miRNAs in multiple sclerosis
miRNA profiles accurately differentiate patients from healthy controls
Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. In this study, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using the human miRNA Geniom Biochip and the Geniom RT Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly deregulated in patients with RRMS as compared to healthy controls.
Experimental setup
5 ml blood was collected from study subjects in PAXgene Blood RNA tubes (BD, Franklin Lakes, New Jersey USA). Total RNA was extracted from blood cells using the miRNeasy Mini Kit (Qiagen GmbH, Hilden, Germany) and stored at -70°C. Samples were analyzed using the Geniom Real Time Analyzer (GRTA, febit GmbH, Heidelberg, Germany) and the Geniom Biochip miRNA homo sapiens. Each array contains 7 replicates of 866 miRNAs and miRNA star sequences as annotated in the Sanger miRBase 12.0. Sample labeling with biotine was carried out by microfluidic-based enzymatic on-chip labelling of miRNAs (MPEA).
Results
Figure 1: Barplots detailing the intensity values for the miRNAs hsa-miR-145 (a), hsa-mir-186 (b), and hsa-miR-20b (c). MS sera are indicated by red bars, control sera are indicated by green bars.
Conclusion
The data presented in this study demonstrates that miRNA profiles differentiate patients with MS from healthy subjects with high accuracy, indicating that miRNAs have the potential to serve as blood-based diagnostic biomarkers for RRMS. It has been shown that miRNA expression patterns, rather than single miRNAs, can serve as biomarker signatures for the detection of human diseases such as MS, applying a non-invasive blood test.
Besides the potential role of miRNAs as biomarkers for RRMS, the finding of deregulated miRNA expression in patients with MS suggests that the disease process of MS may result in altered miRNA expression profiles or that deregulation of miRNAs may contribute to the disease process of MS.
Figure 2:
Boxplot of the classification results (left).
The blue boxes show the classification accuracy, specificity and sensitivity over the repeated cross-validation, the red boxes for permutation test, for a subset of 48 miRNAs. Classification results reached an accuracy of 96.3%, a specificity of 95%, and a sensitivity of 97.6%.
Exemplarily classification result (right).
Logarithm of the quotient of the probability to be an MS sample and the probability to be a control sample for each control (C) and each MS (M) sample is given on the y-axis. If this quotient is greater than one (thus, the logarithm greater zero) the sample is more likely to be an MS sample than a control sample.
Figure 3: Multiple Sclerosis Network.
This network indicates diseases by yellow nodes and miRNAs by red nodes. The network is restricted to the miRNAs significant for MS. Most of the miRNAs are associated with MS but not with other diseases, indicated by the red circles in the right part of this figure.