Gao Bei, Zeng Suling, Maccioni Luca, Shi Xiaochun, Armando Aaron, Quehenberger Oswald, Zhang Xinlian, Stärkel Peter, Schnabl Bernd
School of Marine Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China.
Department of Medicine, University of California San Diego, La Jolla, CA 92093, USA.
Metabolites. 2022 May 11;12(5):433. doi: 10.3390/metabo12050433.
Alcohol-related liver disease is a public health care burden globally. Only 10-20% of patients with alcohol use disorder have progressive liver disease. This study aimed to identify lipid biomarkers for the early identification of progressive alcohol-related liver disease, which is a key step for early intervention. We performed untargeted lipidomics analysis in serum and fecal samples for a cohort of 49 subjects, including 17 non-alcoholic controls, 16 patients with non-progressive alcohol-related liver disease, and 16 patients with progressive alcohol-related liver disease. The serum and fecal lipidome profiles in the two patient groups were different from that in the controls. Nine lipid biomarkers were identified that were significantly different between patients with progressive liver disease and patients with non-progressive liver disease in both serum and fecal samples. We further built a random forest model to predict progressive alcohol-related liver disease using nine lipid biomarkers. Fecal lipids performed better (Area Under the Curve, AUC = 0.90) than serum lipids (AUC = 0.79). The lipid biomarkers identified are promising candidates for the early identification of progressive alcohol-related liver disease.
酒精性肝病是全球公共卫生保健的负担。只有10%-20%的酒精使用障碍患者会发展为进行性肝病。本研究旨在确定脂质生物标志物，以便早期识别进行性酒精性肝病，这是早期干预的关键步骤。我们对49名受试者的血清和粪便样本进行了非靶向脂质组学分析，其中包括17名非酒精性对照者、16名非进行性酒精性肝病患者和16名进行性酒精性肝病患者。两个患者组的血清和粪便脂质组谱与对照组不同。在血清和粪便样本中，确定了9种脂质生物标志物，它们在进行性肝病患者和非进行性肝病患者之间存在显著差异。我们进一步建立了一个随机森林模型，使用9种脂质生物标志物来预测进行性酒精性肝病。粪便脂质的表现优于血清脂质（曲线下面积，AUC = 0.90）（AUC = 0.79）。所确定的脂质生物标志物有望用于早期识别进行性酒精性肝病。
