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基于网络的候选标志物和检测方法选择,以评估口服免疫干预对肠道功能的影响。

Network-Based Selection of Candidate Markers and Assays to Assess the Impact of Oral Immune Interventions on Gut Functions.

机构信息

TNO, Zeist, Netherlands.

Danone Food Safety Center, Utrecht, Netherlands.

出版信息

Front Immunol. 2019 Nov 13;10:2672. doi: 10.3389/fimmu.2019.02672. eCollection 2019.

DOI:10.3389/fimmu.2019.02672
PMID:31798593
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6863931/
Abstract

To assess the safety and efficacy of oral immune interventions, it is important and required by regulation to assess the impact of those interventions not only on the immune system, but also on other organs such as the gut as the porte d'entrée. Despite clear indications that the immune system interacts with several physiological functions of the gut, it is still unknown which pathways and molecules are crucial to assessing the impact of nutritional immune interventions on gut functioning. Here we used a network-based systems biology approach to clarify the molecular relationships between immune system and gut functioning and to identify crucial biomarkers to assess effects on gut functions upon nutritional immune interventions. First, the different gut functionalities were categorized based on literature and EFSA guidance documents. Moreover, an overview of the current assays and methods to measure gut function was generated. Secondly, gut-function related biological processes and adverse events were selected and subsequently linked to the physiological functions of the GI tract. Thirdly, database terms and annotations from the Gene ontology database and the Comparative Toxicogenomics Database (CTD) related to the previously selected gut-function related processes were selected. Next, database terms and annotations were used to identify the pathways and genes involved in those gut functionalities. In parallel, information from CTD was used to identify immune disease related genes. The resulting lists of both gut and immune function genes showed an overlap of 753 genes out of 1,296 gut-function related genes indicating the close gut-immune relationship. Using bioinformatics enrichment tools DAVID and Panther, the identified gut-immune markers were predicted to be involved in motility, barrier function, the digestion and absorption of vitamins and fat, regulation of the digestive system and gastric acid, and protection from injurious or allergenic material. Concluding, here we provide a promising systems biology approach to identify genes that help to clarify the relationships between immune system and gut functioning, with the aim to identify candidate biomarkers to monitor nutritional immune intervention assays for safety and efficacy in the general population. This knowledge helps to optimize future study designs to predict effects of nutritional immune intervention on gut functionalities.

摘要

为了评估口服免疫干预措施的安全性和有效性,根据规定,不仅要评估这些干预措施对免疫系统的影响,还要评估它们对肠道等门户器官的影响,这一点很重要。尽管有明确的迹象表明免疫系统与肠道的几个生理功能相互作用,但仍不清楚哪些途径和分子对于评估营养免疫干预对肠道功能的影响至关重要。在这里,我们使用基于网络的系统生物学方法来阐明免疫系统和肠道功能之间的分子关系,并确定关键的生物标志物来评估营养免疫干预对肠道功能的影响。首先,根据文献和 EFSA 指导文件对不同的肠道功能进行了分类。此外,还生成了一份评估肠道功能的当前检测和方法概述。其次,选择了与肠道功能相关的生物过程和不良事件,并随后将其与胃肠道的生理功能联系起来。第三,从基因本体数据库和比较毒理学基因组数据库(CTD)中选择与之前选择的与肠道功能相关的过程相关的数据库术语和注释。接下来,使用数据库术语和注释来识别涉及这些肠道功能的途径和基因。同时,使用 CTD 的信息来识别与免疫疾病相关的基因。在 1296 个与肠道功能相关的基因中,这两个肠道和免疫功能基因的列表显示出 753 个基因重叠,表明肠道和免疫之间存在密切的关系。使用生物信息学富集工具 DAVID 和 Panther,预测鉴定出的肠道-免疫标志物与运动、屏障功能、维生素和脂肪的消化和吸收、消化系统和胃酸的调节以及对有害或变应原物质的保护有关。综上所述,我们在这里提供了一种有前途的系统生物学方法来识别有助于阐明免疫系统和肠道功能之间关系的基因,目的是确定候选生物标志物来监测营养免疫干预试验的安全性和有效性在普通人群中。这些知识有助于优化未来的研究设计,以预测营养免疫干预对肠道功能的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/93b4c5a56386/fimmu-10-02672-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/672599a2488a/fimmu-10-02672-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/d07df5852f35/fimmu-10-02672-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/ad42628b2903/fimmu-10-02672-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/93b4c5a56386/fimmu-10-02672-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/672599a2488a/fimmu-10-02672-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/d07df5852f35/fimmu-10-02672-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/ad42628b2903/fimmu-10-02672-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d40b/6863931/93b4c5a56386/fimmu-10-02672-g0004.jpg

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