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Open Access Highly Accessed Research

Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditions

Hyojung Paik123, Hyoung-Sam Heo1, Hyo-jeong Ban14 and Seong Beom Cho1*

  • * Corresponding author: Seong B Cho sbcho@korea.kr

  • † Equal contributors

Author Affiliations

1 Division of Bio-Medical Informatics, Center for Genome Science, National Institute of Health, OHTAC, 187 Osongsaengmyeong2(i)-ro, Gangoe-myeon, Cheongwon-gun, ChoongchungBuk-do, South Korea

2 Department of Pediatrics and the Department of Medicine, Stanford University School of Medicine, 94305 Stanford, CA, USA

3 Lucile Packard Children’s Hospital, 725 Welch Road, 94304 Palo Alto, CA, USA

4 Division of Molecular and Life Sciences, Hanyang University, Gyeonggi-do 425-791, Ansan, South Korea

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Journal of Translational Medicine 2014, 12:99  doi:10.1186/1479-5876-12-99

Published: 14 April 2014

Abstract

Background

Human diseases frequently cause complications such as obesity-induced diabetes and share numbers of pathological conditions, such as inflammation, by dysfunctions of common functional modules, such as protein–protein interactions (PPIs).

Methods

Our developed pipeline, ICod (Interaction analysis for disease Comorbidity), grades similarities between pairs of disease-related PPIs including comorbid diseases and pathological conditions. ICod displayed a disease similarity network consisting of nodes of disease PPIs and edges of similarity value. As a proof of concept, eight complex diseases and pathological conditions, such as type 2 diabetes, obesity, inflammation, and cancers, were examined to discover whether PPIs shared between diseases were associated with comorbidities.

Results

By comparing Medicare reports of disease co-occurrences from 31 million patients, the disease similarity network shows that PPIs of pathological conditions, including insulin resistance, and inflammation, overlap significantly with PPIs of various comorbid diseases, including diabetes, obesity, and cancers (p < 0.05). Interestingly, maintaining connectivity between essential genes was more drastically perturbed by removing a node of a disease-related gene rather than a pathological condition-related gene, such as one related to inflammations.

Conclusion

Thus, PPIs of pathological symptoms are underlying functional modules across diseases accompanying comorbidity phenomena, whereas they contribute only marginally to maintaining interactions between essential genes.

Keywords:
Comorbidity; Protein–protein interaction; Attack tolerance