Chen Li, Zhu Ruiqin, Ma Yaxing, Huang Chuixiu, Shen Xiantao
Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection and State Key Laboratory of Environmental Health (Incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of Forensic Medicine, Huazhong University of Science and Technology, Wuhan, China.
Front Pharmacol. 2024 Aug 22;15:1441755. doi: 10.3389/fphar.2024.1441755. eCollection 2024.
LC-MS/MS-based metabolomics is an important tool for studying disease-related biomarkers. Conventionally, different strategies have been used to screen biomarkers. However, many studies for biomarker screening by different strategies have ignored the dose-response relationship between the biomarker level and exposure level, and no relevant studies have described and compared different strategies in detail. Phenobarbital (PHB) which belongs to the barbiturates, was selected as the typical representative of neurotoxins. Acylcarnitines have been promising candidates for diagnostic biomarkers for several neurological disorders and neurotoxicity. In this work, we aimed to use an acute PHB poisoning animal model to clarify PHB poisoning effects on plasma and brain acylcarnitine changes and how to rationally analyze data from LC-MS/MS.
The acylcarnitine profiles in plasma and brain regions in an actuate PHB poisoning animal model were utilized. The dose-response relationship between plasma PHB and carnitine and acylcarnitines (CARs) in plasma and brain were assessed by the variance analysis trend test and Spearman's rank correlation test. In different strategies, principal component analysis (PCA) and partial least squares discriminant analysis (OPLS-DA) screened the differential CARs, variable importance plots (VIPs) were utilized to select putative biomarkers for PHB-induced toxicity, and receiver operating characteristic (ROC) curve analysis then illustrated the reliability of biomarkers.
Under the first strategy, 14 potential toxicity biomarkers were obtained including eight downregulated CARs with AUC >0.8. Under the second strategy, 11 potential toxicity biomarkers were obtained containing five downregulated CARs with AUC >0.8. Only when the dose-response relationship was fully considered, different strategies screen for the same biomarkers (plasma acetyl-carnitine (C2) and plasma decanoyl-carnitine (C10)), which indicated plasma acylcarnitines might serve as toxicity biomarkers. In addition, the plasma CAR level changes showed differences from brain CAR level changes, and correlations between plasma CARs and their brain counterparts were weak.
We found that plasma C2 and C10 might serve as toxicity biomarkers for PHB poisoning disorders, and PHB poisoning effects on changes in plasma CARs may not be fully representative of changes in brain CARs.
基于液相色谱-串联质谱(LC-MS/MS)的代谢组学是研究疾病相关生物标志物的重要工具。传统上,人们采用了不同的策略来筛选生物标志物。然而,许多通过不同策略进行生物标志物筛选的研究忽略了生物标志物水平与暴露水平之间的剂量反应关系,且尚无相关研究对不同策略进行详细描述和比较。苯巴比妥(PHB)属于巴比妥类药物,被选为神经毒素的典型代表。酰基肉碱有望成为多种神经系统疾病和神经毒性诊断生物标志物的候选物质。在本研究中,我们旨在利用急性PHB中毒动物模型,阐明PHB中毒对血浆和脑酰基肉碱变化的影响,以及如何合理分析LC-MS/MS数据。
利用急性PHB中毒动物模型中的血浆和脑区酰基肉碱谱。通过方差分析趋势检验和Spearman秩相关检验评估血浆PHB与血浆和脑中肉碱及酰基肉碱(CARs)之间的剂量反应关系。在不同策略中,主成分分析(PCA)和偏最小二乘判别分析(OPLS-DA)筛选差异CARs,利用变量重要性投影(VIPs)选择PHB诱导毒性的潜在生物标志物,然后通过受试者工作特征(ROC)曲线分析说明生物标志物的可靠性。
在第一种策略下,获得了14种潜在毒性生物标志物,包括8种下调的CARs,其曲线下面积(AUC)>0.8。在第二种策略下,获得了11种潜在毒性生物标志物,其中包括5种下调的CARs,AUC>0.8。只有在充分考虑剂量反应关系时,不同策略才会筛选出相同的生物标志物(血浆乙酰肉碱(C2)和血浆癸酰肉碱(C10)),这表明血浆酰基肉碱可能作为毒性生物标志物。此外,血浆CAR水平变化与脑CAR水平变化存在差异,血浆CARs与其脑内对应物之间的相关性较弱。
我们发现血浆C2和C10可能作为PHB中毒疾病的毒性生物标志物,且PHB中毒对血浆CARs变化的影响可能不能完全代表脑CARs的变化。