ReviewClinical pharmacokinetics2014
The role of pharmacogenetics in the disposition of and response to tacrolimus in solid organ transplantation.
Review in Clinical pharmacokinetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04645667 (Development of a Population Pharmacokinetic Model to Optimize Tacrolimus Dosing in Adult Recipients of Allogeneic Hematopoietic Stem Cell Transplant.), which is not on this map. Cited by 123 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Development of a Population Pharmacokinetic Model to Optimize Tacrolimus Dosing in Adult Recipients of Allogeneic Hematopoietic Stem Cell Transplant.
Who cites it
123 citing papers in PubMed, 4 syntheses or guidelines pooled it, 231 citations in OpenAlex.
- A Systematic Review and Meta-Analysis of Pharmacogenetic Studies in Patients with Chronic Kidney Disease.International journal of molecular sciences · 2021Pooled it
- Therapeutic Efficacy and Adverse Events of Tacrolimus in Patients with Crohn's Disease: Systematic Review and Meta-Analysis.Digestive diseases and sciences · 2019Pooled it
- Risk factors for calcineurin inhibitor nephrotoxicity after renal transplantation: a systematic review and meta-analysis.Drug design, development and therapy · 2018Pooled it
- Pooled it
- Tacrolimus Exposure is Associated with Acute Rejection in the Early Phase After Kidney Transplantation: A Joint Modeling Approach.Therapeutic drug monitoring · 2025Trial
- The effect of the very low dosage diltiazem on tacrolimus exposure very early after kidney transplantation: a randomized controlled trial.Scientific reports · 2022Trial
- Evaluation of the performance of a prior tacrolimus population pharmacokinetic kidney transplant model among adult allogeneic hematopoietic stem cell transplant patients.Clinical and translational science · 2021Trial
- A Population Pharmacokinetic Model Does Not Predict the Optimal Starting Dose of Tacrolimus in Pediatric Renal Transplant Recipients in a Prospective Study: Lessons Learned and Model Improvement.Clinical pharmacokinetics · 2020Trial
- Population Pharmacokinetics and Bayesian Estimators for Refined Dose Adjustment of a New Tacrolimus Formulation in Kidney and Liver Transplant Patients.Clinical pharmacokinetics · 2017Trial
- A pharmacogenomic study on the pharmacokinetics of tacrolimus in healthy subjects using the DMETThe pharmacogenomics journal · 2017Trial
- Impact of cytochrome P450 2C19 polymorphisms on the pharmacokinetics of tacrolimus when coadministered with voriconazole.Journal of clinical pharmacology · 2016Trial
- Higher tacrolimus concentrations early after transplant reduce the risk of acute GvHD in reduced-intensity allogeneic stem cell transplantation.Bone marrow transplantation · 2016Trial
- Concentration-to-Dose Ratio Differences Between Once-Daily Tacrolimus Formulations: A Five-Year Real-World Pharmacokinetic Study in Kidney Transplantation.European journal of drug metabolism and pharmacokinetics · 2026Article
- Article
- Introduction to Pharmacogenomics: Role of the Histocompatibility and Immunogenetics Laboratory in Personalised Medicine-Current Status and Future Prospects.International journal of immunogenetics · 2026Review
- Effects of CYP3A4, CYP3A5, and ABCB1 genetic variants on tacrolimus metabolism during the early period after kidney transplantation.The pharmacogenomics journal · 2026Article
- External evaluation of population pharmacokinetic models for tacrolimus in kidney transplant recipients: implications for model-informed precision dosing.BMC nephrology · 2026Article
- Phenotypic personalized tacrolimus dosing: a step toward precision immunosuppression in liver transplantation.Hepatobiliary surgery and nutrition · 2026Article
- An Integrated Population Pharmacokinetic and Machine Learning Model for Predicting Tacrolimus Exposure in Adult Patients with Nephrotic Syndrome.Drug design, development and therapy · 2026Article
- Discordance between trough concentration and tacrolimus exposure on the day of kidney transplantation: a prospective pharmacokinetic study.Frontiers in pharmacology · 2026Article
63 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The calcineurin inhibitor tacrolimus is the backbone of immunosuppressive drug therapy after solid organ transplantation. Tacrolimus is effective in preventing acute rejection but has considerable toxicity and displays marked inter-individual variability in its pharmacokinetics and pharmacodynamics. The genetic basis of these phenomena is reviewed here. With regard to its pharmacokinetic variability, a single nucleotide polymorphism (SNP) in cytochrome P450 (CYP) 3A5 (6986A>G) has been consistently associated with tacrolimus dose requirement. Patients expressing CYP3A5 (those carrying the A nucleotide, defined as the *1 allele) have a dose requirement that is around 50 % higher than non-expressers (those homozygous for the G nucleotide, defined as the *3 allele). A randomised controlled study in kidney transplant recipients has demonstrated that a CYP3A5 genotype-based approach to tacrolimus dosing leads to more patients reaching the target concentration early after transplantation. However, no improvement of clinical outcomes (rejection incidence, toxicity) was observed, which may have been the result of the design of this particular study. In addition to CYP3A5 genotype, other genetic variants may also contribute to the variability in tacrolimus pharmacokinetics. Among these, the CYP3A4*22 and POR*28 SNPs are the most promising. Individuals carrying the CYP3A4*22 T-variant allele have a lower tacrolimus dose requirement than individuals with the CYP3A4*22 CC genotype and this effect appears to be independent of CYP3A5 genotype status. Individuals carrying the POR*28 T-variant allele have a higher tacrolimus dose requirement than POR*28 CC homozygotes but this association was only found in CYP3A5-expressing individuals. Other, less well-defined SNPs have been inconsistently associated with tacrolimus dose requirement. It is envisaged that in the future, algorithms incorporating clinical, demographic and genetic variables will be developed that will aid clinicians with the determination of the tacrolimus starting dose for an individual transplant recipient. Such an approach may limit early tacrolimus under-exposure and toxicity. With regard to tacrolimus pharmacodynamics, no strong genotype-phenotype relationships have been identified. Certain SNPs associate with rejection risk but these observations await replication. Likewise, the genetic basis of tacrolimus-induced toxicity remains unclarified. SNPs in the genes encoding for the drug transporter ABCB1 and the CYP3A enzymes may relate to chronic nephrotoxicity but findings have been inconsistent. No genetic markers reliably predict new-onset diabetes mellitus after transplantation, hypertension or neurotoxicity. The CYP3A5*1 SNP is currently the most promising biomarker for tailoring tacrolimus treatment. However, before CYP3A5 genotyping is incorporated into the routine clinical care of transplant recipients, prospective clinical trials are needed to determine whether such a strategy improves patient outcomes. The role of pharmacogenetics in tacrolimus pharmacodynamics should be explored further by the study of intra-lymphocyte and tissue tacrolimus concentrations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.