Department of Hepatology, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Artificial Cells, Tianjin Third Central Hospital, Tianjin Medical University, Tianjin, China.
J Viral Hepat. 2010 Mar;17 Suppl 1:18-23. doi: 10.1111/j.1365-2893.2010.01267.x.
Chronic hepatitis B virus (HBV)-infected patients with liver failure have a poor prognosis, and no satisfactory biomarkers are available for diagnosis before the end-stage. We explored serum peptide profiling for diagnosis and prediction of progression to liver failure in HBV-infected patients. Serum samples (164) from healthy subjects (n = 20), or subjects with chronic hepatitis B without cirrhosis and liver failure [chronic hepatitis B subjects without cirrhosis and liver failure (CHB); n = 33], with compensated liver cirrhosis (compensated liver cirrhosis (LC); n = 35), with acute-on-chronic liver failure [acute-on-chronic liver failure (ACLF); n = 38] or with chronic liver failure [chronic liver failure (CLF), n = 38] were applied to ClinProt magnetic beads, and bound peptides/proteins were analyzed by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Our classification diagnostic models of liver disease were generated based on the Genetic Algorithm (GA) and Quick Classifier Algorithm (QC). Differentially expressed peptides were found among all test groups, with patterns of difference that readily distinguished between healthy and various HBV-associated liver disease samples. The model generated seven characteristic peptide peaks at 4053 m/z, 3506 m/z, 4963 m/z, 9289 m/z, 2628 m/z, 3193 m/z and 6432 m/z, giving overall predictive capability of 54.27%. Two-way comparisons of LC, ACLF or CLF vs CHB had predictive capabilities of 79.8%, 91.41% and 97.99%, respectively. Comparisons of ACLF or CLF vs LC were predictive at 87.72% and 82.18%, respectively and ACLF vs CLF was predictive at 75.05%. These classification diagnostic models generated by different peptide peaks were further validated in blinded tests with 67-100% accuracy. Serum peptide patterns vary during progression of chronic HBV infection to liver failure and may be used to distinguish different stages of the disease.
慢性乙型肝炎病毒（HBV）感染所致肝衰竭患者预后不良，在终末期前尚无满意的诊断标志物。我们探讨了血清肽谱分析在 HBV 感染患者肝衰竭诊断和预测中的作用。纳入健康对照者（20 例）、慢性乙型肝炎无肝硬化和肝衰竭患者[慢性乙型肝炎无肝硬化和肝衰竭（CHB）；33 例]、代偿性肝硬化患者（代偿性肝硬化（LC）；35 例）、慢加急性肝衰竭患者[慢加急性肝衰竭（ACLF）；38 例]和慢性肝衰竭患者[慢性肝衰竭（CLF），38 例]血清标本（164 例），应用 ClinProt 磁珠进行血清肽谱分析，基质辅助激光解吸电离飞行时间（MALDI-TOF）质谱分析结合遗传算法（GA）和快速分类算法（QC）建立疾病分类诊断模型。所有检测组均存在差异表达肽段，差异模式可区分健康对照和各种 HBV 相关肝病样本。该模型在 4053 m/z、3506 m/z、4963 m/z、9289 m/z、2628 m/z、3193 m/z 和 6432 m/z 处产生 7 个特征性肽峰，总体预测率为 54.27%。LC、ACLF 或 CLF 与 CHB 的双向比较预测能力分别为 79.8%、91.41%和 97.99%。ACLF 或 CLF 与 LC 比较的预测能力分别为 87.72%和 82.18%，ACLF 与 CLF 比较的预测能力为 75.05%。通过不同肽峰生成的分类诊断模型在盲法验证中准确率为 67%-100%。慢性 HBV 感染进展为肝衰竭过程中血清肽谱发生变化，可能用于区分疾病的不同阶段。
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