用于检测对乙酰氨基酚中毒的代谢组学方法：一项系统评价。
完整摘要 · 中文译文
引言：在代谢变化中检测毒性模式是潜在威胁的关键指标。代谢组学可能为寻找药物过量和毒性的生物标志物提供一种替代方法。在对乙酰氨基酚过量的情况下，谷胱甘肽清除导致线粒体功能障碍和肝细胞死亡。代谢组学方法已能够发现对乙酰氨基酚（APAP）过量肝损伤的新机制。 方法：我们进行了一项同行评审的科学综述，以评估代谢组学在APAP中毒中应用的研究。我们检索了PubMed和Scopus数据库，截止到2025年2月28日，寻找相关的原始文章。我们还查阅了clinicaltrials.gov网站和印度临床试验注册库。 结果：我们的初步检索在去重和初步筛选后得到302篇文章。二百零九（209）篇文章进行了全文审查。其中，191篇被排除，18项研究被纳入。共有1503名受试者，使用了24种代谢组学技术。在clinicaltrials.gov上注册了7项试验，而在CTRI中未注册任何试验。 讨论：代谢中间产物更有可能在细胞死亡前穿过完整的细胞膜并在血液中被检测到。因此，代谢组学可能是一种潜在的策略，用于识别在较早时期具有相关性的损伤生物标志物。 结论：对乙酰氨基酚（APAP）可被视为一种不良反应显著较少的多功能药物；然而，长期使用时仍会影响肝脏。科学家们继续推进数据提取的边界，且人们普遍认为，缺乏数据整合工具阻碍了代谢组学技术的充分应用。本研究增进了我们对代谢组学在对乙酰氨基酚诱导的肝损伤中应用的理解。
完整摘要 · 英文原文
INTRODUCTION: Detecting toxicity patterns in metabolic changes is a key indicator of potential threats. Metabolomics may provide an alternative way to find biomarkers for drug overdose and toxicity. In an acetaminophen overdose, glutathione scavenging causes mitochondrial malfunction and hepatocyte death. Metabolomics methods have enabled the discovery of novel mechanisms of liver injury in acetaminophen (APAP) overdose. METHODS: We conducted a peer-reviewed scientific review to assess the studies on the application of metabolomics in APAP poisoning. We searched PubMed and Scopus databases until February 28, 2025, for relevant original articles. We also looked into the clinicaltrials.gov website and the Indian clinical trial registry. RESULTS: Our initial search yielded 302 articles, after duplicates and initial screening. Two hundred and nine (209) articles underwent full-text review. Of these, 191 articles were excluded, and 18 studies were included. There were 1503 subjects, and 24 metabolomics techniques were used. Seven trials were registered in clinicaltrials.gov, and none were registered in the CTRI. DISCUSSION: Metabolic intermediates are more likely to pass through intact cell membranes and be detected in blood before cell death. Thus, metabolomics could be a potential strategy to identify damage biomarkers relevant at earlier periods. CONCLUSION: APAP can be considered a multifunctional drug with significantly fewer adverse effects; however, it still affects the liver when used chronically. Scientists continue to push the boundaries of data extraction, and it is widely acknowledged that a lack of tools for data integration hampers the full manifestation of metabolomics technologies. This research increases our understanding of metabolomics use in APAP-induced liver injury.