应用蛋白质组学方法检测系统性红斑狼疮的生物学标记物
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摘要
第一部分：神经精神狼疮脑脊液蛋白质指纹图谱及分析
目的筛选神经精神狼疮(NPSLE)脑脊液生物标志物,并建立相应NPSLE疾病的树形分类模型。材料和方法用MALDI-TOF-MS联合WCX磁珠生成脑脊液蛋白质谱,比较NPSLE治疗前组(39例)与无神经精神症状的系统性红斑狼疮组(non-NPSLE,10例)之间和脊柱侧凸组(17例)的差异蛋白峰；建立NPSLE的树形分类模型,并用其他中枢神经系统受累疾病(伴神经精神症状的自身免疫性疾病5例,腰椎间盘突出13例)进行盲法检验。比较26例NPSLE患者治疗前后脑脊液蛋白质谱的差异蛋白峰。结果NPSLE治疗前组与非精神神经狼疮组(脊柱侧凸和non-NPSLE)脑脊液蛋白质谱共有25个差异峰,用其中质荷比为3237,4312,4514,4550,6688,6378,6822,8349,8595,11744和16230差异峰建立NPSLE树形分类模型,其对源数据的敏感性92.1%,特异性100%,盲法检验显示该模型分类NPSLE的特异性为85.7%。26例NPSLE患者治疗前后脑脊液质谱有18个差异峰,其中质荷比为4450、6822和8595蛋白峰显著降低,而在一例难治性NPSLE中,这三个差异峰并无变化。结论MALDI-TOF-MS联合WCX磁珠可用于脑脊液蛋白质组研究,发现了多个潜在脑脊液生物标志物可能用于NPSLE检测、诊断和病情评估,建立了敏感性及特异性均好的NPSLE树形分类模型。
第二部分：神经精神狼疮脑脊液蛋白质指纹图谱差异蛋白峰鉴定
研究背景及目的泛素蛋白(ubiquitin)是一种大多数真核细胞中76氨基酸蛋白,主要功能是标记需要分解掉的蛋白质,使其被水解。多项研究鉴定脑脊液SELDI-TOF-MS质谱的质荷比为8.6kda蛋白峰对应泛素蛋白(ubiquitin)。试验拟鉴定脑脊液质谱质荷比8.6kda的差异蛋白峰为ubiquitin蛋白。材料和方法使用兔抗人ubiquitin抗体进行脑脊液免疫沉淀后,分别运用MALDI-TOF-MS联合WCX磁珠法和免疫印迹法检测免疫沉淀反应后上清及沉淀蛋白。结果ubiquitin抗体免疫沉淀后上清蛋白质谱中质荷比8.6kda的蛋白峰强度显著下降；NPSLE患者CSF原液在免疫印迹中出现分子量介于6kd和14kd的目的条带,在加入ubiquitin抗体免疫沉淀后上清没有发现介于6kd和14kd的目的条带；抗ubiquitin的酶联免疫吸附测定(ELISA)检测NPSLE脑脊液中ubiquitin浓度较无神经精神症状的SLE组明显升高。结论脑脊液蛋白质谱的质荷比8.6kda蛋白峰对应ubiquitin蛋白,神经精神ubiquitin蛋白,神经精神狼疮(NPSLE)患者脑脊液泛素蛋白(ubiquitin)水平升高,提示泛素蛋白(ubiquitin)可能成为NPSLE的生物标志物。
第三部分活动性红斑狼疮甲基强的松龙冲击前后的蛋白质指纹图谱及分析
目的筛选活动性系统性红斑狼疮(SLE)甲基强的松龙冲击治疗前后血清生物标志物,并建立相应SLE甲基强的松龙冲击前后的树形分类模型。材料和方法用MALDI-TOF-MS联合WCX磁珠生成血清蛋白质谱,比较(38例)冲击治疗前后相关的血清的差异蛋白峰。结果冲击治疗前有效组和无效组蛋白质谱共有8个差异峰,用其中质荷比为4492、9198、5713、8469、10751、3456、9059差异峰建立SLE冲击治疗前的树形分类模型,其对数据源的敏感性为92.6%、特异性为100.0%；冲击治疗十四天后有效组和无效组蛋白质谱共有25个差异峰,用其中5261、5350、5939、6001、6122、7217、7997、8891、10901等差异峰建立SLE冲击治疗十四天后关于治疗有效组和无效组的树形分类模型,其对数据源的敏感性为96.3%、特异性为100.0%；SLE治疗前组(38例)和后组(38例)蛋白质谱共有18个差异峰,用其中质荷比为6958、27186、22844、6743、11404和3054差异峰建立SLE甲强冲击前后树形分类模型,其对源数据的敏感性84.2%,特异性89.5%；结论MALDI-TOF-MS联合WCX磁珠可用于血清蛋白质组研究,发现了多个潜在血清生物标志物可能用于SLE诊断、激素冲击治疗反应判断和进行SLE活动性评估,建立了敏感性及特异性均好的SLE树形分类模型。
PART one:Proteomic profiling of cerebrospinal fluid identifies biomarkers for neuropsychiatric systemic lupus erythematosus
Objective:To identify neuropsychiatric systemic lupus erythematosus (NPSLE) specific cerebrospinal fluid (CSF) biomarkers and construct a decision tree model for NPSLE classification. Methods:we compared the proteomic profile of CSF from39patients with neuropsychiatric systemic lupus erythematosus (NPSLE),10SLE patients without neuropsychiatric symptoms (non-NPSLE) and17patients with scoliosis, using matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. We developed a decision tree model for NPSLE classification with biomarker patterns software, and tested the model with other independent CNS diseases (18samples). Results:We identified25mass-to-charge (m/z) peaks with statistically significant (p<0.05) differences between NPSLE (before treatment) patients and control group1(non-NPSLE). Of them, the m/z peaks at3237,4312,4514,4550,6688,6378,6822,8349,8595,11744and16230were used to construct a decision tree model to distinguish NPSLE from non-NPSLE patients with a sensitivity of92.1%and a specificity of100.0%based on learning data, with a specificity of85.7%based on external blind testing data. There were18m/z peaks with statistically significant (p<0.05) differences between before and after treatment in the same group of NPSLE patients. Of them4550,6822and8595decreased, while in a refractory case, they did not decrease. Conclusion: Our data suggested a potential application of MALDI-TOF-MS combined with weak cationic exchange magnetic beads to profile CSF proteome, several potential CSF biomarkers were indicated to detect, diagnose and monitor NPSLE, a decision tree model for NPSLE classification was set up with high sensitivity and specificity.
