系统性硬化症肺部病变的临床分析和生物标志物的初步研究
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摘要
目的
(1)寻找与系统性硬化病(systemic sclerosis, SSc)合并肺动脉高压(pulmonary arterial hypertension, PAH)相关的临床危险因素,为SSc-PAH的早期诊断、病情评估和预后判断提供新的依据；(2)筛选并验证与SSc合并肺间质病变(interstitial lung disease, ILD)相关的外周血microRNA标志物；(3)筛选与SSc-PAH及SSc-ILD相关的血清蛋白标志物。
方法
(1)收集北京协和医院门诊及住院SSc患者的临床资料和实验室检查结果,应用右心导管确定PAH的诊断,将患者分为SSc-PAH组和SSc-nonPAH组,应用二元logistic回归分析和相关性分析寻找与SSc-PAH相关的危险因素；(2)收集在北京协和医院风湿免疫科和皮肤科门诊就诊的SSc患者的临床资料和外周血标本,通过microRNA芯片筛选和扩大样本实时定量PCR验证,寻找与SSc-ILD相关血浆和外周血单个核细胞(PBMC)的microRNA标志物,并通过生物信息学分析初步确定受其调控的相应靶基因；(3)通过血清蛋白芯片筛选与SSc肺部病变(包括肺间质病变和肺动脉高压)相关的血清蛋白标志物。
结果
(1)与未合并PAH的患者相比,SSc-PAH组胃食管返流症状(60%vs.36%,P<0.05)、指端溃疡(52%vs.31%,P<0.05)和毛细血管扩张症(64%vs.38%,P<0.05)发生率更高,血清IgA水平显著升高(36%vs.16%,P<0.05),而抗RNP抗体、抗SSA抗体和抗SSB抗体的阳性率亦高(分别为60%vs.18%,36%vs.18%,16%vs.4%,P<0.05),但抗Scl-70抗体阳性率更低(8%vs.50%,P<0.05),肺功能检查中FVC%、FEV1%、TLCO%和TLCO/VA%减少患者的比例在SSc-PAH组显著增多(分别为65%vs.34%,65%vs.37%,100%vs.74%,100%vs.60%,P<0.05),而FVC%/TLCO%比值在这组人群中显著升高(1.934"0.67vs.1.29±0.29,P<0.05)。二元logistic回归分析显示胃食管返流、毛细血扩张症、IgA升高、抗RNP抗体阳性、FVC%/TLCO%比值升高是SSc患者合并PAH的独立危险因素。
(2)通过5例SSc患者及3例健康志愿者外周血microRNA芯片筛查,最终获得了25个差异表达的microRNA(7个上调,18个下调)。经生物信息学分析,挑选5条可能与ILD或SSc发病机制相关的microRNA (has-miR-29b、has-miR-320a、has-miR-320b、has-miR-320c和has-miR-423-5p),在30例SSc患者和16例健康志愿者中进行qPCR验证。结果显示miR-320a、miR-320b及miR-423-5p在SSc组的血浆中下调(RQ值分别为0.58±0.36vs.1.12±0.66,0.67±0.27vs.1.44±1.08,0.744±0.47vs.1.38.4±1.00,P<0.05),而miR-29、miR-320a、miR-320b及miR-423-5p在SSc-ILD患者的外周血甲.个核细胞(PBMC)中表达量均显著下调(RQ值分别为0.43±0.14vs.1.03±0.65,0.48±0.22vs.0.92±0.48,0.31±0.18vs.0.83±0.59,0.32±0.14vs.0.95±0.66,P<0.05),但在无ILD的SSc患者中其表达量与健康志愿者组无显著差异。相关性分析显示发现血浆和PBMC中的某些microRNA(血浆中的miR-320a合PBMC中的miR-29b、miR-320a, miR-320b, miR-320c以及miR-423-5p)部调与SSc合并指端溃疡有关(相关系数分别为0.603,0.436,0.547,0.470,0.728以及0.513,P<0.05),而血浆中miR-320b表达量升高与SSc合并毛细血管扩张相关(相关系数为0.527,P<0.05)。
(3)通过15例SSc及5例健康志愿者外周血血清样本的蛋白质芯片筛查,获得了12个在SSc中差异表达的细胞因了,其中GDNF, IL-26, TRA-1-81, Calcitonin, SRMS, Aldolase A表达上调,Fibronectin, Serpin A5, Chordin-Like2, Serpin A1, Serpin A4, C3a表达下调。对比SSc-PAH和SSc-ILD患者的血清蛋白质表达谱,发现在SSc-PAH中IL-17D,RYK, IL-13R alpha I, CD97, Fyn表达上调,而在SSc-ILD患者中NETI, Netrin G2, Galanin表达上调。
结论
(1)SSc患者的某些临床症状、血清学和肺功能指标是其合并PAH的危险因索,对于此类患者进一步行有创性血流动力学检查(右心导管)可能有助于早期诊断并改善预后;(2)SSc患者血浆和PBMC中存在着多种microRNA的差异性表达,并可能与SSc不同器官受累相关：(3)SSc患者血清中存在多种细胞因子的差异性表达,并可能与其合并ILD和PAH存在相关性。
Objective
(1) We researched on some clinical risk factors which were correlated with pulmonary arterial hypertensions (PAHs) in systemic sclerosis (SSc), in order to make an early diagnosis and evaluation of SSc and to predict the prognosis in these patients;(2) We screened and verified the peripheral blood microRNA markers in SSc patients with interstitial lung diseases (ILDs);(3) We screened the serum protein spectrum of SSc patients with PAHs or ILDs.
