血浆长链非编码RNAs作为系统性红斑狼疮生物标志物的分子流行病学研究

发布时间：2017-12-28 23:16

  本文关键词：血浆长链非编码RNAs作为系统性红斑狼疮生物标志物的分子流行病学研究　出处：《安徽医科大学》2017年博士论文　论文类型：学位论文

  更多相关文章： 长链非编码RNA 系统性红斑狼疮 狼疮肾炎 血浆 生物标志物

【摘要】：背景系统性红斑狼疮(systemic lupus erythematosus,SLE)具有复杂的遗传背景,涉及编码基因和非编码基因,过去普遍认为编码基因在疾病的发生发展中起重要作用,但很少关注基因组中的非编码RNA(non-coding RNA,nc RNA)。按长度大小,具有调控作用的nc RNA主要分为两类:≤200 nt的短链非编码RNA(主要为微小RNA(micro RNA,简称mi RNA))和200 nt的长链非编码RNA(long non-coding RNA,lnc RNA)。大量研究表明mi RNA在SLE的发病过程中发挥着关键作用,可作为一种新型生物标志物用于SLE的诊断和预后评估。与mi RNA相比,lnc RNA的种类繁多且数量庞大,能够从表观遗传水平、转录水平、转录后水平和蛋白质代谢等多个层面调控基因表达。Lnc RNA在人类多种疾病的发生发展过程中也起着非常重要的调控作用。新近研究表明,在SLE患者外周血单核细胞中,linc0949(ENST00000500949)和NEAT1(nuclear enriched abundant transcript 1)的表达水平明显异常,且与疾病活动度和肾脏受累有关,NEAT1通过丝裂原活化蛋白激酶(mitogen-activated protein kinase,MAPK)通路,促进相关趋化因子和炎症因子的表达,进而参与SLE的发病过程。由于SLE临床表现复杂多样,病情反复多变,早期诊断困难,因此迫切需要寻求一种新型、特异性及敏感性较高的生物标志物用于SLE的诊断和预后评估。研究证实lnc RNA在血浆中稳定存在,可作为肿瘤和心血管疾病的早期生物标志物和治疗靶点,用于疾病的早期筛查、诊断和预后评估。然而目前,关于lnc RNA在SLE患者中的研究还很有限,且探讨血浆lnc RNA作为SLE疾病易感性标志物的研究尚未见报道。目的筛选在SLE患者血浆中异常表达的lnc RNAs,并进行独立验证,评估差异血浆lnc RNAs作为SLE辅助诊断的生物标志物的价值;利用生物信息学分析,对差异lnc RNAs进行功能预测,探讨其在SLE发病中的作用机制。方法本研究共分为两部分:第一部分:SLE患者血浆差异lnc RNAs的筛选、验证及作为生物标志物的价值本部分采用的是四阶段病例-对照设计:第一阶段:收集新发SLE非肾炎患者、新发狼疮肾炎(lupus nephritis,LN)患者和正常对照血浆各12例,各组每4例血浆总RNA等量混合,即形成每组各3份血浆总RNA池。利用lnc RNA芯片检测血浆lnc RNA表达谱,筛选差异lnc RNAs。第二阶段:小样本初步验证,在原单个血浆标本中,采用定量逆转录聚合酶链反应(quantitative reverse transcription polymerase chain reaction,q RT-PCR)技术,对从芯片中筛选出的10个候选差异lnc RNAs和根据文献挑选的5个候选lnc RNAs(ENST00000500597:linc0597;ENST00000500949:linc0949;ENST00000449289:GAS5或lnc9289;ENST00000587298:lnc-DC;ENST00000495032:HOTAIRM1)的表达水平进行初步验证。第三阶段:大样本独立验证,另收集240例SLE患者和120例正常对照的血浆标本,随机分为训练组(SLE患者160例,正常对照80例)和测试组(SLE患者80例,正常对照40例)。首先,在训练组中,采用q RT-PCR技术检测从小样本初步验证中得到的差异lnc RNAs;然后,在测试组中,应用q RT-PCR技术对从训练组中验证出的差异lnc RNAs给予进一步验证;最后,在240例SLE患者中,探讨最终验证出的差异lnc RNAs与主要临床指标的关联性。此外,为了评价血浆差异lnc RNAs单个或组合作为SLE生物标志物的价值,我们首先采用受试者工作特征(receiver operating characteristic,ROC)曲线分析各单个差异lnc RNAs的诊断价值,然后基于训练组,应用logistic回归分析构建预测SLE风险的lnc RNAs联合判别模型,并在训练组和测试组中,采用ROC曲线分析探讨其联合诊断价值。最后,我们在240例SLE患者中,按照有无肾炎将SLE患者分为LN组和SLE非肾炎组,应用logistic回归分析构建预测LN风险的lnc RNAs联合判别模型,采用ROC曲线分析探讨血浆差异lnc RNAs单个或组合作为鉴别LN和SLE非肾炎生物标志物的价值。第四阶段:应用q RT-PCR技术检测差异lnc RNAs在疾病对照组(类风湿关节炎(rheumatoid arthritis,RA)患者30例,原发性干燥综合征(primary Sjogren's syndrome,p SS)患者31例)血浆中的表达情况,评估差异lnc RNAs作为SLE生物标志物的特异性,并采用ROC曲线分析对联合判别模型的诊断价值给予进一步验证。第二部分:SLE相关m RNAs及lnc RNAs的生物信息学研究对lnc RNA芯片建立的SLE患者血浆m RNA差异表达谱,进行基因本体论(gene ontology,GO)和KEGG生物学途径(Kyoto encyclopedia of genes and genomes pathway)分析;同时结合q RT-PCR验证结果,建立差异lnc RNA-m RNA共表达网络分析;采用竞争性内源RNA(competitive endogenous RNA,ce RNA)分析,构建m RNA-mi RNA-lnc RNA调控网络,探寻可作为ce RNA的lnc RNA。结果第一部分:SLE患者血浆差异lnc RNAs的筛选、验证及作为生物标志物的价值本研究通过lnc RNA芯片建立了SLE非肾炎和LN的血浆lnc RNA和m RNA差异表达谱(差异倍数≥2倍,P≤0.05),从中筛选出10个候选血浆差异表达lnc RNAs,并结合文献挑选的5个候选lnc RNAs进行小样本初步验证。小样本初步验证发现,与正常对照相比,在SLE患者血浆中15个候选lnc RNAs(ENST00000450640:lnc0640;ENST00000583643:lnc3643;ENST00000584688:lnc4688;ENST00000425150:lnc5150;ENST00000506655:lnc6655;NR_027074:lnc7074;ENST00000507514:lnc7514;ENST00000458228:lnc8228;ENST00000519603:lnc9603;uc001agf.1:lncagf.1;GAS5;linc0597;linc0949;lnc-DC;HOTAIRM1)中共有9个lnc RNAs(GAS5,linc0597,lnc0640,lnc5150,lnc3643,lnc6655,lnc7074,lnc7514,lncagf.1)的表达水平存在显著变化(均有P0.05)。