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一项全面的基因表达荟萃分析确定了类风湿性关节炎患者新的免疫特征。

A Comprehensive Gene Expression Meta-analysis Identifies Novel Immune Signatures in Rheumatoid Arthritis Patients.

作者信息

Afroz Sumbul, Giddaluru Jeevan, Vishwakarma Sandeep, Naz Saima, Khan Aleem Ahmed, Khan Nooruddin

机构信息

Department of Biotechnology and Bioinformatics, School of Life Sciences, University of Hyderabad , Hyderabad , India.

Centre for Liver Research and Diagnostics, Central Laboratory for Stem Cell Research and Translational Medicine, Deccan College of Medical Sciences, Kanchanbagh , Hyderabad , India.

出版信息

Front Immunol. 2017 Feb 2;8:74. doi: 10.3389/fimmu.2017.00074. eCollection 2017.

Abstract

Rheumatoid arthritis (RA), a symmetric polyarticular arthritis, has long been feared as one of the most disabling forms of arthritis. Identification of gene signatures associated with RA onset and progression would lead toward development of novel diagnostics and therapeutic interventions. This study was undertaken to identify unique gene signatures of RA patients through large-scale meta-profiling of a diverse collection of gene expression data sets. We carried out a meta-analysis of 8 publicly available RA patients' (107 RA patients and 76 healthy controls) gene expression data sets and further validated a few meta-signatures in RA patients through quantitative real-time PCR (RT-qPCR). We identified a robust meta-profile comprising 33 differentially expressed genes, which were consistently and significantly expressed across all the data sets. Our meta-analysis unearthed upregulation of a few novel gene signatures including , and , which were validated in peripheral blood mononuclear cell samples of RA patients. Further, functional and pathway enrichment analysis reveals perturbation of several meta-genes involved in signaling pathways pertaining to inflammation, antigen presentation, hypoxia, and apoptosis during RA. Additionally, PLCG2 (phospholipase Cγ2) popped out as a novel meta-gene involved in most of the pathways relevant to RA including inflammasome activation, platelet aggregation, and activation, thereby suggesting PLCG2 as a potential therapeutic target for controlling excessive inflammation during RA. In conclusion, these findings highlight the utility of meta-analysis approach in identifying novel gene signatures that might provide mechanistic insights into disease onset, progression and possibly lead toward the development of better diagnostic and therapeutic interventions against RA.

摘要

类风湿关节炎(RA)是一种对称性多关节关节炎,长期以来一直被视为最致残的关节炎形式之一。识别与RA发病和进展相关的基因特征将有助于开发新的诊断方法和治疗干预措施。本研究旨在通过对各种基因表达数据集进行大规模元分析,以识别RA患者独特的基因特征。我们对8个公开可用的RA患者(107例RA患者和76例健康对照)的基因表达数据集进行了荟萃分析,并通过定量实时PCR(RT-qPCR)在RA患者中进一步验证了一些元特征。我们确定了一个由33个差异表达基因组成的强大元特征,这些基因在所有数据集中均持续且显著表达。我们的荟萃分析发现了一些新基因特征的上调,包括 、 和 ,这些在RA患者的外周血单核细胞样本中得到了验证。此外,功能和通路富集分析揭示了RA期间参与炎症、抗原呈递、缺氧和凋亡相关信号通路的几个元基因受到干扰。此外,PLCG2(磷脂酶Cγ2)作为一个新的元基因出现,参与了与RA相关的大多数通路,包括炎性小体激活、血小板聚集和激活,从而表明PLCG2是控制RA期间过度炎症的潜在治疗靶点。总之,这些发现突出了荟萃分析方法在识别新基因特征方面的实用性,这些特征可能为疾病的发病、进展提供机制性见解,并可能有助于开发针对RA的更好的诊断和治疗干预措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ad1/5288395/d0c64a912f8a/fimmu-08-00074-g001.jpg

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