CIDO ontology updates and secondary analysis of host responses to COVID-19 infection based on ImmPort reports and literature.

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Biomedical Semantics Pub Date : 2021-08-28 DOI:10.1186/s13326-021-00250-4
Anthony Huffman, Anna Maria Masci, Jie Zheng, Nasim Sanati, Timothy Brunson, Guanming Wu, Yongqun He
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引用次数: 0

Abstract

Background: With COVID-19 still in its pandemic stage, extensive research has generated increasing amounts of data and knowledge. As many studies are published within a short span of time, we often lose an integrative and comprehensive picture of host-coronavirus interaction (HCI) mechanisms. As of early April 2021, the ImmPort database has stored 7 studies (with 6 having details) that cover topics including molecular immune signatures, epitopes, and sex differences in terms of mortality in COVID-19 patients. The Coronavirus Infectious Disease Ontology (CIDO) represents basic HCI information. We hypothesize that the CIDO can be used as the platform to represent newly recorded information from ImmPort leading the reinforcement of CIDO.

Methods: The CIDO was used as the semantic platform for logically modeling and representing newly identified knowledge reported in the 6 ImmPort studies. A recursive eXtensible Ontology Development (XOD) strategy was established to support the CIDO representation and enhancement. Secondary data analysis was also performed to analyze different aspects of the HCI from these ImmPort studies and other related literature reports.

Results: The topics covered by the 6 ImmPort papers were identified to overlap with existing CIDO representation. SARS-CoV-2 viral S protein related HCI knowledge was emphasized for CIDO modeling, including its binding with ACE2, mutations causing different variants, and epitope homology by comparison with other coronavirus S proteins. Different types of cytokine signatures were also identified and added to CIDO. Our secondary analysis of two cohort COVID-19 studies with cytokine panel detection found that a total of 11 cytokines were up-regulated in female patients after infection and 8 cytokines in male patients. These sex-specific gene responses were newly modeled and represented in CIDO. A new DL query was generated to demonstrate the benefits of such integrative ontology representation. Furthermore, IL-10 signaling pathway was found to be statistically significant for both male patients and female patients.

Conclusion: Using the recursive XOD strategy, six new ImmPort COVID-19 studies were systematically reviewed, the results were modeled and represented in CIDO, leading to the enhancement of CIDO. The enhanced ontology and further seconary analysis supported more comprehensive understanding of the molecular mechanism of host responses to COVID-19 infection.

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基于import报告和文献的CIDO本体更新和宿主对COVID-19感染反应的二次分析。
背景:随着新冠肺炎仍处于大流行阶段,广泛的研究产生了越来越多的数据和知识。由于许多研究都是在短时间内发表的,我们经常失去对宿主冠状病毒相互作用(HCI)机制的综合和全面的了解。截至2021年4月初,ImmPort数据库已存储了7项研究(其中6项有详细信息),涉及新冠肺炎患者的分子免疫特征、表位和死亡率性别差异等主题。冠状病毒传染病本体论(CIDO)代表了基本的HCI信息。我们假设CIDO可以作为平台来表示来自ImmPort的新记录信息,从而加强CIDO。方法:将CIDO用作语义平台,对6项ImmPort研究中报告的新识别知识进行逻辑建模和表示。建立了一种递归的可扩展本体开发(XOD)策略来支持CIDO的表示和增强。还进行了二次数据分析,以分析来自这些ImmPort研究和其他相关文献报告的HCI的不同方面。结果:6篇ImmPort论文所涵盖的主题被确定为与加拿大国际开发署现有的代表重叠。CIDO建模强调了严重急性呼吸系统综合征冠状病毒2型病毒S蛋白相关的HCI知识,包括其与ACE2的结合、导致不同变体的突变,以及与其他冠状病毒S蛋白相比的表位同源性。还鉴定了不同类型的细胞因子特征,并将其添加到CIDO中。我们对新冠肺炎两项细胞因子组检测队列研究的二次分析发现,女性患者感染后共有11种细胞因子上调,男性患者共有8种细胞因子下调。这些性别特异性基因反应是新建模的,并在CIDO中得到了体现。生成了一个新的DL查询来展示这种集成本体表示的好处。此外,发现IL-10信号通路对男性患者和女性患者都具有统计学意义。结论:采用递归XOD策略,对6项新的新冠肺炎免疫研究进行了系统回顾,并在CIDO中对结果进行了建模和表示,从而增强了CIDO。增强的本体论和进一步的分离分析支持更全面地理解宿主对新冠肺炎感染反应的分子机制。
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来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
期刊最新文献
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