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Network Analysis of Human Common Complex Diseases

Friday, November 08, 2013 — Poster Session III

10:00 a.m. – 12:00 p.m.

FAES Academic Center (Upper-Level Terrace)

NIA

GEN-2

Authors

  • KG Becker
  • Z Ashour
  • S De
  • Y Zhang

Abstract

Complex multigenic diseases such as cardiovascular disease, metabolic disorders, autoimmune disorders, neurodegenerative disorders and metabolic diseases make up a majority of mortality and morbidity in developed countries, contributing to many age related chronic conditions. Often, related disorders or subphenotypes of disease have overlapping genetic components contributing to overall disease risk. In this study, positive disease associations from the Genetic Association Database (GAD) were used to develop gene sets corresponding to over 1,400 human common disease phenotypes. This included information from candidate gene studies as well as Genome Wide Association Studies (GWAS). These gene sets were then compared to each other to determine gene-gene overlap between disorders. The software package GEPHI was used to visualize disease networks, comparing major disease groups as well as local communities within disease groups. This comparison demonstrates the utility of network analysis of genomic data and visualizes, on a global scale, genetic overlap between and within common disease categories.

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