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. 2019 Jan 31;19(Suppl 1):20.
doi: 10.1186/s12911-019-0738-7.

Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD

Guocai Chen  1 , Yuxi Jia  1   2 , Lisha Zhu  1 , Ping Li  3 , Lin Zhang  4 , Cui Tao  5 , W Jim Zheng  6
Affiliations

Gene fingerprint model for literature based detection of the associations among complex diseases: a case study of COPD

Guocai Chen et al. BMC Med Inform Decis Mak. .

Abstract

Background: Disease comorbidity is very common and has significant impact on disease treatment. Revealing the associations among diseases may help to understand the mechanisms of diseases, improve the prevention and treatment of diseases, and support the discovery of new drugs or new uses of existing drugs.

Methods: In this paper, we introduced a mathematical model to represent gene related diseases with a series of associated genes based on the overrepresentation of genes and diseases in PubMed literature. We also illustrated an efficient way to reveal the implicit connections between COPD and other diseases based on this model.

Results: We applied this approach to analyze the relationships between Chronic Obstructive Pulmonary Disease (COPD) and other diseases under the Lung diseases branch in the Medical subject heading index system and detected 4 novel diseases relevant to COPD. As judged by domain experts, the F score of our approach is up to 77.6%.

Conclusions: The results demonstrate the effectiveness of the gene fingerprint model for diseases on the basis of medical literature.

Keywords: COPD; Chronic obstructive pulmonary disease; Disease connection; Gene fingerprint model.

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Competing interests

The authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
Work flow Diagram
Fig. 2
Fig. 2
Illustration of the connections between the 5 diseases through shared genes. The genes in pink are associated with more than 2 diseases
Fig. 3
Fig. 3
IPA identified 17 genes that affect COPD, Pulmonary Sarcoidosis, Lung Injury and Acute Lung Injury. Blue nodes represent genes and red nodes represent diseases. The four diseases discussed in Results section are located in the middle of the circle
Fig. 4
Fig. 4
Connections between Acute Lung Injury, Lung Injury and COPD in the semantic network generated in Semantic MEDLINE
Fig. 5
Fig. 5
Enrichment analysis with DAVID 6.8 of the associated genes for the 4 novel diseases and COPD. Two enriched KEGG pathways shared by the four diseases. a Venn graph to show the number of overlapping enriched KEGG pathways among the 4 diseases. LI: Lung injury; PS: Pulmonary Sarcoidosis; COPD: Chronic Obstructive Pulmonary Disease; ALI: Acute Lung Injury. Two KEGG pathways are shared by the four diseases. b HIF-1 Signaling pathway. c Pathways in cancer. Different colors of the box represent the genes in the pathway that are shared by different diseases. Blue: ALI & COPD; red: ALI & LI & COPD & PS; yellow: ALI & COPD & PS; black: LI & COPD; purple: ALI & LI & COPD; orange: COPD & PS; gray: COPD unique except for LPAR1 which is LI unique. RELA belongs to LI & COPD, ERBB2 belongs to ALI & COPD, MMP2 and MMP9 belong to ALI & LI & COPD, LPAR1 is LI unique. Since they correspond to the same KEGG symbol with other genes, the colors are represented by the first gene in each group
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