Evaluating The Sensitivity And Specificity Of Promising Circulating Biomarkers To Diagnose Liver Injury In Humans

TOXICOLOGICAL SCIENCES(2021)

引用 16|浏览14
暂无评分
摘要
Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and postmarketing. The objective of this study was to evaluate the diagnostic performance of promising biomarkers of liver injury-glutamate dehydrogenase (GLDH), cytokeratin-18 (K18), caspase-cleaved K18 (ccK18), osteopontin (OPN), macrophage colony-stimulating factor (MCSF), MCSF receptor (MCSFR), and microRNA-122 (miR-122) in comparison to the traditional biomarker alanine aminotransferase (ALT). Biomarkers were evaluated individually and as a multivariate model in a cohort of acetaminophen overdose (n=175) subjects and were further tested in cohorts of healthy adults (n=135), patients with liver damage from various causes (n=104), and patients with damage to the muscle (n=74), kidney (n=40), gastrointestinal tract (n=37), and pancreas (n=34). In the acetaminophen cohort, a multivariate model with GLDH, K18, and miR-122 was able to detect DILI more accurately than individual biomarkers alone. Furthermore, the three-biomarker model could accurately predict patients with liver injury compared with healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract, and kidney. Expression of K18, GLDH, and miR-122 was evaluated using a database of transcriptomic profiles across multiple tissues/organs in humans and rats. K18 mRNA (Krt18) and MiR-122 were highly expressed in liver whereas GLDH mRNA (Glud1) was widely expressed. We performed a comprehensive, comparative performance assessment of 7 promising biomarkers and demonstrated that a 3-biomarker multivariate model can accurately detect liver injury.
更多
查看译文
关键词
keratin-18, microRNA, glutamate dehydrogenase, diagnosis, liver
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要