TWI755750B - A method for diagnosis and subtyping of adult-onset still's disease - Google Patents

A method for diagnosis and subtyping of adult-onset still's disease Download PDF

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TWI755750B
TWI755750B TW109119409A TW109119409A TWI755750B TW I755750 B TWI755750 B TW I755750B TW 109119409 A TW109119409 A TW 109119409A TW 109119409 A TW109119409 A TW 109119409A TW I755750 B TWI755750 B TW I755750B
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陳得源
楊晶安
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Abstract

The invention relates to a method for diagnosis of a subject suffering from adult-onset Still's disease and further to determine the disease course of the subject suffering from adult-onset Still's disease.

Description

診斷及分型成人發作型史迪兒症之方法 Methods for the diagnosis and classification of adult-onset Still's disease

本發明涉及一種診斷和分型成人發作型史迪兒症的對象的方法。 The present invention relates to a method of diagnosing and classifying subjects with adult-onset Still's disease.

成人發作型史迪兒症(adult-Onset Still’ sDisease，AOSD)是一種自發性炎性疾病，其特徵在於發燒、皮疹、關節痛或關節炎，多系統受累以及急性期反應物水平升高。由於持續的尖峰發燒，通常會延遲診斷。大多數患者僅在出現繼發症狀且排除更常見的情況(如感染或其他惡性疾病)後才被診斷。儘管存在這些困難，但Yamaguchi標准(Yamaguchi criteria)在當前的臨床診斷中為AOSD診斷提供了最高的靈敏度和準確性。 Adult-Onset Still's Disease (AOSD) is an idiopathic inflammatory disorder characterized by fever, rash, arthralgia or arthritis, multisystem involvement, and elevated levels of acute-phase reactants. Diagnosis is often delayed due to persistent spiking fever. Most patients are diagnosed only after developing secondary symptoms and ruling out more common conditions such as infection or other malignant disease. Despite these difficulties, the Yamaguchi criteria provide the highest sensitivity and accuracy for AOSD diagnosis among current clinical diagnoses.

其特徵還在於與17型T輔助(Th17)相關的細胞因子和促炎細胞因子，例如腫瘤壞死因子(TNF)-α、白介素(IL)-1β、IL-6、IL-8和IL-18；然而，確切的發病機理仍然難以捉摸。最近報導指出病毒感染與AOSD的關聯性。先前的研究還顯示，AOSD患者中NLRP3炎性小體的表達升高。另外，在AOSD患者中觀察到循環微小RNA-134的增加，可能由toll樣受體(toll liker receptor，TLR)-3配體(poly I：C)調節，其表現量與疾病活動呈正相關。儘管有這樣的證據，仍然缺乏診斷標記，並且AOSD的診斷通常是根據臨床標准進行的。 It is also characterized by cytokines associated with T helper type 17 (Th17) and pro-inflammatory cytokines, such as tumor necrosis factor (TNF)-alpha, interleukin (IL)-1beta, IL-6, IL-8, and IL-18 ; however, the exact pathogenesis remains elusive. Recent reports point to the association of viral infection with AOSD. Previous studies have also shown that the expression of the NLRP3 inflammasome is elevated in AOSD patients. In addition, an increase in circulating microRNA-134 was observed in AOSD patients, possibly regulated by toll-like receptor (TLR)-3 ligand (poly I:C), and its expression was positively correlated with disease activity. Despite this evidence, diagnostic markers are still lacking, and the diagnosis of AOSD is usually based on clinical criteria.

AOSD的病程可能有很大不同，可以分為兩種主要的亞型，其預 後不同：全身性亞型(systemic subtype)和關節性亞型(articular subtype)。儘管促炎細胞因子促成AOSD發病機理，但由於亞型之間的廣泛重疊，它們在預測疾病進程中的用途有限。包括我們在內的數名研究人員揭示了關節性亞型AOSD患者的TNF-α水平顯著升高，針對該患者的生物製劑已證明TNF-α可有效治療AOSD病人。 The course of AOSD can vary widely and can be divided into two main subtypes, After the difference: systemic subtype (systemic subtype) and articular subtype (articular subtype). Although proinflammatory cytokines contribute to AOSD pathogenesis, their use in predicting disease progression is limited due to the extensive overlap between subtypes. Several investigators, including us, have revealed significantly elevated levels of TNF-α in patients with the articular subtype of AOSD, and biologics targeting this patient have demonstrated that TNF-α is effective in the treatment of AOSD patients.

從輕度到重度的表現，AOSD的病程難以評估。因此，準確評估病程對於治療決策很重要。實驗室中使用了一些急性期反應物，包括C反應蛋白和鐵蛋白，以監測AOSD疾病的活動。然而，這些標記物是非特異性的並且與疾病進程沒有很好的相關性。Pouchot評分(Pouchot score)可用於評估疾病進程，包括肝酶升高、心包炎、肌痛、中性粒細胞減少和淋巴結病。 From mild to severe manifestations, the course of AOSD is difficult to assess. Therefore, accurate assessment of disease course is important for treatment decisions. Several acute phase reactants, including C-reactive protein and ferritin, are used in the laboratory to monitor AOSD disease activity. However, these markers are nonspecific and do not correlate well with disease progression. The Pouchot score can be used to assess disease progression, including elevated liver enzymes, pericarditis, myalgia, neutropenia, and lymphadenopathy.

對於AOSD的治療，AOSD的一線治療是非類固醇消炎藥(non-steroidal anti-inflammatory drugs，NSAID)和糖皮質激素(glucocorticoids)。在缺乏對一線治療的臨床反應後，進行二線治療，包括合成疾病調節抗風濕藥物(Disease modifying anti-rheumatic drugs，DMARDS)和生物製劑。使用DMARDS，如：甲氨蝶呤(methotrexate)、硫唑嘌呤(azathioprine)和來氟米特(leflunomide)通常用於減少所用皮質類固醇的量。生物製劑，包括靜脈內免疫球蛋白、抗TNF-α藥物，如：etanercept、infliximab和adalimumab以及抗IL-6藥物，如：tocilizumab，似乎也能充分控制常規無反應者的疾病治療。 For the treatment of AOSD, the first-line treatments for AOSD are non-steroidal anti-inflammatory drugs (NSAIDs) and glucocorticoids. After a lack of clinical response to first-line therapy, second-line therapy, including synthetic disease-modifying anti-rheumatic drugs (DMARDS) and biologics. The use of DMARDS such as methotrexate, azathioprine and leflunomide is commonly used to reduce the amount of corticosteroids used. Biologics, including intravenous immunoglobulins, anti-TNF- α drugs such as etanercept, infliximab, and adalimumab, and anti-IL-6 drugs such as tocilizumab, also appear to adequately control disease in those who do not respond to conventional therapy.

長的非編碼RNA(Long non-coding RNAs，lncRNA)，長度大於200個核苷酸的非蛋白質編碼轉錄物，已經在基因調控的不同階段出現了新 的作用。LncRNA可透過RNA-DNA、RNA-RNA或RNA-蛋白質相互作用參與染色質重塑、轉錄過程和細胞反應。最近的研究還顯示出lncRNAs在免疫細胞中可以被誘導表現並作為炎症反應的關鍵調節因子。另外，lncRNA已經涉及針對病毒感染的先天免疫。儘管發現了越來越多的lncRNA，但是其生物學功能和作用機制在很大程度上尚不清楚。 Long non-coding RNAs (lncRNAs), non-protein-coding transcripts longer than 200 nucleotides, have emerged in different stages of gene regulation. effect. LncRNAs can participate in chromatin remodeling, transcriptional processes and cellular responses through RNA-DNA, RNA-RNA or RNA-protein interactions. Recent studies have also shown that lncRNAs can be induced to express and act as key regulators of inflammatory responses in immune cells. Additionally, lncRNAs have been implicated in innate immunity against viral infection. Although more and more lncRNAs have been discovered, their biological functions and mechanisms of action are largely unknown.

本發明對與免疫調節或炎性反應有關並且可能與AOSD或病毒感染的發病有關的六個lncRNA特別感興趣。這六個lncRNA分別是MIAT(10.18kb,NONHSAT192181.1)、THRIL(1.98kb,NONHSAT164169.1)、NTT(17.57kb,NONHSAT115106.2)、RMR(0.27kb,NONHSAT130962.2)、PACERR(0.83kb,NONHSAT150184.1和NEAT1(22.74kb,NONHSAT022112.2)。MIAT(myocardial infarction associated transcript)已知與多種疾病的發病機制有關，包括：心肌梗塞、微血管功能障礙和肌痛性腦脊髓炎/慢性疲勞綜合徵(myalgic encephalomyelitis/chronic fatigue syndrome，ME/CFS)。THRIL(TNFα and hnRNPL-related immunoregulatory lincRNA)通過與異質核糖核蛋白L(heterogeneous nuclear ribonucleoprotein L，hnRNPL)相互作用而充當支架並且該複合物與TNF-α啟動子結合，從而在TLR2激活後誘導其轉錄。NTT(non-coding transcript in T cells)是在被人免疫缺陷病毒(human immunodeficiency virus，HIV)胜肽刺激的活化CD4+ T細胞中發現的，顯示出其在適應性免疫中的作用。先前的研究表明NTT是單核細胞炎症的調節劑，其活化參與單核細胞/巨噬細胞的分化，並有助於類風濕關節炎(rheumatoid arthritis，RA)的發病機理。RMRP(RNA component of the mitochondrial RNA-processing endoribonuclease)促進 RORγtDDX5裝配，並被募集到RORγt佔據的Th17效應子程序中特別涉及的關鍵基因組。PACERR(p50-associated COX-2 extragenic RNA，也稱為PACER)是TLR4激活後人上皮細胞和巨噬細胞樣細胞中COX-2表達的正向調節劑。NEAT1(nuclear enriched abundant transcript 1)對於形成核體旁斑(nuclear body paraspeckles)至關重要，有助於IL-8轉錄激活。在刺激TLR3配體poly(I：C)(代表活性病毒感染的雙鏈RNA的合成類似物)刺激後，NEAT1表達也增加。但是，尚無關於AOSD患者中循環lncRNA表達的研究數據。 The present invention is of particular interest to six lncRNAs that are involved in immune regulation or inflammatory responses and may be involved in the pathogenesis of AOSD or viral infection. The six lncRNAs are MIAT (10.18kb, NONHSAT192181.1), THRIL (1.98kb, NONHSAT164169.1), NTT (17.57kb, NONHSAT115106.2), RMR (0.27kb, NONHSAT130962.2), PACERR (0.83kb) , NONHSAT150184.1 and NEAT1 (22.74kb, NONHSAT022112.2). MIAT (myocardial infarction associated transcript) is known to be involved in the pathogenesis of various diseases, including: myocardial infarction, microvascular dysfunction and myalgic encephalomyelitis/chronic fatigue Syndrome (myalgic encephalomyelitis/chronic fatigue syndrome, ME/CFS). THRIL (TNFα and hnRNPL-related immunoregulatory lincRNA) acts as a scaffold by interacting with heterogeneous nuclear ribonucleoprotein L (hnRNPL) and this complex interacts with TNF-α promoter binds to induce its transcription upon activation of TLR2. NTT (non-coding transcript in T cells) is in activated CD4 + T cells stimulated by human immunodeficiency virus (HIV) peptides found, showing its role in adaptive immunity. Previous studies have shown that NTT is a regulator of monocyte inflammation, and its activation is involved in monocyte/macrophage differentiation and contributes to rheumatoid arthritis ( Pathogenesis of rheumatoid arthritis, RA). RMRP (RNA component of the mitochondrial RNA-processing endoribonuclease) promotes RORγt DDX5 assembly and is recruited to key genomes specifically involved in the RORγt-occupied Th17 effector program. PACERR (p50-associated COX- 2 extragenic RNA, also known as PACER) is a positive regulator of COX-2 expression in human epithelial cells and macrophage-like cells after TLR4 activation. NEAT1 (nuclear enriched abundant transcript 1) is essential for the formation of nuclear body paraspeckles) are crucial and contribute to IL -8 Transcriptional activation. NEAT1 expression was also increased upon stimulation with the TLR3 ligand poly(I:C), a synthetic analog representing double-stranded RNA for active viral infection. However, there are no research data on circulating lncRNA expression in AOSD patients.