Method
(1) We collected the clinical records and lab results of SSc patients in clinics and hospitalized patients in Pekin Union Medical College Hospital (PUMCH). Then we used right heart catheterization results to decide the PAH diagnosis, deviding the patients into two groups of SSc-PAH group and SSc-nonPAH group. According to the data, we used binary logistic regression and relative analysis to analyze them in order to find out the risk factors of SSc-PAH.(2) We collected the clinical records and blood samples of SSc patients in clinics and hospitalized patients in PUMCH. We screened the microRNA spectrum in these patients'peripheral blood and verified these results using real time PCR in a larger sample number. According to the statistic analysis, we found out the microRNA markers related to SSc-ILD in both plasma samples and peripheral blood mononuclear cells (PBMCs). Then, we did bioinformatics analysis to predict the target genes.(3) We screened the serum protein spectrum in a group of SSc patients with or without PAH and ILD, so as to find out the related biomarkers.
Result
(1) In the analysis of clinical features, we found out some items related with PAH in SSc, which were the presence of gastroesophageal refluxes (60%vs.36%, P<0.05), digital ulcers (52%vs.31%, P<0.05) and telangiectasias (64%vs.38%, P<0.05), the positivity of anti-RNP antibodies, anti-SSA antibodies and anti-SSB antibodies (respectively60%vs.18%,36%vs.18%,16%vs.4%, P<0.05), the negativity of anti-Scl-70antibodies (8%vs.50%, P<0.05), the decrease of FVC%predicted, FEV1% predicted, TLCO%predicted and TLCO/VA%predicted (respectively65%vs.34%,65%vs.37%,100%vs.74%,100%vs.60%,P<0.05), and the increase of the calculated ratio of FVC%predicted and TLCO%predicted (1.93±0.67vs.1.29±0.29, P<0.05). After the logistic regression, we found five risk factors of PAH in SSc, which were the presence of gastroesophageal refluxes and telangiectasias, the elevation of IgA levels, the positivity of anti-RNP antibodies, and the increase in the calculated ratio of FVC%predicted and TLCO%predicted.
(2) In the microRNA microarray analysis, we got25differential expressed microRNA, including7up-regulated and18down-regulated ones in five SSc patients versus three healthy people. In these25microRNAs, we picked out five ones with possibilities of participations in SSc pathogenesis, which were has-miR-29b, has-miR-320a, has-miR-320b, has-miR-320c and has-miR-423-5p.Then the real time PCR results of these five microRNAs in30SSc patients versus16healthy people were as follows:in plasma, miR-320a, miR-320b and miR-423-5p were significantly down-regulated (RQs are respectively0.58±0.36vs.1.12±0.66,0.67±0.27vs.1.44±1.08,0.74±0.47vs.1.38±1.00, P<0.05), while the rest two had tendencies of down-regulation; in peripheral blood mononuclear cells (PBMCs), there were significant down-regulations of miR-29b, miR-320a, miR-320b and miR-423-5p in SSc patients with ILD (0.43±0.14vs.1.03±0.65,0.48±0.22vs.0.92±0.48,0.31±0.18vs.0.83±0.59,0.32±0.14vs.0.95±0.66, P<0.05), and a tendency of down-regulation of miR-320c; In correlation analysis, some microRNAs (miR-320a in plasma; miR-29b, miR-320a, miR-320b, miR-320c and miR-423-5p in PBMC) levels in both plasma and PBMCs showed correlations with the presence of digital ulcers (relative coefficients respectively0.603,0.436,0.547,0.470,0.728and0.513,P<0.05), and miR-320b level (relative coefficient=0.527,P<0.05) in plasma showed a correlation with the presence of telangiectasias.
(3) In the serum protein microarray analysis in15SSc patients versus5healthy people, we got12differential expressed cytokins, with six ones up-regulated (GDNF, IL-26, TRA-1-81, Calcitonin, SRMS, Aldolase A) and six ones down-regulated (Fibronectin, Serpin A5, Chordin-Like2, Serpin Al, Serpin A4, C3a).Compared the SSc patients with PAH and those without, we found out five cytokins up-regulated, which were IL-17D, RYK, IL-13R alpha l, CD97and Fyn. Compared the SSc patients with ILD and those without, we found out three cytokins up-regulated, which were NET1, Netrin G2and Galanin.
Conclusion
(1) We found out some clinical features and laboratory results useful in the prediction of PAH in SSc, which would be the basis for making decisions of invasive exams;(2) We found out some differential expressed microRNAs in peripheral blood, which may be correlated with distinct organ involvements in SSc patients;(3) We screened out some serum cytokins which may be correlated with pulmonary diseases in SSc patients, including PAHs and ILDs.
