Bioinformatics-Led Discovery of Osteoarthritis Biomarkers and Inflammatory Infiltrates.
Bioinformatics-Led Discovery of Osteoarthritis Biomarkers and Inflammatory Infiltrates.
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DOI：
10.3389/fimmu.2022.871008
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发表时间：
2022
影响因子：
7.3
通讯作者：
中科院分区：
文献类型：
--
作者：
骨关节炎是最常见的慢性疾病，其分子机制仍然无法解释。本研究旨在利用生物信息学的方法来确定骨关节炎的关键生物标志物和免疫浸润。基因表达谱（GSE 55235、GSE 55457、GSE 77298和GSE 82107）选自Gene Expression Omnibus数据库。建立蛋白质-蛋白质相互作用网络，并使用基因本体（GO）和京都基因和基因组百科全书（KEGG）数据库进行功能富集分析和基因组富集分析。使用CIBERSORT方法分析骨关节炎组织和对照组织之间的免疫细胞浸润。在R软件中使用一致的聚类方法，使用RissuscapterPlus包识别免疫模式。通过分子生物学研究发现软骨细胞中的重要基因。共鉴定出105个差异表达基因。GO和KEGG数据库分析显示，差异表达基因在免疫反应、趋化因子介导的信号通路和炎症反应中富集。两种不同的免疫模式（免疫A和免疫B），确定了使用的免疫系统。A群患者的静息树突状细胞、M2巨噬细胞、静息肥大细胞、活化自然杀伤细胞和调节性T细胞显著低于B群B患者。在体外qPCR实验中，IL-1β诱导组中TCA 1、TLR 7、MMP 9、CXCL 10、CXCL 13、HLA-CRP和ADIPOQSPP 1的表达水平显著高于骨关节炎组。解释骨关节炎组织与正常组织之间免疫浸润的差异将有助于理解骨关节炎的发展。
The molecular mechanisms of osteoarthritis, the most common chronic disease, remain unexplained. This study aimed to use bioinformatic methods to identify the key biomarkers and immune infiltration in osteoarthritis. Gene expression profiles (GSE55235, GSE55457, GSE77298, and GSE82107) were selected from the Gene Expression Omnibus database. A protein-protein interaction network was created, and functional enrichment analysis and genomic enrichment analysis were performed using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) databases. Immune cell infiltration between osteoarthritic tissues and control tissues was analyzed using the CIBERSORT method. Identify immune patterns using the ConsensusClusterPlus package in R software using a consistent clustering approach. Molecular biological investigations were performed to discover the important genes in cartilage cells. A total of 105 differentially expressed genes were identified. Differentially expressed genes were enriched in immunological response, chemokine-mediated signaling pathway, and inflammatory response revealed by the analysis of GO and KEGG databases. Two distinct immune patterns (ClusterA and ClusterB) were identified using the ConsensusClusterPlus. Cluster A patients had significantly lower resting dendritic cells, M2 macrophages, resting mast cells, activated natural killer cells and regulatory T cells than Cluster B patients. The expression levels of TCA1, TLR7, MMP9, CXCL10, CXCL13, HLA-DRA, and ADIPOQSPP1 were significantly higher in the IL-1β-induced group than in the osteoarthritis group in an in vitro qPCR experiment. Explaining the differences in immune infiltration between osteoarthritic tissues and normal tissues will contribute to the understanding of the development of osteoarthritis.
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影响因子：
9.8
作者：
Bhattacharya S;Dunn P;Thomas CG;Smith B;Schaefer H;Chen J;Hu Z;Zalocusky KA;Shankar RD;Shen-Orr SS;Thomson E;Wiser J;Butte AJ
通讯作者：
Butte AJ
影响因子：
3.7
作者：
Broeren MG;de Vries M;Bennink MB;van Lent PL;van der Kraan PM;Koenders MI;Thurlings RM;van de Loo FA
通讯作者：
van de Loo FA
影响因子：
5.8
作者：
Chakraborty, Sutirtha;Datta, Somnath;Datta, Susmita
通讯作者：
Datta, Susmita
影响因子：
5.7
作者：
Folkersen, Lasse;Brynedal, Boel;Berg, Louise
通讯作者：
Berg, Louise
DOI：
10.1093/bioinformatics/btp101
发表时间：
2009-04-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Bindea G;Mlecnik B;Hackl H;Charoentong P;Tosolini M;Kirilovsky A;Fridman WH;Pagès F;Trajanoski Z;Galon J
通讯作者：
Galon J