在本發明中，研究了在AOSD患者中的六個lncRNA的表達特徵和潛在的診斷價值。類風濕關節炎(rheumatoid arthritis，RA)和系統性紅斑狼瘡(systemic lupus erythematosus，SLE)的患者也入選本研究。進一步亦在人單核細胞系THP-1中評估了TLR3配體poly(I：C)和TLR4配體LPS對lncRNA表達的影響。另外，建立了從lncRNA和促炎細胞因子的表現量得出的預測分數，用於AOSD診斷和疾病進程預測。 In the present invention, the expression profile and potential diagnostic value of six lncRNAs in AOSD patients were investigated. Patients with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) were also included in this study. The effect of TLR3 ligand poly(I:C) and TLR4 ligand LPS on lncRNA expression was further evaluated in the human monocyte cell line THP-1. Additionally, prediction scores derived from the expression of lncRNAs and proinflammatory cytokines were established for AOSD diagnosis and disease progression prediction.

本發明涉及一種檢測個體罹患成人發作型史笛兒氏症的方法，該方法包括以下步驟：(a)提供一血液樣本和一周邊血液單核細胞；檢測該血液樣本中一蛋白質生物標誌物之表現量，其中該蛋白質生物標幟物係為IL-18；(b)檢測該周邊血液單核細胞中一長鏈非編碼核糖核酸生物標誌物的表現量，其中該長鏈非編碼核糖核酸生物標誌物為MIAT或THRIL；(c)將步驟(b)所得偵測到的IL18、MIAT和THRIL的表現量以一預測函數計算出一A分數，其中該預測函數係由一多元迴歸分析(multiple regression analysis) 得到；以及(d)將步驟(c)所計算的該A分數與一臨界值比較，其中該臨界值係透過接收器操作員特徵(Receiver Operator Characteristic，ROC)方法獲得，其中該臨界值對應於ROC曲線下的面積(the area under an ROC curve，AUC)達到最大值，其中A分數高於該臨界值則代表該個體罹患成人發作型史笛兒氏症。 The present invention relates to a method for detecting that an individual suffers from adult-onset Strudel's disease, the method comprising the following steps: (a) providing a blood sample and a peripheral blood mononuclear cell; detecting a protein biomarker in the blood sample Expression level, wherein the protein biomarker is IL-18; (b) detecting the expression level of a long-chain non-coding RNA biomarker in the peripheral blood mononuclear cells, wherein the long-chain non-coding RNA biomarker The marker is MIAT or THRIL; (c) the expression levels of IL18, MIAT and THRIL detected in step (b) are used to calculate an A-score with a predictive function, wherein the predictive function is determined by a multiple regression analysis ( multiple regression analysis) and (d) comparing the A-score calculated in step (c) with a threshold, wherein the threshold is obtained by a Receiver Operator Characteristic (ROC) method, wherein the threshold corresponds to The area under an ROC curve (AUC) reaches the maximum value, where the A-score is higher than the critical value, indicating that the individual suffers from adult-onset Stubbs disease.

在一方面，本發明涉及一種檢測一罹患成人發作型史笛兒氏症的個體的疾病病程的方法，該方法包括以下步驟：(a)提供一血液樣本和一周邊血液單核細胞，其中該血液樣本和該周邊血液單核細胞係由一罹患成人發作型史笛兒氏症的個體中收集而來；(b)檢測該血液樣本中一蛋白質生物標誌物之表現量，其中該蛋白質生物標幟物係為TNF-α；檢測該周邊血液單核細胞中一長鏈非編碼核糖核酸生物標誌物的表現量，其中該長鏈非編碼核糖核酸生物標誌物為NTT；(c)將步驟(b)所得偵測到的TNFα和NTT的表現量以一預測函數計算出一B分數，其中該預測函數係由一多元迴歸分析(multiple regression analysis)得到；以及(d)將步驟(c)所計算的該B分數與一臨界值比較，其中該臨界值係透過接收器操作員特徵(Receiver Operator Characteristic，ROC)方法獲得，其中該臨界值對應於ROC曲線下的面積(the area under an ROC curve，AUC)達到最大值，其中B分數高於該臨界值則代表該罹患成人發作型史笛兒氏症的個體疾病病程為一全身性亞型或是一關節性亞型。 In one aspect, the invention relates to a method of detecting the disease course of an individual suffering from adult-onset Stubbs' disease, the method comprising the steps of: (a) providing a blood sample and a peripheral blood mononuclear cell, wherein the The blood sample and the peripheral blood mononuclear cell line are collected from an individual suffering from adult-onset Stubbs' disease; (b) detecting the expression of a protein biomarker in the blood sample, wherein the protein biomarker The marker is TNF-α; the expression level of a long-chain non-coding ribonucleic acid biomarker in the peripheral blood mononuclear cells is detected, wherein the long-chain non-coding ribonucleic acid biomarker is NTT; (c) adding step ( b) the resulting detected expression of TNFα and NTT calculates a B-score with a predictive function, wherein the predictive function is obtained by a multiple regression analysis; and (d) applying step (c) The calculated B-score is compared to a threshold obtained by a receiver operator characteristic (ROC) method, wherein the threshold corresponds to the area under an ROC curve curve, AUC) reaches the maximum value, wherein the B-score higher than the cut-off value indicates that the disease course of the individual suffering from adult-onset Stubbs is a systemic subtype or an articular subtype.

在另一方面，本發明涉及一種用於診斷患有成人發作型史笛兒氏症的個體的試劑盒，其中所述試劑盒包含選自以下的試劑：(a)用於檢測IL-18蛋白的試劑；(b)用於檢測MIAT和THRIL的lncRNA的試劑；以及(c) 說明手冊，提供預測方程式和臨界值，用於確定受試者是否患有成人發作型史笛兒氏症。 In another aspect, the present invention relates to a kit for diagnosing an individual with adult-onset Stubbs' disease, wherein the kit comprises a reagent selected from the group consisting of: (a) for detecting IL-18 protein Reagents for ; (b) Reagents for lncRNA Detection of MIAT and THRIL; and (c) Instruction manual providing prediction equations and cutoff values for determining whether a subject has adult-onset Stubbs disease.

在另一方面，本發明涉及一種用於診斷患有成人發作型史笛兒氏症的個體病程的試劑盒，其中所述試劑盒包含選自以下的試劑：(a)試劑用於檢測TNF-α蛋白；(b)用於檢測NTT的lncRNA的試劑；以及(c)說明手冊，提供預測方程式和臨界值，用於確定患有成人發作型史笛兒氏症的個體是全身性亞型還是關節性亞型。 In another aspect, the present invention relates to a kit for diagnosing the course of an individual with adult-onset Stubbs disease, wherein the kit comprises reagents selected from the group consisting of: (a) reagents for the detection of TNF- alpha protein; (b) reagents for the detection of lncRNAs for NTT; and (c) an instruction manual providing prediction equations and cutoff values for determining whether individuals with adult-onset Stubbs are the systemic subtype or the Arthritis subtype.

圖1. 在AOSD患者和健康對照者中lncRNA和細胞因子的表達譜。a-f.從健康對照(Control)、AOSD全身性亞型患者(AOSD-systemic)和AOSD關節性亞型患者(AOSD-arthritis)，a：MIAT，b：THRIL，c：NTT，d：NEAT1，e：RMRP，f：PACERR。g-k.在健康對照者、AOSD全身性亞型患者和AOSD關節性亞型患者中檢測到血漿細胞因子的表現量。g：IL-1α，h：IL-6，iIL-17A，j：IL-18，k：TNF-α。線代表中位數。*：p<0.05,**：p<0.01,***：p<0.001 calculated by Kruskal-Wallis tests.*：p<0.05，**：p<0.01，***：p<0.001，通過kruskal-Wallis檢驗計算。 Figure 1. Expression profiles of lncRNAs and cytokines in AOSD patients and healthy controls. af. From healthy controls (Control), patients with systemic subtype of AOSD (AOSD-systemic) and patients with articular subtype of AOSD (AOSD-arthritis), a: MIAT, b: THRIL, c: NTT, d: NEAT1, e : RMRP, f: PACERR. g-k. Plasma cytokine expression was detected in healthy controls, patients with the systemic subtype of AOSD, and patients with the articular subtype of AOSD. g: IL-1α, h: IL-6, iIL-17A, j: IL-18, k: TNF-α. Lines represent medians. *: p<0.05, **: p<0.01, ***: p<0.001 calculated by Kruskal-Wallis tests.*: p<0.05, **: p<0.01, ***: p<0.001, by kruskal -Wallis test calculation.

