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基于单细胞 RNA 测序分析的骨关节炎免疫治疗相关免疫生物标志物的鉴定。

The Identification of Immune-Related Biomarkers for Osteoarthritis Immunotherapy Based on Single-Cell RNA Sequencing Analysis.

机构信息

Orthopedics Department, Yaan Hospital of Traditional Chinese Medicine, Yaan, China.

出版信息

Genet Res (Camb). 2023 Mar 14;2023:5574636. doi: 10.1155/2023/5574636. eCollection 2023.

DOI:10.1155/2023/5574636
PMID:36960385
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10030227/
Abstract

Osteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predisposition. As the pathogenesis of OA is unknown, there are almost no effective treatments available to prevent the onset or progression of the disease. In recent years, many researchers focused on bioinformatics analysis to explore new biomarkers for the diagnosis, treatment, and prognosis of human diseases. In this work, we obtain the traditional RNA sequencing data of OA patients from the GEO database. By performing the differentially expressed analysis, we successfully obtain the genes that are closely associated with the OA. In addition, the Venn diagram was applied to evaluate the genes that are involved in OA and immune-related genes. The protein-protein interaction analysis was further conducted to explore the hub genes. The single-cell RNA sequencing analysis was used to evaluate the expression distribution of the MMP, VEGFA, SPI1, and IRF8 in synovial tissues of patients with osteoarthritis. Finally, the GSVA enrichment analysis discovered the potential pathways involved in OA patients. Our analysis provides a new direction for the exploration of the process of OA patients. In addition, VEGFA may be considered a promising biomarker in OA.

摘要

骨关节炎(OA)是一种影响全球约 5 亿人慢性肌肉骨骼疾病。在全球范围内,OA 是最常见和主要的致残原因之一。几种遗传因素与 OA 有关,包括遗传基因、遗传易感性和遗传倾向。由于 OA 的发病机制尚不清楚,因此几乎没有有效的治疗方法可以预防疾病的发生或进展。近年来,许多研究人员专注于生物信息学分析,以探索用于人类疾病诊断、治疗和预后的新生物标志物。在这项工作中,我们从 GEO 数据库中获取 OA 患者的传统 RNA 测序数据。通过进行差异表达分析,我们成功获得了与 OA 密切相关的基因。此外,应用 Venn 图评估了涉及 OA 和免疫相关基因的基因。进一步进行了蛋白质-蛋白质相互作用分析,以探讨枢纽基因。单细胞 RNA 测序分析用于评估 MMP、VEGFA、SPI1 和 IRF8 在 OA 患者滑膜组织中的表达分布。最后,GSVA 富集分析发现了 OA 患者中涉及的潜在途径。我们的分析为 OA 患者的探索过程提供了一个新的方向。此外,VEGFA 可被视为 OA 有前途的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c94/10030227/ec29cf8ee145/GR2023-5574636.006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c94/10030227/f5fc75856cb9/GR2023-5574636.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c94/10030227/83325d981281/GR2023-5574636.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3c94/10030227/5d0aabc346de/GR2023-5574636.003.jpg
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