本文關(guān)鍵詞：血漿長鏈非編碼RNAs作為系統(tǒng)性紅斑狼瘡生物標(biāo)志物的分子流行病學(xué)研究　出處：《安徽醫(yī)科大學(xué)》2017年博士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 長鏈非編碼RNA 系統(tǒng)性紅斑狼瘡 狼瘡腎炎 血漿 生物標(biāo)志物

【摘要】：背景系統(tǒng)性紅斑狼瘡(systemic lupus erythematosus,SLE)具有復(fù)雜的遺傳背景,涉及編碼基因和非編碼基因,過去普遍認(rèn)為編碼基因在疾病的發(fā)生發(fā)展中起重要作用,但很少關(guān)注基因組中的非編碼RNA(non-coding RNA,nc RNA)。按長度大小,具有調(diào)控作用的nc RNA主要分為兩類:≤200 nt的短鏈非編碼RNA(主要為微小RNA(micro RNA,簡稱mi RNA))和200 nt的長鏈非編碼RNA(long non-coding RNA,lnc RNA)。大量研究表明mi RNA在SLE的發(fā)病過程中發(fā)揮著關(guān)鍵作用,可作為一種新型生物標(biāo)志物用于SLE的診斷和預(yù)后評估。與mi RNA相比,lnc RNA的種類繁多且數(shù)量龐大,能夠從表觀遺傳水平、轉(zhuǎn)錄水平、轉(zhuǎn)錄后水平和蛋白質(zhì)代謝等多個(gè)層面調(diào)控基因表達(dá)。Lnc RNA在人類多種疾病的發(fā)生發(fā)展過程中也起著非常重要的調(diào)控作用。新近研究表明,在SLE患者外周血單核細(xì)胞中,linc0949(ENST00000500949)和NEAT1(nuclear enriched abundant transcript 1)的表達(dá)水平明顯異常,且與疾病活動度和腎臟受累有關(guān),NEAT1通過絲裂原活化蛋白激酶(mitogen-activated protein kinase,MAPK)通路,促進(jìn)相關(guān)趨化因子和炎癥因子的表達(dá),進(jìn)而參與SLE的發(fā)病過程。由于SLE臨床表現(xiàn)復(fù)雜多樣,病情反復(fù)多變,早期診斷困難,因此迫切需要尋求一種新型、特異性及敏感性較高的生物標(biāo)志物用于SLE的診斷和預(yù)后評估。研究證實(shí)lnc RNA在血漿中穩(wěn)定存在,可作為腫瘤和心血管疾病的早期生物標(biāo)志物和治療靶點(diǎn),用于疾病的早期篩查、診斷和預(yù)后評估。然而目前,關(guān)于lnc RNA在SLE患者中的研究還很有限,且探討血漿lnc RNA作為SLE疾病易感性標(biāo)志物的研究尚未見報(bào)道。目的篩選在SLE患者血漿中異常表達(dá)的lnc RNAs,并進(jìn)行獨(dú)立驗(yàn)證,評估差異血漿lnc RNAs作為SLE輔助診斷的生物標(biāo)志物的價(jià)值;利用生物信息學(xué)分析,對差異lnc RNAs進(jìn)行功能預(yù)測,探討其在SLE發(fā)病中的作用機(jī)制。方法本研究共分為兩部分:第一部分:SLE患者血漿差異lnc RNAs的篩選、驗(yàn)證及作為生物標(biāo)志物的價(jià)值本部分采用的是四階段病例-對照設(shè)計(jì):第一階段:收集新發(fā)SLE非腎炎患者、新發(fā)狼瘡腎炎(lupus nephritis,LN)患者和正常對照血漿各12例,各組每4例血漿總RNA等量混合,即形成每組各3份血漿總RNA池。利用lnc RNA芯片檢測血漿lnc RNA表達(dá)譜,篩選差異lnc RNAs。第二階段:小樣本初步驗(yàn)證,在原單個(gè)血漿標(biāo)本中,采用定量逆轉(zhuǎn)錄聚合酶鏈反應(yīng)(quantitative reverse transcription polymerase chain reaction,q RT-PCR)技術(shù),對從芯片中篩選出的10個(gè)候選差異lnc RNAs和根據(jù)文獻(xiàn)挑選的5個(gè)候選lnc RNAs(ENST00000500597:linc0597;ENST00000500949:linc0949;ENST00000449289:GAS5或lnc9289;ENST00000587298:lnc-DC;ENST00000495032:HOTAIRM1)的表達(dá)水平進(jìn)行初步驗(yàn)證。第三階段:大樣本獨(dú)立驗(yàn)證,另收集240例SLE患者和120例正常對照的血漿標(biāo)本,隨機(jī)分為訓(xùn)練組(SLE患者160例,正常對照80例)和測試組(SLE患者80例,正常對照40例)。首先,在訓(xùn)練組中,采用q RT-PCR技術(shù)檢測從小樣本初步驗(yàn)證中得到的差異lnc RNAs;然后,在測試組中,應(yīng)用q RT-PCR技術(shù)對從訓(xùn)練組中驗(yàn)證出的差異lnc RNAs給予進(jìn)一步驗(yàn)證;最后,在240例SLE患者中,探討最終驗(yàn)證出的差異lnc RNAs與主要臨床指標(biāo)的關(guān)聯(lián)性。