圖2. 通過MIAT、THRIL和IL-18的表達特徵將AOSD患者與健康對照者區分開。a. 3D散點圖，顯示每個樣品的MIAT、THRIL和IL-18表現量。圓圈：健康對照；三角形：AOSD患者(包含兩種亞型)。b.從MIAT、THRIL和IL-18的表現量可得出AOSD預測得分(A分數)的受試者工作特徵曲線(receiver operating characteristic curve,ROC curve)。在預測AOSD診斷時，臨界值>7.114時曲線下面積(AUC)=0.998，靈敏度=94.87%，特異 性=100%。 Figure 2. AOSD patients are differentiated from healthy controls by expression profiles of MIAT, THRIL and IL-18. a. 3D scatter plot showing the expression of MIAT, THRIL and IL-18 for each sample. Circles: healthy controls; triangles: AOSD patients (including both subtypes). b. The receiver operating characteristic curve (ROC curve) of the AOSD prediction score (A score) can be obtained from the expression levels of MIAT, THRIL and IL-18. In predicting the diagnosis of AOSD, the area under the curve (AUC) = 0.998, the sensitivity = 94.87%, the specificity when the cut-off value > 7.114 Sex = 100%.

圖3. 透過NTT和TNF-α的表現特徵來區分AOSD亞型的疾病結果。a. 3D散點圖，顯示每個樣品的NTT、TNF-α和IL-18表現量。圓圈：AOSD-關節性亞型；三角形：AOSD全身性亞型。b.從NTT和TNF-α表現量得出AOSD亞型預測分數(B分數)的ROC曲線分析。在預測AOSD患者中的AOSD全身性亞型時，AUC=0.855(臨界值>0.266，靈敏度=66.7%，特異性=90.9%)。 Figure 3. Disease outcomes for AOSD subtypes differentiated by NTT and TNF-α expression characteristics. a. 3D scatter plot showing the expression of NTT, TNF-α and IL-18 for each sample. Circles: AOSD-articular subtype; triangles: AOSD systemic subtype. b. ROC curve analysis of AOSD subtype prediction scores (B scores) derived from NTT and TNF -α expression levels. In predicting the systemic subtype of AOSD in AOSD patients, AUC=0.855 (cutoff >0.266, sensitivity=66.7%, specificity=90.9%).

圖4. lncRNA表現量與細胞因子或AOSD疾病活性的相關性。a.低RMRP和PACERR表現量與AOSD疾病活動的關係。將所有AOSD患者分為(RMRP dCT+PACERR dCT)>17或(RMRP dCT+PACERR dCT)<17，並通過Mann-Whitney U檢驗比較兩組患者的疾病活動水平。b. IL-18表現量與AOSD疾病活動性的相關性(AOSD，n=38)。通過線性回歸分析，r2=0.38，p<0.0001。c.配對圖顯示了每個AOSD患者樣品中所有lncRNA與細胞因子表現量之間的散點圖(由R軟件繪製)。*：p<0.05。條形表示平均值±SEM。 Figure 4. Correlation of lncRNA expression with cytokine or AOSD disease activity. a. Association of low RMRP and PACERR expression with AOSD disease activity. All AOSD patients were divided into (RMRP dCT+PACERR dCT)>17 or (RMRP dCT+PACERR dCT)<17, and the disease activity levels of the two groups were compared by Mann-Whitney U test. b. Correlation of IL-18 expression with AOSD disease activity (AOSD, n=38). By linear regression analysis, r 2 =0.38, p<0.0001. c. Paired plots show scatter plots (plotted by R software) between all lncRNAs and cytokine expression in each AOSD patient sample. *: p<0.05. Bars represent mean ± SEM.

圖5. 比較AOSD患者治療前後lncRNA表現模式。a-b.單獨接受prednisolone或cyclosporin(a)或IL-6受體抑製劑：tocilizumab(b)治療的AOSD患者中，NEAT1表現量的變化。Tx：治療。c.治療前後(所有治療)NEAT1和PIK3CA dCT表現量的相關性。d.配對圖顯示出治療前後每兩個lncRNA表達之間的相關性以及lncRNA與PIK3CA dCT表現量的相關性。皮爾遜相關係數(Pearson correlation coefficient)及其p值顯示在圖表的右下角。 Figure 5. Comparison of lncRNA expression patterns before and after treatment in AOSD patients. a-b. Changes in NEAT1 expression in AOSD patients treated with prednisolone or cyclosporin (a) or the IL-6 receptor inhibitor: tocilizumab (b) alone. Tx: Treatment. c. Correlation of NEAT1 and PIK3CA dCT expression levels before and after treatment (all treatments). d. Paired plots showing the correlation between the expression of each two lncRNAs before and after treatment and the correlation between the lncRNA and the amount of PIK3CA dCT expression. The Pearson correlation coefficient and its p-value are shown in the lower right corner of the graph.

圖6. 使用STRING的lncRNA相關分子的相互作用的網絡分析(蛋白-蛋白相互作用網絡功能性富集分析)。暗灰色原點代表炎症反應豐富的途徑的分子(GO：0006954)。 Figure 6. Network analysis of interactions of lncRNA-associated molecules using STRING (protein-protein interaction network functional enrichment analysis). Dark grey origins represent molecules of inflammatory response-rich pathways (GO: 0006954).

圖7. 在人類單核細胞株THP-1中，在poly(I：C)或LPS刺激下的LncRNA表達模式。用50μg/ml poly(I：C)或100ng/ml LPS刺激THP-1細胞4小時或24小時。僅在無LPS RPMI培養基中培養指定時間的THP-1細胞用作各個實驗的對照。通過即時定量PCR測量lncRNA或PIK3CA的表現量。a.六個lncRNA的表現量。b. PIK3CA的表現量。4h poly(I：C)刺激：n=6-8；4h LPS刺激：n=3-5：24h poly(I：C)刺激：n=5-6；24h LPS刺激：n=3-5。條形表示平均值±SEM。 Figure 7. LncRNA expression patterns in the human monocytic cell line THP-1 upon stimulation with poly(I:C) or LPS. THP-1 cells were stimulated with 50 μg/ml poly(I:C) or 100 ng/ml LPS for 4 hours or 24 hours. Only THP-1 cells cultured in LPS-free RPMI medium for the indicated times were used as controls for each experiment. The amount of expression of lncRNA or PIK3CA was measured by real-time quantitative PCR. a. Expression of six lncRNAs. b. The amount of expression of PIK3CA. 4h poly(I:C) stimulation: n=6-8; 4h LPS stimulation: n=3-5: 24h poly(I:C) stimulation: n=5-6; 24h LPS stimulation: n=3-5. Bars represent mean ± SEM.

圖8. RA和SLE轉錄組中MIAT和IL-18的表現量。a-b.對RA中的MIAT(a)和IL-18(b)的表現量進行總體轉錄體學(Meta-transcriptomics)的分析。c-d.對SLE中的MIAT(c)和IL-18(d)的表現量進行總體轉錄體學(Meta-transcriptomics)的分析。使用MetaSignature網站(http：//metasignature.stanford.edu/)進行總體轉錄體學分析。每個框代表通過MetaSignature網站從“基因表達綜合”(GEO)存儲庫中選擇的疾病隊列轉錄組數據集。 Figure 8. Expression of MIAT and IL-18 in RA and SLE transcriptomes. a-b. Meta-transcriptomics analysis of expression levels of MIAT (a) and IL-18 (b) in RA. c-d. Meta-transcriptomics analysis of expression levels of MIAT (c) and IL-18 (d) in SLE. Global transcriptomic analysis was performed using the MetaSignature website (http://metasignature.stanford.edu/). Each box represents a disease cohort transcriptome dataset selected from the Gene Expression Omnibus (GEO) repository via the MetaSignature website.

圖9. 使用組合的MIAT(dCT)、THRIL(dCT)和IL-18(pg/ml)表達模式，從RA和SLE樣品中區分AOSD樣品。a. 3D散點圖中顯示每個樣品的MIAT(dCT)、THRIL(dCT)和IL-18(pg/ml)表現量。Diamond：AOSD；cross：RA；triangle：SLE.菱形：AOSD；交叉：RA；三角形：SLE。b. AOSD、RA和SLE患者的PBMC的MIAT(dCT)、THRIL(dCT)和IL-18(pg/ml) 值的主成分分析(PCA)。c-d.與健康對照組相比，RA和SLE PBMC中的MIAT dCT值。e. MIAT在敗血症和健康對照血細胞中的相對表現量(GSE 28750數據)。n.s.不顯著，* p<0.05(通過Mann-Whitney U檢驗)。 Figure 9. Differentiation of AOSD samples from RA and SLE samples using combined MIAT (dCT), THRIL (dCT) and IL-18 (pg/ml) expression patterns. a. The amount of MIAT (dCT), THRIL (dCT) and IL-18 (pg/ml) expressed for each sample is shown in a 3D scatterplot. Diamond: AOSD; cross: RA; triangle: SLE. Diamond: AOSD; cross: RA; triangle: SLE. b. MIAT (dCT), THRIL (dCT) and IL-18 (pg/ml) of PBMCs of AOSD, RA and SLE patients Principal Component Analysis (PCA) of the values. c-d. MIAT dCT values in RA and SLE PBMCs compared to healthy controls. e. Relative expression of MIAT in sepsis and healthy control blood cells (GSE 28750 data). n.s. not significant, *p<0.05 (by Mann-Whitney U test).

圖10. AOSD、RA、SLE和敗血症患者中lncRNA表達模式的比較。a-b.從AOSD識別RA(a：臨界值>12.57時AUC=0.829)或從AOSD識別SLE(b：臨界值>11.39時AUC=0.881)的AOSD預測分數(A分數)的受試者工作特徵曲線(receiver operating characteristic curve,ROC curve)。c.與健康對照者中的PBMC相比，AOSD、RA、SLE或敗血症中的PIK3CA表現量。線代表中位數。通過Mann-Whitney U檢驗，* p<0.05，*** p<0.001。通過減去GAPDH CT值來計算PIK3CA dCT。敗血症微陣列血液細胞轉錄組數據集GSE28750收集自Gene Expression Omnibus(GEO)，顯示出敗血症和健康對照者中的血液細胞中PIK3CA的相對表現量。n.s：根據Mann-Whitney U檢驗沒有統計學意義。d. MIAT與AOSD、RA、SLE或敗血症患者血液細胞中PIK3CA表現量的相關性。皮爾遜相關係數r/p值顯示在圖表的右下角。 Figure 10. Comparison of lncRNA expression patterns in AOSD, RA, SLE and sepsis patients. ab. Receiver operating characteristic curve of AOSD prediction score (A-score) for identifying RA from AOSD (a: AUC=0.829 at cutoff >12.57) or SLE from AOSD (b: AUC=0.881 at cutoff >11.39) (receiver operating characteristic curve, ROC curve). c. PIK3CA expression in AOSD, RA, SLE or sepsis compared to PBMC in healthy controls. Lines represent medians. *p<0.05, ***p<0.001 by Mann-Whitney U test. PIK3CA dCT was calculated by subtracting GAPDH CT values. The sepsis microarray blood cell transcriptome dataset GSE28750, collected from the Gene Expression Omnibus (GEO), shows the relative expression of PIK3CA in blood cells in sepsis and healthy controls. n.s: Not statistically significant according to the Mann-Whitney U test. d. Correlation between MIAT and PIK3CA expression in blood cells of patients with AOSD, RA, SLE or sepsis. The Pearson correlation coefficient r/p value is displayed in the lower right corner of the graph.

