Literature DB >> 28576708

A systems level analysis of epileptogenesis-associated proteome alterations.

Michael Keck1, Ganna Androsova2, Fabio Gualtieri1, Andreas Walker1, Eva-Lotta von Rüden1, Vera Russmann1, Cornelia A Deeg3, Stefanie M Hauck4, Roland Krause5, Heidrun Potschka6.   

Abstract

Despite intense research efforts, the knowledge about the mechanisms of epileptogenesis and epilepsy is still considered incomplete and limited. However, an in-depth understanding of molecular pathophysiological processes is crucial for the rational selection of innovative biomarkers and target candidates. Here, we subjected proteomic data from different phases of a chronic rat epileptogenesis model to a comprehensive systems level analysis. Weighted Gene Co-expression Network analysis identified several modules of interconnected protein groups reflecting distinct molecular aspects of epileptogenesis in the hippocampus and the parahippocampal cortex. Characterization of these modules did not only further validate the data but also revealed regulation of molecular processes not described previously in the context of epilepsy development. The data sets also provide valuable information about temporal patterns, which should be taken into account for development of preventive strategies in particular when it comes to multi-targeting network pharmacology approaches. In addition, principal component analysis suggests candidate biomarkers, which might inform the design of novel molecular imaging approaches aiming to predict epileptogenesis during different phases or confirm epilepsy manifestation. Further studies are necessary to distinguish between molecular alterations, which correlate with epileptogenesis versus those reflecting a mere consequence of the status epilepticus.
Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bioinformatics; Epilepsy; Mass spectrometry; Network; Proteome; Status epilepticus; WGCNA

Mesh:

Substances:

Year:  2017        PMID: 28576708     DOI: 10.1016/j.nbd.2017.05.017

Source DB:  PubMed          Journal:  Neurobiol Dis        ISSN: 0969-9961            Impact factor:   5.996


  8 in total

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  8 in total

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