PART two:Identifying one protein in the proteomic signature as ubiquitin
Background and Objective:Ubiquitin is a protein containing76amino acid protein in eukaryotic cells. The main function is to mark proteins need to be broken down,then be hydrolyzed. A number of studies identified CSF by MALDI-TOF-MS that mass to charge ratio8.6kda protein peak corresponding to the ubiquitin. We undertook this study to prove the presence of m/z peak of8.6kda in CSF profile as ubiquitin.
Methods:CSF was immunoprecipitated with rabbit anti(Hu)-ubiquitin antibody, after immunoprecipitation, the proteins of supernatant and agarose beads were detected by
MALDI-TOF-MS and western blot, respectively. Results:The m/z peak of8.6kda in CSF profile was validated to be ubiquitin protein by both immunoprecipitation combining with MALDI-TOF-MS&WCX magnetic beads, immunoprecipitation combining with western blot and anti-ubiquitin ELISA. Conclusion:CSF protein mass spectra peaks corresponding to charge ratio8.6kda protein ubiquitin protein, neuropsychiatric systemic lupus erythematosus (NPSLE) patients with cerebrospinal fluid ubiquitin protein (ubiquitin) elevated, suggesting that the ubiquitin protein (ubiquitin) may be biomarkers of NPSLE。
PART three:Proteomics profiles of Methylprednisolone Pulse Therapy in the treatment of Systemic Lupus Erythematosus flares
Objective:To identify serum biomarkers of systemic lupus erythematosus (SLE) before and after methylprednisolone pulse therapy and construct a decision tree model for NPSLE classification. Methods:we compared the proteomic profile of serum from38patients with SLE flares before and14days after methylprednisolone pulse therapy, using matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. Results:Before the treatment, there were8discriminating peaks between effective group and ineffective group, and we used them to construct a decision tree model to distinguish effective from ineffective patients with a sensitivity of92.6%and a specificity of100%based on learning data. After14days of there were25discriminating peaks between effective group and ineffective group, and we used them to construct a decision tree model to distinguish effective from ineffective patients with a sensitivity of96.3%and a specificity of100%based on learning data. And we found18discriminating peaks between group before treatment and group after treatment, and construct a decision tree model to distinguish effective from ineffective patients with a sensitivity of84.2%and a specificity of89.5%based on learning data. Conclusion:Our data suggested a potential application of MALDI-TOF-MS combined with weak cationic exchange magnetic beads to profile serum proteome, several potential biomarkers were indicated to diagnosis and management of SLE, a decision tree model for NPSLE classification was set up with high sensitivity and specificity.
