丹麦哥本哈根大学Matthias Mann研究小组近日取得一项新成果。经过不懈努力，他们研发了利用非侵入性蛋白质组学生物标志物方法预判酒精相关肝病（ALD）。相关论文发表在2022年6月2日出版的《自然-医学》杂志上。

研究人员开发了一种配对的肝-血浆蛋白质组学方法来推断分子病理生理学，并探索该血浆蛋白质组学在596名个体（137名对照个体和459名ALD患者）的诊断和预后判断方面的潜能，其中360名患者同时进行了基于活检的组织学评估。研究使用基于质谱(MS)的蛋白质组学工作流程分析了所有血浆样本和79个肝脏活检样本，该工作流程具有较短的梯度时间和增强的、与数据无关的采集方案，测量时间仅需3周。在血浆和肝活检组织中，与代谢相关的功能下调，而与纤维化相关的信号传导和免疫反应上调。

利用机器学习模型识别蛋白质组学生物标志物的方法比现有方法能更准确地检测到明显纤维化（受体操作特征-曲线下面积(ROC-AUC)， 0.92，准确度， 0.82）和轻度炎症（ROC-AUC， 0.87，准确度， 0.79）临床试验（DeLong 检验，P < 0.05）。这些生物标志物组可准确预测未来肝脏相关事件和全因死亡率，Harrell C指数分别为0.90和0.79。一个独立的验证队列重现了该诊断模型的结果，这为基于MS的常规肝病检测奠定了基础。

据了解，ALD是全球肝脏相关死亡的主要原因，但对该疾病的三个关键病理特征-纤维化、炎症和脂肪变性-了解甚少。

附：英文原文

Title: Noninvasive proteomic biomarkers for alcohol-related liver disease

Author: Niu, Lili, Thiele, Maja, Geyer, Philipp E., Rasmussen, Ditlev Nytoft, Webel, Henry Emanuel, Santos, Alberto, Gupta, Rajat, Meier, Florian, Strauss, Maximilian, Kjaergaard, Maria, Lindvig, Katrine, Jacobsen, Suganya, Rasmussen, Simon, Hansen, Torben, Krag, Aleksander, Mann, Matthias

Issue&Volume: 2022-06-02

Abstract: Alcohol-related liver disease (ALD) is a major cause of liver-related death worldwide, yet understanding of the three key pathological features of the disease—fibrosis, inflammation and steatosis—remains incomplete. Here, we present a paired liver–plasma proteomics approach to infer molecular pathophysiology and to explore the diagnostic and prognostic capability of plasma proteomics in 596individuals (137controls and 459individuals with ALD), 360 of whom had biopsy-based histological assessment. We analyzed all plasma samples and 79liver biopsies using a mass spectrometry (MS)-based proteomics workflow with short gradient times and an enhanced, data-independent acquisition scheme in only 3weeks of measurement time. In plasma and liver biopsy tissues, metabolic functions were downregulated whereas fibrosis-associated signaling and immune responses were upregulated. Machine learning models identified proteomics biomarker panels that detected significant fibrosis (receiver operating characteristic–area under the curve (ROC–AUC),0.92, accuracy,0.82) and mild inflammation (ROC–AUC,0.87, accuracy,0.79) more accurately than existing clinical assays (DeLong’s test, P<0.05). These biomarker panels were found to be accurate in prediction of future liver-related events and all-cause mortality, with a Harrell’s C-index of 0.90 and 0.79, respectively. An independent validation cohort reproduced the diagnostic model performance, laying the foundation for routine MS-based liver disease testing.

DOI: 10.1038/s41591-022-01850-y

Source: https://www.nature.com/articles/s41591-022-01850-y