大样本独立验证进一步确定了在训练组和测试组的血浆样本中,linc0597、GAS5、lnc0640、lnc5150和lnc7074的表达水平均显著变化(均有P0.05)。且在训练组和测试组中,LN患者与SLE非肾炎患者比较,lnc7074、lnc3643、lnc0640、lnc7514和lnc6655的表达水平均显著上调(均有P0.05)。关联性研究结果显示血浆linc0597和GAS5的表达水平与C3水平均呈显著负相关(分别为P0.001和P=0.009);lnc5150的表达水平与血小板减少和C3水平显著相关(分别为P=0.008和P=0.001);lnc0640的表达水平与低补体、血小板减少和C3水平显著相关(分别为P=0.001、P=0.017和P0.001);lnc7074的表达水平与血小板减少和C3水平显著相关(分别为P=0.028和P0.001)。在训练组中,血浆linc0597、GAS5、lnc0640、lnc5150和lnc7074作为SLE生物标志物的ROC曲线下面积(area under the curve,AUC)分别为0.634、0.824、0.598、0.625和0.602,5个lnc RNAs组合预测SLE风险的判别公式为logit(P=SLE)=-2.594+7.503×linc0597-14.253×GAS5+2.853×lnc5150-7.012×lnc7074+6.233×lnc0640,AUC为0.966。在测试组中,血浆linc0597、GAS5、lnc0640、lnc5150和lnc7074作为SLE生物标志物的AUC分别为0.649、0.851、0.615、0.683和0.662,联合判别模型的AUC为0.968。与测试组SLE患者相比,在RA患者的血浆中,GAS5和linc0597的表达水平均显著上调(均有P0.05);在p SS患者的血浆中,GAS5和lnc7074的表达水平均显著上调(均有P0.05)。在测试组SLE患者和RA患者中,联合判别模型的AUC为0.683;在测试组SLE患者和p SS患者中,联合判别模型的AUC为0.910;在测试组SLE患者和RA患者+p SS患者中,联合判别模型的AUC为0.798。在240例SLE患者中,肾炎组和非肾炎组相比,血浆lnc0640、lnc3643、lnc5150、lnc6655、lnc7074和lnc7514的表达水平均显著上调(均有P0.05)。lnc0640、lnc3643、lnc5150、lnc6655、lnc7074和lnc7514用于鉴别LN和SLE非肾炎的AUC分别为0.644、0.671、0.601、0.631、0.665和0.684;lnc3643、lnc5150和lnc7514可联合作为鉴别LN和SLE非肾炎的生物标志物,3个lnc RNAs预测LN风险的联合判别公式为logit(P=LN)=-0.139+1.387×lnc3643-2.048×lnc5150+1.647×lnc7514,AUC为0.716。第二部分:SLE相关m RNAs及lnc RNAs的生物信息学研究GO分析结果显示,在SLE患者下调的血浆m RNAs中,“ion homeostasis”、“cation transmembrane transporter activity”和“plasma membrane part”分别在生物过程(biological process,BP)、分子功能(molecular function,MF)和细胞组分(cellular component,CC)中富集程度最高;在SLE患者上调的血浆m RNAs中,“cell-cell signaling”、“anion:cation symporter activity”和“cell periphery”分别在BP、MF和CC中富集程度最高。KEGG Pathway分析结果显示,在SLE患者下调的血浆m RNAs中,“axon guidance-Homo sapiens(human)”通路富集程度最高;在SLE患者上调的血浆m RNAs中,“MAPK signaling pathway-Homo sapiens(human)”通路富集程度最高。Lnc RNA-m RNA共表达网络分析结果显示,GAS5、lnc0640、lnc5150、lnc7074、lnc3643、lnc6655和lnc7514分别与174、18、48、30、36、28和20个m RNAs有较一致的表达模式(Pearson相关系数≥0.935)。其中,DUSP4(dual specificity phosphatase 4)、ARRB2(arrestin beta 2)和RPS6KA5(ribosomal protein S6 kinase A5)可能分别是GAS5、lnc0640和lnc5150正向调控的靶基因,GAS5、lnc0640和lnc5150可能均通过MAPK通路参与SLE的发病过程;C4orf26(chromosome 4open reading frame 26)可能为lnc0640、lnc5150、lnc6655和lnc7074共同作用的靶基因;PARP16(poly(ADP-ribose)polymerase family member 16)可能为lnc3643、lnc5150、lnc6655和lnc7074共同作用的靶基因。Ce RNA分析结果显示,GAS5、lnc0640、lnc3643、lnc6655和lnc7074可作为ce RNA与预测靶基因竞争靶向mi RNAs,进而影响靶向mi RNAs对其预测靶基因的调控。结论1.与正常对照相比,SLE患者血浆中GAS5和lnc7074表达水平显著下调,linc0597、lnc0640和lnc5150表达水平显著上调;SLE患者血浆中linc0597和GAS5的表达水平显著低于RA患者,GAS5和lnc7074的表达水平显著低于p SS患者;2.血浆linc0597、GAS5、lnc0640、lnc5150和lnc7074联合有望作为SLE潜在的生物标志物;lnc3643、lnc5150和lnc7514联合有望作为鉴别LN和SLE非肾炎潜在的生物标志物;3.GAS5、lnc0640和lnc5150可能通过MAPK通路参与SLE的发病过程;4.GAS5、lnc0640、lnc3643、lnc6655和lnc7074可能作为ce RNA,影响靶向mi RNAs对其预测靶基因的调控。
