Bulk and single cell transcriptomic data indicate that a dichotomy between inflammatory pathways in peripheral blood and arthritic joints complicates biomarker discovery
Bulk and single cell transcriptomic data indicate that a dichotomy between inflammatory pathways in peripheral blood and arthritic joints complicates biomarker discovery
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DOI：
10.1016/j.cyto.2019.154960
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发表时间：
2020-03-01
期刊：
影响因子：
3.8
通讯作者：
Benson, Mikael
中科院分区：
文献类型：
--
作者：
Lee, Eun Jung;Lilja, Sandra;Benson, Mikael
背景资料：使用不同的全基因组方法的无偏倚研究已经确定了几种新的生物标志物，用于诊断和治疗风湿性关节炎（RA）。然而，临床翻译已被证明是困难的。在这里，我们假设，一个原因可能是，外周血中的炎症反应是不同的，从那些在arthritic joint.Methods：我们进行荟萃分析的基因表达微阵列数据从滑膜，全血细胞（WBC），外周血单核细胞（PBMC），和CD 4 + T细胞RA患者和健康对照，以确定重叠的途径，上游监管机构和潜在的生物标志物。我们还分析了单细胞RNA测序，来自抗原诱导的关节炎的小鼠模型的外周血和全关节的scRNA-seq数据。对来自RA患者和健康对照的滑膜的两个谱数据集的分析都显示了具有已知致病相关性的途径的显著激活，例如Th 1途径，NFAT在免疫应答调节中的作用，树突状细胞成熟，T辅助细胞中的iCOS-iCOSL信号传导、Fc γ受体介导的吞噬作用、干扰素信号传导、Cdc 42信号传导和细胞毒性T淋巴细胞介导的凋亡。最活跃的上游调节因子包括TNF，一个重要的药物靶点，以及IFN-γ和CD 40 LG，所有这些都是已知的RA中发挥重要的致病作用。滑膜差异表达的基因包括几个潜在的生物标志物，如CCL 5、CCL 13、CCL 18、CX 3CL 1、CXCL 6、CXCL 9、CXCL 10、CXCL 13、ILLS、IL 32、IL 1 RN、SPP 1和TNFSF 11。相比之下，WBC，PBMC和CD 4 + T细胞的微阵列研究显示可变的途径和有限的途径与滑膜重叠。类似地，来自关节炎小鼠模型的scRNA-seq数据不支持外周血中的炎症反应反映关节炎关节中的炎症反应。这些数据表明，小鼠关节细胞和滑膜RA患者之间的通路重叠，但不与细胞在外周blood.Conclusions：我们的研究结果表明，基因表达的变化，通路，上游调控和生物标志物之间的二分法滑膜和细胞类型在外周血中，这复杂的生物标志物在血液中的识别。
Background: Unbiased studies using different genome-wide methods have identified several novel biomarkers for diagnosis and treatment response in Rheumatoid Arthritis (RA). However, clinical translation has proven difficult. Here, we hypothesized that one reason could be that inflammatory responses in peripheral blood are different from those in the arthritic joint.Methods: We performed meta-analysis of gene expression microarray data from synovium, whole blood cells (WBC), peripheral blood mononuclear cells (PBMC), and CD4+ T cells from patients with RA and healthy controls in order to identify overlapping pathways, upstream regulators and potential biomarkers. We also analyzed single cell RNA-sequencing (scRNA-seq) data from peripheral blood and whole joints from a mouse model of antigen-induced arthritis.Results: Analyses of two profiling data sets from synovium from RA patients and healthy controls all showed significant activation of pathways with known pathogenic relevance, such as the Th1 pathway, the role of NFAT in regulation of the immune response, dendritic cell maturation, iCOS-iCOSL signaling in T helper cells, Fc gamma receptor-mediated phagocytosis, interferon signaling, Cdc42 signaling, and cytotoxic T lymphocyte-mediated apoptosis. The most activated upstream regulators included TNF, an important drug target, as well as IFN-gamma and CD40LG, all of which are known to play important pathogenic roles in RA. The differentially expressed genes from synovium included several potential biomarkers, such as CCL5, CCL13, CCL18, CX3CL1, CXCL6, CXCL9, CXCL10, CXCL13, ILLS, IL32, IL1RN, SPP1, and TNFSF11. By contrast, microarray studies of WBC, PBMC and CD4+ T cells showed variable pathways and limited pathway overlap with synovium. Similarly, scRNA-seq data from a mouse model of arthritis did not support that inflammatory responses in peripheral blood reflect those in the arthritic joints. These data showed pathway overlap between mouse joint cells and synovium from patients with RA, but not with cells in peripheral blood.Conclusions: Our findings indicate a dichotomy between gene expression changes, pathways, upstream regulators and biomarkers in synovium and cell types in peripheral blood, which complicates identification of biomarkers in blood.