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高通量数据的使用为巨细胞动脉炎颞动脉过程提供了新的见解。

Use of high-plex data provides novel insights into the temporal artery processes of giant cell arteritis.

机构信息

Division of Rheumatology, Mayo Clinic, Rochester, MN, United States.

Division of Internal Medicine, Dupuytren University Hospital, Limoges, France.

出版信息

Front Immunol. 2023 Sep 6;14:1237986. doi: 10.3389/fimmu.2023.1237986. eCollection 2023.

DOI:10.3389/fimmu.2023.1237986
PMID:37744332
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10512077/
Abstract

OBJECTIVE

To identify the key coding genes underlying the biomarkers and pathways associated with giant cell arteritis (GCA), we performed an spatial profiling of molecules involved in the temporal arteries of GCA patients and controls. Furthermore, we performed pharmacogenomic network analysis to identify potential treatment targets.

METHODS

Using human formalin-fixed paraffin-embedded temporal artery biopsy samples (GCA, n = 9; controls, n = 7), we performed a whole transcriptome analysis using the NanoString GeoMx Digital Spatial Profiler. In total, 59 regions of interest were selected in the intima, media, adventitia, and perivascular adipose tissue (PVAT). Differentially expressed genes (DEGs) (fold-change > 2 or < -2, p-adjusted < 0.01) were compared across each layer to build a spatial and pharmacogenomic network and to explore the pathophysiological mechanisms of GCA.

RESULTS

Most of the transcriptome (12,076 genes) was upregulated in GCA arteries, compared to control arteries. Among the screened genes, 282, 227, 40, and 5 DEGs were identified in the intima, media, adventitia, and PVAT, respectively. Genes involved in the immune process and vascular remodeling were upregulated within GCA temporal arteries but differed across the arterial layers. The immune-related functions and vascular remodeling were limited to the intima and media.

CONCLUSION

This study is the first to perform an spatial profiling characterization of the molecules involved in GCA. The pharmacogenomic network analysis identified potential target genes for approved and novel immunotherapies.

摘要

目的

为了确定与巨细胞动脉炎(GCA)相关的生物标志物和途径的关键编码基因,我们对 GCA 患者和对照者的颞动脉中涉及的分子进行了空间分析。此外,我们还进行了药物基因组网络分析,以确定潜在的治疗靶点。

方法

使用福尔马林固定石蜡包埋的人类颞动脉活检样本(GCA,n=9;对照,n=7),我们使用 NanoString GeoMx Digital Spatial Profiler 进行了全转录组分析。总共在内膜、中膜、外膜和血管周围脂肪组织(PVAT)中选择了 59 个感兴趣区域。在各层之间比较差异表达基因(DEG)(fold-change > 2 或 < -2,p-adjusted < 0.01),以构建空间和药物基因组网络,并探索 GCA 的病理生理机制。

结果

与对照动脉相比,GCA 动脉中的大部分转录组(12076 个基因)上调。在筛选出的基因中,内膜、中膜、外膜和 PVAT 分别鉴定出 282、227、40 和 5 个 DEG。参与免疫过程和血管重塑的基因在 GCA 颞动脉中上调,但在动脉各层之间存在差异。免疫相关功能和血管重塑仅限于内膜和中膜。

结论

本研究首次对 GCA 相关分子进行了空间分析。药物基因组网络分析确定了已批准和新型免疫疗法的潜在靶基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/44ea0cf5dc2b/fimmu-14-1237986-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/eacca88c78be/fimmu-14-1237986-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/552365a09ee2/fimmu-14-1237986-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/55a257366810/fimmu-14-1237986-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/4eb14acf2f27/fimmu-14-1237986-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/be7c5db17ccd/fimmu-14-1237986-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/44ea0cf5dc2b/fimmu-14-1237986-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/eacca88c78be/fimmu-14-1237986-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/552365a09ee2/fimmu-14-1237986-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/55a257366810/fimmu-14-1237986-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/4eb14acf2f27/fimmu-14-1237986-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/be7c5db17ccd/fimmu-14-1237986-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a606/10512077/44ea0cf5dc2b/fimmu-14-1237986-g006.jpg

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Immunology of Giant Cell Arteritis.巨细胞动脉炎的免疫学。
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