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系统生物学方法突出了克罗恩病和溃疡性结肠炎之间的机制差异。

Systems biology approach highlights mechanistic differences between Crohn's disease and ulcerative colitis.

机构信息

Philip Morris International R&D, Philip Morris Products S.A., Quai Jeanrenaud 5, 2000, Neuchâtel, Switzerland.

出版信息

Sci Rep. 2021 Jun 1;11(1):11519. doi: 10.1038/s41598-021-91124-3.

DOI:10.1038/s41598-021-91124-3
PMID:34075172
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8169754/
Abstract

The molecular mechanisms of IBD have been the subject of intensive exploration. We, therefore, assembled the available information into a suite of causal biological network models, which offer comprehensive visualization of the processes underlying IBD. Scientific text was curated by using Biological Expression Language (BEL) and compiled with OpenBEL 3.0.0. Network properties were analysed by Cytoscape. Network perturbation amplitudes were computed to score the network models with transcriptomic data from public data repositories. The IBD network model suite consists of three independent models that represent signalling pathways that contribute to IBD. In the "intestinal permeability" model, programmed cell death factors were downregulated in CD and upregulated in UC. In the "inflammation" model, PPARG, IL6, and IFN-associated pathways were prominent regulatory factors in both diseases. In the "wound healing" model, factors promoting wound healing were upregulated in CD and downregulated in UC. Scoring of publicly available transcriptomic datasets onto these network models demonstrated that the IBD models capture the perturbation in each dataset accurately. The IBD network model suite can provide better mechanistic insights of the transcriptional changes in IBD and constitutes a valuable tool in personalized medicine to further understand individual drug responses in IBD.

摘要

IBD 的分子机制一直是深入研究的课题。因此,我们将现有的信息整合到一套因果生物网络模型中,为 IBD 提供了全面的可视化过程。科学文本使用 Biological Expression Language (BEL) 进行整理,并使用 OpenBEL 3.0.0 进行编译。网络特性通过 Cytoscape 进行分析。通过来自公共数据存储库的转录组数据对网络模型进行计算,以计算网络模型的扰动幅度。IBD 网络模型套件由三个独立的模型组成,代表导致 IBD 的信号通路。在“肠道通透性”模型中,程序性细胞死亡因子在 CD 中下调,在 UC 中上调。在“炎症”模型中,PPARG、IL6 和 IFN 相关途径是两种疾病的主要调节因子。在“伤口愈合”模型中,促进伤口愈合的因素在 CD 中上调,在 UC 中下调。将公开的转录组数据集评分到这些网络模型上表明,IBD 模型准确地捕捉到了每个数据集的扰动。IBD 网络模型套件可以提供对 IBD 中转录变化的更好的机制见解,并构成个性化医学中进一步了解 IBD 中个体药物反应的有价值工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/9223043d3abb/41598_2021_91124_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/d5c16ea10309/41598_2021_91124_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/23e1a519cef5/41598_2021_91124_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/46ac488c8de5/41598_2021_91124_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/fa36a9739925/41598_2021_91124_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/0400c0831732/41598_2021_91124_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/9223043d3abb/41598_2021_91124_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/d5c16ea10309/41598_2021_91124_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/23e1a519cef5/41598_2021_91124_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/46ac488c8de5/41598_2021_91124_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/fa36a9739925/41598_2021_91124_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/0400c0831732/41598_2021_91124_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6da/8169754/9223043d3abb/41598_2021_91124_Fig6_HTML.jpg

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