[Abstract]:The background of systemic lupus erythematosus (systemic lupus, erythematosus, SLE) has a complex genetic background, involving genes encoding and non encoding gene encoding gene, it is widely accepted that play an important role in the development of diseases, but little attention to non encoding in the genome of RNA (non-coding RNA, NC RNA). According to the size of NC RNA is regulated mainly divided into two categories: less than 200 short chain NT non RNA encoding (mainly for micro RNA (micro RNA, MI RNA)) and long chain 200 NT encoding RNA (long non-coding non RNA, LNC RNA). A large number of studies have shown that MI RNA plays a key role in the pathogenesis of SLE, and can be used as a new biomarker for the diagnosis and prognosis evaluation of SLE. Compared with MI RNA, LNC RNA has many kinds and huge quantity. It can regulate gene expression from many aspects, such as epigenetic level, transcriptional level, post transcriptional level and protein metabolism. Lnc RNA also plays a very important role in the development and development of various human diseases. Recent studies have shown that in patients with SLE in peripheral blood mononuclear cells, linc0949 (ENST00000500949) and NEAT1 (nuclear enriched abundant transcript 1) the expression level was abnormal, and the disease activity and renal involvement, through the NEAT1 mitogen activated protein kinase (mitogen-activated protein, kinase, MAPK) pathway, promote the expression of chemotaxis cytokines and inflammatory factors, and pathogenesis in SLE. Because of the complex and varied clinical manifestations of SLE, the early diagnosis is difficult. Therefore, it is urgent to find a new, specific and sensitive biomarker for the diagnosis and prognosis of SLE. Studies have confirmed that LNC RNA is stable in plasma. It can be used as an early biomarker and therapeutic target for cancer and cardiovascular disease, and can be used for early screening, diagnosis and prognosis evaluation of diseases. However, the study of LNC RNA in SLE patients is still limited, and the study of plasma LNC RNA as a marker of susceptibility to SLE disease has not yet been reported. Objective to screen the abnormal expression of SLE in plasma of patients with LNC in RNAs, and independent verification, to evaluate the difference of plasma LNC RNAs SLE as the auxiliary diagnostic value of biomarkers; using bioinformatics analysis, function prediction of the difference of LNC RNAs, discuss its role in the pathogenesis of SLE. Methods this study is divided into two parts: the first part: screening and verification of SLE in plasma of patients with RNAs and LNC as the difference between the value of biomarkers used in this part is the four stage case-control design: the first stage: the collection of new SLE, new non nephritis patients with lupus nephritis (lupus nephritis, LN) and patients the normal control of plasma in all 12 cases, 4 cases of each group of plasma total mixture of RNA, namely the formation of each of the 3 samples of plasma total RNA pool. The expression of LNC RNA in plasma was detected by LNC RNA chip, and the differential LNC RNAs was screened. The second stage: the small sample preliminary verification, in a single plasma sample, using quantitative reverse transcriptase polymerase chain reaction (quantitative reverse transcription polymerase chain reaction Q RT-PCR) technology, the chip selected from 10 candidate LNC RNAs and differences according to the literature selected 5 candidate LNC RNAs (ENST00000500597:linc0597; ENST00000449289:GAS5 