Microarray analysis of circulating micro RNAs in the serum of patients with polymyositis and dermatomyositis reveals a distinct disease expression profile and is associated with disease activity

Clin Exp Rheumatol. Jan-Feb 2016;34(1):17-24. Epub 2015 Nov 17.

Abstract

Objectives: The aim of this study was a large scale investigation of myositis-associated circulating miRNA molecules and also determination of expression of these candidate molecules in relation to clinical activity of myositis.

Methods: RNA, containing also miRNAs, was isolated from sera of 28 patients suffering from idiopathic inflammatory myopathies (IIM) and 16 healthy controls. Expression of miRNAs was determined using a miRNA microarray method. Statistical analysis of miRNA expression was carried out using Arraystar software.

Results: Our results showed 23 significantly differentially expressed miRNAs. Six miRNAs were differentially expressed in IIM compared to healthy controls. In dermatomyositis (DM) we found 3 and in polymyositis (PM) 6 differentially expressed miRNAs compared to controls. Three miRNAs were up-regulated in patients with highly active disease compared to patients with low disease activity. Furthermore, we found 26 significantly differentially expressed miRNAs in SLE patients compared to IIM, DM and PM patients.

Conclusions: This is the first study that comprehensively describes expression levels of circulating miRNAs in serum of patients suffering from IIM. It can be expected that some of these deregulated miRNA molecules are involved in aetiology of IIM and may potentially serve as molecular markers for IIM development or for monitoring of disease activity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Case-Control Studies
  • Dermatomyositis / blood
  • Dermatomyositis / genetics*
  • Female
  • Gene Expression Profiling / methods*
  • Gene Expression Regulation
  • Genetic Markers
  • Genetic Predisposition to Disease
  • Humans
  • Male
  • MicroRNAs / blood
  • MicroRNAs / genetics*
  • Middle Aged
  • Oligonucleotide Array Sequence Analysis*
  • Phenotype
  • Predictive Value of Tests
  • Severity of Illness Index
  • Software

Substances

  • Genetic Markers
  • MicroRNAs