目的筛选神经精神狼疮(NPSLE)脑脊液生物标志物,并建立相应NPSLE疾病的树形分类模型。材料和方法用MALDI-TOF-MS联合WCX磁珠生成脑脊液蛋白质谱,比较NPSLE治疗前组(39例)与无神经精神症状的系统性红斑狼疮组(non-NPSLE,10例)之间和脊柱侧凸组(17例)的差异蛋白峰；建立NPSLE的树形分类模型,并用其他中枢神经系统受累疾病(伴神经精神症状的自身免疫性疾病5例,腰椎间盘突出13例)进行盲法检验。比较26例NPSLE患者治疗前后脑脊液蛋白质谱的差异蛋白峰。结果NPSLE治疗前组与非精神神经狼疮组(脊柱侧凸和non-NPSLE)脑脊液蛋白质谱共有25个差异峰,用其中质荷比为3237,4312,4514,4550,6688,6378,6822,8349,8595,11744和16230差异峰建立NPSLE树形分类模型,其对源数据的敏感性92.1%,特异性100%,盲法检验显示该模型分类NPSLE的特异性为85.7%。26例NPSLE患者治疗前后脑脊液质谱有18个差异峰,其中质荷比为4450、6822和8595蛋白峰显著降低,而在一例难治性NPSLE中,这三个差异峰并无变化。结论MALDI-TOF-MS联合WCX磁珠可用于脑脊液蛋白质组研究,发现了多个潜在脑脊液生物标志物可能用于NPSLE检测、诊断和病情评估,建立了敏感性及特异性均好的NPSLE树形分类模型。
第二部分：神经精神狼疮脑脊液蛋白质指纹图谱差异蛋白峰鉴定
研究背景及目的泛素蛋白(ubiquitin)是一种大多数真核细胞中76氨基酸蛋白,主要功能是标记需要分解掉的蛋白质,使其被水解。多项研究鉴定脑脊液SELDI-TOF-MS质谱的质荷比为8.6kda蛋白峰对应泛素蛋白(ubiquitin)。试验拟鉴定脑脊液质谱质荷比8.6kda的差异蛋白峰为ubiquitin蛋白。材料和方法使用兔抗人ubiquitin抗体进行脑脊液免疫沉淀后,分别运用MALDI-TOF-MS联合WCX磁珠法和免疫印迹法检测免疫沉淀反应后上清及沉淀蛋白。结果ubiquitin抗体免疫沉淀后上清蛋白质谱中质荷比8.6kda的蛋白峰强度显著下降；NPSLE患者CSF原液在免疫印迹中出现分子量介于6kd和14kd的目的条带,在加入ubiquitin抗体免疫沉淀后上清没有发现介于6kd和14kd的目的条带；抗ubiquitin的酶联免疫吸附测定(ELISA)检测NPSLE脑脊液中ubiquitin浓度较无神经精神症状的SLE组明显升高。结论脑脊液蛋白质谱的质荷比8.6kda蛋白峰对应ubiquitin蛋白,神经精神ubiquitin蛋白,神经精神狼疮(NPSLE)患者脑脊液泛素蛋白(ubiquitin)水平升高,提示泛素蛋白(ubiquitin)可能成为NPSLE的生物标志物。
第三部分活动性红斑狼疮甲基强的松龙冲击前后的蛋白质指纹图谱及分析
目的筛选活动性系统性红斑狼疮(SLE)甲基强的松龙冲击治疗前后血清生物标志物,并建立相应SLE甲基强的松龙冲击前后的树形分类模型。材料和方法用MALDI-TOF-MS联合WCX磁珠生成血清蛋白质谱,比较(38例)冲击治疗前后相关的血清的差异蛋白峰。结果冲击治疗前有效组和无效组蛋白质谱共有8个差异峰,用其中质荷比为4492、9198、5713、8469、10751、3456、9059差异峰建立SLE冲击治疗前的树形分类模型,其对数据源的敏感性为92.6%、特异性为100.0%；冲击治疗十四天后有效组和无效组蛋白质谱共有25个差异峰,用其中5261、5350、5939、6001、6122、7217、7997、8891、10901等差异峰建立SLE冲击治疗十四天后关于治疗有效组和无效组的树形分类模型,其对数据源的敏感性为96.3%、特异性为100.0%；SLE治疗前组(38例)和后组(38例)蛋白质谱共有18个差异峰,用其中质荷比为6958、27186、22844、6743、11404和3054差异峰建立SLE甲强冲击前后树形分类模型,其对源数据的敏感性84.2%,特异性89.5%；结论MALDI-TOF-MS联合WCX磁珠可用于血清蛋白质组研究,发现了多个潜在血清生物标志物可能用于SLE诊断、激素冲击治疗反应判断和进行SLE活动性评估,建立了敏感性及特异性均好的SLE树形分类模型。
PART one:Proteomic profiling of cerebrospinal fluid identifies biomarkers for neuropsychiatric systemic lupus erythematosus
Objective:To identify neuropsychiatric systemic lupus erythematosus (NPSLE) specific cerebrospinal fluid (CSF) biomarkers and construct a decision tree model for NPSLE classification. Methods:we compared the proteomic profile of CSF from39patients with neuropsychiatric systemic lupus erythematosus (NPSLE),10SLE patients without neuropsychiatric symptoms (non-NPSLE) and17patients with scoliosis, using matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. We developed a decision tree model for NPSLE classification with biomarker patterns software, and tested the model with other independent CNS diseases (18samples). Results:We identified25mass-to-charge (m/z) peaks with statistically significant (p<0.05) differences between NPSLE (before treatment) patients and control group1(non-NPSLE). Of them, the m/z peaks at3237,4312,4514,4550,6688,6378,6822,8349,8595,11744and16230were used to construct a decision tree model to distinguish NPSLE from non-NPSLE patients with a sensitivity of92.1%and a specificity of100.0%based on learning data, with a specificity of85.7%based on external blind testing data. There were18m/z peaks with statistically significant (p<0.05) differences between before and after treatment in the same group of NPSLE patients. Of them4550,6822and8595decreased, while in a refractory case, they did not decrease. Conclusion: Our data suggested a potential application of MALDI-TOF-MS combined with weak cationic exchange magnetic beads to profile CSF proteome, several potential CSF biomarkers were indicated to detect, diagnose and monitor NPSLE, a decision tree model for NPSLE classification was set up with high sensitivity and specificity.
