Lian Jiang-Shan, Liu Wei, Hao Shao-Rui, Chen Dde-Ying, Wang Yin-Yin, Yang Jian-Le, Jia Hong-Yu, Huang Jian-Rong
Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases; State Key Laboratory for Diagnosis and Treatment of Infectious Disease, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China. Email:
Hepatobiliary Pancreat Dis Int. 2015 Aug;14(4):413-21. doi: 10.1016/s1499-3872(15)60393-9.
Because of the diversity of the clinical and laboratory manifestations, the diagnosis of autoimmune liver disease (AILD) remains a challenge in clinical practice. The value of metabolomics has been studied in the diagnosis of many diseases. The present study aimed to determine whether the metabolic profiles, based on ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), differed between autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC), to identify specific metabolomic markers, and to establish a model for the diagnosis of AIH and PBC.
Serum samples were collected from 20 patients with PBC, 19 patients with AIH, and 25 healthy individuals. UPLC-MS data of the samples were analyzed using principal component analysis, partial least squares discrimination analysis and orthogonal partial least squares discrimination analysis.
The partial least squares discrimination analysis model (R2Y=0.991, Q2=0.943) was established between the AIH and PBC groups and exhibited both sensitivity and specificity of 100%. Five groups of biomarkers were identified, including bile acids, free fatty acids, phosphatidylcholines, lysolecithins and sphingomyelin. Bile acids significantly increased in the AIH and PBC groups compared with the healthy control group. The other biomarkers decreased in the AIH and PBC groups compared with those in the healthy control group. In addition, the biomarkers were downregulated in the AIH group compared with the PBC group.
The biomarkers identified revealed the pathophysiological changes in AILD and helped to discriminate between AIH and PBC. The predictability of this method suggests its potential application in the diagnosis of AILD.
由于临床和实验室表现的多样性,自身免疫性肝病(AILD)的诊断在临床实践中仍然是一项挑战。代谢组学在许多疾病的诊断中已有研究。本研究旨在确定基于超高效液相色谱 - 质谱联用(UPLC - MS)的代谢谱在自身免疫性肝炎(AIH)和原发性胆汁性肝硬化(PBC)之间是否存在差异,以识别特定的代谢组学标志物,并建立AIH和PBC的诊断模型。
收集了20例PBC患者、19例AIH患者和25名健康个体的血清样本。使用主成分分析、偏最小二乘判别分析和正交偏最小二乘判别分析对样本的UPLC - MS数据进行分析。
在AIH组和PBC组之间建立了偏最小二乘判别分析模型(R2Y = 0.991,Q2 = 0.943),其敏感性和特异性均为100%。识别出五组生物标志物,包括胆汁酸、游离脂肪酸、磷脂酰胆碱、溶血卵磷脂和鞘磷脂。与健康对照组相比,AIH组和PBC组的胆汁酸显著增加。与健康对照组相比,AIH组和PBC组的其他生物标志物减少。此外,与PBC组相比,AIH组的生物标志物下调。
所识别出的生物标志物揭示了AILD的病理生理变化,并有助于区分AIH和PBC。该方法的可预测性表明其在AILD诊断中的潜在应用价值。