(1)寻找与系统性硬化病(systemic sclerosis, SSc)合并肺动脉高压(pulmonary arterial hypertension, PAH)相关的临床危险因素,为SSc-PAH的早期诊断、病情评估和预后判断提供新的依据；(2)筛选并验证与SSc合并肺间质病变(interstitial lung disease, ILD)相关的外周血microRNA标志物；(3)筛选与SSc-PAH及SSc-ILD相关的血清蛋白标志物。
方法
(1)收集北京协和医院门诊及住院SSc患者的临床资料和实验室检查结果,应用右心导管确定PAH的诊断,将患者分为SSc-PAH组和SSc-nonPAH组,应用二元logistic回归分析和相关性分析寻找与SSc-PAH相关的危险因素；(2)收集在北京协和医院风湿免疫科和皮肤科门诊就诊的SSc患者的临床资料和外周血标本,通过microRNA芯片筛选和扩大样本实时定量PCR验证,寻找与SSc-ILD相关血浆和外周血单个核细胞(PBMC)的microRNA标志物,并通过生物信息学分析初步确定受其调控的相应靶基因；(3)通过血清蛋白芯片筛选与SSc肺部病变(包括肺间质病变和肺动脉高压)相关的血清蛋白标志物。
结果
(1)与未合并PAH的患者相比,SSc-PAH组胃食管返流症状(60%vs.36%,P<0.05)、指端溃疡(52%vs.31%,P<0.05)和毛细血管扩张症(64%vs.38%,P<0.05)发生率更高,血清IgA水平显著升高(36%vs.16%,P<0.05),而抗RNP抗体、抗SSA抗体和抗SSB抗体的阳性率亦高(分别为60%vs.18%,36%vs.18%,16%vs.4%,P<0.05),但抗Scl-70抗体阳性率更低(8%vs.50%,P<0.05),肺功能检查中FVC%、FEV1%、TLCO%和TLCO/VA%减少患者的比例在SSc-PAH组显著增多(分别为65%vs.34%,65%vs.37%,100%vs.74%,100%vs.60%,P<0.05),而FVC%/TLCO%比值在这组人群中显著升高(1.934"0.67vs.1.29±0.29,P<0.05)。二元logistic回归分析显示胃食管返流、毛细血扩张症、IgA升高、抗RNP抗体阳性、FVC%/TLCO%比值升高是SSc患者合并PAH的独立危险因素。
(2)通过5例SSc患者及3例健康志愿者外周血microRNA芯片筛查,最终获得了25个差异表达的microRNA(7个上调,18个下调)。经生物信息学分析,挑选5条可能与ILD或SSc发病机制相关的microRNA (has-miR-29b、has-miR-320a、has-miR-320b、has-miR-320c和has-miR-423-5p),在30例SSc患者和16例健康志愿者中进行qPCR验证。结果显示miR-320a、miR-320b及miR-423-5p在SSc组的血浆中下调(RQ值分别为0.58±0.36vs.1.12±0.66,0.67±0.27vs.1.44±1.08,0.744±0.47vs.1.38.4±1.00,P<0.05),而miR-29、miR-320a、miR-320b及miR-423-5p在SSc-ILD患者的外周血甲.个核细胞(PBMC)中表达量均显著下调(RQ值分别为0.43±0.14vs.1.03±0.65,0.48±0.22vs.0.92±0.48,0.31±0.18vs.0.83±0.59,0.32±0.14vs.0.95±0.66,P<0.05),但在无ILD的SSc患者中其表达量与健康志愿者组无显著差异。相关性分析显示发现血浆和PBMC中的某些microRNA(血浆中的miR-320a合PBMC中的miR-29b、miR-320a, miR-320b, miR-320c以及miR-423-5p)部调与SSc合并指端溃疡有关(相关系数分别为0.603,0.436,0.547,0.470,0.728以及0.513,P<0.05),而血浆中miR-320b表达量升高与SSc合并毛细血管扩张相关(相关系数为0.527,P<0.05)。
(3)通过15例SSc及5例健康志愿者外周血血清样本的蛋白质芯片筛查,获得了12个在SSc中差异表达的细胞因了,其中GDNF, IL-26, TRA-1-81, Calcitonin, SRMS, Aldolase A表达上调,Fibronectin, Serpin A5, Chordin-Like2, Serpin A1, Serpin A4, C3a表达下调。对比SSc-PAH和SSc-ILD患者的血清蛋白质表达谱,发现在SSc-PAH中IL-17D,RYK, IL-13R alpha I, CD97, Fyn表达上调,而在SSc-ILD患者中NETI, Netrin G2, Galanin表达上调。
结论
(1)SSc患者的某些临床症状、血清学和肺功能指标是其合并PAH的危险因索,对于此类患者进一步行有创性血流动力学检查(右心导管)可能有助于早期诊断并改善预后;(2)SSc患者血浆和PBMC中存在着多种microRNA的差异性表达,并可能与SSc不同器官受累相关：(3)SSc患者血清中存在多种细胞因子的差异性表达,并可能与其合并ILD和PAH存在相关性。
Objective
(1) We researched on some clinical risk factors which were correlated with pulmonary arterial hypertensions (PAHs) in systemic sclerosis (SSc), in order to make an early diagnosis and evaluation of SSc and to predict the prognosis in these patients;(2) We screened and verified the peripheral blood microRNA markers in SSc patients with interstitial lung diseases (ILDs);(3) We screened the serum protein spectrum of SSc patients with PAHs or ILDs.
Method
(1) We collected the clinical records and lab results of SSc patients in clinics and hospitalized patients in Pekin Union Medical College Hospital (PUMCH). Then we used right heart catheterization results to decide the PAH diagnosis, deviding the patients into two groups of SSc-PAH group and SSc-nonPAH group. According to the data, we used binary logistic regression and relative analysis to analyze them in order to find out the risk factors of SSc-PAH.(2) We collected the clinical records and blood samples of SSc patients in clinics and hospitalized patients in PUMCH. We screened the microRNA spectrum in these patients'peripheral blood and verified these results using real time PCR in a larger sample number. According to the statistic analysis, we found out the microRNA markers related to SSc-ILD in both plasma samples and peripheral blood mononuclear cells (PBMCs). Then, we did bioinformatics analysis to predict the target genes.(3) We screened the serum protein spectrum in a group of SSc patients with or without PAH and ILD, so as to find out the related biomarkers.
