基于化学计量学辅助UPLC/Q-TOF/MS/MS的口服利托那韦治疗COVID-19后血浆代谢组学特征

IF 3.1 3区 医学 Q2 CHEMISTRY, ANALYTICAL Journal of pharmaceutical and biomedical analysis Pub Date : 2025-03-15 Epub Date: 2024-12-16 DOI:10.1016/j.jpba.2024.116638
Fatma Demirkaya Miloglu, Burak Bayrak, Busra Yuksel, Sema Nur Demir, Gulsah Gundogdu, Yucel Kadioglu, A M Abd El-Aty
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引用次数: 0

摘要

通过代谢组学了解利托那韦的药效学,可以深入了解其副作用,并有助于开发更安全的治疗方法。本研究旨在通过代谢组学方法研究利托那韦治疗对家兔代谢谱的影响,目的是阐明其对各种生化途径的影响,并确定相关的生物标志物。采用超高效液相色谱/四极杆飞行时间质谱(UPLC/Q-TOF/MS/MS)对血浆样品进行分析。根据质量电荷比(m/z)鉴定代谢物,并通过XCMS软件进行验证。通过主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA)对fold变化≥ 1.5和P ≤ 0.01的代谢物进行组间区分。使用MetaboAnalyst 6.0进行途径分析,识别利托那韦影响的代谢途径。PCA和OPLS-DA模型显示对照组和利托那韦治疗组之间存在明显的分离,高R²和Q²值表明模型性能稳健。途径分析显示,利托那韦治疗显著影响了几种代谢途径,包括与醚脂、苯丙氨酸、鞘脂和甘油磷脂代谢相关的代谢途径。在脂质代谢、氧化应激反应和细胞信号传导相关的代谢物中观察到特别显著的变化。利托那韦显著影响代谢途径,特别是脂质代谢和氧化应激反应,这可能影响免疫反应和药物相互作用。该研究还强调了将代谢组学与个性化医学方法相结合的潜力,以优化利托那韦的治疗策略并减少不良反应。这些发现表明,利托那韦除了具有抗病毒特性外,还显著影响细胞稳态和代谢过程。这凸显了了解利托那韦的代谢作用以加强其临床应用的必要性,特别是在COVID-19治疗中的应用。需要进一步的研究来探索这些改变及其对治疗策略的影响。
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Plasma metabolomic signatures after oral administration of ritonavir in COVID-19 treatment via chemometrics-assisted UPLC/Q-TOF/MS/MS.

Understanding the pharmacodynamics of ritonavir through metabolomics offers insights into its side effects and helps in the development of safer therapies. This study aimed to investigate the effects of ritonavir treatment on the metabolic profiles of rabbits via a metabolomics approach, with the objective of elucidating its impact on various biochemical pathways and identifying relevant biomarkers. The rabbits were divided into control and ritonavir-treated groups, and their plasma samples were analyzed via ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF/MS/MS). Metabolites were identified on the basis of the masscharge ratio (m/z) and validated via XCMS software. Metabolites with a fold change ≥ 1.5 and P ≤ 0.01 were analyzed via principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) to distinguish between the groups. MetaboAnalyst 6.0 was used for pathway analysis to identify metabolic pathways affected by ritonavir. The PCA and OPLS-DA models revealed clear separation between the control and ritonavir-treated groups, with high R² and Q² values indicating robust model performance. Pathway analysis revealed that ritonavir treatment significantly affected several metabolic pathways, including those related to ether lipid, phenylalanine, sphingolipid, and glycerophospholipid metabolism. Particularly significant changes were observed in metabolites related to lipid metabolism, oxidative stress responses and cellular signaling. Ritonavir significantly impacts metabolic pathways, particularly those involved in lipid metabolism, and oxidative stress responses, which may influence immune responses and drug interactions. This study also highlights the potential of integrating metabolomics with personalized medicine approaches to optimize ritonavir treatment strategies and reduce adverse effects. These findings indicate that ritonavir significantly influences cellular homeostasis and metabolic processes in addition to its antiviral properties. This highlights the necessity of comprehending the metabolic effects of ritonavir to enhance its clinical application, especially in the management of COVID-19. Further research is warranted to explore these alterations and their implications for therapeutic strategies.

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来源期刊
CiteScore
6.70
自引率
5.90%
发文量
588
审稿时长
37 days
期刊介绍: This journal is an international medium directed towards the needs of academic, clinical, government and industrial analysis by publishing original research reports and critical reviews on pharmaceutical and biomedical analysis. It covers the interdisciplinary aspects of analysis in the pharmaceutical, biomedical and clinical sciences, including developments in analytical methodology, instrumentation, computation and interpretation. Submissions on novel applications focusing on drug purity and stability studies, pharmacokinetics, therapeutic monitoring, metabolic profiling; drug-related aspects of analytical biochemistry and forensic toxicology; quality assurance in the pharmaceutical industry are also welcome. Studies from areas of well established and poorly selective methods, such as UV-VIS spectrophotometry (including derivative and multi-wavelength measurements), basic electroanalytical (potentiometric, polarographic and voltammetric) methods, fluorimetry, flow-injection analysis, etc. are accepted for publication in exceptional cases only, if a unique and substantial advantage over presently known systems is demonstrated. The same applies to the assay of simple drug formulations by any kind of methods and the determination of drugs in biological samples based merely on spiked samples. Drug purity/stability studies should contain information on the structure elucidation of the impurities/degradants.
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