Cytokeratin-18 is a sensitive biomarker of alanine transaminase increase in a placebo-controlled, randomized, crossover trial of therapeutic paracetamol dosing (PATH-BP biomarker substudy).

IF 3.4 3区 医学 Q2 TOXICOLOGY
Kathleen M Scullion, Iain M MacIntyre, Sian Sloan-Dennison, Benjamin Clark, Paul Fineran, Joanne Mair, David Creasey, Cicely Rathmell, Karen Faulds, Duncan Graham, David J Webb, James W Dear
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引用次数: 0

Abstract

Drug-induced liver injury (DILI) is a challenge in clinical medicine and drug development. Highly sensitive novel biomarkers have been identified for detecting DILI following a paracetamol overdose. The study objective was to evaluate biomarker performance in a 14-day trial of therapeutic dose paracetamol. The PATH-BP trial was a double-blind, placebo-controlled, crossover study. Individuals (n = 110) were randomized to receive 1 g paracetamol 4× daily or matched placebo for 2 weeks followed by a 2-week washout before crossing over to the alternate treatment. Blood was collected on days 0 (baseline), 4, 7, and 14 in both arms. Alanine transaminase (ALT) activity was measured in all patients. MicroRNA-122 (miR-122), cytokeratin-18 (K18), and glutamate dehydrogenase (GLDH) were measured in patients who had an elevated ALT on paracetamol treatment (≥50% from baseline). ALT increased in 49 individuals (45%). All 3 biomarkers were increased at the time of peak ALT (K18 paracetamol arm: 18.9 ± 9.7 ng/ml, placebo arm: 11.1 ± 5.4 ng/ml, ROC-AUC = 0.80, 95% CI 0.71-0.89; miR-122: 15.1 ± 12.9fM V 4.9 ± 4.7fM, ROC-AUC = 0.83, 0.75-0.91; and GLDH: 24.6 ± 31.1U/l V 12.0 ± 11.8U/l, ROC-AUC = 0.66, 0.49-0.83). All biomarkers were correlated with ALT (K18 r = 0.68, miR-122 r = 0.67, GLDH r = 0.60). To assess sensitivity, biomarker performance was analyzed on the visit preceding peak ALT (mean 3 days earlier). K18 identified the subsequent ALT increase (K18 ROC-AUC = 0.70, 0.59-0.80; miR-122 ROC-AUC = 0.60, 0.49-0.72, ALT ROC-AUC = 0.59, 0.48-0.70; GLDH ROC-AUC = 0.70, 0.50-0.90). Variability was lowest for ALT and K18. In conclusion, K18 was more sensitive than ALT, miR-122, or GLDH and has potential significant utility in the early identification of DILI in trials and clinical practice.

在对乙酰氨基酚治疗剂量的安慰剂对照、随机、交叉试验(PATH-BP 生物标志物子研究)中,细胞角蛋白-18 是丙氨酸转氨酶升高的敏感生物标志物。
药物性肝损伤(DILI)是临床医学和药物开发中的一项挑战。目前已经发现了用于检测扑热息痛过量后 DILI 的高灵敏度新型生物标记物。这项研究的目的是评估生物标记物在为期 14 天的治疗剂量扑热息痛试验中的表现。PATH-BP 试验是一项双盲、安慰剂对照、交叉研究。研究人员(n = 110)被随机分配接受 1 克扑热息痛(4×daily)或相匹配的安慰剂治疗 2 周,然后进行为期 2 周的冲洗,再转为交替治疗。两组患者均在第 0 天(基线)、第 4 天、第 7 天和第 14 天采集血液。对所有患者的丙氨酸转氨酶(ALT)活性进行了测量。对乙酰胆碱酯酶(ALT)升高(与基线相比≥50%)的患者进行了微RNA-122(miR-122)、细胞角蛋白-18(K18)和谷氨酸脱氢酶(GLDH)的测定。有 49 人(45%)ALT 升高。在 ALT 达到峰值时,所有 3 种生物标志物均升高(K18 扑热息痛治疗组:18.9 ± 9.7 ng/mL,安慰剂治疗组:11.1 ± 5.4 ng/mL,ROC-AUC = 0.80,95%CI 0.71-0.89; miR-122: 15.1 ± 12.9fM V 4.9 ± 4.7fM, ROC-AUC = 0.83, 0.75-0.91; and GLDH : 24.6 ± 31.1U/L V 12.0 ± 11.8U/L, ROC-AUC = 0.66,0.49-0.83).所有生物标记物均与谷丙转氨酶相关(K18 r = 0.68,miR-122 r = 0.67,GLDH r = 0.60)。为评估灵敏度,对 ALT 峰值前一次就诊(平均提前 3 天)的生物标志物表现进行了分析。K18 能识别随后的 ALT 升高(K18 ROC-AUC = 0.70,0.59-0.80;miR-122 ROC-AUC = 0.60,0.49-0.72;ALT ROC-AUC = 0.59,0.48-0.70;GLDH ROC-AUC = 0.70,0.50-0.90)。ALT 和 K18 的变异性最低。总之,K18比ALT、miR-122或GLDH更敏感,在试验和临床实践中具有早期识别DILI的潜在重要作用。
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来源期刊
Toxicological Sciences
Toxicological Sciences 医学-毒理学
CiteScore
7.70
自引率
7.90%
发文量
118
审稿时长
1.5 months
期刊介绍: The mission of Toxicological Sciences, the official journal of the Society of Toxicology, is to publish a broad spectrum of impactful research in the field of toxicology. The primary focus of Toxicological Sciences is on original research articles. The journal also provides expert insight via contemporary and systematic reviews, as well as forum articles and editorial content that addresses important topics in the field. The scope of Toxicological Sciences is focused on a broad spectrum of impactful toxicological research that will advance the multidisciplinary field of toxicology ranging from basic research to model development and application, and decision making. Submissions will include diverse technologies and approaches including, but not limited to: bioinformatics and computational biology, biochemistry, exposure science, histopathology, mass spectrometry, molecular biology, population-based sciences, tissue and cell-based systems, and whole-animal studies. Integrative approaches that combine realistic exposure scenarios with impactful analyses that move the field forward are encouraged.
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