本發明涉及一種檢測個體罹患成人發作型史笛兒氏症的方法，該方法包括以下步驟：(a)提供一血液樣本和一周邊血液單核細胞；檢測該血液樣本中一蛋白質生物標誌物之表現量，其中該蛋白質生物標幟物係為IL18；(b)檢測該周邊血液單核細胞中一長鏈非編碼核糖核酸生物標誌物的表現量，其中該長鏈非編碼核糖核酸生物標誌物為MIAT或THRIL；(c)將步驟(b)所得偵測到的IL-18、MIAT和THRIL的表現量以一預測函數計算出一A分數，其中該預測函數係由一多元迴歸分析(multiple regression analysis) 得到；以及(d)將步驟(c)所計算的該A分數與一臨界值比較，其中該臨界值係透過接收器操作員特徵(Receiver Operator Characteristic，ROC)方法獲得，其中該臨界值對應於ROC曲線下的面積(the area under an ROC curve，AUC)達到最大值，其中A分數高於該臨界值則代表該個體罹患成人發作型史笛兒氏症。 The present invention relates to a method for detecting that an individual suffers from adult-onset Strudel's disease, the method comprising the following steps: (a) providing a blood sample and a peripheral blood mononuclear cell; detecting a protein biomarker in the blood sample Expression level, wherein the protein biomarker is IL18; (b) detecting the expression level of a long-chain non-coding RNA biomarker in the peripheral blood mononuclear cells, wherein the long-chain non-coding RNA biomarker is MIAT or THRIL; (c) calculates an A-score with a predictive function of the detected expression levels of IL-18, MIAT and THRIL obtained in step (b), wherein the predictive function is determined by a multiple regression analysis ( multiple regression analysis) and (d) comparing the A-score calculated in step (c) with a threshold, wherein the threshold is obtained by a Receiver Operator Characteristic (ROC) method, wherein the threshold corresponds to The area under an ROC curve (AUC) reaches the maximum value, where the A-score is higher than the critical value, indicating that the individual suffers from adult-onset Stubbs disease.

在上述方法中，該方法進一步包括以下步驟：(e)對受試者施用有效量的AOSD治療藥物。 In the above method, the method further comprises the step of: (e) administering to the subject an effective amount of a therapeutic drug for AOSD.

在一實施例中，預測方程為：A分數=1.62 *THRIL △CT-1.43 *MIAT △CT+0.02 * IL-18(pg/ml) In one embodiment, the prediction equation is: A-score = 1.62 * THRIL ΔCT - 1.43 * MIAT ΔCT + 0.02 * IL-18 (pg/ml)

在另一個實施例中，臨界值在5.85至7.12之間，靈敏度為94.4%-100%，特異性為93.7-100%。 In another embodiment, the cut-off value is between 5.85 and 7.12, the sensitivity is 94.4%-100%, and the specificity is 93.7-100%.

在另一個實施例中，臨界值為7.114，敏感性為94.87%，特異性為100%。 In another embodiment, the cutoff value is 7.114, the sensitivity is 94.87%, and the specificity is 100%.

在上述方法中，進一步檢測該周邊血液單核細胞中一PIK3CA的基因表現量，其中該PIK3CA基因表現量高於一健康個體時則該個體被排除患有系統性紅斑狼瘡、類風濕性關節炎或敗血症。 In the above method, the gene expression level of a PIK3CA in the peripheral blood mononuclear cells is further detected, and when the PIK3CA gene expression level is higher than that of a healthy individual, the individual is excluded from systemic lupus erythematosus, rheumatoid arthritis or sepsis.

在上述方法中，其中該健康個體係為未罹患一風濕疾病的個體。 In the above method, wherein the healthy individual is an individual not suffering from a rheumatic disease.

在上述方法中，步驟(b)中檢測蛋白質生物標誌物表現量的方法是免疫學測定。 In the above method, the method for detecting the expression level of the protein biomarker in step (b) is an immunological assay.

在上述方法中，步驟(b)中檢測lncRNA表現量的方法為聚合酶鏈反應。 In the above method, the method for detecting the expression level of lncRNA in step (b) is polymerase chain reaction.

在上述方法中，其中所述血液樣品是全血、血清或血漿。 In the above method, wherein the blood sample is whole blood, serum or plasma.

在另一方面，本發明涉及一種檢測一罹患成人發作型史笛兒氏症的個體的疾病病程的方法，該方法包括以下步驟：(a)提供一血液樣本和一周邊血液單核細胞，其中該血液樣本和該周邊血液單核細胞係由一罹患成人發作型史笛兒氏症的個體中收集而來；(b)檢測該血液樣本中一蛋白質生物標誌物之表現量，其中該蛋白質生物標幟物係為TNF-α；檢測該周邊血液單核細胞中一長鏈非編碼核糖核酸生物標誌物的表現量，其中該長鏈非編碼核糖核酸生物標誌物為NTT；(c)將步驟(b)所得偵測到的TNFα和NTT的表現量以一預測函數計算出一B分數，其中該預測函數係由一多元迴歸分析(multiple regression analysis)得到；以及(d)將步驟(c)所計算的該B分數與一臨界值比較，其中該臨界值係透過接收器操作員特徵(Receiver Operator Characteristic，ROC)方法獲得，其中該臨界值對應於ROC曲線下的面積(the area under an ROC curve，AUC)達到最大值，其中B分數高於該臨界值則代表該罹患成人發作型史笛兒氏症的個體疾病病程為一全身亞型或是一關節亞型。 In another aspect, the invention relates to a method of detecting the disease course of an individual suffering from adult-onset Stubbs disease, the method comprising the steps of: (a) providing a blood sample and a peripheral blood mononuclear cell, wherein The blood sample and the peripheral blood mononuclear cells are collected from an individual with adult-onset Stubbs' disease; (b) detecting the expression of a protein biomarker in the blood sample, wherein the protein biomarker The marker is TNF-α; the expression of a long-chain non-coding ribonucleic acid biomarker in the peripheral blood mononuclear cells is detected, wherein the long-chain non-coding ribonucleic acid biomarker is NTT; (c) adding step (b) the resulting detected expression of TNFα and NTT calculates a B-score with a predictive function, wherein the predictive function is obtained by a multiple regression analysis; and (d) applying step (c) ) The calculated B-score is compared to a threshold obtained by the Receiver Operator Characteristic (ROC) method, wherein the threshold corresponds to the area under the ROC curve (the area under an ROC curve). ROC curve, AUC) reaches the maximum value, wherein the B-score is higher than the critical value, indicating that the individual disease course of adult-onset Stubbs disease is a systemic subtype or a joint subtype.

在上述方法中，該方法進一步包括以下步驟：(e)對受試者施用有效量的AOSD治療藥物。 In the above method, the method further comprises the step of: (e) administering to the subject an effective amount of a therapeutic drug for AOSD.

在一實施例中，預測方程為：B分數=0.22 * NTT △CT-0.01 * TNF-α(pg/ml). In one embodiment, the prediction equation is: B-score = 0.22 * NTT ΔCT - 0.01 * TNF-α(pg/ml) .

在另一個實施例中，臨界值在0.17至0.83之間，靈敏度為57.1%-71.4%，特異性為66.7-100%。 In another embodiment, the cut-off value is between 0.17 and 0.83, the sensitivity is 57.1%-71.4%, and the specificity is 66.7-100%.

In another embodiment,the cutoff value of 0.266,with sensitivity of 66.7% and specificity of 90.9%.在另一個實施例中，臨界值為0.266，敏感性 為66.7%，特異性為90.9% In another embodiment, the cutoff value of 0.266, with sensitivity of 66.7% and specificity of 90.9%. was 66.7% and the specificity was 90.9%

在上述方法中，步驟(b)中檢測蛋白質生物標誌物表現量的方法是免疫學測定。 In the above method, the method for detecting the expression level of the protein biomarker in step (b) is an immunological assay.

在上述方法中，步驟(b)中檢測lncRNA表現量的方法為聚合酶鏈反應。 In the above method, the method for detecting the expression level of lncRNA in step (b) is polymerase chain reaction.

在上述方法中，其中所述血液樣品是全血、血清或血漿。 In the above method, wherein the blood sample is whole blood, serum or plasma.

在另一方面，本發明涉及一種用於診斷患有成人發作型史笛兒氏症的個體的試劑盒，其中所述試劑盒包含選自以下的試劑：(a)用於檢測IL-18蛋白的試劑；(b)用於檢測MIAT和THRIL的lncRNA的試劑；以及(c)說明手冊，提供預測方程式和臨界值，用於確定受試者是否患有成人發作型史笛兒氏症。 In another aspect, the present invention relates to a kit for diagnosing an individual with adult-onset Stubbs' disease, wherein the kit comprises a reagent selected from the group consisting of: (a) for detecting IL-18 protein (b) reagents for the detection of lncRNAs of MIAT and THRIL; and (c) an instruction manual providing prediction equations and cut-off values for determining whether a subject has adult-onset Stubbs disease.

在另一方面，本發明涉及一種用於診斷患有成人發作型史笛兒氏症的個體病程的試劑盒，其中所述試劑盒包含選自以下的試劑：(a)試劑用於檢測TNF-α蛋白；(b)用於檢測NTT的lncRNA的試劑；以及(c)說明手冊，提供預測方程式和臨界值，用於確定患有成人發作型史笛兒氏症的病程的個體是全身性亞型還是關節性亞型。 In another aspect, the present invention relates to a kit for diagnosing the course of an individual with adult-onset Stubbs disease, wherein the kit comprises reagents selected from the group consisting of: (a) reagents for the detection of TNF- alpha protein; (b) reagents for the detection of lncRNAs for NTT; and (c) an instruction manual providing prediction equations and cutoff values for determining whether individuals with a course of adult-onset Stubbs disease are systemic subtypes type or articular subtype.

