A systems level analysis of epileptogenesis-associated proteome alterations

• Published in: Neurobiology of disease 2017-09, Vol.105, p.164-178
• Main Authors: Keck, Michael, Androsova, Ganna, Gualtieri, Fabio, Walker, Andreas, von Rüden, Eva-Lotta, Russmann, Vera, Deeg, Cornelia A, Hauck, Stefanie M, Krause, Roland, Potschka, Heidrun
• Format: Article
• Language: English
• Subjects: Animals; Bioinformatics; Brain - drug effects; Brain - metabolism; Chromatography, Liquid; Disease Models, Animal; Epilepsy; Female; Gene Regulatory Networks; Mass spectrometry; Muscarinic Agonists - toxicity; Network; Neurology; Pilocarpine - toxicity; Principal Component Analysis; Proteome; Proteome - genetics; Proteome - metabolism; Rats; Rats, Sprague-Dawley; Signal Transduction - drug effects; Signal Transduction - genetics; Status epilepticus; Status Epilepticus - chemically induced; Status Epilepticus - metabolism; Status Epilepticus - pathology; Tandem Mass Spectrometry; Time Factors; WGCNA
• ISSN: 0969-9961; 1095-953X
• DOI: 10.1016/j.nbd.2017.05.017

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.