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Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients
Tacrolimus, an immunosuppressant used in solid organ transplantation, has a narrow therapeutic index and exhibits inter-individual pharmacokinetic variability. Achieving and maintaining a therapeutic level of the drug by giving appropriate doses is crucial for successful immunosuppression, especiall...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669916/ https://www.ncbi.nlm.nih.gov/pubmed/34916931 http://dx.doi.org/10.3389/fphar.2021.726784 |
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author | Srinivas, Lekshmy Gracious, Noble Nair, Radhakrishnan R. |
author_facet | Srinivas, Lekshmy Gracious, Noble Nair, Radhakrishnan R. |
author_sort | Srinivas, Lekshmy |
collection | PubMed |
description | Tacrolimus, an immunosuppressant used in solid organ transplantation, has a narrow therapeutic index and exhibits inter-individual pharmacokinetic variability. Achieving and maintaining a therapeutic level of the drug by giving appropriate doses is crucial for successful immunosuppression, especially during the initial post-transplant period. We studied the effect of CYP3A5, CYP3A4, and ABCB1 gene polymorphisms on tacrolimus trough concentrations in South Indian renal transplant recipients from Kerala to formulate a genotype-based dosing equation to calculate the required starting daily dose of tacrolimus to be given to each patient to attain optimal initial post-transplant period drug level. We also investigated the effect of these genes on drug-induced adverse effects and rejection episodes and looked into the global distribution of allele frequencies of these polymorphisms. One hundred forty-five renal transplant recipients on a triple immunosuppressive regimen of tacrolimus, mycophenolate mofetil, and steroid were included in this study. Clinical data including tacrolimus daily doses, trough levels (C(0)) and dose-adjusted tacrolimus trough concentration (C(0)/D) in blood at three time points (day 6, 6 months, and 1-year post-transplantation), adverse drug effects, rejection episodes, serum creatinine levels, etc., were recorded. The patients were genotyped for CYP3A5*3, CYP3A4*1B, CYP3A4*1G, ABCB1 G2677T, and ABCB1 C3435T polymorphisms by the PCR-RFLP method. We found that CYP3A5*3 polymorphism was the single most strongly associated factor determining the tacrolimus C(0)/D in blood at all three time points (p < 0.001). Using multiple linear regression, we formulated a simple and easy to compute equation that will help the clinician calculate the starting tacrolimus dose per kg body weight to be administered to a patient to attain optimal initial post-transplant period tacrolimus level. CYP3A5 expressors had an increased chance of rejection than non-expressors (p = 0.028), while non-expressors had an increased risk for new-onset diabetes mellitus after transplantation (NODAT) than expressors (p = 0.018). Genotype-guided initial tacrolimus dosing would help transplant recipients achieve optimal initial post-transplant period tacrolimus levels and thus prevent the adverse effects due to overdose and rejection due to inadequate dose. We observed inter-population differences in allele frequencies of drug metabolizer and transporter genes, emphasizing the importance of formulating population-specific dose prediction models to draw results of clinical relevance. |
format | Online Article Text |
id | pubmed-8669916 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86699162021-12-15 Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients Srinivas, Lekshmy Gracious, Noble Nair, Radhakrishnan R. Front Pharmacol Pharmacology Tacrolimus, an immunosuppressant used in solid organ transplantation, has a narrow therapeutic index and exhibits inter-individual pharmacokinetic variability. Achieving and maintaining a therapeutic level of the drug by giving appropriate doses is crucial for successful immunosuppression, especially during the initial post-transplant period. We studied the effect of CYP3A5, CYP3A4, and ABCB1 gene polymorphisms on tacrolimus trough concentrations in South Indian renal transplant recipients from Kerala to formulate a genotype-based dosing equation to calculate the required starting daily dose of tacrolimus to be given to each patient to attain optimal initial post-transplant period drug level. We also investigated the effect of these genes on drug-induced adverse effects and rejection episodes and looked into the global distribution of allele frequencies of these polymorphisms. One hundred forty-five renal transplant recipients on a triple immunosuppressive regimen of tacrolimus, mycophenolate mofetil, and steroid were included in this study. Clinical data including tacrolimus daily doses, trough levels (C(0)) and dose-adjusted tacrolimus trough concentration (C(0)/D) in blood at three time points (day 6, 6 months, and 1-year post-transplantation), adverse drug effects, rejection episodes, serum creatinine levels, etc., were recorded. The patients were genotyped for CYP3A5*3, CYP3A4*1B, CYP3A4*1G, ABCB1 G2677T, and ABCB1 C3435T polymorphisms by the PCR-RFLP method. We found that CYP3A5*3 polymorphism was the single most strongly associated factor determining the tacrolimus C(0)/D in blood at all three time points (p < 0.001). Using multiple linear regression, we formulated a simple and easy to compute equation that will help the clinician calculate the starting tacrolimus dose per kg body weight to be administered to a patient to attain optimal initial post-transplant period tacrolimus level. CYP3A5 expressors had an increased chance of rejection than non-expressors (p = 0.028), while non-expressors had an increased risk for new-onset diabetes mellitus after transplantation (NODAT) than expressors (p = 0.018). Genotype-guided initial tacrolimus dosing would help transplant recipients achieve optimal initial post-transplant period tacrolimus levels and thus prevent the adverse effects due to overdose and rejection due to inadequate dose. We observed inter-population differences in allele frequencies of drug metabolizer and transporter genes, emphasizing the importance of formulating population-specific dose prediction models to draw results of clinical relevance. Frontiers Media S.A. 2021-11-30 /pmc/articles/PMC8669916/ /pubmed/34916931 http://dx.doi.org/10.3389/fphar.2021.726784 Text en Copyright © 2021 Srinivas, Gracious and Nair. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Srinivas, Lekshmy Gracious, Noble Nair, Radhakrishnan R. Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients |
title | Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients |
title_full | Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients |
title_fullStr | Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients |
title_full_unstemmed | Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients |
title_short | Pharmacogenetics Based Dose Prediction Model for Initial Tacrolimus Dosing in Renal Transplant Recipients |
title_sort | pharmacogenetics based dose prediction model for initial tacrolimus dosing in renal transplant recipients |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669916/ https://www.ncbi.nlm.nih.gov/pubmed/34916931 http://dx.doi.org/10.3389/fphar.2021.726784 |
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