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滑膜中六个与巨噬细胞相关的基因构成骨关节炎的新型诊断标志物。

Six macrophage-associated genes in synovium constitute a novel diagnostic signature for osteoarthritis.

机构信息

Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China.

Department of Rehabilitation Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

出版信息

Front Immunol. 2022 Jul 28;13:936606. doi: 10.3389/fimmu.2022.936606. eCollection 2022.

Abstract

BACKGROUND

Synovial macrophages play important roles in the formation and progression of osteoarthritis (OA). This study aimed to explore the biological and clinical significance of macrophage-associated genes (MAGs) in OA.

METHODS

The OA synovial gene expression profiles GSE89408 and GSE82107 were obtained from the GEO database. Single-sample gene set enrichment analysis (ssGSEA) and GSEA were employed to decipher differences in immune infiltration and macrophage-associated biological pathways, respectively. Protein-protein interaction (PPI) network analysis and machine learning were utilized to establish a macrophage-associated gene diagnostic signature (MAGDS). RT-qPCR was performed to test the expression of key MAGs in murine models.

RESULTS

OA synovium presented high levels of immune infiltration and activation of macrophage-associated biological pathways. A total of 55 differentially expressed MAGs were identified. Using PPI analysis and machine learning, a MAGDS consisting of IL1B, C5AR1, FCGR2B, IL10, IL6, and TYROBP was established for OA diagnosis (AUC = 0.910) and molecular pathological evaluation. Patients with high MAGDS scores may possess higher levels of immune infiltration and expression of matrix metalloproteinases (MMPs), implying poor biological alterations. The diagnostic value of MAGDS was also validated in an external cohort (AUC = 0.886). The expression of key MAGs was validated in a murine model using RT-qPCR. Additionally, a competitive endogenous RNA network was constructed to reveal the potential posttranscriptional regulatory mechanisms.

CONCLUSIONS

We developed and validated a MAGDS model with the ability to accurately diagnose and characterize biological alterations in OA. The six key MAGs may also be latent targets for immunoregulatory therapy.

摘要

背景

滑膜巨噬细胞在骨关节炎(OA)的形成和进展中发挥重要作用。本研究旨在探讨 OA 中与巨噬细胞相关的基因(MAGs)的生物学和临床意义。

方法

从 GEO 数据库中获取 OA 滑膜基因表达谱 GSE89408 和 GSE82107。采用单样本基因集富集分析(ssGSEA)和 GSEA 分别解析免疫浸润和巨噬细胞相关生物学途径的差异。采用蛋白质-蛋白质相互作用(PPI)网络分析和机器学习建立巨噬细胞相关基因诊断特征(MAGDS)。通过 RT-qPCR 检测在鼠模型中关键 MAGs 的表达。

结果

OA 滑膜呈现高水平的免疫浸润和巨噬细胞相关生物学途径的激活。共鉴定出 55 个差异表达的 MAGs。通过 PPI 分析和机器学习,建立了一个由 IL1B、C5AR1、FCGR2B、IL10、IL6 和 TYROBP 组成的 MAGDS,用于 OA 诊断(AUC=0.910)和分子病理评估。MAGDS 评分高的患者可能具有更高水平的免疫浸润和基质金属蛋白酶(MMPs)的表达,提示生物学改变较差。MAGDS 的诊断价值也在外部队列中得到验证(AUC=0.886)。使用 RT-qPCR 在鼠模型中验证了关键 MAGs 的表达。此外,构建了竞争性内源性 RNA 网络,以揭示潜在的转录后调控机制。

结论

我们开发并验证了一个 MAGDS 模型,该模型能够准确诊断和描述 OA 中的生物学改变。这六个关键的 MAGs 也可能是免疫调节治疗的潜在靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/59d0/9368762/bdd8e7a2696e/fimmu-13-936606-g001.jpg

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