PART two:Identifying one protein in the proteomic signature as ubiquitin
Background and Objective:Ubiquitin is a protein containing76amino acid protein in eukaryotic cells. The main function is to mark proteins need to be broken down,then be hydrolyzed. A number of studies identified CSF by MALDI-TOF-MS that mass to charge ratio8.6kda protein peak corresponding to the ubiquitin. We undertook this study to prove the presence of m/z peak of8.6kda in CSF profile as ubiquitin.
Methods:CSF was immunoprecipitated with rabbit anti(Hu)-ubiquitin antibody, after immunoprecipitation, the proteins of supernatant and agarose beads were detected by
MALDI-TOF-MS and western blot, respectively. Results:The m/z peak of8.6kda in CSF profile was validated to be ubiquitin protein by both immunoprecipitation combining with MALDI-TOF-MS&WCX magnetic beads, immunoprecipitation combining with western blot and anti-ubiquitin ELISA. Conclusion:CSF protein mass spectra peaks corresponding to charge ratio8.6kda protein ubiquitin protein, neuropsychiatric systemic lupus erythematosus (NPSLE) patients with cerebrospinal fluid ubiquitin protein (ubiquitin) elevated, suggesting that the ubiquitin protein (ubiquitin) may be biomarkers of NPSLE。
PART three:Proteomics profiles of Methylprednisolone Pulse Therapy in the treatment of Systemic Lupus Erythematosus flares
Objective:To identify serum biomarkers of systemic lupus erythematosus (SLE) before and after methylprednisolone pulse therapy and construct a decision tree model for NPSLE classification. Methods:we compared the proteomic profile of serum from38patients with SLE flares before and14days after methylprednisolone pulse therapy, using matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) combined with weak cationic exchange magnetic beads. Results:Before the treatment, there were8discriminating peaks between effective group and ineffective group, and we used them to construct a decision tree model to distinguish effective from ineffective patients with a sensitivity of92.6%and a specificity of100%based on learning data. After14days of there were25discriminating peaks between effective group and ineffective group, and we used them to construct a decision tree model to distinguish effective from ineffective patients with a sensitivity of96.3%and a specificity of100%based on learning data. And we found18discriminating peaks between group before treatment and group after treatment, and construct a decision tree model to distinguish effective from ineffective patients with a sensitivity of84.2%and a specificity of89.5%based on learning data. Conclusion:Our data suggested a potential application of MALDI-TOF-MS combined with weak cationic exchange magnetic beads to profile serum proteome, several potential biomarkers were indicated to diagnosis and management of SLE, a decision tree model for NPSLE classification was set up with high sensitivity and specificity.
引文
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