Pathway Crosstalk Analysis based on Signaling Pathway Impact Analysis in Alzheimer's Disease

Background: Identifying dysregulated pathways from significant differential expression genes (DEGs) to infer underlying biological insights play an important role in discovering pathogenesis of diseases. However, current pathway-based methods only focus on single pathways in isolation and the analysis of the pathways crosstalk that contains DEGs could improve our understanding of alterations in biological processes. Objective: To explore the underlying dysregulated pathways of Alzheimer's disease (AD) efficiently by the crosstalk analysis on both the significant DEGs and the pathways with high contributions. Method: A novel signaling pathway impact analysis method is used to calculate and rank the signaling pathways of AD. Distance correlation model based on the pathways with ranking contributions is applied to calculate the crosstalk of pathways of AD. Results: The method not only confirms the presence of known pathways associated with AD including Parkinson's disease, Vegf signaling pathway and so on but also predicts the presence of unknown pathways such as Basal cell carcinoma and Olfactory transduction pathways that are significantly associated with the onset and deterioration of AD. Conclusion: The results provide useful supplement and basis for the biological experiments of AD pathogenesis.