Result
(1) In the analysis of clinical features, we found out some items related with PAH in SSc, which were the presence of gastroesophageal refluxes (60%vs.36%, P<0.05), digital ulcers (52%vs.31%, P<0.05) and telangiectasias (64%vs.38%, P<0.05), the positivity of anti-RNP antibodies, anti-SSA antibodies and anti-SSB antibodies (respectively60%vs.18%,36%vs.18%,16%vs.4%, P<0.05), the negativity of anti-Scl-70antibodies (8%vs.50%, P<0.05), the decrease of FVC%predicted, FEV1% predicted, TLCO%predicted and TLCO/VA%predicted (respectively65%vs.34%,65%vs.37%,100%vs.74%,100%vs.60%,P<0.05), and the increase of the calculated ratio of FVC%predicted and TLCO%predicted (1.93±0.67vs.1.29±0.29, P<0.05). After the logistic regression, we found five risk factors of PAH in SSc, which were the presence of gastroesophageal refluxes and telangiectasias, the elevation of IgA levels, the positivity of anti-RNP antibodies, and the increase in the calculated ratio of FVC%predicted and TLCO%predicted.
(2) In the microRNA microarray analysis, we got25differential expressed microRNA, including7up-regulated and18down-regulated ones in five SSc patients versus three healthy people. In these25microRNAs, we picked out five ones with possibilities of participations in SSc pathogenesis, which were has-miR-29b, has-miR-320a, has-miR-320b, has-miR-320c and has-miR-423-5p.Then the real time PCR results of these five microRNAs in30SSc patients versus16healthy people were as follows:in plasma, miR-320a, miR-320b and miR-423-5p were significantly down-regulated (RQs are respectively0.58±0.36vs.1.12±0.66,0.67±0.27vs.1.44±1.08,0.74±0.47vs.1.38±1.00, P<0.05), while the rest two had tendencies of down-regulation; in peripheral blood mononuclear cells (PBMCs), there were significant down-regulations of miR-29b, miR-320a, miR-320b and miR-423-5p in SSc patients with ILD (0.43±0.14vs.1.03±0.65,0.48±0.22vs.0.92±0.48,0.31±0.18vs.0.83±0.59,0.32±0.14vs.0.95±0.66, P<0.05), and a tendency of down-regulation of miR-320c; In correlation analysis, some microRNAs (miR-320a in plasma; miR-29b, miR-320a, miR-320b, miR-320c and miR-423-5p in PBMC) levels in both plasma and PBMCs showed correlations with the presence of digital ulcers (relative coefficients respectively0.603,0.436,0.547,0.470,0.728and0.513,P<0.05), and miR-320b level (relative coefficient=0.527,P<0.05) in plasma showed a correlation with the presence of telangiectasias.
(3) In the serum protein microarray analysis in15SSc patients versus5healthy people, we got12differential expressed cytokins, with six ones up-regulated (GDNF, IL-26, TRA-1-81, Calcitonin, SRMS, Aldolase A) and six ones down-regulated (Fibronectin, Serpin A5, Chordin-Like2, Serpin Al, Serpin A4, C3a).Compared the SSc patients with PAH and those without, we found out five cytokins up-regulated, which were IL-17D, RYK, IL-13R alpha l, CD97and Fyn. Compared the SSc patients with ILD and those without, we found out three cytokins up-regulated, which were NET1, Netrin G2and Galanin.
Conclusion
(1) We found out some clinical features and laboratory results useful in the prediction of PAH in SSc, which would be the basis for making decisions of invasive exams;(2) We found out some differential expressed microRNAs in peripheral blood, which may be correlated with distinct organ involvements in SSc patients;(3) We screened out some serum cytokins which may be correlated with pulmonary diseases in SSc patients, including PAHs and ILDs.
引文
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19. Pilewski JM, Liu L, Henry AC, Knauer AV, Feghali-Bostwick CA. Insulin-like growth factor binding proteins 3 and 5 are overexpressed in idiopathic pulmonary fibrosis and contribute to extracellular matrix deposition. Am J Pathol. Feb 2005;166(2):399-407.
20. Wynn TA, Ramalingam TR. Mechanisms of fibrosis:therapeutic translation for fibrotic disease. Nat Med. Jul 2012;18(7):1028-1040.
21. Bowen T, Jenkins RH, Fraser DJ. MicroRNAs, transforming growth factor beta-1, and tissue fibrosis. J Pathol. Jan 2013;229(2):274-285.
22. Chen SY, Wang Y, Telen MJ, Chi JT. The genomic analysis of erythrocyte microRNA expression in sickle cell diseases. PLoS One.2008;3(6):e2360.
23. Dai Y, Sui W, Lan H, Yan Q, Huang H, Huang Y. Comprehensive analysis of microRNA expression patterns in renal biopsies of lupus nephritis patients. Rheumatol Int. May 2009;29(7):749-754.
24. Sharbati J, Lewin A, Kutz-Lohroff B, Kamal E, Einspanier R, Sharbati S. Integrated microRNA-mRNA-analysis of human monocyte derived macrophages upon Mycobacterium avium subsp. hominissuis infection. PLoS One.2011;6(5):e20258.
25. Villa C, Ridolfi E, Fenoglio C, et al. Expression of the Transcription Factor Spl and its Regulatory hsa-miR-29b in Peripheral Blood Mononuclear Cells from Patients with Alzheimer's Disease. J Alzheimers Dis. Jan 12013;35(3):487-494.
