Rheumatoid arthritis (RA) frequently seen chronic synovial inflammation causing joint destruction, chronic disability and reduced life expectancy. The pathogenesis of RA is not completely known. In this study, several gene expression data including synovial tissue and macrophages from synovial tissues were integrated with a holistic perspective and the molecular targets and signatures in RA were determined. Differentially expressed genes (DEGs) were identified from each dataset by comparing diseased and healthy samples. Afterward, the RA-specific protein-protein interaction (PPI) and the transcriptional regulatory network were reconstructed by using several biomolecule interaction data. Key biomolecules were determined through a statistical test employing the hypergeometric probability density function by using the physical interactions of transcriptional regulators and PPI. The integrative analyses of DEGs indicated that there were 110 and 494 common genes between synovial tissues and macrophages related datasets, respectively. Common DEGs of all datasets were identified as 25 genes and these core genes which might be feasible to uncover the mutual biological mechanism insights behind the RA pathogenesis were used for disease specific biological networks reconstruction. It was determined the hub proteins, novel key biomolecules (i.e. receptor, transcription factors and miRNAs) and biomolecules interactions by using the core DEGs. It was identified STAT1, RAC2 and KYNU as hub proteins, PEPD as a receptor, NR4A1, MEOX2, KLF4, IRF1 and MYB as TFs, miR-299, miR-8078, miR-146a, miR-3659 and miR-6882 as key miRNAs. It was determined that biomolecule interaction scenarios using identified key biomolecules and novel biomolecules including RAC2, PEPD, NR4A1, MEOX2, miR-299, miR-8078, miR-3659 and miR-6882 in RA. Our novel findings could be a crucial resource for the understanding of RA molecular mechanism and may be considered as drug targets and development of novel diagnostic strategies. Corresponding genes and miRNAs should be validated via experimental studies.

中文翻译：

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通过重建综合的疾病特异性生物网络，鉴定类风湿关节炎中的关键生物分子。

类风湿关节炎（RA）经常见于慢性滑膜炎症，导致关节破坏，慢性残疾和预期寿命缩短。RA的发病机制尚不完全清楚。在这项研究中，从整体角度整合了包括滑膜组织和来自滑膜组织的巨噬细胞在内的几种基因表达数据，并确定了RA中的分子靶标和特征。通过比较患病和健康样本，从每个数据集中鉴定出差异表达基因（DEG）。随后，通过使用一些生物分子相互作用数据重建了RA特异性蛋白-蛋白相互作用（PPI）和转录调控网络。通过使用超几何概率密度函数通过统计测试确定关键生物分子，该函数使用转录调节因子和PPI的物理相互作用。DEGs的综合分析表明，滑膜组织和巨噬细胞相关的数据集之间分别有110和494个共同基因。所有数据集的共同DEGs被识别为25个基因，这些可能揭示RA发病机制背后的相互生物学机制见解的核心基因被用于疾病特异性生物学网络的重建。通过使用核心DEG，确定了毂蛋白，新型关键生物分子（即受体，转录因子和miRNA）以及生物分子之间的相互作用。已确定STAT1，RAC2和KYNU为中枢蛋白，PEPD为受体，NR4A1，MEOX2，KLF4，IRF1和MYB作为TF，miR-299，miR-8078，miR-146a，miR-3659和miR-6882作为关键miRNA。已确定使用RA中已鉴定的关键生物分子和新型生物分子（包括RAC2，PEPD，NR4A1，MEOX2，miR-299，miR-8078，miR-3659和miR-6882）进行生物分子相互作用的情况。我们的新发现可能是理解RA分子机制的重要资源，并且可以被视为药物靶点和新诊断策略的发展。相应的基因和miRNA应通过实验研究进行验证。我们的新发现可能是理解RA分子机制的重要资源，并且可以被视为药物靶点和新诊断策略的发展。相应的基因和miRNA应通过实验研究进行验证。我们的新发现可能是理解RA分子机制的重要资源，并且可以被视为药物靶点和新诊断策略的发展。相应的基因和miRNA应通过实验研究进行验证。