结核性脑膜炎的潜在体液生物标志物研究

发布时间：2018-03-03 20:12

本文选题：结核性脑膜炎　切入点：生物标志物　出处：《重庆医科大学》2014年博士论文　论文类型：学位论文

【摘要】：背景结核性脑膜炎（Tuberculous meningitis, TBM）是由结核分枝杆菌（Mycobacterium tuberculosis, MTB）引起的中枢神经系统感染性疾病，约占结核病的7～10%，是以脑膜、大脑实质受损为主，并可波及脊髓、脊膜的非化脓性炎症。近年来由于人口流动频繁、免疫抑制剂广泛应用、耐药性结核菌株的出现及人免疫缺陷病毒的流行，TBM发病率有逐渐增高的趋势。而TBM的防治和诊疗过程中，早期准确的诊断与预后和治疗效果紧密相关联，因此准确有效的诊断方法在防治TBM中仍是当今亟待解决的重要医学问题。当前TBM的诊断主要依靠脑脊液（CSF）细胞、生化等检查。然而在TBM发生早期，CSF细胞学、生化变化多不典型，早期TBM诊断十分困难。本实验拟采用iTRAQ标记结合液相色谱串联质谱(iTRAQ—LC—MS／MS)的定量蛋白组学研究策略，，比较TBM患者和健康对照CSF蛋白质表型，鉴定出TBM相关的差异蛋白质，为探讨TBM病理生理机制和筛选潜在诊断标志物提供新的证据。 TBM常伴有血脑屏障的破坏，这使得TBM相关的代谢分子极易从CSF扩散至外周血液，提示检测TBM血液的代谢改变有望发现其潜在诊断标志物。本实验拟采用核磁共振（NMR）的代谢组学方法，筛选出TBM的潜在血液诊断标志物。目的 1.采用iTRAQ的定量蛋白组学技术，分析TBM和正常的脑脊液蛋白质改变、筛选并验证TBM的潜在CSF蛋白质诊断标志物； 2.采用核磁共振（NMR）的代谢组学方法，比较结核性脑膜炎患者与正常对照的血浆代谢谱，筛选TBM的潜在血浆代谢诊断标志物。方法 1.第一部分：通过iTRAQ标记蛋白组学方法，比较TBM疾病组（n=12）和正常对照(n=12)脑脊液蛋白谱，通过液相色谱-串联质谱（LC-MS/MS）鉴定TBM相关的脑脊液差异蛋白，通过生物信息学分析对差异蛋白进行功能注释和通路分析。进一步将筛选出的潜在的生物标志物蛋白进行WB验证，并构建诊断模型进行诊断效能评估。 2.第二部分：采用核磁共振（NMR）的代谢组学方法，比较结核性脑膜炎患者与正常对照的血浆代谢谱，筛选出结核性脑膜炎患者相对于健康对照者的血浆差异代谢物；分析差异代谢物的分子功能，初步探讨这些血浆差异代谢物在结核性脑膜炎发病中的潜在作用。结果１．使用iTRAQ定量蛋白质组学技术鉴别出81例差异蛋白质，对这部分蛋白质进行生物信息学分析，结果显示这些蛋白质的功能主要与凝血级联反应，炎症反应，细胞粘附密切相关。WB蛋白印迹实验验证结果指出NELL2水平在TBM疾病组相对于健康对照组呈现显著下降。ROC曲线分析结果提示NELL2的诊断效能：83.3%的敏感性和75%的特异性。该结果提示NELL2是TBM具有良好诊断效能的潜在生物标志物。２．采用核磁共振（NMR）偶联OPLS-DA的统计方法鉴定出TBM血浆相对于正常对照中的差异代谢物如下：有24个血浆差异代谢物质在结核性脑膜炎组与正常组区分中起主要作用（VIP1.0）。N-乙酰糖蛋白（N-acetylglycoprotein）、丙酮酸盐(Pyruvate)、葡萄糖（Glucose）、烟酰胺（Nicotinamide）、1-甲基组氨酸（1-Methylhistidine）、葡萄糖-内酯（Glucono-delta-lactone）在结核性脑膜炎中的表达量增高；低密度脂蛋白（LDL）、极低密度脂蛋白（VLDL）、脂质（Lipid）、异亮氨酸（Isoleucine）、亮氨酸（Leucine）、缬氨酸（Valine）、谷氨酸（Glutamine）、蛋氨酸（Methoinine）、组氨酸（Histidine）、3-羟基丁酸酯（3-Hydroxybutyrate）、乙酸（Acetate）、丙酮(Acetone)、乙醇（Ethanol）、磷酸胆碱（PC）、甘油磷酸胆碱（GPC）、乙酰乙酸（Acetoacetate）、谷氨酰胺（Glutamate）、 N-甲基烟酰胺（N-Methylnicotinamide）在结核性脑膜炎中的表达量降低。四种生物标志物N-乙酰糖蛋白（N-acetylglycoprotein）、烟酰胺（Nicotinamide）、葡萄糖（α-Glucose，β-Glucose）经二元Logistical Regression分析，在训练集中可区分结核性脑膜炎患者与正常对照，AUC值为0.810。在测试集中，这四种生物标志物可区分12例结核性脑膜炎患者与13例正常对照，AUC值为0.827。在病毒性脑膜炎与结核性脑膜炎训练集中，这四种生物标志物的AUC值为0.782。结论 1. NELL2可作为TBM潜在的生物标志物。 2.通过TBM患者血浆的代谢组学分析，我们鉴定出TBM相关的血浆差异代谢物质。分析这些差异代谢物质的分子功能，并采用独立样本验证相关差异代谢物的临床诊断价值，为寻找TBM的客观诊断方法提供了候选标志物。
[Abstract]:background
Tuberculous meningitis (Tuberculous meningitis, TBM) by Mycobacterium tuberculosis (Mycobacterium, tuberculosis, MTB) of central nervous system diseases caused by infection, accounting for about 7 to 10% TB, with meninges, brain parenchyma damage, and can spread to the spinal cord, spinal non suppurative inflammation. In recent years due to the floating population frequently, widely used immunosuppressant, emergence of drug-resistant strains of TB and HIV epidemic, has gradually increased the incidence rate of TBM. And the prevention and treatment of TBM in diagnosis and prognosis and treatment effect of accurate early closely related, so the medical problem diagnosis method is accurate and effective in the prevention and treatment of TBM is still an urgent.
The diagnosis of TBM mainly depends on the cerebrospinal fluid (CSF) cells, biochemical examination. However, in the early TBM, CSF cytology, biochemical changes are atypical, TBM early diagnosis is very difficult. This study combined with liquid chromatography tandem mass spectrometry using iTRAQ markers (iTRAQ - LC - MS / MS) the study strategy of quantitative protein group TBM patients and healthy controls CSF protein phenotype, identified differentially expressed proteins related to TBM, TBM to explore the pathophysiological mechanism and screening of potential diagnostic biomarkers provide new evidence.
TBM is often accompanied by the destruction of the blood-brain barrier, the metabolism of TBM related molecules easily from the diffusion of CSF to peripheral blood, prompt detection of TBM blood metabolic change is expected to find the potential diagnostic markers. This study using magnetic resonance imaging (NMR) metabonomics was screened for potential blood biomarkers in the diagnosis of TBM.
objective
1. the quantitative proteomic techniques of iTRAQ were used to analyze the protein changes in TBM and normal cerebrospinal fluid, and to screen and verify the potential diagnostic markers of the potential CSF protein of TBM.
