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. 2012 Dec 20;3(1):18.
doi: 10.1186/2041-1480-3-18.

Identification of Fever and Vaccine-Associated Gene Interaction Networks Using Ontology-Based Literature Mining

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Free PMC article

Identification of Fever and Vaccine-Associated Gene Interaction Networks Using Ontology-Based Literature Mining

Junguk Hur et al. J Biomed Semantics. .
Free PMC article

Abstract

Background: Fever is one of the most common adverse events of vaccines. The detailed mechanisms of fever and vaccine-associated gene interaction networks are not fully understood. In the present study, we employed a genome-wide, Centrality and Ontology-based Network Discovery using Literature data (CONDL) approach to analyse the genes and gene interaction networks associated with fever or vaccine-related fever responses.

Results: Over 170,000 fever-related articles from PubMed abstracts and titles were retrieved and analysed at the sentence level using natural language processing techniques to identify genes and vaccines (including 186 Vaccine Ontology terms) as well as their interactions. This resulted in a generic fever network consisting of 403 genes and 577 gene interactions. A vaccine-specific fever sub-network consisting of 29 genes and 28 gene interactions was extracted from articles that are related to both fever and vaccines. In addition, gene-vaccine interactions were identified. Vaccines (including 4 specific vaccine names) were found to directly interact with 26 genes. Gene set enrichment analysis was performed using the genes in the generated interaction networks. Moreover, the genes in these networks were prioritized using network centrality metrics. Making scientific discoveries and generating new hypotheses were possible by using network centrality and gene set enrichment analyses. For example, our study found that the genes in the generic fever network were more enriched in cell death and responses to wounding, and the vaccine sub-network had more gene enrichment in leukocyte activation and phosphorylation regulation. The most central genes in the vaccine-specific fever network are predicted to be highly relevant to vaccine-induced fever, whereas genes that are central only in the generic fever network are likely to be highly relevant to generic fever responses. Interestingly, no Toll-like receptors (TLRs) were found in the gene-vaccine interaction network. Since multiple TLRs were found in the generic fever network, it is reasonable to hypothesize that vaccine-TLR interactions may play an important role in inducing fever response, which deserves a further investigation.

Conclusions: This study demonstrated that ontology-based literature mining is a powerful method for analyzing gene interaction networks and generating new scientific hypotheses.

Figures

Figure 1
Figure 1
Workflow. CONDL workflow for discovering gene-gene and gene-vaccine interaction networks associated with fever and vaccine-associated fever events.
Figure 2
Figure 2
Gene-gene interaction networks in fever and vaccine/VO-associated fever literature. (A) The generic fever-related network. Thickness of edge corresponds to the number of sentences containing its respective interactions. (B) The vaccine/VO associated network. Nodes and edges in yellow were additionally identified by using VO terms. (C) Summary of the three generated gene interaction networks.
Figure 3
Figure 3
Gene-vaccine interaction network. Fever-related gene-vaccine interaction network incorporating all fever-related gene-gene and gene-vaccine interactions. The sub-network related to vaccine is zoomed-in. Node colors (green = vaccine; red = genes; cyan = genes associated with vaccines).
Figure 4
Figure 4
Gene-vaccine interaction networks expanded with HPRD PPI. (A) The generic gene-gene interaction network derived from fever-related literature (Figure 2A) was compared against a protein-protein interaction network generated based on the HPRD. Interactions between genes in the two networks were compared, and 51 such interactions were common to both types of networks. (B) The HPRD PPI network was merged into the fever-associated gene-vaccine network (Figure 3) to create a comprehensive gene-gene-vaccine interaction network in the fever and vaccine domain. (C) A zoomed-in network illustrates the interactions around TNF-α and TNFRSF1A, and their interacting partners. Node colors (green = vaccine; red = genes; cyan = genes associated with vaccines), edge colors (yellow = common to both networks; black = literature-derived vaccine network only; green = HPRD only).

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