A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer's disease progression

BMC Bioinformatics. 2017 Dec 20;18(1):579. doi: 10.1186/s12859-017-1946-8.

Abstract

Background: Alzheimer's disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease.

Results: Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain ("EC", "HIP", "PC", "MTG", "SFG", and "VCX") affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules.

Conclusions: In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst "betweenness centrality" and "degree" of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD.

Keywords: Gene co-expression networks; Hierarchical clustering; Module preservation measures; Rank aggregation.

MeSH terms

  • Alzheimer Disease* / genetics
  • Alzheimer Disease* / metabolism
  • Alzheimer Disease* / physiopathology
  • Brain / metabolism
  • Computational Biology / methods*
  • Disease Progression
  • Gene Expression Profiling / methods*
  • Gene Regulatory Networks / genetics*
  • Humans
  • Transcriptome* / genetics
  • Transcriptome* / physiology