2., we used nuclear magnetic resonance (NMR) metabonomics to compare the plasma metabolic profiles of tuberculous meningitis patients and normal controls, and screened the potential diagnostic markers of plasma metabolism of TBM.
Method
The 1. part: the first method by iTRAQ marker protein group, TBM disease group (n=12) and normal control (n=12) of cerebrospinal fluid protein, by liquid chromatography tandem mass spectrometry (LC-MS/MS) identification of TBM cerebrospinal fluid is related to the difference of the protein by bioinformatics analysis and functional annotation of proteins. The potential difference pathway the biomarker protein will be further screened for WB verification, and establish the diagnostic model for the diagnostic efficacy evaluation.
The second part 2.: using magnetic resonance imaging (NMR) metabonomics approach, comparison of tuberculosis meningitis in patients with normal plasma metabolic control spectrum, screened patients with tuberculous meningitis compared with healthy controls the difference of plasma metabolites; analysis of molecular function of different metabolites, preliminary study on the potential role of plasma metabolites in the pathogenesis of these differences in tuberculous meningitis in.
Result
1. using iTRAQ quantitative proteomics technique to identify 81 cases of differential proteomics, bioinformatics analysis of the protein, the results show that these proteins function and coagulation cascade reaction, inflammatory reaction, cell adhesion is closely related to.WB blot experiment results indicate that the NELL2 level of healthy control group showed significantly decreased.ROC curve analysis showed that the diagnostic value of NELL2 in the TBM group: compared with the sensitivity of 75% and specificity of 83.3%. The results suggest that NELL2 is a potential biomarker for TBM has good diagnostic performance.
2. using nuclear magnetic resonance (NMR) statistical method of coupling OPLS-DA identified TBM plasma metabolites in difference compared to normal control as follows: there are 24 different plasma metabolites play a major role in differentiating tuberculous meningitis group and normal group (VIP1.0).N- glycoprotein (N-acetylglycoprotein), acetyl pyruvate (Pyruvate), glucose (Glucose), nicotinamide (Nicotinamide), 1- methylhistidine (1-Methylhistidine), glucose (Glucono-delta-lactone) - lactone expression in tuberculous meningitis increased; low density lipoprotein (LDL), very low density lipoprotein (VLDL), lipid (Lipid), isoleucine (Isoleucine), leucine, valine ((Leucine) Valine), glutamic acid (Glutamine), methionine (Methoinine), histidine (Histidine), 3- hydroxybutyrate (3-Hydroxybutyrate), acetic acid (Acetate), acetone (Acetone), ethanol (Ethanol), choline phosphate (PC), Glycerophosphorylcholine (GPC), acetoacetate (Acetoacetate), glutamine (Glutamate), N- (N-Methylnicotinamide) methylnicotinamide expression in tuberculous meningitis decreased. Four biomarkers of N- glycoprotein (N-acetylglycoprotein), acetyl nicotinoyl amine (Nicotinamide), glucose (-Glucose alpha, beta -Glucose) analyzed by two yuan Logistical Regression, in the training set can distinguish patients with tuberculous meningitis and normal control, AUC value of 0.810. in the test set, these four biomarkers can differentiate 12 cases of tuberculous meningitis patients and 13 cases of normal control, AUC value of 0.827. in viral meningitis and tuberculous meningitis in the training set, the four species the AUC value of 0.782. markers
conclusion
1. NELL2 can be used as a potential biomarker for TBM.
The 2. group of TBM patients by metabolic analysis, we identified the differences related to the metabolism of plasma TBM. Molecular analysis of functional metabolites of these differences, and by independent sample validation related clinical diagnostic value of different metabolites, as objective diagnostic methods for TBM has provided the candidate markers.

【学位授予单位】：重庆医科大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：R529.3

【相似文献】