26. Feng B, Chakrabarti S. miR-320 Regulates Glucose-Induced Gene Expression in Diabetes. ISRN Endocrinol.2012;2012:549875.
27. Lin J, Huang S, Wu S, et al. MicroRNA-423 promotes cell growth and regulates G(1)/S transition by targeting p21Cip1/Waf1 in hepatocellular carcinoma. Carcinogenesis. Nov 2011;32(11):1641-1647.
28. Smith RA, Jedlinski DJ, Gabrovska PN, Weinstein SR, Haupt L, Griffiths LR. A genetic variant located in miR-423 is associated with reduced breast cancer risk. Cancer Genomics Proteomics. May-Jun 2012;9(3):115-118.
29. Li H, Yang R, Fan X, et al. MicroRNA array analysis of microRNAs related to systemic scleroderma. Rheumatol Int. Feb 2012;32(2):307-313.
30. Zhu H, Li Y, Qu S, et al. MicroRNA expression abnormalities in limited cutaneous scleroderma and diffuse cutaneous scleroderma. J Clin Immunol. Jun 2012;32(3):514-522.
31. Maurer B, Stanczyk J, Jungel A, et al. MicroRNA-29, a key regulator of collagen expression in systemic sclerosis. Arthritis Rheum. Jun 2010;62(6):1733-1743.
32. Luo Y, Wang Y, Wang Q, Xiao R, Lu Q. Systemic sclerosis:genetics and epigenetics. J Autoimmun. Mar 2013;41:161-167.
33. Hor S, Pirzer H, Dumoutier L, et al. The T-cell lymphokine interleukin-26 targets epithelial cells through the interleukin-20 receptor 1 and interleukin-10 receptor 2 chains. J Biol Chem. Aug 6 2004;279(32):33343-33351.
34. Hikami K, Ehara Y, Hasegawa M, et al. Association of IL-10 receptor 2 (IL10RB) SNP with systemic sclerosis. Biochem Biophys Res Commun. Aug 29 2008;373(3):403-407.
35. Salim PH, Jobim M, Bredemeier M, et al. Interleukin-10 gene promoter and NFKB1 promoter insertion/deletion polymorphisms in systemic sclerosis. Scand J Immunol. Feb 2013;77(2):162-168.
36. Schneider M, Lohmann J, Krummenerl T, Gerlach U. Concentration of fibronectin and granulocyte elastase in plasma of patients with systemic connective-tissue diseases. IntJ Tissue React.1987;9(4):355-359.
37. Barnes TC, Cross A, Anderson ME, Edwards SW, Moots RJ. Relative alpha(1)-anti-trypsin deficiency in systemic sclerosis. Rheumatology (Oxford). Aug 2011;50(8):1373-1378.
38. Shirahama R, Miyazaki Y, Okamoto T, Inase N, Yoshizawa Y. Proteome analysis of bronchoalveolar lavage fluid in lung fibrosis associated with systemic sclerosis. Allergol Int. Dec 2010;59(4):409-415.
39. Postiglione L, Montuori N, Riccio A, et al. The plasminogen activator system in fibroblasts from systemic sclerosis. Int J Immunopathol Pharmacol. Jul-Sep 2010;23(3):891-900.
40. Del Rosso A, Distler 0, Milia AF, et al. Increased circulating levels of tissue kallikrein in systemic sclerosis correlate with microvascular involvement. Ann Rheum Dis. Mar 2005;64(3):382-387.
41. Lorda-Diez Cl, Montero JA, Rodriguez-Leon J, Garcia-Porrero JA, Hurle JM. Expression and functional study of extracellular BMP antagonists during the morphogenesis of the digits and their associated connective tissues. PLoS One.2013;8(4):e60423.
42. Wild G, Watkins J, Ward AM, Hughes P, Hume A, Rowell NR. Complement activation in systemic sclerosis. J Clin Lab Immunol. Jan 1990;31(1):39-41.
43. Toledano C, Gain M, Kettaneh A, et al. Aldolase predicts subsequent myopathy occurrence in systemic sclerosis. Arthritis Res Ther.2012;14(3):R152.
44. Hsu E, Shi H, Jordan RM, Lyons-Weiler J, Pilewski JM, Feghali-Bostwick CA. Lung tissues in patients with systemic sclerosis have gene expression patterns unique to pulmonary fibrosis and pulmonary hypertension. Arthritis Rheum. Mar 2011;63(3):783-794.
45. Ambrosi A, Espinosa A, Wahren-Herlenius M. IL-17:a new actor in IFN-driven systemic autoimmune diseases. EurJ Immunol. Sep 2012;42(9):2274-2284.
46. Bailey JR, Bland PW, Tarlton JF, et al. IL-13 promotes collagen accumulation in Crohn's disease fibrosis by down-regulation of fibroblast MMP synthesis:a role for innate lymphoid cells? PLoS One.2012;7(12):e52332.
47. Gourh P, Arnett FC, Assassi S, et al. Plasma cytokine profiles in systemic sclerosis:associations with autoantibody subsets and clinical manifestations. Arthritis Res Ther.2009;11(5):R147.
1. Choi AM, Ryter SW, Levine B. Autophagy in human health and disease. N Engl J Med. Feb 14 2013;368(7):651-662.
2. Martelli AM, Evangelisti C, Chiarini F, et al. The emerging role of the phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin signaling network in normal myelopoiesis and leukemogenesis. Biochim Biophys Acta. Sep 2010;1803(9):991-1002.