or ENST00000500949:linc0949; lnc9289; ENST00000587298:lnc-DC; ENST00000495032:HOTAIRM1) verified the expression level. The third stage: large sample independent validation, and another 240 cases of SLE patients and 120 cases of normal control plasma samples were randomly divided into training group (160 cases of SLE, 80 cases of normal control) and test group (80 cases of SLE patients, 40 cases of normal control). First of all, in the training group, using Q RT-PCR to detect small samples obtained in the preliminary verification of the difference of LNC RNAs; then, in the test group, the application of Q RT-PCR technology to further verify the differences of verification from the training group in LNC RNAs; finally, in 240 cases of SLE patients, to explore the relevance of the final test the difference between LNC RNAs and the main clinical indicators. In addition, in order to evaluate the difference of plasma LNC RNAs SLE as a single or a combination of the value of biomarkers, we first used the receiver operating characteristic (receiver operating, characteristic, ROC) diagnostic value of individual differences in LNC RNAs curve analysis, and then based on the training set, using logistic regression analysis to construct the predictive risk of SLE LNC RNAs combined with discriminant model and, in the training and test group, ROC curve analysis was used to investigate the diagnostic value of combined. Finally, we in the 240 SLE patients, with nephritis SLE patients were divided into LN group and SLE without nephritis group, logistic regression analysis was applied to construct the prediction of LN risk LNC RNAs combined with discriminant model, ROC curve analysis was used to investigate the difference of plasma LNC RNAs single or a combination of LN and SLE for the identification of non nephritis biomarker the value of. The fourth stage: the application of Q RT-PCR technique to detect differences of LNC RNAs in disease control group (rheumatoid arthritis (rheumatoid arthritis, RA) in 30 patients with primary Sjogren syndrome (primary Sjogren's syndrome, P SS) in 31 patients) expression in plasma, the difference of LNC RNAs SLE as evaluation of biomarkers specific, and give analysis to validate the diagnostic value of combined discriminant model by ROC curve. The second part: the expression of M SLE in plasma of patients with RNA between the study of LNC RNA chip to establish biological information related to SLE RNAs and M LNC RNAs, Gene Ontology (gene ontology GO) and KEGG (Kyoto Encyclopedia of genes biological pathway and genomes pathway) analysis; at the same time with Q RT-PCR to verify the results, establish difference LNC RNA-m RNA co expression network analysis; the competition of endogenous RNA (competitive endogenous RNA, CE RNA) m RNA-mi RNA-lnc RNA analysis, construction of regulatory network, can be used as a LNC RNA CE search RNA. Results the first part: the screening, validation and as a biomarker of the plasma difference of LNC RNAs in SLE patients
【学位授予单位】：安徽医科大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：R593.241
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