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比较甲氨蝶呤、抗 TNFa、阿巴西普或托珠单抗治疗的类风湿关节炎患者单核细胞的转录组谱。

Transcriptomic profile comparison of monocytes from rheumatoid arthritis patients in treatment with methotrexate, anti-TNFa, abatacept or tocilizumab.

机构信息

Department of Health Sciences, School of Medicine, University of Piemonte Orientale, Novara, Italy.

Department of Life Sciences and System Biology, University of Torino, Torino, Italy.

出版信息

PLoS One. 2023 Mar 6;18(3):e0282564. doi: 10.1371/journal.pone.0282564. eCollection 2023.

DOI:10.1371/journal.pone.0282564
PMID:36877690
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9987802/
Abstract

It is well documented that patients affected by rheumatoid arthritis (RA) have distinct susceptibility to the different biologic DMARDs available on the market, probably because of the many facets of the disease. Monocytes are deeply involved in the pathogenesis of RA and we therefore evaluated and compared the transcriptomic profile of monocytes isolated from patients on treatment with methotrexate alone or in combination with tocilizumab, anti-TNFα or abatacept and from healthy donors. Whole-genome transcriptomics yielded a list of regulated genes by Rank Product statistics and DAVID was then used for functional annotation enrichment analysis. Last, data were validated by qRT-PCR. Abatacept, tocilizumab and anti-TNFa cohorts were separately compared with methotrexate, leading to the identification of 78, 6, and 436 differentially expressed genes, respectively. The upper-most ranked genes were related to inflammatory processes and immune responses. Such an approach draws the genomic profile of monocytes in treated RA patients and lays the basis for finding gene signature for tailored therapeutic choices.

摘要

有大量文献记载,患有类风湿关节炎(RA)的患者对市场上可用的不同生物 DMARDs 具有明显的易感性,这可能是由于该疾病的诸多方面。单核细胞在 RA 的发病机制中起着重要作用,因此我们评估并比较了单独使用甲氨蝶呤或联合使用托珠单抗、抗 TNFα 或阿巴西普以及来自健康供体的患者分离的单核细胞的转录组谱。全基因组转录组学通过 Rank Product 统计生成了一个受调控基因列表,然后使用 DAVID 进行功能注释富集分析。最后,通过 qRT-PCR 验证数据。将 abatacept、tocilizumab 和抗 TNFa 组分别与甲氨蝶呤进行比较,分别鉴定出 78、6 和 436 个差异表达基因。排名最高的基因与炎症过程和免疫反应有关。这种方法描绘了治疗 RA 患者单核细胞的基因组图谱,并为寻找针对特定治疗选择的基因特征奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/7150c5d81661/pone.0282564.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/0940fbc053ff/pone.0282564.g001.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/1b6a2dafae75/pone.0282564.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/7150c5d81661/pone.0282564.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/0940fbc053ff/pone.0282564.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/704557b3e634/pone.0282564.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/9fc87e500726/pone.0282564.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/e54098f192b3/pone.0282564.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/0e6fcf304dd3/pone.0282564.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/1b6a2dafae75/pone.0282564.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e7bb/9987802/7150c5d81661/pone.0282564.g007.jpg

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