實施例Example

通過下面的具體實施例，可以進一步證明本發明的實際應用範圍。僅是本發明的優選實施例，而並不限制本發明的範圍。因此，根據本發明的範圍和本發明的說明書的內容進行的任何簡單的改變和修改仍然被本發明的範圍覆蓋。 The practical application scope of the present invention can be further proved by the following specific examples. It is only a preferred embodiment of the present invention, and does not limit the scope of the present invention. Therefore, any simple changes and modifications made in accordance with the scope of the present invention and the contents of the description of the present invention are still covered by the scope of the present invention.

方法 method

受試者：連續41名符合Yamaguchi標準的AOSD患者。排除患有感染，惡性腫瘤或其他風濕性疾病的患者(表1)。 Subjects: 41 consecutive AOSD patients who met Yamaguchi criteria. Patients with infections, malignancies, or other rheumatic diseases were excluded (Table 1).

表一、成人史迪爾氏症的診斷標準

Figure 109119409-A0202-12-0013-3
Table 1. Diagnostic criteria for Still's disease in adults
Figure 109119409-A0202-12-0013-3

使用改良的Pouchot評分評估每位AOSD患者的全身活動，其中活動AOSD定義為活動評分為4或更高。該全身活動評分(範圍0-12)為以下12種表現中的每一種賦予一個分數：發燒，e逝性皮疹，喉嚨痛，關節痛或關節炎，肌痛，胸膜炎，心包炎，肺炎，淋巴結病，肝腫大或肝功能異常，白細胞計數升高≧15,000/mm3，血清鐵蛋白水平>3000μg/L。 Whole body activity was assessed in each patient with AOSD using the modified Pouchot score, where active AOSD was defined as an activity score of 4 or higher. This systemic activity score (range 0-12) assigns a score to each of the following 12 manifestations: fever, evanescent rash, sore throat, arthralgia or arthritis, myalgia, pleurisy, pericarditis, pneumonia, lymph nodes Disease, hepatomegaly or abnormal liver function, increased white blood cell count ≥ 15,000/mm3, serum ferritin level> 3000μg/L.

在研究開始時，處於活耀狀態的所有患者都接受了具有/不具有皮質類固醇的非類固醇消炎藥治療，但是均未接受傳統合成的具有改善病情的抗風濕藥物(conventional synthetic disease-modifying anti-rheumatic drugs，csDMARDs)或生物療法。經過調查，有35名(85.4%)接受了csDMARD中的至少一種，包括甲氨蝶呤(n=32)、羥氯喹(n=29)、環孢菌素(n=15)和硫唑嘌呤(n=10)。所有隨訪至少一年的AOSD患者被 分為兩種疾病亞型：一種包括病程為單週期的和多週期形式的全身亞型，另一種是關節亞型(持續性關節炎，至少涉及一個關節，持續時間更長，超過6個月)。符合美國風濕病學院(American College of Rheumatology,ACR)/歐洲風濕病聯盟(European League Against Rheumatism,EULAR)合作倡議的2010年RA分類標準的20名患者和符合1997年修訂的SLE ACR標準的20名患者被列為疾病對照。使用32名年齡相匹配的健康對照者，他們沒有任何風濕病。機構審查委員會批准了這項研究(CMUH108-REC1-099)，並且根據赫爾辛基宣言獲得了每個參與者的書面同意。 At the start of the study, all patients in active status were receiving NSAIDs with or without corticosteroids, but none were receiving conventional synthetic disease-modifying antirheumatic drugs (conventional synthetic disease-modifying anti-rheumatic drugs) rheumatic drugs, csDMARDs) or biological therapy. After investigation, 35 (85.4%) received at least one of the csDMARDs, including methotrexate (n=32), hydroxychloroquine (n=29), cyclosporine (n=15), and azathioprine (n=10). All AOSD patients with at least one year of follow-up were Divided into two disease subtypes: a systemic subtype that includes a single-cycle and multi-cycle form of the disease course, and a joint subtype (persistent arthritis, involving at least one joint, longer duration, more than 6 months ). Twenty patients who met the 2010 RA classification criteria of the American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) collaborative initiative and 20 patients who met the 1997 revised SLE ACR criteria Patients were included as disease controls. Thirty-two age-matched healthy controls without any rheumatism were used. The institutional review board approved this study (CMUH108-REC1-099), and written consent was obtained from each participant in accordance with the Declaration of Helsinki.

用於lncRNA的RNA提取和實時定量PCR(qRT-PCR)：早晨從參與者的周邊靜脈血中抽取約8ml靜脈全血。立即使用Ficoll-PaqueTM PLUS(GE Healthcare Biosciences,Illinois,USA)密度梯度離心法分離周邊血液單核球細胞(Peripheral blood mononuclear cells，PBMC)。將PBMC放入-80℃的冰箱中，直到同時檢測lncRNA。通過TRIzol®試劑(Sigma-Aldrich,Missouri,USA)提取來自PBMC的總RNA，並根據製造商的說明使用RNeasy MinElute Cleanup Kit(QIAGEN,Germany)進行純化。 RNA extraction and quantitative real-time PCR (qRT-PCR) for lncRNA: Approximately 8 ml of venous whole blood was drawn from participants' peripheral venous blood in the morning. Peripheral blood mononuclear cells (PBMC) were immediately isolated using Ficoll-Paque ™ PLUS (GE Healthcare Biosciences, Illinois, USA) density gradient centrifugation. Place PBMCs in a -80 °C freezer until simultaneous detection of lncRNAs. Total RNA from PBMCs was extracted by TRIzol® reagent (Sigma-Aldrich, Missouri, USA) and purified using the RNeasy MinElute Cleanup Kit (QIAGEN, Germany) according to the manufacturer's instructions.

使用ND-1000分光光度計(Nanodrop Tcchnology,USA)在OD260和280nm處定量純化的RNA。核酸質量低的兩名患者被排除在進一步分析之外。使用高容量cDNA反轉錄酶試劑盒(ThermoFisher Scientific-Invitrogen,Waltham,Massachusetts,USA)將2μg RNA反轉錄為cDNA，用於qRT-PCR分析。人類甘油醛3-磷酸脫氫酶(glyceraldehyde 3-phosphate dehydrogenase，GAPDH)基因表達被用作內源性對照。所有引 子均由台灣台北的Genomics BioSci & Tech設計和合成。本發明使用的引子序列列於表2中。 Purified RNA was quantified at OD260 and 280 nm using an ND-1000 spectrophotometer (Nanodrop Tcchnology, USA). Two patients with low nucleic acid quality were excluded from further analysis. 2 μg of RNA was reverse transcribed into cDNA for qRT-PCR analysis using a high capacity cDNA reverse transcriptase kit (ThermoFisher Scientific-Invitrogen, Waltham, Massachusetts, USA). Human glyceraldehyde 3-phosphate dehydrogenase (GAPDH) gene expression was used as an endogenous control. All quotes Both were designed and synthesized by Genomics BioSci & Tech in Taipei, Taiwan. The primer sequences used in the present invention are listed in Table 2.

表2.用於qRT-PCR的寡核苷酸的核苷酸序列

Figure 109119409-A0202-12-0015-37
Table 2. Nucleotide sequences of oligonucleotides used for qRT-PCR
Figure 109119409-A0202-12-0015-37

Figure 109119409-A0202-12-0016-4
Figure 109119409-A0202-12-0016-4

使用IQ2 TaqMan Probe qPCR系統(hermo Fisher Scientific,Massachusetts,USA)在Roche LightCycler Instrument 480上進行qRT-PCR反應。使用40-200ng cDNA進行一個即時PCR的循環，即在95℃下預孵育30秒，進行50個擴增循環(95℃ 10秒，60℃ 30秒，72℃ 10秒)，最後在40℃下冷卻30秒鐘。使用比較閾值循環(CT)方法計算每個樣品中目標基因相對於平均的內源性對照基因的表達差異。 qRT-PCR reactions were performed on a Roche LightCycler Instrument 480 using the IQ2 TaqMan Probe qPCR system (hermo Fisher Scientific, Massachusetts, USA). Use 40-200ng of cDNA for one cycle of real-time PCR of 30 sec preincubation at 95°C, 50 cycles of amplification (10 sec at 95°C, 30 sec at 60°C, 10 sec at 72°C), and finally at 40°C Cool for 30 seconds. The difference in expression of the gene of interest relative to the average endogenous control gene in each sample was calculated using the comparative threshold cycle (CT) method.

體外細胞株研究：將人單核細胞細胞株(THP-1)(ATCC TIB-202；American Type Culture Collection,Rockville,Md.)以不含LPS且添加10%胎牛血清RPMI培養基(Gibco,ThermoFisher Scientific,USA)於37℃、5%CO2的培養箱中進行培養。在不含LPS的RPMI培養基中培養的一百萬個細胞，並且分別用類鐸受體(Toll-like receptor,TLR)3的配體poly(I：C)或TLR4配體LPS處理4小時和24小時。在不含LPS的RPMI培養基中培養4小時和24小時的THP-1細胞最為相對應實驗的對照組。然後從THP-1細胞中提取RNA，用於進一步的qRT-PCR分析。使用比較閾值循環(CT)方法計算每個樣品中靶基因相對於平均內部對照基因的表達差異，並通過△CT(CTlncRNA-CTGAPDH)進行評估。計算對照孔中THP-1細胞多次重複的中值△CT值。通過2 -△△CT計算分析的THP-1細胞中lncRNA的表達倍數，其中△△CT的計算公式為：[(CT lncRNA-CT GAPDH)-對照基因的平均△CT]。 In vitro cell line studies: Human monocyte cell line (THP-1) (ATCC TIB-202; American Type Culture Collection, Rockville, Md.) was cultured in RPMI medium (Gibco, ThermoFisher) without LPS and supplemented with 10% fetal bovine serum. Scientific, USA) in a 37°C, 5% CO2 incubator. One million cells were cultured in RPMI medium without LPS and treated with either the Toll-like receptor (TLR) 3 ligand poly(I:C) or the TLR4 ligand LPS for 4 hours and 24 hours. THP-1 cells cultured in RPMI medium without LPS for 4 hours and 24 hours most corresponded to the experimental control group. RNA was then extracted from THP-1 cells for further qRT-PCR analysis. Differences in expression of target genes relative to the mean internal control gene in each sample were calculated using the comparative threshold cycle (CT) method and assessed by ΔCT ( CTlncRNA - CTGAPDH ). The median ΔCT value of multiple replicates of THP-1 cells in control wells was calculated. The expression fold of lncRNA in THP-1 cells was calculated by 2 - ΔΔCT, where the formula for ΔΔCT was: [(CT lncRNA-CT GAPDH)-average ΔCT of control gene].

