Diagnostic Biomarkers and Metabolic Mechanisms of Polymyxin B-Induced Acute Kidney Injury.
6 affiliations
- 1Department of Pharmacy, China-Japan Friendship Hospital, No. 2 Yinghua Road, Beijing 100029, China.
- 2Department of Pharmacy Administration and Clinical Pharmacy, School of Pharmaceutical Sciences, Peking University, Beijing 100191, China.
- 3Institute of Chemicals Safety, Chinese Academy of Inspection and Quarantine, Beijing 100176, China.
- 4Comprehensive Test Center, Chinese Academy of Inspection and Quarantine, Beijing 100123, China.
- 5Department of Analysis and Testing, Shimadzu (China) Co., Ltd., Beijing 100020, China.
- 6Beijing Key Laboratory of Critical Bridging Technologies for Chronic Disease Drug Development, China-Japan Friendship Hospital, Beijing 100029, China.
Abstract
Background/objectives
The clinical utility of polymyxin B (PB), a critical last-line antibiotic for multidrug-resistant Gram-negative infections, is severely compromised by acute kidney injury (AKI). However, the lack of specific diagnostic biomarkers and the incomplete understanding of pathogenic mechanisms pose substantial challenges to clinical management of PB-associated AKI.Methods
We enrolled 83 patients receiving PB regimens (23 AKI, 60 non-AKI) and quantified the plasma concentrations of five PB components to identify the optimal therapeutic drug monitoring (TDM) metric for nephrotoxicity. A rat model of PB-induced AKI was established to map renal PB distribution via mass spectrometry imaging and screen targets for tubular accumulation virtually. Untargeted metabolomics was performed on clinical and rat samples to identify metabolic dysregulation, with key pathways validated by reverse transcription quantitative real-time PCR (RT-qPCR). Diagnostic models were constructed using the eXtreme Gradient Boosting (XGBoost) algorithm and evaluated using Area Under the Curve (AUC). Shapley Additive exPlanations (SHAP) analysis was applied to interpret the models, and decision curve analysis (DCA) was used to assess clinical utility.Results
A novel PB-component model outperformed the conventional TDM index (AUC 0.703 vs. 0.561), and a 6-metabolite exploratory classifier achieved 0.95 accuracy and AUC 1.000 for PB-AKI discrimination on an independent test set. Mechanistically, high PB concentrations might saturate P-glycoprotein (P-gp), leading to PB accumulation in renal tubules and subsequent metabolic dysregulation, manifested as upregulation of fatty acid pathways and downregulation of the TCA cycle.Conclusions
These findings advance our understanding of metabolic dysregulation in PB-induced AKI and support the potential utility of responsive metabolic features in the clinical diagnosis of PB-induced AKI.
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BibTeX
@article{zhao2026diagnostic,
title = {{Diagnostic Biomarkers and Metabolic Mechanisms of Polymyxin B-Induced Acute Kidney Injury.}},
author = {Sirui Zhao and Wei Qin and Zirui Zhao and Ying Liu and Wenqian Chen and Yue Zhang and Juan Ren and Liang Sun and Lizhi Chen and Jingjing Shen and Pengmei Li and Xiaoxue Wang},
journal = {Antibiotics (Basel, Switzerland)},
year = {2026},
month = sep,
doi = {10.3390/antibiotics15100966},
url = {https://europepmc.org/article/MED/42938707},
note = {CC BY},
}
RIS
TY - JOUR
TI - Diagnostic Biomarkers and Metabolic Mechanisms of Polymyxin B-Induced Acute Kidney Injury.
AU - Sirui Zhao
AU - Wei Qin
AU - Zirui Zhao
AU - Ying Liu
AU - Wenqian Chen
AU - Yue Zhang
AU - Juan Ren
AU - Liang Sun
AU - Lizhi Chen
AU - Jingjing Shen
AU - Pengmei Li
AU - Xiaoxue Wang
PY - 2026
DA - 2026/09/30
JO - Antibiotics (Basel, Switzerland)
DO - 10.3390/antibiotics15100966
UR - https://europepmc.org/article/MED/42938707
AB - Background/objectives The clinical utility of polymyxin B (PB), a critical last-line antibiotic for multidrug-resistant Gram-negative infections, is severely compromised by acute kidney injury (AKI). However, the lack of specific diagnostic biomarkers and the incomplete understanding of pathogenic mechanisms pose substantial challenges to clinical management of PB-associated AKI.Methods We enrolled 83 patients receiving PB regimens (23 AKI, 60 non-AKI) and quantified the plasma concentrations of five PB components to identify the optimal therapeutic drug monitoring (TDM) metric for nephrotoxicity. A rat model of PB-induced AKI was established to map renal PB distribution via mass spectrometry imaging and screen targets for tubular accumulation virtually. Untargeted metabolomics was performed on clinical and rat samples to identify metabolic dysregulation, with key pathways validated by reverse transcription quantitative real-time PCR (RT-qPCR). Diagnostic models were constructed using the eXtreme Gradient Boosting (XGBoost) algorithm and evaluated using Area Under the Curve (AUC). Shapley Additive exPlanations (SHAP) analysis was applied to interpret the models, and decision curve analysis (DCA) was used to assess clinical utility.Results A novel PB-component model outperformed the conventional TDM index (AUC 0.703 vs. 0.561), and a 6-metabolite exploratory classifier achieved 0.95 accuracy and AUC 1.000 for PB-AKI discrimination on an independent test set. Mechanistically, high PB concentrations might saturate P-glycoprotein (P-gp), leading to PB accumulation in renal tubules and subsequent metabolic dysregulation, manifested as upregulation of fatty acid pathways and downregulation of the TCA cycle.Conclusions These findings advance our understanding of metabolic dysregulation in PB-induced AKI and support the potential utility of responsive metabolic features in the clinical diagnosis of PB-induced AKI.
SN - 2079-6382
ER -