ArticleAnnals of medicine2026
Genetic and clinical determinants of tacrolimus accumulation in early liver transplantation: evidence for a combined genotype-antibiotic effect.
Article in Annals of medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundTacrolimus is a first-line immunosuppressant essential for preventing graft rejection after liver transplantation, but its narrow therapeutic index and extensive interindividual pharmacokinetic variability complicate optimal dosing during the early postoperative phase.
methodsThe pharmacokinetics of tacrolimus were analyzed in liver transplant recipients from longitudinal trough concentrations collected within the first 30 days of administration using non-compartmental models. Associations between pharmacokinetic indices and covariates were assessed using Spearman's correlation, t-tests, ANOVA, Wilcoxon rank-sum, or Kruskal-Wallis tests, and genotype-drug combined effects by ANOVA. Protein models were generated by ColabFold and docked with drugs using CB-Dock2. Machine-learning models predicted pharmacokinetic parameters.
resultsTacrolimus trough accumulation dynamics showed interindividual variability, with the time to maximum trough concentration (t(C0,max)) ranging across patients. The ABCB1 rs2032582 AC genotype in recipients was associated with earlier t(C0,max) and greater accumulation, while donor CYP3A4 rs4646437 was linked to differences in a trough accumulation index. Cefoperazone/sulbactam administration was associated with more pronounced trough accumulation and shorter t(C0,max), and a combined genotype-antibiotic effect was observed, whereby rs2032582 AC carriers receiving cefoperazone/sulbactam reached peak trough levels earlier. Docking analyses suggested that cefoperazone may competitively bind ABCB1 at sites overlapping tacrolimus binding, particularly in the rs2032582 AC variant. Multiple biomarkers for liver function, coagulation, and hematologic indices were associated with pharmacokinetic metrics, findings supported by machine-learning models.
conclusionsThese findings highlight a combined effect of genetic background and antibiotic use on tacrolimus trough exposure dynamics, providing mechanistic insight that may inform individualized monitoring and dosing in the early phase after liver transplantation.
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