3. Kroemer G, Marino G, Levine B. Autophagy and the integrated stress response. Mol Cell. Oct 22 2010;40(2):280-293.
4. Hilscher M, Hernandez-Gea V, Friedman SL. Autophagy and mesenchymal cell fibrogenesis. Biochim Biophys Acta. Nov 9 2012.
5. Hamasaki M, Yoshimori T. Where do they come from? Insights into autophagosome formation. FEBS Lett. Apr 2 2010;584(7):1296-1301.
6. Xie Z, Klionsky DJ. Autophagosome formation:core machinery and adaptations. Nat Cell Biol. Oct 2007;9(10):1102-1109.
7. Del Principe D, Lista P, Malorni W, Giammarioli AM. Fibroblast autophagy in fibrotic disorders. J Pathol. Jan 2013;229(2):208-220.
8. Rubinsztein DC. The roles of intracellular protein-degradation pathways in neurodegeneration. Nature. Oct 19 2006;443(7113):780-786.
9. Jin SM, Youle RJ. PINK1- and Parkin-mediated mitophagy at a glance. J Cell Sci. Feb 15 2012;125(Pt4):795-799.
10. Narendra DP, Youle RJ. Targeting mitochondrial dysfunction:role for PINK1 and Parkin in mitochondrial quality control. Antioxid Redox Signal. May 15 2011;14(10):1929-1938.
11. Green DR, Galluzzi L, Kroemer G. Mitochondria and the autophagy-inflammation-cell death axis in organismal aging. Science. Aug 26 2011;333(6046):1109-1112.
12. Kraft C, Deplazes A, Sohrmann M, Peter M. Mature ribosomes are selectively degraded upon starvation by an autophagy pathway requiring the Ubp3p/Bre5p ubiquitin protease. Nat Cell Biol. May 2008;10(5):602-610.
13. Kim PK, Hailey DW, Mullen RT, Lippincott-Schwartz J. Ubiquitin signals autophagic degradation of cytosolic proteins and peroxisomes. Proc Natl Acad Sci U S A. Dec 30 2008;105(52):20567-20574.
14. Bernales S, McDonald KL, Walter P. Autophagy counterbalances endoplasmic reticulum expansion during the unfolded protein response. PLoS Biol. Nov 2006;4(12):e423.
15. Johansen T, Lamark T. Selective autophagy mediated by autophagic adapter proteins. Autophagy. Mar 2011;7(3):279-296.
16. Klionsky DJ, Abdalla FC, Abeliovich H, et al. Guidelines for the use and interpretation of assays for monitoring autophagy. Autophagy. Apr 2012;8(4):445-544.
17. Kirisako T, Ichimura Y, Okada H, et al. The reversible modification regulates the membrane-binding state of Apg8/Aut7 essential for autophagy and the cytoplasm to vacuole targeting pathway. J Cell Biol. Oct 16 2000;151(2):263-276.
18. Feldman ME, Apsel B, Uotila A, et al. Active-site inhibitors of mTOR target rapamycin-resistant outputs of mTORC1 and mTORC2. PLoS Biol. Feb 10 2009;7(2):e38.
19. Datta SR, Dudek H, Tao X, et al. Akt phosphorylation of BAD couples survival signals to the cell-intrinsic death machinery. Cell. Oct 17 1997;91(2):231-241.
20. Petiot A, Ogier-Denis E, Blommaart EF, Meijer AJ, Codogno P. Distinct classes of phosphatidylinositol 3'-kinases are involved in signaling pathways that control macroautophagy in HT-29 cells. J Biol Chem. Jan 14 2000;275(2):992-998.
21. Amalinei C, Caruntu ID, Giusca SE, Balan RA. Matrix metalloproteinases involvement in pathologic conditions. Rom J Morphol Embryol.2010;51 (2):215-228.
22. Jacob M, Chang L, Pure E. Fibroblast activation protein in remodeling tissues. Curr Mol Med. Dec 2012; 12(10):1220-1243.
23. Galluzzi L, Vanden Berghe T, Vanlangenakker N, et al. Programmed necrosis from molecules to health and disease. Int Rev Cell Mol Biol.2011;289:1-35.
24. Gilmore AP. Anoikis. Cell Death Differ. Nov 2005;12 Suppl 2:1473-1477.
25. Overholtzer M, Mailleux AA, Mouneimne G, et al. A nonapoptotic cell death process, entosis, that occurs by cell-in-cell invasion. Cell. Nov 302007;131(5):966-979.
26. Klionsky DJ. Autophagy:from phenomenology to molecular understanding in less than a decade. Nat Rev Mol Cell Biol. Nov 2007;8(11):931-937.
27. Nishiyama J, Matsuda K, Kakegawa W, et al. Reevaluation of neurodegeneration in lurcher mice: constitutive ion fluxes cause cell death with, not by, autophagy. J Neurosci. Feb 10 2010;30(6):2177-2187.
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19. Pilewski JM, Liu L, Henry AC, Knauer AV, Feghali-Bostwick CA. Insulin-like growth factor binding proteins 3 and 5 are overexpressed in idiopathic pulmonary fibrosis and contribute to extracellular matrix deposition. Am J Pathol. Feb 2005;166(2):399-407.
20. Wynn TA, Ramalingam TR. Mechanisms of fibrosis:therapeutic translation for fibrotic disease. Nat Med. Jul 2012;18(7):1028-1040.
21. Bowen T, Jenkins RH, Fraser DJ. MicroRNAs, transforming growth factor beta-1, and tissue fibrosis. J Pathol. Jan 2013;229(2):274-285.
