Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

The periphery and the core properties explain the omnigenic model in the human interactome

Bingbo Wang, Kimberly Glass, Annika Röhl, Marc Santolini, Damien C. Croteau-Chonka, Scott T. Weiss, Benjamin A. Raby, Amitabh Sharma
doi: https://doi.org/10.1101/749358
Bingbo Wang
1School of Computer Science and Technology, Xidian University, Xi’an 710071, China.
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kimberly Glass
3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Annika Röhl
3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marc Santolini
2Center for Complex Network Research, Northeastern University, Boston, MA, USA
4The Center for Research and Interdisciplinarity, Paris, France 75004
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Damien C. Croteau-Chonka
3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Scott T. Weiss
3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Benjamin A. Raby
3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amitabh Sharma
2Center for Complex Network Research, Northeastern University, Boston, MA, USA
3Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: amitabh.sharma@channing.harvard.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

Understanding the connectivity patterns of genes in a localized disease neighborhood or disease module in a molecular interaction network (interactome) is a key step toward advancing the knowledge about molecular mechanisms underlying a complex disease. In this work, we introduce a framework that detects peripheral and core regions of a disease in the human interactome. We leverage gene expression data on 104 diseases and analyze the connectivity of differentially expressed genes (quantified by a p-value < 0.05) and their topological membership in the network to distinguish between peripheral and core genes. Per definition, peripheral and core genes are topologically different and we show that they also differ biologically. Core genes are more enriched for Genome-wide association study (GWAS) and Online Mendelian Inheritance in Man (OMIM) data, whereas peripheral genes are more shared across different disease states and their overlap helps predict disease proximity in the human interactome. Based on this observation, we propose a flower model to explain the organization of genes in the human interactome, with core genes of different diseases as the petals and the peripheral genes as the (shared) stem. We show that this network model is an important step towards finding novel drug targets and improving disease classification. Overall, we were able to demonstrate how perturbations percolate through the human interactome and contribute to peripheral and core regions, an important novel feature of the omnigenic model.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted August 29, 2019.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
The periphery and the core properties explain the omnigenic model in the human interactome
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
The periphery and the core properties explain the omnigenic model in the human interactome
Bingbo Wang, Kimberly Glass, Annika Röhl, Marc Santolini, Damien C. Croteau-Chonka, Scott T. Weiss, Benjamin A. Raby, Amitabh Sharma
bioRxiv 749358; doi: https://doi.org/10.1101/749358
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
The periphery and the core properties explain the omnigenic model in the human interactome
Bingbo Wang, Kimberly Glass, Annika Röhl, Marc Santolini, Damien C. Croteau-Chonka, Scott T. Weiss, Benjamin A. Raby, Amitabh Sharma
bioRxiv 749358; doi: https://doi.org/10.1101/749358

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3479)
  • Biochemistry (7318)
  • Bioengineering (5296)
  • Bioinformatics (20196)
  • Biophysics (9976)
  • Cancer Biology (7703)
  • Cell Biology (11250)
  • Clinical Trials (138)
  • Developmental Biology (6417)
  • Ecology (9916)
  • Epidemiology (2065)
  • Evolutionary Biology (13280)
  • Genetics (9352)
  • Genomics (12553)
  • Immunology (7674)
  • Microbiology (18939)
  • Molecular Biology (7417)
  • Neuroscience (40889)
  • Paleontology (298)
  • Pathology (1226)
  • Pharmacology and Toxicology (2126)
  • Physiology (3140)
  • Plant Biology (6838)
  • Scientific Communication and Education (1270)
  • Synthetic Biology (1891)
  • Systems Biology (5296)
  • Zoology (1085)