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. 2018 Apr 23:2018:7305380.
doi: 10.1155/2018/7305380. eCollection 2018.

MicroRNA Expression Profiling in Psoriatic Arthritis

Andrea Pelosi  1 , Claudio Lunardi  2 , Piera Filomena Fiore  1 , Elisa Tinazzi  2 , Giuseppe Patuzzo  2 , Giuseppe Argentino  2 , Francesca Moretta  2 , Antonio Puccetti  1   3 , Marzia Dolcino  2
Affiliations

MicroRNA Expression Profiling in Psoriatic Arthritis

Andrea Pelosi et al. Biomed Res Int. .

Abstract

Background: Psoriatic arthritis (PsA) is an inflammatory arthritis, characterized by bone erosions and new bone formation. MicroRNAs (miRNAs) are key regulators of the immune responses. Differential expression of miRNAs has been reported in several inflammatory autoimmune diseases; however, their role in PsA is not fully elucidated. We aimed to identify miRNA expression signatures associated with PsA and to investigate their potential implication in the disease pathogenesis.

Methods: miRNA microarray was performed in blood cells of PsA patients and healthy controls. miRNA pathway analyses were performed and the global miRNA profiling was combined with transcriptome data in PsA. Deregulation of selected miRNAs was validated by real-time PCR.

Results: We identified specific miRNA signatures associated with PsA patients with active disease. These miRNAs target pathways relevant in PsA, such as TNF, MAPK, and WNT signaling cascades. Network analysis revealed several miRNAs regulating highly connected genes within the PsA transcriptome. miR-126-3p was the most downregulated miRNA in active patients. Noteworthy, miR-126 overexpression induced a decreased expression of genes implicated in PsA.

Conclusions: This study sheds light on some epigenetic aspects of PsA identifying specific miRNAs, which may represent promising candidates as biomarkers and/or for the design of novel therapeutic strategies in PsA.

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Figures

Figure 1
Figure 1
Overlap of deregulated miRNAs in active and nonactive PsA patients. Venn diagram representing the overlap between significantly deregulated miRNAs in PsA active and in nonactive patients. Deregulated miRNAs belonging to the three subsets identified as “PsA only active,” “PsA common,” and “PsA only nonactive” are listed.
Figure 2
Figure 2
Pathway enrichment analysis for deregulated miRNAs in PsA. (a) Histograms representing enrichment p values for selected KEGG pathways obtained by DIANA-miRPath v.3 software analysis. Functional analyses were conducted for the PsA only active, PsA only nonactive, and PsA common miRNA list. Overrepresentation statistical analysis was performed for the union of targeted genes by miRNA lists (“Genes Union” option) based on TARBASE 7.0. (b) Enrichment analysis comparison between miRNA subsets for the KEGG pathway “proteoglycans in cancer.” Enrichment p value, number of genes targeted (#genes), and number of miRNAs (#miRNAs) for each subset are shown.
Figure 3
Figure 3
Comparison of deregulated miRNAs target genes with PsA-associated transcriptional profiles. (a) Pie chart showing percentages of DEGs in PsA from [8] not targeted or targeted by PsA only active and PsA common deregulated miRNAs. DEGs targeted by two or more miRNAs with different modulation in PsA (up- and downmodulated) are defined as “targeting: both opposite and concordant.” (b) Protein-protein interaction (PPI) network of DEGs in PsA patients (from [8]). (c) Modules originated from the interaction network. Genes targeted by deregulated miRNAs are highlighted in red.
Figure 4
Figure 4
Heat-map of biological processes and deregulated miRNAs in PsA. The heat-map shows the percentage of genes targeted by PsA only active miRNAs in the GO biological processes selected. The miRNAs are ordered for the absolute values of fold change according to the microarray analysis.
Figure 5
Figure 5
Validation of differentially expressed miRNAs by real-time PCR. (a) Real-time PCR for the indicated miRNAs were performed in healthy controls (Healthy), PsA active, and nonactive samples included in the microarray and in 7 patients affected by RA. (b) Real-time PCR for miR-126-3p in an expanded cohort of healthy (15 patients), PsA active (11 patients), and PsA nonactive (12 patients) groups. Values are calculated with ΔCt method. miR-16-5p and miR-26a-5p were used as endogenous controls for miRNA expression (see Methods). Histograms indicate mean values; bars indicate standard deviation (SD). ∗p ≤ 0.05; ∗∗p ≤ 0.01; ∗∗∗p ≤ 0.001 (Mann–Whitney rank sum test). (c) Real-time PCR expression of miR-126-3p in Jurkat cells after 48 h from transfection with miRNA mimics. miR-16-5p and miR-26a-5p were used as endogenous controls. (d) Identification of novel miR-126-3p targets. Real-time PCR expression of the indicated transcripts in mimic miR-126-3p-transfected and control cells. Beta-Actin was used as endogenous control. Values were calculated with ΔΔCt method as fold change with respect to mimic negative control-transfected samples. All the histograms indicate mean values of at least three independent experiments; bars indicate standard deviation (SD). ∗p ≤ 0.05; ∗∗p ≤ 0.01; ∗∗∗p ≤ 0.001 (Student's t-test).
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