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The Pathway Coexpression Network: Revealing pathway relationships.

Yered Pita-Juárez1, Gabriel Altschuler2, Sokratis Kariotis2

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We developed the Pathway Coexpression Network (PCxN) to map functional interactions between biological pathways using gene coexpression. PCxN reveals novel disease mechanisms and expands pathway relationship insights.

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Area of Science:

  • Genomics
  • Systems biology
  • Bioinformatics

Background:

  • Understanding biological process relationships is a key genomics goal.
  • Existing pathway databases (e.g., KEGG, Reactome) offer discrete annotations but limited global functional interaction data.
  • Current methods for inferring pathway relationships rely on gene set enrichment or simple gene overlap, which can be imprecise.

Purpose of the Study:

  • To establish a comprehensive framework for interpreting functional interactions between biological pathways.
  • To systematically quantify coexpression between canonical pathways to create the Pathway Coexpression Network (PCxN).
  • To demonstrate PCxN's utility in uncovering disease mechanisms, using Alzheimer's Disease (AD) as a case study.

Main Methods:

  • Quantified coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB).
  • Utilized a curated collection of 3,207 microarrays from 72 normal human tissues to estimate pathway correlations.
  • Developed PCxN to account for shared genes, estimating correlations between pathways with related functions, not just similar annotations.

Main Results:

  • Established the Pathway Coexpression Network (PCxN) by systematically quantifying coexpression between 1,330 canonical pathways.
  • Demonstrated PCxN's ability to provide novel insights into complex diseases, exemplified by an Alzheimer's Disease (AD) case study.
  • PCxN identified significantly correlated pathways for AD, including those involved in cell adhesion, oxidative stress, and the extracellular matrix, complementing existing methods.

Conclusions:

  • PCxN offers a unifying interpretation of functional pathway interactions by quantifying coexpression.
  • PCxN provides a powerful new framework for interrogating global pathway relationships and understanding complex biological systems.
  • The PCxN resource (http://pcxn.org/) enables comprehensive exploration of pathway connections and aids in disease mechanism discovery.