SFP-48 – Pathologie osseuse et rhumatologie – Anakinra dans la forme systémique d’arthrite juvénile idiopathique

Quartier, Pierre; Allantaz, Florence; Cimaz, Rolando; Pillet, P.; Desjonquères, Marine; Richer, Olivier; Duquesne, Agnès; Lemelle, I.; Koné‐Paut, Isabelle; Neven, B.; Bardin, Christophe; Dimet, Isabelle; Bienvenu, Jacques; Boutten, Anne; Bossuyt, Xavier; Messiaen, Claude; Ménoni, Véronique; Mogenet, Agnès; Tréluyer, J.M.; Bresson, J.L.; Landais, Paul; Pascual, Virginia

doi:10.1016/s0929-693x(08)72115-8

Cited by 1 publication

(1 citation statement)

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“…To identify DEGs significantly related to sJIA, the GSE17590, GSE80060, and GSE112057 gene expression datasets were acquired from the Gene Expression Omnibus database (https://www.ncbi.nlm.nih.gov/geo/) (Quartier et al, 2011;Brachat et al, 2017;Mo et al, 2018). The data were derived from the GPL6106 (Sentrix Human-6 v2 Expression BeadChip), GPL570 (Affymetrix Human Genome U133 Plus 2.0 Array), and GPL11154 (Illumina HiSeq 2000 (Homo sapiens)) platforms.…”

Section: Microarray Datamentioning

confidence: 99%

Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis

Zhang

Dai

Zhao

et al. 2021

Front. Mol. Biosci.

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Systemic juvenile idiopathic arthritis (sJIA) is a rare and serious type of JIA characterized by an unknown etiology and atypical manifestations in the early stage, and early diagnosis and effective treatment are needed. We aimed to identify diagnostic biomarkers, immune cells and pathways involved in sJIA pathogenesis as well as potential treatment targets. The GSE17590, GSE80060, and GSE112057 gene expression profiles from the Gene Expression Omnibus (GEO) database were screened to obtain differentially expressed genes (DEGs) between sJIA and healthy controls. Common DEGs were subjected to pathway enrichment analysis; a protein-protein interaction network was constructed, and hub genes were identified. In addition, functional annotation of hub genes was performed with GenCLiP2. Immune infiltration analysis was then conducted with xCell, and correlation analysis between immune cells and the enriched pathways identified from gene set variation analysis was performed. The Connectivity Map database was used to identify candidate molecules for treating sJIA patients. Finally, quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was carried out, and the GEO dataset GSE8361 was applied for validation of hub gene expression levels in blood samples from healthy individuals with sJIA. A total of 73 common DEGs were identified, and analysis indicated enrichment of neutrophil and platelet functions and the MAPK pathway in sJIA. Six hub genes were identified, of which three had high diagnostic sensitivity and specificity; ARG1 and PGLYRP1 were validated by qRT-PCR and microarray data of the GSE8361 dataset. We found that increased megakaryocytes and decreased Th1 cells correlated positively and negatively with the MAPK pathway, respectively. Furthermore, MEK inhibitors and some kinase inhibitors of the MAPK family were identified as candidate agents for sJIA treatment. Our results indicate two candidate markers for sJIA diagnosis and reveal the important roles of platelets and the MAPK pathway in the pathogenesis of sJIA, providing a new perspective for exploring potential molecular targets for sJIA treatment.

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Section: Microarray Datamentioning

confidence: 99%