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人类肝移植后早期移植物功能障碍的基因组谱和预测因子。

Genomic profiles and predictors of early allograft dysfunction after human liver transplantation.

机构信息

Department of Molecular and Experimental Medicine, The Scripps Research Institute, La Jolla, CA.

Penn Transplant Institute, Department of Surgery, University of Pennsylvania, Philadelphia, PA.

出版信息

Am J Transplant. 2015 Jun;15(6):1605-14. doi: 10.1111/ajt.13145. Epub 2015 Mar 31.

DOI:10.1111/ajt.13145
PMID:25828101
Abstract

Early hepatic allograft dysfunction (EAD) manifests posttransplantation with high serum transaminases, persistent cholestasis, and coagulopathy. The biological mechanisms are poorly understood. This study investigates the molecular mechanisms involved in EAD and defines a gene expression signature revealing different biological pathways in subjects with EAD from those without EAD, a potential first step in developing a molecular classifier as a potential clinical diagnostic. Global gene expression profiles of 30 liver transplant recipients of deceased donor grafts with EAD and 26 recipients without graft dysfunction were investigated using microarrays of liver biopsies performed at the end of cold storage and after graft reperfusion prior to closure. Results reveal a shift in inflammatory and metabolic responses between the two time points and differences between EAD and non-EAD. We identified relevant pathways (PPARα and NF-κB) and targets (such as CXCL1, IL1, TRAF6, TIPARP, and TNFRSF1B) associated with the phenotype of EAD. Preliminary proof of concept gene expression classifiers that distinguish EAD from non-EAD patients, with Area Under the Curve (AUC) >0.80 were also identified. This data may have mechanistic and diagnostic implications for EAD.

摘要

早期肝移植功能障碍(EAD)表现为移植后血清转氨酶升高、持续胆汁淤积和凝血功能障碍。其生物学机制尚不清楚。本研究探讨了 EAD 相关的分子机制,并确定了一个基因表达特征,揭示了 EAD 患者和无 EAD 患者之间不同的生物学途径,这可能是开发分子分类器作为潜在临床诊断的第一步。通过对 30 例 EAD 患者和 26 例无移植物功能障碍患者的肝移植供体冷保存结束时和再灌注后行肝活检的微阵列进行研究,调查了 EAD 和无 EAD 患者的基因表达谱。结果显示,在两个时间点之间存在炎症和代谢反应的转变,EAD 和非 EAD 之间存在差异。我们确定了与 EAD 表型相关的相关途径(PPARα 和 NF-κB)和靶点(如 CXCL1、IL1、TRAF6、TIPARP 和 TNFRSF1B)。还确定了区分 EAD 和非 EAD 患者的初步概念验证基因表达分类器,AUC>0.80。这些数据可能对 EAD 具有机制和诊断意义。

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