促炎細胞因子表現量的測定：血漿中細胞因子表現量通過商業化的ELISA試劑盒針對IL-1β(RayBiotech Inc.,Norcross,GA,USA)，IL-6(PeproTech Inc.,Rocky Hill,NJ,USA)，IL-17A(RayBiotech Inc.,Norcross, GA,USA)，IL-18(Medical & Biology Laboratories Co,Ltd.,Naka-Ku,Nagoya,Japan)，和TNF-α(R&D Systems,Minneapolis,MN,USA)根據每個製造商的說明書進行測定。所有測定均在測定間和測定內變異係數(CV)均小於10%的情況下進行。 Determination of pro-inflammatory cytokine expression: Cytokine expression in plasma was detected by commercial ELISA kits for IL-1β (RayBiotech Inc., Norcross, GA, USA), IL-6 (PeproTech Inc., Rocky Hill, NJ) , USA), IL-17A (RayBiotech Inc., Norcross, GA, USA), IL-18 (Medical & Biology Laboratories Co, Ltd., Naka-Ku, Nagoya, Japan), and TNF-α (R&D Systems, Minneapolis, MN, USA) were assayed according to each manufacturer's instructions . All assays were performed with inter- and intra-assay coefficients of variation (CV) of less than 10%.

生物信息學和統計分析：通過GraphPad Prism 5進行Kruskal-Wallis檢驗，以分析AOSD患者亞型和健康對照組中lncRNA和細胞因子表現量的差異。使用R軟件v.3.6.0(R Foundation for Statistical Computing,Vienna,Austria)的廣義線性模型(glm)函數，以lncRNA表現量(△CT)和血漿細胞因子表現量(pg/ml)作為診斷AOSD的變量進行多項式回歸分析。透過使用R軟件將來自AOSD患者和健康對照的每個樣品的lncRNA表達特徵繪製在3D散點圖上且進一步可視覺化用以區分AOSD患者與對照者的關鍵變量。 Bioinformatics and statistical analysis: Kruskal-Wallis test was performed by GraphPad Prism 5 to analyze differences in lncRNA and cytokine expression between subtypes of AOSD patients and healthy controls. The generalized linear model (glm) function of R software v.3.6.0 (R Foundation for Statistical Computing, Vienna, Austria) was used to diagnose AOSD with lncRNA expression (ΔCT) and plasma cytokine expression (pg/ml) A polynomial regression analysis was performed on the variables. The lncRNA expression profile of each sample from AOSD patients and healthy controls was plotted on a 3D scatter plot by using R software and further visualized key variables to distinguish AOSD patients from controls.

將AOSD組群隨機分為測試數據集(樣本的70%)和驗證數據集(樣本的30%)，並使用選擇的變量構建混淆矩陣(Confusion matrix)去總結分類演算法的性能(R software,glm function)。通過給出最佳正確分類率的變量組合來建立AOSD預測分數(如通過上述分析所得到的結果)。使用MedCalc v.14執行接收者操作特徵曲線(Receiver operating characteristic curve，ROC)分析，以確定ROC曲線(the area under ROC curve，AUC)下的面積、靈敏度、特異性和準確性。 The AOSD cohort was randomly divided into a test dataset (70% of the sample) and a validation dataset (30% of the sample), and a confusion matrix was constructed using the selected variables to summarize the performance of the classification algorithm (R software, glm function). The AOSD prediction score (as obtained by the above analysis) was established by the combination of variables that gave the best correct classification rate. Receiver operating characteristic curve (ROC) analysis was performed using MedCalc v.14 to determine the area under the ROC curve (AUC), sensitivity, specificity and accuracy.

Pearson’s correlations用來測定lncRNA表現量與促炎細胞因子或PIK3CA表現量之間的關係。在MetaSignature網站(http：//metasignature.stanford.edu/)上對其他風濕性疾病(包括RA和SLE) 的轉錄組上可用的lncRNA MIAT和IL-18的表現量進行了Meta-analyses。 Pearson's correlations were used to determine the relationship between the expression of lncRNA and the expression of pro-inflammatory cytokines or PIK3CA. Other rheumatic diseases (including RA and SLE) on the MetaSignature website (http://metasignature.stanford.edu/) Meta-analyses were performed on the transcriptomes of available lncRNA MIAT and IL-18 expression.

結果 result

AOSD病人的臨床特徵 Clinical features of AOSD patients

在最初選入的41例患者中，有2例的核酸質量低，而另一例則為實驗室數據不完整的患者被排除在進一步分析之外。在38例活動性AOSD患者中，有37例(97.4%)，31例(81.6%)，30例(78.9%)，24(63.2%)，20(52.6%)和14(36.8%)分別出現了尖峰熱(

Figure 109119409-A0202-12-0018-36
39℃)，皮疹，關節痛或關節炎，喉嚨痛，肝功能障礙和淋巴結病。如表3所示，AOSD患者與健康對照(HC)之間的進入年齡或女性比例均無顯著差異。27例患者患有系統性亞型，其他患者患有慢性關節亞型。 Of the 41 patients initially enrolled, 2 had low nucleic acid quality, while another patient with incomplete laboratory data was excluded from further analysis. Among the 38 patients with active AOSD, 37 (97.4%), 31 (81.6%), 30 (78.9%), 24 (63.2%), 20 (52.6%) and 14 (36.8%) patients, respectively spike fever (
Figure 109119409-A0202-12-0018-36
39°C), rash, arthralgia or arthritis, sore throat, liver dysfunction and lymphadenopathy. As shown in Table 3, there were no significant differences in entry age or proportion of females between AOSD patients and healthy controls (HC). Twenty-seven patients had the systemic subtype and the others had the chronic joint subtype.

表3. 成人發作型史迪兒症(AOSD)和健康對照(HC)患者的人口統計數據和實驗室檢查結果#。

Figure 109119409-A0202-12-0018-5
Table 3. Demographics and laboratory findings of adult-onset Still's disease (AOSD) and healthy controls (HC) patients#.
Figure 109119409-A0202-12-0018-5

AOSD和HC患者LncRNA的表達特徵和細胞因子資料 Expression characteristics and cytokine profiles of LncRNAs in AOSD and HC patients

通過qRT-PCR，顯示了在AOSD系統性亞型、AOSD關節性亞型和健康對照(HC)中每個個體的六個lncRNA△CT(CTlncRNA-CTGAPDH)的表達水平，結果顯示於圖1a-1f中。與HC的中位數相比，兩種AOSD亞型的MIAT的平均值△CT水平似乎較低(圖1a)，而兩種AOSD亞型的THRIL△CT的平均值趨勢較高(圖1b)。然而，如通過Kruskal-Wallis檢驗所計算的，差異均未達到統計學顯著性。表3和圖1顯示出AOSD患者的IL-1β、IL-6、IL-17A、IL-18和TNF-α的血漿水平明顯高於HC。值得注意的是，各組之間IL-6、IL-18和TNF-α水平的差異具有較低的p值(IL-6、IL-18和TNF-α的p值均<0.01)。 By qRT-PCR, the expression levels of six lncRNAΔCT ( CTlncRNA - CTGAPDH ) in each individual in AOSD systemic subtype, AOSD articulating subtype and healthy controls (HC) were shown, and the results are shown in Fig. 1a-1f. The mean ΔCT level of MIAT appeared to be lower for both AOSD subtypes compared to the median of HC (Fig. 1a), while the mean THRILΔCT trended higher for both AOSD subtypes (Fig. 1b) . However, none of the differences reached statistical significance as calculated by the Kruskal-Wallis test. Table 3 and Figure 1 show that the plasma levels of IL-1β, IL-6, IL-17A, IL-18 and TNF- α were significantly higher in AOSD patients than in HC. Notably, differences in IL-6, IL-18, and TNF-α levels between groups had lower p-values (p-values for IL-6, IL-18, and TNF-α were all <0.01).

利用lncRNAs表達特徵和細胞因子建立預測評分 Establishment of predictive scores using lncRNAs expression signatures and cytokines

為建立基於lncRNA表達的AOSD診斷模型，我們進一步採用MIAT和THRIL的△CT值作為變量進行多元回歸分析，以預測AOSD的發生。MIAT的係數為-1.43，p=0.003，THRIL的係數為1.62，p=0.001。我們還使用IL-6、IL-18和TNF-α表現量進行了多元回歸分析，以預測AOSD，但只有IL-18的表現量達到了統計學顯著性(p=0.027)。使用R軟件將每個樣品的MIAT、THRIL和IL-18的表達量投影到3D散點圖上。如圖2a所示，可以通過一組新推定的生物標記物(包括MIAT、THRIL和IL-18的表現量)將AOSD樣品與對照樣品最佳分離。此外，隨機選擇70%的樣本作為測試數據集，另外的30%的樣本作為驗證數據集，以建立一個混淆矩陣來評估使用此新集合的分類算法的性能。測試數據集和驗證數據集用於預測AOSD的準確性均為100%。 To establish a diagnostic model for AOSD based on lncRNA expression, we further used the ΔCT values of MIAT and THRIL as variables to perform multiple regression analysis to predict the occurrence of AOSD. The coefficient for MIAT is -1.43, p=0.003, and the coefficient for THRIL is 1.62, p=0.001. We also performed multiple regression analysis using IL-6, IL-18 and TNF- α expression to predict AOSD, but only IL-18 expression reached statistical significance (p=0.027). The expression levels of MIAT, THRIL and IL-18 of each sample were projected onto a 3D scatterplot using R software. As shown in Figure 2a, AOSD samples could be best separated from control samples by a set of new putative biomarkers including expression of MIAT, THRIL and IL-18. In addition, 70% of the samples were randomly selected as the test dataset and the other 30% as the validation dataset to build a confusion matrix to evaluate the performance of the classification algorithm using this new set. Both the test dataset and the validation dataset were used to predict AOSD with 100% accuracy.