22. Chen SY, Wang Y, Telen MJ, Chi JT. The genomic analysis of erythrocyte microRNA expression in sickle cell diseases. PLoS One.2008;3(6):e2360.
23. Dai Y, Sui W, Lan H, Yan Q, Huang H, Huang Y. Comprehensive analysis of microRNA expression patterns in renal biopsies of lupus nephritis patients. Rheumatol Int. May 2009;29(7):749-754.
24. Sharbati J, Lewin A, Kutz-Lohroff B, Kamal E, Einspanier R, Sharbati S. Integrated microRNA-mRNA-analysis of human monocyte derived macrophages upon Mycobacterium avium subsp. hominissuis infection. PLoS One.2011;6(5):e20258.
25. Villa C, Ridolfi E, Fenoglio C, et al. Expression of the Transcription Factor Spl and its Regulatory hsa-miR-29b in Peripheral Blood Mononuclear Cells from Patients with Alzheimer's Disease. J Alzheimers Dis. Jan 12013;35(3):487-494.
26. Feng B, Chakrabarti S. miR-320 Regulates Glucose-Induced Gene Expression in Diabetes. ISRN Endocrinol.2012;2012:549875.
27. Lin J, Huang S, Wu S, et al. MicroRNA-423 promotes cell growth and regulates G(1)/S transition by targeting p21Cip1/Waf1 in hepatocellular carcinoma. Carcinogenesis. Nov 2011;32(11):1641-1647.
28. Smith RA, Jedlinski DJ, Gabrovska PN, Weinstein SR, Haupt L, Griffiths LR. A genetic variant located in miR-423 is associated with reduced breast cancer risk. Cancer Genomics Proteomics. May-Jun 2012;9(3):115-118.
29. Li H, Yang R, Fan X, et al. MicroRNA array analysis of microRNAs related to systemic scleroderma. Rheumatol Int. Feb 2012;32(2):307-313.
30. Zhu H, Li Y, Qu S, et al. MicroRNA expression abnormalities in limited cutaneous scleroderma and diffuse cutaneous scleroderma. J Clin Immunol. Jun 2012;32(3):514-522.
31. Maurer B, Stanczyk J, Jungel A, et al. MicroRNA-29, a key regulator of collagen expression in systemic sclerosis. Arthritis Rheum. Jun 2010;62(6):1733-1743.
32. Luo Y, Wang Y, Wang Q, Xiao R, Lu Q. Systemic sclerosis:genetics and epigenetics. J Autoimmun. Mar 2013;41:161-167.
33. Hor S, Pirzer H, Dumoutier L, et al. The T-cell lymphokine interleukin-26 targets epithelial cells through the interleukin-20 receptor 1 and interleukin-10 receptor 2 chains. J Biol Chem. Aug 6 2004;279(32):33343-33351.
34. Hikami K, Ehara Y, Hasegawa M, et al. Association of IL-10 receptor 2 (IL10RB) SNP with systemic sclerosis. Biochem Biophys Res Commun. Aug 29 2008;373(3):403-407.
35. Salim PH, Jobim M, Bredemeier M, et al. Interleukin-10 gene promoter and NFKB1 promoter insertion/deletion polymorphisms in systemic sclerosis. Scand J Immunol. Feb 2013;77(2):162-168.
36. Schneider M, Lohmann J, Krummenerl T, Gerlach U. Concentration of fibronectin and granulocyte elastase in plasma of patients with systemic connective-tissue diseases. IntJ Tissue React.1987;9(4):355-359.
37. Barnes TC, Cross A, Anderson ME, Edwards SW, Moots RJ. Relative alpha(1)-anti-trypsin deficiency in systemic sclerosis. Rheumatology (Oxford). Aug 2011;50(8):1373-1378.
38. Shirahama R, Miyazaki Y, Okamoto T, Inase N, Yoshizawa Y. Proteome analysis of bronchoalveolar lavage fluid in lung fibrosis associated with systemic sclerosis. Allergol Int. Dec 2010;59(4):409-415.
39. Postiglione L, Montuori N, Riccio A, et al. The plasminogen activator system in fibroblasts from systemic sclerosis. Int J Immunopathol Pharmacol. Jul-Sep 2010;23(3):891-900.
40. Del Rosso A, Distler 0, Milia AF, et al. Increased circulating levels of tissue kallikrein in systemic sclerosis correlate with microvascular involvement. Ann Rheum Dis. Mar 2005;64(3):382-387.
41. Lorda-Diez Cl, Montero JA, Rodriguez-Leon J, Garcia-Porrero JA, Hurle JM. Expression and functional study of extracellular BMP antagonists during the morphogenesis of the digits and their associated connective tissues. PLoS One.2013;8(4):e60423.
42. Wild G, Watkins J, Ward AM, Hughes P, Hume A, Rowell NR. Complement activation in systemic sclerosis. J Clin Lab Immunol. Jan 1990;31(1):39-41.
43. Toledano C, Gain M, Kettaneh A, et al. Aldolase predicts subsequent myopathy occurrence in systemic sclerosis. Arthritis Res Ther.2012;14(3):R152.
44. Hsu E, Shi H, Jordan RM, Lyons-Weiler J, Pilewski JM, Feghali-Bostwick CA. Lung tissues in patients with systemic sclerosis have gene expression patterns unique to pulmonary fibrosis and pulmonary hypertension. Arthritis Rheum. Mar 2011;63(3):783-794.
