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Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes
Drug-induced liver injury (DILI) is an adverse toxic hepatic clinical reaction associated to the administration of a drug that can occur both at early clinical stages of drug development, as well after normal clinical usage of approved drugs. Because of its unpredictability and clinical relevance, i...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380240/ https://www.ncbi.nlm.nih.gov/pubmed/34274980 http://dx.doi.org/10.1007/s00204-021-03114-z |
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author | Quintás, Guillermo Martínez-Sena, Teresa Conde, Isabel Pareja Ibars, Eugenia Kleinjans, Jos Castell, José V. |
author_facet | Quintás, Guillermo Martínez-Sena, Teresa Conde, Isabel Pareja Ibars, Eugenia Kleinjans, Jos Castell, José V. |
author_sort | Quintás, Guillermo |
collection | PubMed |
description | Drug-induced liver injury (DILI) is an adverse toxic hepatic clinical reaction associated to the administration of a drug that can occur both at early clinical stages of drug development, as well after normal clinical usage of approved drugs. Because of its unpredictability and clinical relevance, it is of medical concern. Three DILI phenotypes (hepatocellular, cholestatic, and mixed) are currently recognized, based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values. However, this classification lacks accuracy to distinguish among the many intermediate mixed types, or even to estimate the magnitude and progression of the injury. It was found desirable to have additional elements for better evaluation criteria of DILI. With this aim, we have examined the serum metabolomic changes occurring in 79 DILI patients recruited and monitored using established clinical criteria, along the course of the disease and until recovery. Results revealed that free and conjugated bile acids, and glycerophospholipids were among the most relevant metabolite classes for DILI phenotype characterization. Using an ensemble of PLS–DA models, metabolomic information was integrated into a ternary diagram to display the disease phenotype, the severity of the liver damage, and its progression. The modeling implemented and the use of such compiled information in an easily understandable and visual manner facilitates a straightforward DILI phenotyping and allow to monitor its progression and recovery prediction, usefully complementing the concise information drawn out by the ALT and ALP classification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00204-021-03114-z. |
format | Online Article Text |
id | pubmed-8380240 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-83802402021-09-08 Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes Quintás, Guillermo Martínez-Sena, Teresa Conde, Isabel Pareja Ibars, Eugenia Kleinjans, Jos Castell, José V. Arch Toxicol Toxicogenomics and Omics Technologies Drug-induced liver injury (DILI) is an adverse toxic hepatic clinical reaction associated to the administration of a drug that can occur both at early clinical stages of drug development, as well after normal clinical usage of approved drugs. Because of its unpredictability and clinical relevance, it is of medical concern. Three DILI phenotypes (hepatocellular, cholestatic, and mixed) are currently recognized, based on serum alanine aminotransferase (ALT) and alkaline phosphatase (ALP) values. However, this classification lacks accuracy to distinguish among the many intermediate mixed types, or even to estimate the magnitude and progression of the injury. It was found desirable to have additional elements for better evaluation criteria of DILI. With this aim, we have examined the serum metabolomic changes occurring in 79 DILI patients recruited and monitored using established clinical criteria, along the course of the disease and until recovery. Results revealed that free and conjugated bile acids, and glycerophospholipids were among the most relevant metabolite classes for DILI phenotype characterization. Using an ensemble of PLS–DA models, metabolomic information was integrated into a ternary diagram to display the disease phenotype, the severity of the liver damage, and its progression. The modeling implemented and the use of such compiled information in an easily understandable and visual manner facilitates a straightforward DILI phenotyping and allow to monitor its progression and recovery prediction, usefully complementing the concise information drawn out by the ALT and ALP classification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00204-021-03114-z. Springer Berlin Heidelberg 2021-07-17 2021 /pmc/articles/PMC8380240/ /pubmed/34274980 http://dx.doi.org/10.1007/s00204-021-03114-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Toxicogenomics and Omics Technologies Quintás, Guillermo Martínez-Sena, Teresa Conde, Isabel Pareja Ibars, Eugenia Kleinjans, Jos Castell, José V. Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes |
title | Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes |
title_full | Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes |
title_fullStr | Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes |
title_full_unstemmed | Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes |
title_short | Metabolomic analysis to discriminate drug-induced liver injury (DILI) phenotypes |
title_sort | metabolomic analysis to discriminate drug-induced liver injury (dili) phenotypes |
topic | Toxicogenomics and Omics Technologies |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380240/ https://www.ncbi.nlm.nih.gov/pubmed/34274980 http://dx.doi.org/10.1007/s00204-021-03114-z |
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