A plasma peptidomic signature reveals extracellular matrix remodeling and predicts prognosis in alcohol-associated hepatitis.

IF 8.3 2区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY ACS Applied Materials & Interfaces Pub Date : 2024-07-31 eCollection Date: 2024-08-01 DOI:10.1097/HC9.0000000000000510
Khaled Sayed, Christine E Dolin, Daniel W Wilkey, Jiang Li, Toshifumi Sato, Juliane I Beier, Josepmaria Argemi, Vatsalya Vatsalya, Craig J McClain, Ramon Bataller, Abdus S Wahed, Michael L Merchant, Panayiotis V Benos, Gavin E Arteel
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Abstract

Background: Alcohol-associated hepatitis (AH) is plagued with high mortality and difficulty in identifying at-risk patients. The extracellular matrix undergoes significant remodeling during inflammatory liver injury and could potentially be used for mortality prediction.

Methods: EDTA plasma samples were collected from patients with AH (n = 62); Model for End-Stage Liver Disease score defined AH severity as moderate (12-20; n = 28) and severe (>20; n = 34). The peptidome data were collected by high resolution, high mass accuracy UPLC-MS. Univariate and multivariate analyses identified differentially abundant peptides, which were used for Gene Ontology, parent protein matrisomal composition, and protease involvement. Machine-learning methods were used to develop mortality predictors.

Results: Analysis of plasma peptides from patients with AH and healthy controls identified over 1600 significant peptide features corresponding to 130 proteins. These were enriched for extracellular matrix fragments in AH samples, likely related to the turnover of hepatic-derived proteins. Analysis of moderate versus severe AH peptidomes was dominated by changes in peptides from collagen 1A1 and fibrinogen A proteins. The dominant proteases for the AH peptidome spectrum appear to be CAPN1 and MMP12. Causal graphical modeling identified 3 peptides directly linked to 90-day mortality in >90% of the learned graphs. These peptides improved the accuracy of mortality prediction over the Model for End-Stage Liver Disease score and were used to create a clinically applicable mortality prediction assay.

Conclusions: A signature based on plasma peptidome is a novel, noninvasive method for prognosis stratification in patients with AH. Our results could also lead to new mechanistic and/or surrogate biomarkers to identify new AH mechanisms.

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血浆肽组特征揭示细胞外基质重塑并预测酒精相关性肝炎的预后。
背景:酒精相关性肝炎(AH)死亡率高,且难以识别高危患者。细胞外基质在肝脏炎症损伤过程中会发生显著重塑,有可能用于预测死亡率:从AH患者(62人)中采集EDTA血浆样本;终末期肝病模型评分将AH严重程度定义为中度(12-20分;28人)和重度(>20分;34人)。肽组数据由高分辨率、高质量精度的UPLC-MS收集。单变量和多变量分析确定了差异丰富的肽段,这些肽段用于基因本体、母体蛋白矩阵组成和蛋白酶参与。机器学习方法用于开发死亡率预测指标:对AH患者和健康对照者的血浆肽进行分析,发现了与130种蛋白质相对应的1600多个重要肽特征。在AH样本中,细胞外基质片段富集,这可能与肝源性蛋白质的周转有关。对中度和重度 AH 肽组的分析以胶原 1A1 和纤维蛋白原 A 蛋白肽段的变化为主。AH肽组谱的主要蛋白酶似乎是CAPN1和MMP12。在超过90%的学习图谱中,因果图谱建模确定了3种与90天死亡率直接相关的肽。与终末期肝病模型评分相比,这些肽提高了死亡率预测的准确性,并被用于创建临床适用的死亡率预测测定:结论:基于血浆肽组的特征是一种新颖、无创的方法,可用于对AH患者进行预后分层。结论:基于血浆肽组的特征是对急性肝损伤患者进行预后分层的一种新的非侵入性方法,我们的研究结果还可能带来新的机制和/或替代生物标志物,以确定急性肝损伤的新机制。
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来源期刊
ACS Applied Materials & Interfaces
ACS Applied Materials & Interfaces 工程技术-材料科学:综合
CiteScore
16.00
自引率
6.30%
发文量
4978
审稿时长
1.8 months
期刊介绍: ACS Applied Materials & Interfaces is a leading interdisciplinary journal that brings together chemists, engineers, physicists, and biologists to explore the development and utilization of newly-discovered materials and interfacial processes for specific applications. Our journal has experienced remarkable growth since its establishment in 2009, both in terms of the number of articles published and the impact of the research showcased. We are proud to foster a truly global community, with the majority of published articles originating from outside the United States, reflecting the rapid growth of applied research worldwide.
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