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通过化学计量学辅助的超高效液相色谱/四极杆飞行时间串联质谱法对 COVID-19 治疗中口服利托那韦后的血浆代谢组学特征进行分析。

Plasma metabolomic signatures after oral administration of ritonavir in COVID-19 treatment via chemometrics-assisted UPLC/Q-TOF/MS/MS.

作者信息

Demirkaya Miloglu Fatma, Bayrak Burak, Yuksel Busra, Demir Sema Nur, Gundogdu Gulsah, Kadioglu Yucel, Abd El-Aty A M

机构信息

Department of Analytical Chemistry, Faculty of Pharmacy, Atatürk University, Erzurum, Turkey.

Department of Analytical Chemistry, Faculty of Pharmacy, Atatürk University, Erzurum, Turkey.

出版信息

J Pharm Biomed Anal. 2025 Mar 15;255:116638. doi: 10.1016/j.jpba.2024.116638. Epub 2024 Dec 16.

Abstract

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.

摘要

通过代谢组学了解利托那韦的药效学,有助于深入了解其副作用,并推动更安全疗法的开发。本研究旨在通过代谢组学方法研究利托那韦治疗对兔代谢谱的影响,以阐明其对各种生化途径的影响并识别相关生物标志物。将兔分为对照组和利托那韦治疗组,并通过超高效液相色谱/四极杆飞行时间质谱(UPLC/Q-TOF/MS/MS)分析其血浆样本。根据质荷比(m/z)鉴定代谢物,并通过XCMS软件进行验证。对变化倍数≥1.5且P≤0.01的代谢物进行主成分分析(PCA)和正交偏最小二乘判别分析(OPLS-DA),以区分不同组。使用MetaboAnalyst 6.0进行通路分析,以识别受利托那韦影响的代谢通路。PCA和OPLS-DA模型显示对照组和利托那韦治疗组之间有明显分离,高R²和Q²值表明模型性能良好。通路分析表明,利托那韦治疗显著影响了多个代谢通路,包括与醚脂、苯丙氨酸、鞘脂和甘油磷脂代谢相关的通路。在与脂质代谢、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通路,尤其是那些参与脂质代谢和氧化应激反应的通路,这可能会影响免疫反应和药物相互作用。本研究还强调了将代谢组学与个性化医疗方法相结合以优化利托那韦治疗策略并减少不良反应的潜力。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。这凸显了理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的管理中。有必要进行进一步研究以探索这些变化及其对治疗策略的影响。

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