Background: Dysregulated pathway identification is an important task which can gain
insight into the underlying biological processes of disease. Current pathway-identification methods
focus on a set of co-expression genes and single pathways and ignore the correlation between genes
Objective: This study takes into account the internal correlations not only between genes but also
pathways to explore the underlying dysregulated pathways of Alzheimer's disease (AD), the most
common form of dementia.
Methods: In order to find the significantly differential genes for AD, mutual information (MI) is
used to measure interdependencies between genes other than expression valves. Then, by integrating
the topology information from KEGG, the significant pathways involved in the feature genes are
identified. Next, the distance correlation (DC) is applied to measure the pairwise pathway crosstalks
since DC has the advantage of detecting nonlinear correlations when compared to Pearson
correlation. Finally, the pathway pairs with significantly different correlations between normal and
AD samples are known as dysregulated pathways.
Results: We identified 33 dysregulated pathway pairs related to AD in which the crosstalks score
calculated by DC greatly changed from normal to AD samples. The molecular biology analysis
demonstrated that many dysregulated pathways related to AD pathogenesis have been discovered
successfully by the internal correlation detection.
Conclusion: Our studies on the identification of the dysregulated pathways in the development and
deterioration of AD will help to find new effective target genes which are closely related to the
pathogenesis of AD and provide important theoretical guidance for drug design.