Background: Methotrexate (MTX) is the first line treatment for rheumatoid arthritis (RA), but failure of satisfying treatment response occurs in a significant proportion of patients. Here we present a longitudinal multi-omics study aimed at detecting molecular and cellular processes in peripheral blood associated with a successful methotrexate treatment of rheumatoid arthritis.
Methods: Eighty newly diagnosed patients with RA underwent clinical assessment and donated blood before initiation of MTX, and 3 months into treatment. Flow cytometry was used to describe cell types and presence of activation markers in peripheral blood, the expression of 51 proteins was measured in serum or plasma, and RNA sequencing was performed in peripheral blood mononuclear cells (PBMC). Response to treatment after 3 months was determined using the EULAR response criteria. We assessed the changes in biological phenotypes during treatment, and whether these changes differed between responders and non-responders with regression analysis. By using measurements from baseline, we also tried to find biomarkers of future MTX response or, alternatively, to predict MTX response.
Results: Among the MTX responders, (Good or Moderate according to EULAR treatment response classification, n = 60, 75%), we observed changes in 29 partly overlapping cell types proportions, levels of 13 proteins and expression of 38 genes during treatment. These changes were in most cases suppressions that were stronger among responders compared to non-responders. Within responders to treatment, we observed a suppression of FOXP3 gene expression, reduction of immunoglobulin gene expression and suppression of genes involved in cell proliferation. The proportion of many HLA-DR expressing T-cell populations were suppressed in all patients irrespective of clinical response, and the proportion of many IL21R+ T-cells were reduced exclusively in non-responders. Using only the baseline measurements we could not detect any biomarkers or prediction models that could predict response to MTX.
Conclusion: We conclude that a deep molecular and cellular phenotyping of peripheral blood cells in RA patients treated with methotrexate can reveal previously not recognized differences between responders and non-responders during 3 months of treatment with MTX. This may contribute to the understanding of MTX mode of action and explain non-responsiveness to MTX therapy.
Objective: This study aimed to analyze potential biomarkers for systemic sclerosis (SSc) by constructing lncRNA–miRNA–mRNA networks in circulating exosomes (cirexos).
Materials and methods: Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) in SSc cirexos were screened using high-throughput sequencing and detected with real-time quantitative PCR (RT-qPCR). Differentially expressed genes (DEGs) were analyzed using the DisGeNET, GeneCards, GSEA4.2.3, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Receiver operating characteristic (ROC) curves, correlation analyses, and a double-luciferase reporter gene detection assay were used to analyze competing endogenous RNA (ceRNA) networks and clinical data.
Results: In this study, 286 DEmRNAs and 192 DElncRNAs were screened, of which 18 DEGs were the same as the SSc-related genes. The main SSc-related pathways included extracellular matrix (ECM) receptor interaction, local adhesion, platelet activation, and IgA production by the intestinal immune network. A hub gene, COL1A1, was obtained by a protein–protein interaction (PPI) network. Four ceRNA networks were predicted through Cytoscape. The relative expression levels of COL1A1, ENST0000313807, and NON-HSAT194388.1 were significantly higher in SSc, while the relative expression levels of hsa-miR-29a-3p, hsa-miR-29b-3p, and hsa-miR-29c-3p were significantly lower in SSc (P < 0.05). The ROC curve showed that the ENST00000313807-hsa-miR-29a-3p-COL1A1 network as a combined biomarker of SSc is more valuable than independent diagnosis, and that it is correlated with high-resolution CT (HRCT), Scl-70, C-reactive protein (CRP), Ro-52, IL-10, IgM, lymphocyte percentage, neutrophil percentage, albumin divided by globulin, urea, and RDW-SD (P < 0.05). Double-luciferase reporter gene detection showed that ENST00000313807 interacts with hsa-miR-29a-3p, which interacts with COL1A1.
Conclusion: The ENST00000313807-hsa-miR-29a-3p-COL1A1 network in plasma cirexos represents a potential combined biomarker for the clinical diagnosis and treatment of SSc.
Frontiers in Microbiology
Developments in Campylobacter, Helicobacter & Related Organisms Research – CHRO 2019