Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditionsReport as inadecuate




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Journal of Translational Medicine

, 12:99

Computational Modelling and Epidemiology

Abstract

BackgroundHuman 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.

MethodsOur 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.

ResultsBy 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.

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

KeywordsComorbidity Protein–protein interaction Attack tolerance Electronic supplementary materialThe online version of this article doi:10.1186-1479-5876-12-99 contains supplementary material, which is available to authorized users.

Hyojung Paik, Hyoung-Sam Heo contributed equally to this work.

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Author: Hyojung Paik - Hyoung-Sam Heo - Hyo-jeong Ban - Seong Beom Cho

Source: https://link.springer.com/







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