此外,為了評價(jià)血漿差異lnc RNAs單個(gè)或組合作為SLE生物標(biāo)志物的價(jià)值,我們首先采用受試者工作特征(receiver operating characteristic,ROC)曲線分析各單個(gè)差異lnc RNAs的診斷價(jià)值,然后基于訓(xùn)練組,應(yīng)用logistic回歸分析構(gòu)建預(yù)測SLE風(fēng)險(xiǎn)的lnc RNAs聯(lián)合判別模型,并在訓(xùn)練組和測試組中,采用ROC曲線分析探討其聯(lián)合診斷價(jià)值。最后,我們在240例SLE患者中,按照有無腎炎將SLE患者分為LN組和SLE非腎炎組,應(yīng)用logistic回歸分析構(gòu)建預(yù)測LN風(fēng)險(xiǎn)的lnc RNAs聯(lián)合判別模型,采用ROC曲線分析探討血漿差異lnc RNAs單個(gè)或組合作為鑒別LN和SLE非腎炎生物標(biāo)志物的價(jià)值。第四階段:應(yīng)用q RT-PCR技術(shù)檢測差異lnc RNAs在疾病對照組(類風(fēng)濕關(guān)節(jié)炎(rheumatoid arthritis,RA)患者30例,原發(fā)性干燥綜合征(primary Sjogren's syndrome,p SS)患者31例)血漿中的表達(dá)情況,評估差異lnc RNAs作為SLE生物標(biāo)志物的特異性,并采用ROC曲線分析對聯(lián)合判別模型的診斷價(jià)值給予進(jìn)一步驗(yàn)證。第二部分:SLE相關(guān)m RNAs及l(fā)nc RNAs的生物信息學(xué)研究對lnc RNA芯片建立的SLE患者血漿m RNA差異表達(dá)譜,進(jìn)行基因本體論(gene ontology,GO)和KEGG生物學(xué)途徑(Kyoto encyclopedia of genes and genomes pathway)分析;同時(shí)結(jié)合q RT-PCR驗(yàn)證結(jié)果,建立差異lnc RNA-m RNA共表達(dá)網(wǎng)絡(luò)分析;采用競爭性內(nèi)源RNA(competitive endogenous RNA,ce RNA)分析,構(gòu)建m RNA-mi RNA-lnc RNA調(diào)控網(wǎng)絡(luò),探尋可作為ce RNA的lnc RNA。結(jié)果第一部分:SLE患者血漿差異lnc RNAs的篩選、驗(yàn)證及作為生物標(biāo)志物的價(jià)值本研究通過lnc RNA芯片建立了SLE非腎炎和LN的血漿lnc RNA和m RNA差異表達(dá)譜(差異倍數(shù)≥2倍,P≤0.05),從中篩選出10個(gè)候選血漿差異表達(dá)lnc RNAs,并結(jié)合文獻(xiàn)挑選的5個(gè)候選lnc RNAs進(jìn)行小樣本初步驗(yàn)證。小樣本初步驗(yàn)證發(fā)現(xiàn),與正常對照相比,在SLE患者血漿中15個(gè)候選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個(gè)lnc RNAs(GAS5,linc0597,lnc0640,lnc5150,lnc3643,lnc6655,lnc7074,lnc7514,lncagf.1)的表達(dá)水平存在顯著變化(均有P0.05)。大樣本獨(dú)立驗(yàn)證進(jìn)一步確定了在訓(xùn)練組和測試組的血漿樣本中,linc0597、GAS5、lnc0640、lnc5150和lnc7074的表達(dá)水平均顯著變化(均有P0.05)。且在訓(xùn)練組和測試組中,LN患者與SLE非腎炎患者比較,lnc7074、lnc3643、lnc0640、lnc7514和lnc6655的表達(dá)水平均顯著上調(diào)(均有P0.05)。關(guān)聯(lián)性研究結(jié)果顯示血漿linc0597和GAS5的表達(dá)水平與C3水平均呈顯著負(fù)相關(guān)(分別為P0.001和P=0.009);lnc5150的表達(dá)水平與血小板減少和C3水平顯著相關(guān)(分別為P=0.008和P=0.001);lnc0640的表達(dá)水平與低補(bǔ)體、血小板減少和C3水平顯著相關(guān)(分別為P=0.001、P=0.017和P0.001);lnc7074的表達(dá)水平與血小板減少和C3水平顯著相關(guān)(分別為P=0.028和P0.001)。在訓(xùn)練組中,血漿linc0597、GAS5、lnc0640、lnc5150和lnc7074作為SLE生物標(biāo)志物的ROC曲線下面積(area under the curve,AUC)分別為0.634、0.824、0.598、0.625和0.602,5個(gè)lnc RNAs組合預(yù)測SLE風(fēng)險(xiǎn)的判別公式為logit(P=SLE)=-2.594+7.503×linc0597-14.253×GAS5+2.853×lnc5150-7.012×lnc7074+6.233×lnc0640,AUC為0.966。在測試組中,血漿linc0597、GAS5、lnc0640、lnc5150和lnc7074作為SLE生物標(biāo)志物的AUC分別為0.649、0.851、0.615、0.683和0.662,聯(lián)合判別模型的AUC為0.968。與測試組SLE患者相比,在RA患者的血漿中,GAS5和linc0597的表達(dá)水平均顯著上調(diào)(均有P0.05);在p SS患者的血漿中,GAS5和lnc7074的表達(dá)水平均顯著上調(diào)(均有P0.05)。