Literature DB >> 26675399

Comparison of Perturbed Pathways in Two Different Cell Models for Parkinson's Disease with Structural Equation Model.

Daniele Pepe1, Jin Hwan Do2.   

Abstract

Increasing evidence indicates that different morphological types of cell death coexist in the brain of patients with Parkinson's disease (PD), but the molecular explanation for this is still under investigation. In this study, we identified perturbed pathways in two different cell models for PD through the following procedures: (1) enrichment pathway analysis with differentially expressed genes and the Reactome pathway database, and (2) construction of the shortest path model for the enriched pathway and detection of significant shortest path model with fitting time-course microarray data of each PD cell model to structural equation model. Two PD cell models constructed by the same neurotoxin showed different perturbed pathways. That is, one showed perturbation of three Reactome pathways, including cellular senescence, chromatin modifying enzymes, and chromatin organization, while six modules within metabolism pathway represented perturbation in the other. This suggests that the activation of common upstream cell death pathways in PD may result in various down-stream processes, which might be associated with different morphological types of cell death. In addition, our results might provide molecular clues for coexistence of different morphological types of cell death in PD patients.

Entities:  

Keywords:  gene expression; graphs and networks; statistical models

Year:  2015        PMID: 26675399     DOI: 10.1089/cmb.2015.0156

Source DB:  PubMed          Journal:  J Comput Biol        ISSN: 1066-5277            Impact factor:   1.479


  1 in total

1.  Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling.

Authors:  Anna A Igolkina; Chris Armoskus; Jeremy R B Newman; Oleg V Evgrafov; Lauren M McIntyre; Sergey V Nuzhdin; Maria G Samsonova
Journal:  Front Mol Neurosci       Date:  2018-06-11       Impact factor: 5.639

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.