Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury
Background: Anti-tuberculosis drug-induced liver injury (ATB-DILI) is an adverse reaction with a high incidence and the greatest impact on tuberculosis treatment. However, there is a lack of effective biomarkers for the early prediction of ATB-DILI. Herein, this study uses UPLC‒MS/MS to reveal the p...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-10-01
|
| Series: | Frontiers in Pharmacology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fphar.2022.1044808/full |
| _version_ | 1798030435181133824 |
|---|---|
| author | Ming-Gui Wang Ming-Gui Wang Shou-Quan Wu Meng-Meng Zhang Jian-Qing He |
| author_facet | Ming-Gui Wang Ming-Gui Wang Shou-Quan Wu Meng-Meng Zhang Jian-Qing He |
| author_sort | Ming-Gui Wang |
| collection | DOAJ |
| description | Background: Anti-tuberculosis drug-induced liver injury (ATB-DILI) is an adverse reaction with a high incidence and the greatest impact on tuberculosis treatment. However, there is a lack of effective biomarkers for the early prediction of ATB-DILI. Herein, this study uses UPLC‒MS/MS to reveal the plasma metabolic profile and lipid profile of ATB-DILI patients before drug administration and screen new biomarkers for predicting ATB-DILI.Methods: A total of 60 TB patients were enrolled, and plasma was collected before antituberculosis drug administration. The untargeted metabolomics and lipidomics analyses were performed using UPLC‒MS/MS, and the high-resolution mass spectrometer Q Exactive was used for data acquisition in both positive and negative ion modes. The random forest package of R software was used for data screening and model building.Results: A total of 60 TB patients, including 30 ATB-DILI patients and 30 non-ATB-DILI subjects, were enrolled. There were no significant differences between the ATB-DILI and control groups in age, sex, smoking, drinking or body mass index (p > 0.05). Twenty-two differential metabolites were selected. According to KEGG pathway analysis, 9 significantly enriched metabolic pathways were found, and both drug metabolism-other enzymes and niacin and nicotinamide metabolic pathways were found in both positive and negative ion models. A total of 7 differential lipid molecules were identified between the two groups. Ferroptosis and biosynthesis of unsaturated fatty acids were involved in the occurrence of ATB-DILI. Random forest analysis showed that the model built with the top 30 important variables had an area under the ROC curve of 0.79 (0.65–0.93) for the training set and 0.79 (0.55–1.00) for the validation set.Conclusion: This study demonstrated that potential markers for the early prediction of ATB-DILI can be found through plasma metabolomics and lipidomics. The random forest model showed good clinical predictive value for ATB-DILI. |
| first_indexed | 2024-04-11T19:41:25Z |
| format | Article |
| id | doaj.art-1fb18aa6b5f84de695c796de18a3a210 |
| institution | Directory Open Access Journal |
| issn | 1663-9812 |
| language | English |
| last_indexed | 2024-04-11T19:41:25Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Pharmacology |
| spelling | doaj.art-1fb18aa6b5f84de695c796de18a3a2102022-12-22T04:06:42ZengFrontiers Media S.A.Frontiers in Pharmacology1663-98122022-10-011310.3389/fphar.2022.10448081044808Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injuryMing-Gui Wang0Ming-Gui Wang1Shou-Quan Wu2Meng-Meng Zhang3Jian-Qing He4Department of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, Sichuan, ChinaDepartment of Emergency Medical, Sichuan Provincial People’s Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan, ChinaDepartment of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, Sichuan, ChinaDepartment of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, Sichuan, ChinaDepartment of Respiratory and Critical Care Medicine, Clinical Research Center for Respiratory Disease, West China Hospital, Sichuan University, Chengdu, Sichuan, ChinaBackground: Anti-tuberculosis drug-induced liver injury (ATB-DILI) is an adverse reaction with a high incidence and the greatest impact on tuberculosis treatment. However, there is a lack of effective biomarkers for the early prediction of ATB-DILI. Herein, this study uses UPLC‒MS/MS to reveal the plasma metabolic profile and lipid profile of ATB-DILI patients before drug administration and screen new biomarkers for predicting ATB-DILI.Methods: A total of 60 TB patients were enrolled, and plasma was collected before antituberculosis drug administration. The untargeted metabolomics and lipidomics analyses were performed using UPLC‒MS/MS, and the high-resolution mass spectrometer Q Exactive was used for data acquisition in both positive and negative ion modes. The random forest package of R software was used for data screening and model building.Results: A total of 60 TB patients, including 30 ATB-DILI patients and 30 non-ATB-DILI subjects, were enrolled. There were no significant differences between the ATB-DILI and control groups in age, sex, smoking, drinking or body mass index (p > 0.05). Twenty-two differential metabolites were selected. According to KEGG pathway analysis, 9 significantly enriched metabolic pathways were found, and both drug metabolism-other enzymes and niacin and nicotinamide metabolic pathways were found in both positive and negative ion models. A total of 7 differential lipid molecules were identified between the two groups. Ferroptosis and biosynthesis of unsaturated fatty acids were involved in the occurrence of ATB-DILI. Random forest analysis showed that the model built with the top 30 important variables had an area under the ROC curve of 0.79 (0.65–0.93) for the training set and 0.79 (0.55–1.00) for the validation set.Conclusion: This study demonstrated that potential markers for the early prediction of ATB-DILI can be found through plasma metabolomics and lipidomics. The random forest model showed good clinical predictive value for ATB-DILI.https://www.frontiersin.org/articles/10.3389/fphar.2022.1044808/fullmetabolomiclipdomicsATB-DILIbiomarkerprediction |
| spellingShingle | Ming-Gui Wang Ming-Gui Wang Shou-Quan Wu Meng-Meng Zhang Jian-Qing He Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury Frontiers in Pharmacology metabolomic lipdomics ATB-DILI biomarker prediction |
| title | Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury |
| title_full | Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury |
| title_fullStr | Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury |
| title_full_unstemmed | Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury |
| title_short | Plasma metabolomic and lipidomic alterations associated with anti-tuberculosis drug-induced liver injury |
| title_sort | plasma metabolomic and lipidomic alterations associated with anti tuberculosis drug induced liver injury |
| topic | metabolomic lipdomics ATB-DILI biomarker prediction |
| url | https://www.frontiersin.org/articles/10.3389/fphar.2022.1044808/full |
| work_keys_str_mv | AT mingguiwang plasmametabolomicandlipidomicalterationsassociatedwithantituberculosisdruginducedliverinjury AT mingguiwang plasmametabolomicandlipidomicalterationsassociatedwithantituberculosisdruginducedliverinjury AT shouquanwu plasmametabolomicandlipidomicalterationsassociatedwithantituberculosisdruginducedliverinjury AT mengmengzhang plasmametabolomicandlipidomicalterationsassociatedwithantituberculosisdruginducedliverinjury AT jianqinghe plasmametabolomicandlipidomicalterationsassociatedwithantituberculosisdruginducedliverinjury |