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Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics
The clinical pharmacodynamics of tacrolimus in renal transplant patients has significant interindividual variability. T lymphocytes were selected to study the pharmacodynamic response of tacrolimus, which was significantly correlated with renal function and the outcome of renal transplant patients....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182099/ https://www.ncbi.nlm.nih.gov/pubmed/35684454 http://dx.doi.org/10.3390/molecules27113517 |
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author | He, Xiaoying Yang, Xi Yan, Xiaoting Huang, Mingzhu Xiang, Zheng Lou, Yan |
author_facet | He, Xiaoying Yang, Xi Yan, Xiaoting Huang, Mingzhu Xiang, Zheng Lou, Yan |
author_sort | He, Xiaoying |
collection | PubMed |
description | The clinical pharmacodynamics of tacrolimus in renal transplant patients has significant interindividual variability. T lymphocytes were selected to study the pharmacodynamic response of tacrolimus, which was significantly correlated with renal function and the outcome of renal transplant patients. Ultra-performance liquid chromatography–quadrupole time-of-flight mass spectroscopy (UPLC/Q-TOF-MS) was performed to obtain the metabolic profiles of 109 renal transplant patients. A partial least squares (PLS) model was constructed to screen potential biomarkers that could predict the efficacy of tacrolimus. Multinomial logistic regression analysis established a bridge that could quantify the relationship between the efficacy of tacrolimus and biomarkers. The results showed a good correlation between endogenous molecules and the efficacy of tacrolimus. Metabolites such as serum creatinine, mesobilirubinogen, L-isoleucine, 5-methoxyindoleacetate, eicosapentaenoic acid, N(2)-succinoylarginine, tryptophyl-arginine, and butyric acid were indicated as candidate biomarkers. In addition, the key biomarkers could correctly predict the efficacy of tacrolimus with an accuracy of 82.5%. Finally, we explored the mechanism of individual variation by pathway analysis, which showed that amino acid metabolism was significantly related to the efficacy of tacrolimus. Moreover, orthogonal partial least squares discriminant analysis (OPLS-DA) showed that there was no difference in key metabolites among different pharmacodynamic groups at 1 month and 3 months after dose adjustment, suggesting that pharmacometabonomics is a useful tool to predict individual differences in pharmacodynamics and thus to facilitate individualized drug therapy. |
format | Online Article Text |
id | pubmed-9182099 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91820992022-06-10 Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics He, Xiaoying Yang, Xi Yan, Xiaoting Huang, Mingzhu Xiang, Zheng Lou, Yan Molecules Article The clinical pharmacodynamics of tacrolimus in renal transplant patients has significant interindividual variability. T lymphocytes were selected to study the pharmacodynamic response of tacrolimus, which was significantly correlated with renal function and the outcome of renal transplant patients. Ultra-performance liquid chromatography–quadrupole time-of-flight mass spectroscopy (UPLC/Q-TOF-MS) was performed to obtain the metabolic profiles of 109 renal transplant patients. A partial least squares (PLS) model was constructed to screen potential biomarkers that could predict the efficacy of tacrolimus. Multinomial logistic regression analysis established a bridge that could quantify the relationship between the efficacy of tacrolimus and biomarkers. The results showed a good correlation between endogenous molecules and the efficacy of tacrolimus. Metabolites such as serum creatinine, mesobilirubinogen, L-isoleucine, 5-methoxyindoleacetate, eicosapentaenoic acid, N(2)-succinoylarginine, tryptophyl-arginine, and butyric acid were indicated as candidate biomarkers. In addition, the key biomarkers could correctly predict the efficacy of tacrolimus with an accuracy of 82.5%. Finally, we explored the mechanism of individual variation by pathway analysis, which showed that amino acid metabolism was significantly related to the efficacy of tacrolimus. Moreover, orthogonal partial least squares discriminant analysis (OPLS-DA) showed that there was no difference in key metabolites among different pharmacodynamic groups at 1 month and 3 months after dose adjustment, suggesting that pharmacometabonomics is a useful tool to predict individual differences in pharmacodynamics and thus to facilitate individualized drug therapy. MDPI 2022-05-30 /pmc/articles/PMC9182099/ /pubmed/35684454 http://dx.doi.org/10.3390/molecules27113517 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article He, Xiaoying Yang, Xi Yan, Xiaoting Huang, Mingzhu Xiang, Zheng Lou, Yan Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics |
title | Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics |
title_full | Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics |
title_fullStr | Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics |
title_full_unstemmed | Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics |
title_short | Individualized Dosage of Tacrolimus for Renal Transplantation Patients Based on Pharmacometabonomics |
title_sort | individualized dosage of tacrolimus for renal transplantation patients based on pharmacometabonomics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9182099/ https://www.ncbi.nlm.nih.gov/pubmed/35684454 http://dx.doi.org/10.3390/molecules27113517 |
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