Integrated Proteomics and Protein Co-expression Network Analysis Identifies Novel Epileptogenic Mechanism in Mesial Temporal Lobe Epilepsy.

Abstract

Over 50 million people worldwide are affected by epilepsy, a common neurological disorder that has a high rate of drug resistance and diverse comorbidities such as progressive cognitive and behavioural disorders, and increased mortality from direct or indirect effects of seizures and therapies. Despite extensive research with animal models and human studies, limited insights have been gained into the mechanisms underlying seizures and epileptogenesis, which has not translated into significant reductions in drug resistance, morbidities, or mortality. To better understand the molecular signaling networks associated with seizures in MTLE patients, we analyzed the proteome of brain samples from MTLE and control cases using an integrated approach that combines mass spectrometry-based quantitative proteomics, differential expression analysis, and co-expression network analysis. Our analyses of 20 human brain tissues from MTLE patients and 20 controls showed the organization of the brain proteome into a network of 9 biologically meaningful modules of co-expressed proteins. Of these, 6 modules are positively or negatively correlated to MTLE phenotypes with hub proteins that are altered in MTLE patients. Our study is the first to employ an integrated approach of proteomics and protein co-expression network analysis to study patients with MTLE. Our findings reveal a molecular blueprint of altered protein networks in MTLE brain and highlight dysregulated pathways and processes including altered cargo transport, neurotransmitter release from synaptic vesicles, synaptic plasticity, proteostasis, RNA homeostasis, ion transport and transmembrane transport, cytoskeleton disorganization, metabolic and mitochondrial dysfunction, blood micro-particle function, extracellular matrix organization, immune response, neuroinflammation, and cell signaling. These insights into MTLE pathogenesis suggest potential new candidates for future diagnostic and therapeutic development.