摘要目的 应用聚类分析方法解析不同格拉斯哥评分(GCS)的重型颅脑创伤(sTBI)患者血清蛋白质表达谱的变化规律.方法 根据sTBI患者入院时的GCS将病人血清样本分为GCS 3～4分组、GCS 5～6分组、GCS 7～8分组和健康对照组.利用表面增强激光解析离子化(sELDI)蛋白芯片技术检测血清中的差异表达蛋白质,应用Cluster 3.0分析软件制作分层聚类图谱,结合统计学数据解析sELDI蛋白芯片检测结果.结果 应用聚类分析软件将sELDI检测数据成功进行分层聚类,其中GCS 3～4分组与GCS 5～6分组关系最为紧密,GCS 7～8分组次之,与健康对照组关系最疏远.共发现27个密切相关的蛋白质(P<0.05),这些差异蛋白质在sTBI病情演进过程中可能具有相同或相近的功能,或共同参与疾病的同一分子病理通路.结论 聚类分析法是分析sELDI蛋白芯片等大规模实验数据的理想工具.

abstractsObjective To analyze the serum protein profile of severe traumatic brain injury patients by using clustering analysis. Methods Serum samples were divided into four groups : GCS 3～4,GCS 5～6,GCS 7～8,and control group,respectively. Protein chip and SELDI were used to detect differential expression proteins,and the Cluster 3.0 software,combining statistics method were performed to form hierarchical dendrogram and analyze the serum protein profile results from SELDI. Results Hierarchical dendrogram was harvested successfully. There was the closest relationship between GCS 3～4 group and GCS 5～6 group,secondary GCS 7～8 group,and the control Group. 27 proteins were found out,which could be involved in the same pathology crossway of disease development. Conclusion The clustering analysis method is an ideal means in analyzing the serum protein profile from SELDI.