因此，我們基於MIAT、THRIL和IL-18的係數和值，構建了預測方程以計算用於診斷AOSD的分數(稱為“A分數”)。預測方程式如下：A分數=1.62 *THRIL △CT-1.43 *MIAT △CT+0.02 * IL-18(pg/ml) Therefore, based on the coefficients and values of MIAT, THRIL, and IL-18, we constructed prediction equations to calculate a score (referred to as "A-score") for diagnosing AOSD. The prediction equation is as follows: A-score = 1.62 * THRIL △CT - 1.43 * MIAT △CT + 0.02 * IL-18 (pg/ml)

以“A分數”進行診斷AOSD的ROC分析顯示出在臨界值為7.114時，AUC為0.998，其中的靈敏度為94.87%和特異性為100%(圖2b)。為了在第二群組中進行重複測試，因此，進一步收集了一個獨立的群體樣本，該樣本集合為16例活動性AOSD患者。在第二個AOSD病人群組中使用了A分數進行分析，結果顯示出在相同的臨界值(7.114)下，分類正確率達到100%。 ROC analysis for diagnosing AOSD with "A-score" showed an AUC of 0.998 at a cut-off value of 7.114, with a sensitivity of 94.87% and a specificity of 100% (Fig. 2b). For repeat testing in the second cohort, therefore, a further independent cohort sample of 16 patients with active AOSD was collected. Analysis using A-scores in the second AOSD patient cohort showed 100% classification accuracy at the same cutoff value (7.114).

建立用於區分AOSD亞型的預測分數 Establishment of predictive scores for differentiating AOSD subtypes

為了進一步區分疾病進程的AOSD亞型，在3D散點圖上繪製了系統性亞型和關節性亞型中AOSC患者的lncRNA表現量和細胞因子表現量的不同組合。結果顯示出NTT△CT和TNF-α的表現量為最佳地將AOSD全身亞型樣品與關節亞型樣品區分開來(圖3a)。以NTT△CT和TNF-α表現量作為區分AOSD亞型的混淆矩陣的R廣義線性模型顯示出測試數據集的準確性為76.92%(所有樣本的70%)，而驗證數據集的準確性為83.33%(所有樣本的30%)。 To further differentiate AOSD subtypes of disease progression, different combinations of lncRNA expression and cytokine expression in AOSC patients in systemic and articular subtypes were plotted on a 3D scatterplot. The results showed that the expression of NTTΔCT and TNF-α best differentiated samples of the whole body subtype of AOSD from the samples of the joint subtype (Fig. 3a). The R generalized linear model with NTTΔCT and TNF-α expression as the confusion matrix to distinguish AOSD subtypes showed an accuracy of 76.92% on the test dataset (70% of all samples), while the accuracy on the validation dataset was 83.33% (30% of all samples).

建立由回歸分析的係數和NTT和TNF-α的表現量組成的預測方程，以計算用於確定受試者的AOSD病程的分數(稱為“B分數”)。預測公式如下：B分數=0.22 * NTT △CT-0.01 * TNF-α(pg/ml)。 A predictive equation consisting of the coefficients of the regression analysis and the amount of expression of NTT and TNF-[alpha] was established to calculate a score (referred to as "B-score") for determining the course of AOSD in a subject. The prediction formula is as follows: B-score = 0.22 * NTT △CT - 0.01 * TNF-α(pg/ml) .

對區分的AOSD亞型的“B分數”的ROC分析顯示出當臨界值為0.266時，AUC為0.855，其中的敏感性為66.7%，特異性為90.9%(圖3h)。 ROC analysis of the "B-score" for discriminating AOSD subtypes showed an AUC of 0.855 at a cutoff value of 0.266, with a sensitivity of 66.7% and a specificity of 90.9% (Fig. 3h).

lncRNA、細胞因子表現量與AOSD疾病活性的相關性研究 Correlation between lncRNA, cytokine expression and AOSD disease activity

鑑於根據在免疫調節和炎症反應中的功能而選擇了六個lncRNA，因此，檢驗了AOSD患者中lncRNA或細胞因子表現亮與疾病活動性評分的相關性。有趣的是，具有最低RMRP和PACERR表現量(RMRP△CT+PACERR△CT>17)的AOSD樣本具有較高的疾病活性評分(p=0.03，圖4a)。血漿中IL-18值也與AOSD疾病活動密切相關(r2=0.38，p<0.0001，圖4b)。但是NTT、NEAT1、MIAT、RMRP、HRIL和PACERR的表現量與血漿細胞因子表現量沒有顯著相關。在AOSD的系統性或關節性亞型中，每種lncRNA的表達均與疾病活動沒有顯著相關性(圖4c)。 Given that six lncRNAs were selected based on their functions in immune regulation and inflammatory responses, the correlation of lncRNA or cytokine expression with disease activity scores in AOSD patients was examined. Interestingly, the AOSD samples with the lowest expression of RMRP and PACERR (RMRPΔCT+PACERRΔCT>17) had higher disease activity scores (p=0.03, Figure 4a). Plasma IL-18 values were also strongly correlated with AOSD disease activity (r 2 =0.38, p<0.0001, Figure 4b). However, the expression levels of NTT, NEAT1, MIAT, RMRP, HRIL and PACERR were not significantly correlated with the expression levels of plasma cytokines. In the systemic or articular subtypes of AOSD, the expression of each lncRNA did not significantly correlate with disease activity (Fig. 4c).

治療後的AOSD患者lncRNAs表現量和促炎細胞因子的變化 Changes of lncRNAs expression and proinflammatory cytokines in AOSD patients after treatment

研究了10名接受治療的AOSD患者在治療前和治療後6-12個月的6種lncRNA表現量和促炎細胞因子的值的變化。如圖5a-b所示，僅用csDMARDs處理後，NEAT1表現量升高；而在IL-6受體抑製劑tocilizumab治療的AOSD患者中觀察到NEAT1表達下降。 Changes in the expression levels of 6 lncRNAs and the values of pro-inflammatory cytokines before treatment and 6-12 months after treatment in 10 treated AOSD patients were investigated. As shown in Figure 5a–b, NEAT1 expression was elevated after treatment with csDMARDs alone; whereas NEAT1 expression was observed to be decreased in AOSD patients treated with the IL-6 receptor inhibitor tocilizumab.

由於PIK3CA可能是網絡分析顯示的lncRNA的下游調節者(圖6)，在治療後的患者中注意到PIK3CA與NEAT1之間呈正相關(圖5c，r=0.89，p<0.01)。如圖5d所示PIK3CA與6種lncRNA的正相關在治療後變得更加明顯。 As PIK3CA may be a downstream regulator of lncRNAs revealed by network analysis (Fig. 6), a positive correlation between PIK3CA and NEAT1 was noted in post-treatment patients (Fig. 5c, r=0.89, p<0.01). The positive correlation of PIK3CA with the 6 lncRNAs as shown in Fig. 5d became more pronounced after treatment.

LncRNA在單核球細胞株TLR-配體刺激中的表達模式 Expression patterns of LncRNAs in monocyte cell lines stimulated by TLR-ligands

由於已經報導了TLR3的活化與AOSD發病有關。因此，在人類單核球細胞株THP-1中測試了TLR3配體poly(I：C)和TLR4配體LPS刺激後的lncRNA表達模式。如圖4所示，經過4小時或24小時刺激後， poly(I：C)和LPS誘導了不同的lncRNA表達特徵。觀察到由poly(I：C)刺激的THP-1細胞中MIAT表現量上升和THRIL表現量下降，這些結果與AOSD患者中lncRNA表達模式的變化相似。進一步，在以LPS處理的THP-1細胞中檢測到MIAT表現量下降且結合了增加的NEAT1和RMRP表現量。此外，poly(I：C)在4小時和24小時刺激下皆能增加了了NTT表現量，然而LPS則在刺激24小時後亦會提高NTT表現量(圖7a)。另外，結果顯示出以poly(I：C)刺激可增加THP-1細胞中PIK3CA表現量，而LPS刺激的細胞中則否(圖7b)。 Since activation of TLR3 has been reported to be associated with the pathogenesis of AOSD. Therefore, the lncRNA expression patterns after LPS stimulation of TLR3 ligand poly(I:C) and TLR4 ligand were tested in the human monocyte cell line THP-1. As shown in Figure 4, after 4 hours or 24 hours of stimulation, Poly(I:C) and LPS induced distinct lncRNA expression signatures. We observed an increase in MIAT expression and a decrease in THRIL expression in THP-1 cells stimulated by poly(I:C), and these results were similar to changes in lncRNA expression patterns in AOSD patients. Further, decreased expression of MIAT combined with increased expression of NEAT1 and RMRP was detected in LPS-treated THP-1 cells. In addition, poly(I:C) increased NTT expression at both 4 and 24 h stimulation, whereas LPS also increased NTT expression after 24 h stimulation (Fig. 7a). In addition, the results showed that stimulation with poly(I:C) increased PIK3CA expression in THP-1 cells, but not in LPS-stimulated cells (Fig. 7b).

MIAT、THRIL和IL-18在RA、SLE或敗血症(sepsis)的轉錄組中的表達特徵 Expression signature of MIAT, THRIL and IL-18 in the transcriptome of RA, SLE or sepsis

為了研究在AOSD患者中鑑定出的lncRNA表達特徵是否與其他風濕病中的lncRNA表達模式相似，因此使用MetaSignature網站(http：//metasignature.stanford.edu/)針對從基因表達綜合庫(GEO)獲得的RA和SLE中的轉錄組數據進行了轉錄組分析。在AOSD患者的PBMC中觀察到MIAT和IL-18的上升以及THRIL表達的下降。而THRIL的值在RA或SLE轉錄組陣列上無法使用。但是，針對RA和SLE轉錄組數據集上MIAT和IL-18表現量進行Meta分析，結果顯示出與AOSD結果相比，RA和SLE具有不同的特徵。在RA病人中，MIAT和IL-18表現量沒有明顯升高(圖8a-8b)。而在SLE病人中，MIAT的表達下降，而IL-18的表達上升(圖8c-8d)。 To investigate whether the lncRNA expression signatures identified in AOSD patients were similar to lncRNA expression patterns in other rheumatic diseases, the MetaSignature website (http://metasignature.stanford.edu/) was used to target data obtained from the Gene Expression Omnibus (GEO) Transcriptome analysis was performed on the transcriptome data in RA and SLE. An increase in MIAT and IL-18 and a decrease in THRIL expression were observed in PBMCs of AOSD patients. While THRIL values are not available on RA or SLE transcriptome arrays. However, a meta-analysis of MIAT and IL-18 expression on the RA and SLE transcriptome datasets showed that RA and SLE had different characteristics compared to the AOSD results. In RA patients, the expression levels of MIAT and IL-18 were not significantly increased (Fig. 8a-8b). In SLE patients, however, the expression of MIAT decreased, while the expression of IL-18 increased (Figures 8c-8d).

