ArticlePharmacogenetics and genomics2012
The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients.
Article in Pharmacogenetics and genomics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods for the Analysis and Interpretation for Rare Variants Associated with Complex Traits.Current protocols in human genetics · 2019Pooled it
- A pharmacogenomic study on the pharmacokinetics of tacrolimus in healthy subjects using the DMETThe pharmacogenomics journal · 2017Trial
- A published pharmacogenetic algorithm was poorly predictive of tacrolimus clearance in an independent cohort of renal transplant recipients.British journal of clinical pharmacology · 2013Trial
- Discordant associations between SLCO1B1 521T→C and plasma levels of ritonavir-boosted protease inhibitors in AIDS clinical trials group study A5146.Therapeutic drug monitoring · 2013Trial
- Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging.Cell genomics · 2026Review
- Analytical Models to Optimize Tacrolimus Dosing in Solid Organ Transplantation: A Systematic Review.Pharmaceutics · 2026Review
- Sensitivity of estimated tacrolimus population pharmacokinetic profile to assumed dose timing and absorption in real-world data and simulated data.British journal of clinical pharmacology · 2022Article
- Individualized medication based on pharmacogenomics and treatment progress in children with IgAV nephritis.Frontiers in pharmacology · 2022Review
- CYP3A-status is associated with blood concentration and dose-requirement of tacrolimus in heart transplant recipients.Scientific reports · 2021Article
- Precision Dosing for Tacrolimus Using Genotypes and Clinical Factors in Kidney Transplant Recipients of European Ancestry.Journal of clinical pharmacology · 2021Observational
- Functional CYP3A variants affecting tacrolimus trough blood concentrations in Chinese renal transplant recipients.The pharmacogenomics journal · 2021Article
- Building longitudinal medication dose data using medication information extracted from clinical notes in electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Article
- Effect of the Most Relevant CYP3A4 and CYP3A5 Polymorphisms on the Pharmacokinetic Parameters of 10 CYP3A Substrates.Biomedicines · 2020Article
- Development of a System for Postmarketing Population Pharmacokinetic and Pharmacodynamic Studies Using Real-World Data From Electronic Health Records.Clinical pharmacology and therapeutics · 2020Article
- medExtractR: A targeted, customizable approach to medication extraction from electronic health records.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Gene-Based Dose Optimization in Children.Annual review of pharmacology and toxicology · 2020Review
- Personalized medicine: going to the dogs?Human genetics · 2019Review
- PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison.BMC bioinformatics · 2019Article
- Whole exome sequencing for the identification of CYP3A7 variants associated with tacrolimus concentrations in kidney transplant patients.Scientific reports · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
objectiveTacrolimus, an immunosuppressive drug widely prescribed in kidney transplantation, requires therapeutic drug monitoring due to its marked interindividual pharmacokinetic variability and narrow therapeutic index. Previous studies have established that CYP3A5 rs776746 is associated with tacrolimus clearance, blood concentration, and dose requirement. The importance of other drug absorption, distribution, metabolism, and elimination (ADME) gene variants has not been well characterized.
methodsWe used novel DNA biobank and electronic medical record resources to identify ADME variants associated with tacrolimus dose requirement. Broad ADME genotyping was performed on 446 kidney transplant recipients, who had been dosed to a steady state with tacrolimus. The cohort was obtained from Vanderbilt's DNA biobank, BioVU, which contains linked deidentified electronic medical record data. Genotyping included Affymetrix drug-metabolizing enzymes and transporters Plus (1936 polymorphisms), custom Sequenom Massarray iPLEX Gold assay (95 polymorphisms), and ancestry-informative markers. The primary outcome was tacrolimus dose requirement defined as blood concentration to dose ratio.
resultsIn analyses, which adjusted for race and other clinical factors, we replicated the association of tacrolimus blood concentration to dose ratio with CYP3A5 rs776746 (P=7.15×10), and identified associations with nine variants in linkage disequilibrium with rs776746, including eight CYP3A4 variants. No NR1I2 variants were significantly associated. Age, weight, and hemoglobin were also significantly associated with the outcome. In final models, rs776746 explained 39% of variability in dose requirement and 46% was explained by the model containing clinical covariates.
conclusionThis study highlights the utility of DNA biobanks and electronic medical records for tacrolimus pharmacogenomic research.
Indexed as
Identifiers
What OpenQuestion holds
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.