolimus clearance classification, clinical-FIS, and then proposed a novel prospective genetic-EIP classification as a genotyping basis for precisely predicting the clinical-FIS.

Indexed as

drug metabolismgene polymorphismliver transplantationpersonalized medicinetacrolimus

Identifiers

PMID40761401
PMCPMC12319242

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