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

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

Volume: 15 Issue: 2

Author(s): Jin Deng, Wei Kong*, Xiaoyang Mou and Shuaiqun Wang

Affiliation:

• College of Information Engineering, Shanghai Maritime University, 1550 Haigang Ave., Shanghai 201306,China

Keywords: DEGs, pathway-based, crosstalk, distance correlation, Alzheimer's disease, ranking contributions.

Abstract: 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.

Cite this article as:

Deng Jin , Kong Wei *, Mou Xiaoyang and Wang Shuaiqun , Pathway Crosstalk Analysis based on Signaling Pathway Impact Analysis in Alzheimer's Disease, Current Proteomics 2018; 15 (2) . https://dx.doi.org/10.2174/1570164614666171030162949