Steen Samantha O, Iversen Line V, Carlsen Anting Liu, Burton Mark, Nielsen Christoffer T, Jacobsen Søren, Heegaard Niels H H
From the Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut; Department of Dermatology, Bispebjerg Hospital, and the Department of Rheumatology, Rigshospitalet, University of Copenhagen, Copenhagen; Department of Clinical Genetics, and the Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense; Research Unit of Human Genetics, and Clinical Biochemistry, Institute of Clinical Research, University of Southern Denmark, Odense, Denmark.S.O. Steen, MSc; A.L. Carlsen, PhD, Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut; L.V. Iversen, MD, PhD, Department of Dermatology, Bispebjerg Hospital, University of Copenhagen; M. Burton, PhD, Department of Clinical Genetics, Odense University Hospital, and the Institute of Clinical Research, Research Unit of Human Genetics, University of Southern Denmark; C.T. Nielsen, MD, PhD; S. Jacobsen, MD, DMedSc, Department of Rheumatology, Rigshospitalet, University of Copenhagen; N.H.H. Heegaard, MD, DMedSc, DNatSc, Department of Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, and the Department of Clinical Biochemistry and Pharmacology, Odense University Hospital, and the Institute of Clinical Research, Clinical Biochemistry, University of Southern Denmark.
J Rheumatol. 2015 Feb;42(2):214-21. doi: 10.3899/jrheum.140502. Epub 2014 Nov 15.
To evaluate the expression profile of cell-free circulating microRNA (miRNA) in systemic sclerosis (SSc), healthy controls (HC), and systemic lupus erythematosus (SLE).
Total RNA was purified from plasma and 45 different, mature miRNA were measured using quantitative PCR assays after reverse transcription. Samples (n = 189) were from patients with SSc (n = 120), SLE (n = 29), and from HC (n = 40). Expression data were clustered by principal components analysis, and diagnostically specific miRNA profiles were developed by leave-one-out cross-validation. Diagnostic probability scores were derived from stepwise logistic regression.
Thirty-seven miRNA specificities were consistently detected and 26 of these were unaffected by SSc sample age and present in more than two-thirds of SSc samples. SSc cases showed a distinct expression profile with 14/26 miRNA significantly decreased (false discovery rate < 0.05) and 5/26 increased compared with HC. A 21-miRNA classifier gave optimum accuracy (80%) for discriminating SSc from both HC and SLE. The discrimination between HC and SSc (95% accuracy) was strongly driven by miRNA of the 17 ∼ 92 cluster and by miR-16, -223, and -638, while SLE and SSc differed mainly in the expression of miR-142-3p, -150, -223, and -638. Except for a weak correlation between anti-Scl-70 and miR-638 (p = 0.048), there were no correlations with other patient variables.
Circulating miRNA profiles are characteristic for SSc compared with both HC and SLE cases. Some of the predicted targets of the differentially regulated miRNA are of relevance for transforming growth factor-β signaling and fibrosis, but need to be validated in independent studies.
评估系统性硬化症(SSc)、健康对照(HC)和系统性红斑狼疮(SLE)中无细胞循环微小RNA(miRNA)的表达谱。
从血浆中纯化总RNA,逆转录后使用定量PCR测定法测量45种不同的成熟miRNA。样本(n = 189)来自SSc患者(n = 120)、SLE患者(n = 29)和HC(n = 40)。通过主成分分析对表达数据进行聚类,并通过留一法交叉验证建立诊断特异性miRNA谱。诊断概率得分来自逐步逻辑回归。
一致检测到37种miRNA特异性,其中26种不受SSc样本年龄影响且存在于超过三分之二的SSc样本中。与HC相比,SSc病例显示出独特的表达谱,26种miRNA中有14种显著降低(错误发现率<0.05),5种增加。一个21-miRNA分类器在区分SSc与HC和SLE时具有最佳准确性(80%)。HC和SSc之间的区分(95%准确性)主要由17∼92簇的miRNA以及miR-16、-223和-638驱动,而SLE和SSc主要在miR-142-3p、-150、-223和-638的表达上有所不同。除了抗Scl-70与miR-638之间存在弱相关性(p = 0.048)外,与其他患者变量无相关性。
与HC和SLE病例相比,循环miRNA谱是SSc的特征。差异调节的miRNA的一些预测靶标与转化生长因子-β信号传导和纤维化相关,但需要在独立研究中进行验证。