血热证寻常型银屑病病证代谢网络构建与优化研究

Psoriasis vulgar (PV) is a clinically common skin disease with relapsed and refractory characteristic. Blood-heat syndrome is also the key of disease transformation. The construction of the early specific disease-syndrome combination diagnosis index system is of great significance to the Traditional Chinese Medicine (TCM) clinically accurate diagnosis and treatment of PV. From the viewpoint of system biology, disease-syndrome is a characteristic pathological phenotype related to the abnormal expression of the human secreted endogenous small molecule metabolites groups, which results in the human metabolic network unbalance. Based on our previous bases and recent studies, we proposed a scientific hypothesis that the emergence of PV with blood-heat syndrome type is closely associated with the abnormal expression of endogenous small molecule metabolites and the imbalance of metabolic network. In this study, UPLC-ESI-MS/MS metabonomic technique combined with random forest classifier method will be employed to screen the specific metabolic biomarkers in plasma and saliva from blood-heat syndrome of PV patients. Metabo Analyst 2.0, KEGG and other bioinformatics techniques will be used to construct disease-syndrome metabolic networks based on plasma-saliva metabolic biomarkers of PV with blood-heat syndrome type. The ROC curve integrated with “syndrome differentitation through formula effect assessment” methods will be adopted to confirm and optimize disease-syndrome metabolic networks, and finally provide specific indicator cluster for clinical diagnosis, illness evaluation and curative effect assessment system of PV with blood-heat syndrome type. Our research will provide new insight for the disease-syndrome combination diagnosis index system.

银屑病是临床常见的复发难治性皮肤病，血热证是寻常型银屑病中医病证转化的关键，构建早期特异性病证结合诊断指标群，对本病临床精准诊疗具有重要意义。系统生物学认为病证是人体内源性小分子代谢物组（群）异常表达，导致生物代谢网络失衡而呈现的具有特征性的病理表型。基于前期研究和新近认识，我们提出“血热证寻常型银屑病的形成与机体内源性小分子代谢物异常表达及其代谢网络失衡密切相关”的科学假说。本项目拟采用UPLC-ESI-MS/MS代谢组学技术及随机森林算法，筛选血热证型银屑病病证血浆、唾液代谢标志物；采用Metabo Analyst 2.0、KEGG等生物信息学技术构建整合血浆-唾液代谢标志物的病证代谢网络；采用ROC曲线联合以方测证方法验证并优化病证代谢网络，为寻常型银屑病临床病证诊断、病情评估及疗效评价提供特异性指标群，为病证结合诊断体系研究提供新的方法与科学依据。

本项目基于UPLC-MS/MS检测平台、自建数据库以及多元统计分析相结合的方法，研究寻常型银屑病血浆和唾液样本的代谢差异，筛选病证代谢生物标志物，并采用ROC曲线进行验证。对病例中医证候、性别、年龄、BMI、病程、病情严重程度、疾病分期、家族史等因素进行再分层分组，分析组间显著差异代谢物。采用Metabo Analyst 2.0、KEGG等生物信息学技术，明确差异代谢物显著富集相关的代谢通路，分析不同临床分层因素呈现的代谢特征，为构建和优化整合血浆-唾液的病证代谢网络提供前期基础。研究结果显示：寻常型银屑病相对健康人群存在显著的血浆和唾液代谢差异。寻常型银屑病血浆代谢主要涉及有机酸、氨基酸等代谢类别，筛选出L-天冬氨酸、L-谷氨酸、甲酰四氢叶酸、谷氨酸盐、L-胱氨酸、L-半胱氨酸、腺苷-3'-磷酸等7个潜在生物标志物，主要富集于碳代谢、铁死亡、嘌呤代谢等代谢通路。唾液代谢主要涉及脂类等代谢类别，筛选出O-磷酸乙醇胺、磷酸胆碱、溶血卵磷脂酰胆碱等潜在生物标志物，主要富集于甘油磷脂、胆碱代谢等代谢通路。筛选出的差异代谢物及代谢通路有望为寻常型银屑病发病或复发诊疗指标提供参考，也为揭示本病的发生、发展及转归的潜在规律提供新的思路。寻常型银屑病各证候分组在血浆和唾液水平存在显著代谢差异，溶血卵磷脂酰胆碱、2-氨基己二酸、皮质醇等可作为证候分型潜在标志物，其中血热证候涉及了银杏酸、吡咯喹啉醌、L-天冬氨酸等特异性代谢物，其所显著富集的铁死亡等代谢通路的紊乱与调节可能参与了证候的形成与演进过程。性别、年龄、BMI、病程、病情程度、疾病分期、家族史等多因素分层代谢组学显示了各分组间血浆和唾液层面存在显著代谢差异。