Cargando…
Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis
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...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316978/ https://www.ncbi.nlm.nih.gov/pubmed/34336925 http://dx.doi.org/10.3389/fmolb.2021.681526 |
_version_ | 1783729981085450240 |
---|---|
author | Zhang, Min Dai, Rongxin Zhao, Qin Zhou, Lina An, Yunfei Tang, Xuemei Zhao, Xiaodong |
author_facet | Zhang, Min Dai, Rongxin Zhao, Qin Zhou, Lina An, Yunfei Tang, Xuemei Zhao, Xiaodong |
author_sort | Zhang, Min |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8316978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83169782021-07-29 Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis Zhang, Min Dai, Rongxin Zhao, Qin Zhou, Lina An, Yunfei Tang, Xuemei Zhao, Xiaodong Front Mol Biosci Molecular Biosciences 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. Frontiers Media S.A. 2021-07-14 /pmc/articles/PMC8316978/ /pubmed/34336925 http://dx.doi.org/10.3389/fmolb.2021.681526 Text en Copyright © 2021 Zhang, Dai, Zhao, Zhou, An, Tang and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Zhang, Min Dai, Rongxin Zhao, Qin Zhou, Lina An, Yunfei Tang, Xuemei Zhao, Xiaodong Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis |
title | Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis |
title_full | Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis |
title_fullStr | Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis |
title_full_unstemmed | Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis |
title_short | Identification of Key Biomarkers and Immune Infiltration in Systemic Juvenile Idiopathic Arthritis by Integrated Bioinformatic Analysis |
title_sort | identification of key biomarkers and immune infiltration in systemic juvenile idiopathic arthritis by integrated bioinformatic analysis |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316978/ https://www.ncbi.nlm.nih.gov/pubmed/34336925 http://dx.doi.org/10.3389/fmolb.2021.681526 |
work_keys_str_mv | AT zhangmin identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis AT dairongxin identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis AT zhaoqin identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis AT zhoulina identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis AT anyunfei identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis AT tangxuemei identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis AT zhaoxiaodong identificationofkeybiomarkersandimmuneinfiltrationinsystemicjuvenileidiopathicarthritisbyintegratedbioinformaticanalysis |