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SysInflam HuDB,一个用于挖掘与脓毒症全身炎症反应相关的人类血细胞转录组数据的网络资源。

SysInflam HuDB, a Web Resource for Mining Human Blood Cells Transcriptomic Data Associated with Systemic Inflammatory Responses to Sepsis.

机构信息

Sidra Medicine, Doha, Qatar.

Division of Pediatric Cardiothoracic Surgery, Department of Surgery, Washington University School of Medicine, St. Louis, MO; and.

出版信息

J Immunol. 2021 Nov 1;207(9):2195-2202. doi: 10.4049/jimmunol.2100697.

DOI:10.4049/jimmunol.2100697
PMID:34663591
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8525868/
Abstract

Sepsis develops after a dysregulated host inflammatory response to a systemic infection. Identification of sepsis biomarkers has been challenging because of the multifactorial causes of disease susceptibility and progression. Public transcriptomic data are a valuable resource for mechanistic discoveries and cross-studies concordance of heterogeneous diseases. Nonetheless, the approach requires structured methodologies and effective visualization tools for meaningful data interpretation. Currently, no such database exists for sepsis or systemic inflammatory diseases in human. Hence we curated SysInflam HuDB (http://sepsis.gxbsidra.org/dm3/geneBrowser/list), a unique collection of human blood transcriptomic datasets associated with systemic inflammatory responses to sepsis. The transcriptome collection and the associated clinical metadata are integrated onto a user-friendly and Web-based interface that allows the simultaneous exploration, visualization, and interpretation of multiple datasets stemming from different study designs. To date, the collection encompasses 62 datasets and 5719 individual profiles. Concordance of gene expression changes with the associated literature was assessed, and additional analyses are presented to showcase database utility. Combined with custom data visualization at the group and individual levels, SysInflam HuDB facilitates the identification of specific human blood gene signatures in response to infection (e.g., patients with sepsis versus healthy control subjects) and the delineation of major genetic drivers associated with inflammation onset and progression under various conditions.

摘要

脓毒症是宿主对全身感染的炎症反应失调后发展而来的。由于疾病易感性和进展的多因素原因,分离脓毒症生物标志物一直具有挑战性。公共转录组数据是用于机制发现和跨研究异质疾病一致性的有价值的资源。尽管如此,这种方法需要结构化的方法和有效的可视化工具来进行有意义的数据分析解释。目前,人类脓毒症或全身炎症性疾病尚无此类数据库。因此,我们整理了 SysInflam HuDB(http://sepsis.gxbsidra.org/dm3/geneBrowser/list),这是一个与脓毒症全身炎症反应相关的人类血液转录组数据集的独特集合。转录组集合和相关的临床元数据集成到一个用户友好且基于 Web 的界面中,允许同时探索、可视化和解释来自不同研究设计的多个数据集。迄今为止,该集合包含 62 个数据集和 5719 个个体图谱。评估了基因表达变化与相关文献的一致性,并进行了其他分析以展示数据库的实用性。结合组和个体水平的自定义数据可视化,SysInflam HuDB 有助于确定针对感染的特定人类血液基因特征(例如,脓毒症患者与健康对照个体),并描绘在各种条件下与炎症发生和进展相关的主要遗传驱动因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/058b/8525868/2878b4389211/ji2100697absf1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/058b/8525868/2878b4389211/ji2100697absf1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/058b/8525868/2878b4389211/ji2100697absf1.jpg

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Clin Transl Med. 2020 Dec;10(8):e244. doi: 10.1002/ctm2.244.
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A Neutrophil-Driven Inflammatory Signature Characterizes the Blood Transcriptome Fingerprint of Psoriasis.中性粒细胞驱动的炎症特征标志着银屑病血液转录组指纹图谱。
Front Immunol. 2020 Nov 24;11:587946. doi: 10.3389/fimmu.2020.587946. eCollection 2020.
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Annexin A3 in sepsis: novel perspectives from an exploration of public transcriptome data.
转录组谱分析突出了 NUDT16 在脓毒症中的潜在作用。
J Cell Mol Med. 2022 Mar;26(5):1714-1721. doi: 10.1111/jcmm.17240. Epub 2022 Feb 17.
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Transcriptome and Literature Mining Highlight the Differential Expression of ERLIN1 in Immune Cells during Sepsis.转录组和文献挖掘揭示脓毒症期间免疫细胞中ERLIN1的差异表达。
Biology (Basel). 2021 Aug 5;10(8):755. doi: 10.3390/biology10080755.
annexin A3 在脓毒症中的作用:公共转录组数据探索带来的新视角。
Immunology. 2020 Dec;161(4):291-302. doi: 10.1111/imm.13239. Epub 2020 Aug 31.
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An immune-cell signature of bacterial sepsis.细菌脓毒症的免疫细胞特征。
Nat Med. 2020 Mar;26(3):333-340. doi: 10.1038/s41591-020-0752-4. Epub 2020 Feb 17.
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