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药物性肝损伤的生物标志物:通过对乙酰氨基酚肝毒性的机制观点。

Biomarkers of drug-induced liver injury: a mechanistic perspective through acetaminophen hepatotoxicity.

机构信息

Department of Pharmacology, Toxicology & Therapeutics, University of Kansas Medical Center, Kansas City, KS, USA.

出版信息

Expert Rev Gastroenterol Hepatol. 2021 Apr;15(4):363-375. doi: 10.1080/17474124.2021.1857238. Epub 2020 Dec 9.

Abstract

: Liver injury induced by drugs is a serious clinical problem. Many circulating biomarkers for identifying and predicting drug-induced liver injury (DILI) have been proposed.: Biomarkers are mainly predicated on the mechanistic understanding of the underlying DILI, often in the context of acetaminophen overdose. New panels of biomarkers have emerged that are related to recovery/regeneration rather than injury following DILI. We explore the clinical relevance and limitations of these new biomarkers including recent controversies. Extracellular vesicles have also emerged as a promising vector of biomarkers, although the biological role for EVs may limit their clinical usefulness. New technological approaches for biomarker discovery are also explored.: Recent clinical studies have validated the efficacy of some of these new biomarkers, cytokeratin-18, macrophage colony-stimulating factor receptor, and osteopontin for DILI prognosis. Low prevalence of DILI is an inherent limitation to DILI biomarker development. Furthering mechanistic understanding of DILI and leveraging technological advances (e.g. machine learning/omics) is necessary to improve upon the newest generation of biomarkers. The integration of omics approaches with machine learning has led to novel insights in cancer research and DILI research is poised to leverage these technologies for biomarker discovery and development.

摘要

药物引起的肝损伤是一个严重的临床问题。已经提出了许多用于识别和预测药物性肝损伤 (DILI) 的循环生物标志物。生物标志物主要基于对潜在 DILI 的机制理解,通常是在对乙酰氨基酚过量的情况下。新的生物标志物组合已经出现,它们与 DILI 后的恢复/再生有关,而不是损伤。我们探讨了这些新生物标志物的临床相关性和局限性,包括最近的争议。细胞外囊泡也作为生物标志物的一个有前途的载体出现,尽管 EVs 的生物学作用可能限制了它们的临床用途。我们还探讨了用于生物标志物发现的新技术方法。最近的临床研究验证了一些新生物标志物的有效性,例如细胞角蛋白 18、巨噬细胞集落刺激因子受体和骨桥蛋白用于 DILI 预后。DILI 标志物的发展受到 DILI 低患病率的固有限制。进一步深入了解 DILI,并利用技术进步(例如机器学习/组学),对于改进新一代生物标志物是必要的。组学方法与机器学习的整合为癌症研究带来了新的见解,而 DILI 研究也准备利用这些技术进行生物标志物的发现和开发。

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