Journal of Translational Medicine, 2014, 01, 1─8

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

Paik H, Heo HS, Ban HJ, Cho SB

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

• ISBN or ISSN: 1479-5876

• 본 연구는 질병관리본부 연구개발과제(과제번호 2012-NG72001-00) 연구비를 지원받아 수행되었습니다.
• This research was supported by a fund(code 2012-NG72001-00) by Research of Korea Centers for Disease Control and Prevention.