全面的 bulk 和单细胞转录组谱分析为骨关节炎相关滑膜巨噬细胞的特征提供了有用的见解。

Comprehensive bulk and single-cell transcriptome profiling give useful insights into the characteristics of osteoarthritis associated synovial macrophages.

机构信息

Shenzhen Key Laboratory of Nanozymes and Translational Cancer Research, Department of Otolaryngology, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.

Department of Otolaryngology, Shenzhen First People's Hospital, The Affiliated Hospital of Jinan University, Shenzhen, Guangdong, China.

出版信息

Front Immunol. 2023 Jan 5;13:1078414. doi: 10.3389/fimmu.2022.1078414. eCollection 2022.

DOI:10.3389/fimmu.2022.1078414

PMID:36685529

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9849898/

Abstract

BACKGROUND

Osteoarthritis (OA) is a common chronic joint disease, but the association between molecular and cellular events and the pathogenic process of OA remains unclear.

OBJECTIVE

The study aimed to identify key molecular and cellular events in the processes of immune infiltration of the synovium in OA and to provide potential diagnostic and therapeutic targets.

METHODS

To identify the common differential expression genes and function analysis in OA, we compared the expression between normal and OA samples and analyzed the protein-protein interaction (PPI). Additionally, immune infiltration analysis was used to explore the differences in common immune cell types, and Gene Set Variation Analysis (GSVA) analysis was applied to analyze the status of pathways between OA and normal groups. Furthermore, the optimal diagnostic biomarkers for OA were identified by least absolute shrinkage and selection operator (LASSO) models. Finally, the key role of biomarkers in OA synovitis microenvironment was discussed through single cell and Scissor analysis.

RESULTS

A total of 172 DEGs (differentially expressed genes) associated with osteoarticular synovitis were identified, and these genes mainly enriched eight functional categories. In addition, immune infiltration analysis found that four immune cell types, including Macrophage, B cell memory, B cell, and Mast cell were significantly correlated with OA, and LASSO analysis showed that Macrophage were the best diagnostic biomarkers of immune infiltration in OA. Furthermore, using scRNA-seq dataset, we also analyzed the cell communication patterns of Macrophage in the OA synovial inflammatory microenvironment and found that CCL, MIF, and TNF signaling pathways were the mainly cellular communication pathways. Finally, Scissor analysis identified a population of M2-like Macrophages with high expression of CD163 and LYVE1, which has strong anti-inflammatory ability and showed that the TNF gene may play an important role in the synovial microenvironment of OA.

CONCLUSION

Overall, Macrophage is the best diagnostic marker of immune infiltration in osteoarticular synovitis, and it can communicate with other cells mainly through CCL, TNF, and MIF signaling pathways in microenvironment. In addition, TNF gene may play an important role in the development of synovitis.

摘要

背景

骨关节炎（OA）是一种常见的慢性关节疾病，但分子和细胞事件与 OA 的发病机制之间的关系仍不清楚。

目的

本研究旨在确定 OA 滑膜免疫浸润过程中的关键分子和细胞事件，并为其提供潜在的诊断和治疗靶点。

方法

为了鉴定 OA 中的常见差异表达基因和功能分析，我们比较了正常和 OA 样本之间的表达，并进行了蛋白质-蛋白质相互作用（PPI）分析。此外，我们还进行了免疫浸润分析，以探讨常见免疫细胞类型之间的差异，并应用基因集变异分析（GSVA）分析 OA 与正常组之间通路的状态。此外，通过最小绝对收缩和选择算子（LASSO）模型鉴定 OA 的最佳诊断生物标志物。最后，通过单细胞和 Scissor 分析探讨了生物标志物在 OA 滑膜炎微环境中的关键作用。

结果

共鉴定出 172 个与骨关节炎滑膜炎症相关的差异表达基因（DEGs），这些基因主要富集在 8 个功能类别中。此外，免疫浸润分析发现，包括巨噬细胞、B 细胞记忆、B 细胞和肥大细胞在内的四种免疫细胞类型与 OA 显著相关，LASSO 分析显示巨噬细胞是 OA 免疫浸润的最佳诊断生物标志物。此外，我们还使用 scRNA-seq 数据集分析了 OA 滑膜炎症微环境中巨噬细胞的细胞通讯模式，发现 CCL、MIF 和 TNF 信号通路是主要的细胞通讯通路。最后，Scissor 分析确定了一群高表达 CD163 和 LYVE1 的 M2 样巨噬细胞，它们具有很强的抗炎能力，并表明 TNF 基因可能在 OA 的滑膜微环境中发挥重要作用。