此外，另外招募了20名SLE和20名RA患者以研究這6種lncRNA的表現量和促炎細胞因子。結果顯示出透過將組合的THRIL、MIAT 和IL-18的表現量繪製到3D散點圖和主成分分析(PCA)圖上，可以將AOSD與RA和SLE分離(圖9a-9b)。 In addition, an additional 20 SLE and 20 RA patients were recruited to investigate the expression levels and pro-inflammatory cytokines of these 6 lncRNAs. The results show that by combining THRIL, MIAT and IL-18 expression were plotted on 3D scatter plots and principal component analysis (PCA) plots, which could separate AOSD from RA and SLE (Figures 9a-9b).

使用A分數進行檢驗，亦可區分RA和SLE患者與AOSD組，AUC分別為0.829和0.881並且檢測RA和SLE的臨界值更高(分別為12.57和11.39)(圖10a-10b)。鑑於敗血症患者沒有可用的血液樣本，因此對敗血症組群GSE28750(從NCBI的GEO資料庫)的微陣列數據進行了重新分析。在GSE28750中，可以檢索到lncRNA MIAT的表達數據，但不能檢索到THRIL的值。結果顯示出與AOSD、RA或SLE的結果不同，敗血症血液樣品中MIAT的相對表現量明顯高於對照組別(圖1a和圖9c-9e)。而且，在健康或患有AOSD、RA、SLE或敗血症的患者中評估了PIK3CA表現量(表4和表5)。結果顯示出與健康對照組相比，未經治療的AOSD患者中PIK3CA表達明顯更高(圖10c)，顯示出PIK3CA在AOSD中具有潛在的致病作用。相反地，與健康對照組相比，其中RA和SLE患者中PIK3CA的表現量較低，敗血症患者中PIK3CA的表達量則沒有顯著差異。有趣的是，在AOSD患者中PIK3CA的表達量僅與MIAT表現量呈正相關，而在RA、SLE或敗血症中則無相關性(圖10d)。 Tests using A-scores also differentiated RA and SLE patients from the AOSD group, with AUCs of 0.829 and 0.881, respectively, and higher cutoff values for detecting RA and SLE (12.57 and 11.39, respectively) (Figures 10a-10b). Given that no blood samples were available from sepsis patients, microarray data from the sepsis cohort GSE28750 (from NCBI's GEO database) were reanalyzed. In GSE28750, the expression data of lncRNA MIAT could be retrieved, but the value of THRIL could not be retrieved. The results showed that the relative expression of MIAT was significantly higher in the sepsis blood samples than in the controls, unlike the results in AOSD, RA or SLE (Fig. 1a and Figs. 9c-9e). Furthermore, PIK3CA expression was assessed in healthy or patients with AOSD, RA, SLE or sepsis (Tables 4 and 5). The results showed that PIK3CA expression was significantly higher in untreated AOSD patients compared with healthy controls (Fig. 10c), suggesting a potential pathogenic role of PIK3CA in AOSD. Conversely, PIK3CA expression was lower in RA and SLE patients compared with healthy controls, but there was no significant difference in PIK3CA expression in sepsis patients. Interestingly, PIK3CA expression was only positively correlated with MIAT expression in AOSD patients, but not in RA, SLE or sepsis (Fig. 10d).

表4.健康或患有AOSD、RA或SLE的患者中PIK3CA表達(△CT)。

Figure 109119409-A0202-12-0023-6
Table 4. PIK3CA expression (ΔCT) in healthy or patients with AOSD, RA or SLE.
Figure 109119409-A0202-12-0023-6

表5.PIK3CA與健康人和敗血症患者的相對表現量。

Figure 109119409-A0202-12-0024-7
Table 5. Relative expression of PIK3CA to healthy and sepsis patients.
Figure 109119409-A0202-12-0024-7

<110> 中國醫藥大學 <110> China Medical University

<120> 診斷及分型成人發作型史迪兒症之方法 <120> Methods for the diagnosis and classification of adult-onset Still's disease

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Figure 109119409-A0202-12-0031-23

Claims (8)

一種檢測個體罹患成人發作型史笛兒氏症的方法，該方法包括以下步驟：(a)提供一血液樣本和一周邊血液單核細胞；(b)檢測該血液樣本中一蛋白質生物標誌物之表現量，其中該蛋白質生物標幟物係為IL-18；檢測該周邊血液單核細胞中一長鏈非編碼核糖核酸生物標誌物的表現量，其中該長鏈非編碼核糖核酸生物標誌物為MIAT或THRIL；(c)將步驟(b)所得偵測到的IL-18、MIAT和THRIL的表現量以一預測函數計算出一A分數，其中該預測函數係由一多元迴歸分析(multiple regression analysis)得到；以及(d)將步驟(c)所計算的該A分數與一臨界值比較，其中該臨界值係透過接收器操作員特徵(Receiver Operator Characteristic，ROC)方法獲得，其中該臨界值對應於ROC曲線下的面積(the area under an ROC curve，AUC)達到最大值，其中A分數高於該臨界值則代表該個體罹患成人發作型史笛兒氏症，其中該預測函數係為A分數=1.62 *THRIL △CT-1.43 *MIAT △CT+0.02 * IL-18(pg/ml)。 A method of detecting that an individual suffers from adult-onset Stubbs' disease, the method comprising the steps of: (a) providing a blood sample and a peripheral blood mononuclear cell; (b) detecting a protein biomarker in the blood sample Expression level, wherein the protein biomarker is IL-18; detecting the expression level of a long-chain non-coding RNA biomarker in the peripheral blood mononuclear cells, wherein the long-chain non-coding RNA biomarker is MIAT or THRIL; (c) calculating an A-score by applying a predictive function to the detected expression levels of IL-18, MIAT and THRIL obtained in step (b), wherein the predictive function is performed by a multiple regression analysis (multiple regression analysis) regression analysis); and (d) comparing the A-score calculated in step (c) with a threshold, wherein the threshold is obtained by a receiver operator characteristic (ROC) method, wherein the threshold The value corresponds to the area under the ROC curve (the area under an ROC curve, AUC) reaching the maximum value, wherein the A-score higher than the critical value represents that the individual suffers from adult-onset Stubbs disease, wherein the prediction function is A-score=1.62*THRILΔCT-1.43*MIATΔCT+0.02*IL-18(pg/ml). 如申請專利範圍第1項所述之方法，其中該臨界值範圍為5.85至7.12之間。 The method as described in item 1 of the claimed scope, wherein the threshold range is between 5.85 and 7.12. 如申請專利範圍第1項所述之方法，進一步檢測該周邊血液單核細胞中一PIK3CA的基因表現量，其中該PIK3CA基因表現量高於一健康個體時則該個體被排除患有系統性紅斑狼瘡、類風濕性關節炎或敗血症。 According to the method described in item 1 of the scope of the application, the expression level of a PIK3CA gene in the peripheral blood mononuclear cells is further detected, and when the expression level of the PIK3CA gene is higher than that of a healthy individual, the individual is excluded from systemic erythema Lupus, rheumatoid arthritis, or sepsis. 如申請專利範圍第1項所述之方法，其中該健康個體係為未罹患一風濕疾病的個體。 The method of claim 1, wherein the healthy individual system is an individual who does not suffer from a rheumatic disease. 如申請專利範圍第1項所述之方法，其中該血液樣本係為全血、血清或血漿。 The method of claim 1, wherein the blood sample is whole blood, serum or plasma. 一種檢測一罹患成人發作型史笛兒氏症的個體的疾病病程的方法，該方法包括以下步驟：(a)提供一血液樣本和一周邊血液單核細胞，其中該血液樣本和該周邊血液單核細胞係由一罹患成人發作型史笛兒氏症的個體中收集而來；(b)檢測該血液樣本中一蛋白質生物標誌物之表現量，其中該蛋白質生物標幟物係為TNF-α；檢測該周邊血液單核細胞中一長鏈非編碼核糖核酸生物標誌物的表現量，其中該長鏈非編碼核糖核酸生物標誌物為NTT； (c)將步驟(b)所得偵測到的TNF-α和NTT的表現量以一預測函數計算出一B分數，其中該預測函數係由一多元迴歸分析(multiple regression analysis)得到；以及(d)將步驟(c)所計算的該B分數與一臨界值比較，其中該臨界值係透過接收器操作員特徵(Receiver Operator Characteristic，ROC)方法獲得，其中該臨界值對應於ROC曲線下的面積(the area under an ROC curve，AUC)達到最大值，其中B分數高於該臨界值則代表該罹患成人發作型史笛兒氏症的個體疾病病程為一系統性亞型或是一關節炎亞型，其中該罹患成人發作型史笛兒氏症的個體係經由申請專利範圍第1項之方法判斷的個體，且該預測函數係為B分數=0.22 * NTT △CT-0.01 * TNF-α(pg/ml)。 A method of detecting the disease course of an individual suffering from adult-onset Stubbs disease, the method comprising the steps of: (a) providing a blood sample and a peripheral blood mononuclear cell, wherein the blood sample and the peripheral blood mononuclear cell The nuclear cell line is collected from an individual with adult-onset Stilt's disease; (b) the blood sample is detected for the expression of a protein biomarker, wherein the protein biomarker is TNF-α ; detect the expression of a long-chain non-coding ribonucleic acid biomarker in the peripheral blood mononuclear cells, wherein the long-chain non-coding ribonucleic acid biomarker is NTT; (c) calculating a B-score using a predictive function of the detected expression levels of TNF-α and NTT obtained in step (b), wherein the predictive function is obtained by a multiple regression analysis; and (d) comparing the B-score calculated in step (c) with a threshold, wherein the threshold is obtained by a receiver operator characteristic (ROC) method, wherein the threshold corresponds to under the ROC curve The area under an ROC curve (AUC) reaches the maximum value, where the B-score higher than the cut-off value indicates that the disease course of the individual with adult-onset Stubbs is a systemic subtype or a joint inflammatory subtype, wherein the individual system of the adult-onset Stubbs syndrome is determined by the method of claim 1 of the scope of application, and the prediction function is B-score=0.22 * NTT △CT-0.01 * TNF- alpha (pg/ml). 如申請專利範圍第6項所述之方法，其中該臨界值範圍為0.17至0.83之間。 The method as described in item 6 of the claimed scope, wherein the threshold range is between 0.17 and 0.83. 如申請專利範圍第6項所述之方法，其中該血液樣本係為全血、血清或血漿。 The method of claim 6, wherein the blood sample is whole blood, serum or plasma.
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