45. Ambrosi A, Espinosa A, Wahren-Herlenius M. IL-17:a new actor in IFN-driven systemic autoimmune diseases. EurJ Immunol. Sep 2012;42(9):2274-2284.
46. Bailey JR, Bland PW, Tarlton JF, et al. IL-13 promotes collagen accumulation in Crohn's disease fibrosis by down-regulation of fibroblast MMP synthesis:a role for innate lymphoid cells? PLoS One.2012;7(12):e52332.
47. Gourh P, Arnett FC, Assassi S, et al. Plasma cytokine profiles in systemic sclerosis:associations with autoantibody subsets and clinical manifestations. Arthritis Res Ther.2009;11(5):R147.
1. Choi AM, Ryter SW, Levine B. Autophagy in human health and disease. N Engl J Med. Feb 14 2013;368(7):651-662.
2. Martelli AM, Evangelisti C, Chiarini F, et al. The emerging role of the phosphatidylinositol 3-kinase/Akt/mammalian target of rapamycin signaling network in normal myelopoiesis and leukemogenesis. Biochim Biophys Acta. Sep 2010;1803(9):991-1002.
3. Kroemer G, Marino G, Levine B. Autophagy and the integrated stress response. Mol Cell. Oct 22 2010;40(2):280-293.
4. Hilscher M, Hernandez-Gea V, Friedman SL. Autophagy and mesenchymal cell fibrogenesis. Biochim Biophys Acta. Nov 9 2012.
5. Hamasaki M, Yoshimori T. Where do they come from? Insights into autophagosome formation. FEBS Lett. Apr 2 2010;584(7):1296-1301.
6. Xie Z, Klionsky DJ. Autophagosome formation:core machinery and adaptations. Nat Cell Biol. Oct 2007;9(10):1102-1109.
7. Del Principe D, Lista P, Malorni W, Giammarioli AM. Fibroblast autophagy in fibrotic disorders. J Pathol. Jan 2013;229(2):208-220.
8. Rubinsztein DC. The roles of intracellular protein-degradation pathways in neurodegeneration. Nature. Oct 19 2006;443(7113):780-786.
9. Jin SM, Youle RJ. PINK1- and Parkin-mediated mitophagy at a glance. J Cell Sci. Feb 15 2012;125(Pt4):795-799.
10. Narendra DP, Youle RJ. Targeting mitochondrial dysfunction:role for PINK1 and Parkin in mitochondrial quality control. Antioxid Redox Signal. May 15 2011;14(10):1929-1938.
11. Green DR, Galluzzi L, Kroemer G. Mitochondria and the autophagy-inflammation-cell death axis in organismal aging. Science. Aug 26 2011;333(6046):1109-1112.
12. Kraft C, Deplazes A, Sohrmann M, Peter M. Mature ribosomes are selectively degraded upon starvation by an autophagy pathway requiring the Ubp3p/Bre5p ubiquitin protease. Nat Cell Biol. May 2008;10(5):602-610.
13. Kim PK, Hailey DW, Mullen RT, Lippincott-Schwartz J. Ubiquitin signals autophagic degradation of cytosolic proteins and peroxisomes. Proc Natl Acad Sci U S A. Dec 30 2008;105(52):20567-20574.
14. Bernales S, McDonald KL, Walter P. Autophagy counterbalances endoplasmic reticulum expansion during the unfolded protein response. PLoS Biol. Nov 2006;4(12):e423.
15. Johansen T, Lamark T. Selective autophagy mediated by autophagic adapter proteins. Autophagy. Mar 2011;7(3):279-296.
16. Klionsky DJ, Abdalla FC, Abeliovich H, et al. Guidelines for the use and interpretation of assays for monitoring autophagy. Autophagy. Apr 2012;8(4):445-544.
17. Kirisako T, Ichimura Y, Okada H, et al. The reversible modification regulates the membrane-binding state of Apg8/Aut7 essential for autophagy and the cytoplasm to vacuole targeting pathway. J Cell Biol. Oct 16 2000;151(2):263-276.
18. Feldman ME, Apsel B, Uotila A, et al. Active-site inhibitors of mTOR target rapamycin-resistant outputs of mTORC1 and mTORC2. PLoS Biol. Feb 10 2009;7(2):e38.
19. Datta SR, Dudek H, Tao X, et al. Akt phosphorylation of BAD couples survival signals to the cell-intrinsic death machinery. Cell. Oct 17 1997;91(2):231-241.
20. Petiot A, Ogier-Denis E, Blommaart EF, Meijer AJ, Codogno P. Distinct classes of phosphatidylinositol 3'-kinases are involved in signaling pathways that control macroautophagy in HT-29 cells. J Biol Chem. Jan 14 2000;275(2):992-998.
21. Amalinei C, Caruntu ID, Giusca SE, Balan RA. Matrix metalloproteinases involvement in pathologic conditions. Rom J Morphol Embryol.2010;51 (2):215-228.
22. Jacob M, Chang L, Pure E. Fibroblast activation protein in remodeling tissues. Curr Mol Med. Dec 2012; 12(10):1220-1243.
23. Galluzzi L, Vanden Berghe T, Vanlangenakker N, et al. Programmed necrosis from molecules to health and disease. Int Rev Cell Mol Biol.2011;289:1-35.
24. Gilmore AP. Anoikis. Cell Death Differ. Nov 2005;12 Suppl 2:1473-1477.
25. Overholtzer M, Mailleux AA, Mouneimne G, et al. A nonapoptotic cell death process, entosis, that occurs by cell-in-cell invasion. Cell. Nov 302007;131(5):966-979.
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