在測試組SLE患者和RA患者中,聯(lián)合判別模型的AUC為0.683;在測試組SLE患者和p SS患者中,聯(lián)合判別模型的AUC為0.910;在測試組SLE患者和RA患者+p SS患者中,聯(lián)合判別模型的AUC為0.798。在240例SLE患者中,腎炎組和非腎炎組相比,血漿lnc0640、lnc3643、lnc5150、lnc6655、lnc7074和lnc7514的表達(dá)水平均顯著上調(diào)(均有P0.05)。lnc0640、lnc3643、lnc5150、lnc6655、lnc7074和lnc7514用于鑒別LN和SLE非腎炎的AUC分別為0.644、0.671、0.601、0.631、0.665和0.684;lnc3643、lnc5150和lnc7514可聯(lián)合作為鑒別LN和SLE非腎炎的生物標(biāo)志物,3個(gè)lnc RNAs預(yù)測LN風(fēng)險(xiǎn)的聯(lián)合判別公式為logit(P=LN)=-0.139+1.387×lnc3643-2.048×lnc5150+1.647×lnc7514,AUC為0.716。第二部分:SLE相關(guān)m RNAs及l(fā)nc RNAs的生物信息學(xué)研究GO分析結(jié)果顯示,在SLE患者下調(diào)的血漿m RNAs中,“ion homeostasis”、“cation transmembrane transporter activity”和“plasma membrane part”分別在生物過程(biological process,BP)、分子功能(molecular function,MF)和細(xì)胞組分(cellular component,CC)中富集程度最高;在SLE患者上調(diào)的血漿m RNAs中,“cell-cell signaling”、“anion:cation symporter activity”和“cell periphery”分別在BP、MF和CC中富集程度最高。KEGG Pathway分析結(jié)果顯示,在SLE患者下調(diào)的血漿m RNAs中,“axon guidance-Homo sapiens(human)”通路富集程度最高;在SLE患者上調(diào)的血漿m RNAs中,“MAPK signaling pathway-Homo sapiens(human)”通路富集程度最高。Lnc RNA-m RNA共表達(dá)網(wǎng)絡(luò)分析結(jié)果顯示,GAS5、lnc0640、lnc5150、lnc7074、lnc3643、lnc6655和lnc7514分別與174、18、48、30、36、28和20個(gè)m RNAs有較一致的表達(dá)模式(Pearson相關(guān)系數(shù)≥0.935)。其中,DUSP4(dual specificity phosphatase 4)、ARRB2(arrestin beta 2)和RPS6KA5(ribosomal protein S6 kinase A5)可能分別是GAS5、lnc0640和lnc5150正向調(diào)控的靶基因,GAS5、lnc0640和lnc5150可能均通過MAPK通路參與SLE的發(fā)病過程;C4orf26(chromosome 4open reading frame 26)可能為lnc0640、lnc5150、lnc6655和lnc7074共同作用的靶基因;PARP16(poly(ADP-ribose)polymerase family member 16)可能為lnc3643、lnc5150、lnc6655和lnc7074共同作用的靶基因。Ce RNA分析結(jié)果顯示,GAS5、lnc0640、lnc3643、lnc6655和lnc7074可作為ce RNA與預(yù)測靶基因競爭靶向mi RNAs,進(jìn)而影響靶向mi RNAs對其預(yù)測靶基因的調(diào)控。結(jié)論1.與正常對照相比,SLE患者血漿中GAS5和lnc7074表達(dá)水平顯著下調(diào),linc0597、lnc0640和lnc5150表達(dá)水平顯著上調(diào);SLE患者血漿中l(wèi)inc0597和GAS5的表達(dá)水平顯著低于RA患者,GAS5和lnc7074的表達(dá)水平顯著低于p SS患者;2.血漿linc0597、GAS5、lnc0640、lnc5150和lnc7074聯(lián)合有望作為SLE潛在的生物標(biāo)志物;lnc3643、lnc5150和lnc7514聯(lián)合有望作為鑒別LN和SLE非腎炎潛在的生物標(biāo)志物;3.GAS5、lnc0640和lnc5150可能通過MAPK通路參與SLE的發(fā)病過程;4.GAS5、lnc0640、lnc3643、lnc6655和lnc7074可能作為ce RNA,影響靶向mi RNAs對其預(yù)測靶基因的調(diào)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
【學(xué)位授予單位】：安徽醫(yī)科大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：R593.241
，

本文編號：1347835