RNA‐Seq data analysis identifies the comprehensive profile of in vivo interferon‐β‐stimulated genes in multiple sclerosis

Abstract

Objectives Interferon‐beta (IFNβ) is the most widely used drug for reducing the disease activity of multiple sclerosis (MS), although a considerable population of MS patients are refractory to IFNβ. To establish personalized therapy for MS, the molecular mechanism underlying the therapeutic effects of IFNβ in MS should be thoroughly characterized by aid of next‐generation sequencing technology. Methods To elucidate a comprehensive profile of in vivo IFNβ‐stimulated genes (ISGs) in MS patients, we analyzed a RNA sequencing (RNA‐Seq) dataset numbered SRP045500, composed of the genome‐wide transcriptome of whole blood and purified populations of CD4+ T cells, B cells, and monocytes isolated from MS patients at the time‐point before and 24 h after the first treatment with IFNβ1a. Results We identified a set of 914 in vivo ISGs, containing a number of non‐coding RNAs and pseudogenes, along with differential spliced genes in the whole blood of MS patients. The set of 914 ISGs were relevant to the molecular pathways defined as “interferon signaling” and “proteasome,” and were closely associated with gene ontology terms of antiviral and immune responses. We also identified 640, 653 and 1018 ISGs from CD4+ T cells, B cells, and monocytes of MS patients receiving IFNβ treatment, respectively, and extracted 95 genes shared among the three cell types as the core set of ISGs. They included 78 genes that might serve as the most consistent blood biomarkers for assessment of the immediate early in vivo response to IFNβ treatment in MS. Conclusions RNA‐Seq data analysis promotes us to characterize the comprehensive profile of in vivo ISGs in MS patients receiving IFNβ treatment.

Single cell RNA sequencing identifies an early monocyte gene signature in acute respiratory distress syndrome

“…Our findings are further supported by the finding that SOCS3 deficiency in Ly6C + myeloid cells enhances experimental LPS-induced acute lung injury (53). Given that the genes GBP1, IFI44L, IFITM1, and ISG20 -found to be differentially upregulated in the monocytes of ARDS patients, particularly in the CD16 + subsetare known to be type I IFN inducible (35), it appears that SOCS3 deficiency in the monocytes of ARDS patients renders them more responsive to circulating levels of type I IFNs than to increased IL-6-mediated IFN-γ-like signaling. Similar expression of GBP2 (54), GABARAP (36), and LYN (55) in the monocytes of the 2 groups of subjects, genes typically associated with IFN-γ signaling, suggests absence of enhanced response to IFN-γ in the monocytes of ARDS patients.…”

“…Expression of GBP1 -which encodes a member of the family of guanylate-binding proteins (GBPs), with functions in host defense (33,34) was expressed at a higher level in CD16 + monocytes, and the expression of multiple ISGs was also higher in the cells of ARDS patients (Figure 4). Treatment of human monocytes with IFN-β was previously shown to upregulate genes such as GBP1, IFITs, and IFI44L (35). Some of these IFN-target genes (GBP1, IFITM1) were found to be preferentially upregulated in CD16 + monocytes.…”

A four-lncRNA signature for predicting prognosis of recurrence patients with gastric cancer

“…lncRNA C21orf62-AS1 is abnormally expressed in chromophobe renal cell carcinoma, correlating with OS of patients [ 33 ]. Additionally, C21orf62-AS is stimulated by interferon-beta in patients with multiple sclerosis [ 34 ]. lncRNA MIR99AHG is significantly downregulated in colorectal cancer [ 35 ].…”

Ribonucleic acid sequencing data mining: A new tool for understanding neuroimmunological conditions

“…Two studies recently published in the journal, Clinical and Experimental Neuroimmunology, might provide answers to these questions. 4,5 Using various bioinformatics tools, Satoh et al found previously unknown molecular networks or key molecules relevant to neuroimmunology research.…”

“…Two studies recently published in the journal, Clinical and Experimental Neuroimmunology , might provide answers to these questions . Using various bioinformatics tools, Satoh et al.…”