title: Unraveling human protein interaction networks underlying co-occurrences of diseases and pathological conditions.
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.
  
  
  CONCLUSIONS
  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.
authors.forename: Hyojung
authors.initials: H
authors.lastname: Paik
authors.forename: Hyoung-Sam
authors.initials: HS
authors.lastname: Heo
authors.forename: Hyo-jeong
authors.initials: HJ
authors.lastname: Ban
authors.affiliation: 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. sbcho@korea.kr.
authors.forename: Seong Beom
authors.initials: SB
authors.lastname: Cho
mesh_terms: D004194:Disease; D006801:Humans; D006278:Medicare; D011485:Protein Binding; D011506:Proteins / Q000378:metabolism*; D014481:United States
chemical_list: D011506:Proteins
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