FEBS Open Bio · 2020 · 34 citations · 19 references
Life SciencesBioinformaticsMolecular BiologyApoptosisGene ExpressionRheumatologyAutoimmune Rheumatic DiseasesAutophagy In DiseaseNoncoding Rna BiologyNoncoding Rna TranscriptomicsRheumatoid ArthritisRna Sequencing AnalysisBiomarkersLong Non-coding Rna BiomarkersLong Noncoding Rna ProfilingNon-coding Rna CharacterizationNon-coding Rna ProfilingNoncoding Rna In ApoptosisRna SequencingRna Sequencing (Rna-seq)
Long noncoding RNAs (lncRNAs) are >200-bp molecules that do not generally code for proteins. Human lncRNAs have well-characterized roles in gene expression regulation, particularly with regard to protein-coding genes, and their dysregulation has been linked to disease. Here, we set out to investigate changes in the expression of lncRNAs related to apoptosis and autophagy in the peripheral blood mononuclear cells (PBMCs) of rheumatoid arthritis (RA). In addition, we aimed to correlate lncRNA expression profiles with clinical indexes and self-perception of patients (SPP). To this end, we employed RNA sequencing of lncRNAs in PBMCs from three patients with RA and three healthy controls. We used bioinformatics to screen several dysregulated lncRNAs related to apoptosis and autophagy. To validate key lncRNA candidates, we performed quantitative reverse transcriptase-PCR on 20 patients with RA and 20 healthy controls. We found the expression of seven lncRNAs (MAPKAPK5-AS1, ENST00000619282, C5orf17, LINC01189, LINC01006, DSCR9 and MIR22HG) was significantly altered in PBMCs of patients with RA. Receiver operating characteristic curve analysis suggested that MIR22HG [area under the curve (AUC) = 0.846, P = 0.000], DSCR9 (AUC = 0.783, P = 0.005), LINC01189 (AUC = 0.677, P = 0.034), MAPKAPK5-AS1 (AUC = 0.644, P = 0.025) and ENST00000619282 (AUC = 0.636, P = 0.043) are potential biomarkers of RA. Spearman's correlation analysis revealed selected lncRNAs correlated with clinical indexes and SPP. Therefore, we highlight that some lncRNAs related to apoptosis and autophagy may serve as potential biomarkers for diagnosis and monitoring of RA progression, which also correlate with several clinical indexes and SPP.
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