WGCNA combined with GSVA to explore biomarkers of refractory neocortical epilepsy.

Abstract

About two-thirds of epilepsy patients relapse within five years after surgery. It is significant to note that the limitations of current treatments stem from a lack of understanding of molecular mechanisms. In this study, Weighted Gene Co-expression Network Analysis (WGCNA) and Gene set variation analysis (GSVA) methods were used to analyze the total RNA data from 20 surgical removal samples (epileptogenic zone and irritative zone, EZ and IZ) of 10 Chinese patients with refractory neocortical epilepsy downloaded from the original microarray dataset (GSE31718) of the National Center for Biological Information -Gene Expression Omnibus database (NCBI-GEO). The late stages of the estrogen response pathway, the IL6-JAK-STAT3-signal pathway and G2 checkpoints are correlated with the EZ, whereas the early stages of the estrogen response pathway and TGF-β signal are more strongly expressed in the IZ. The allogeneic rejection, apical surface and the TGF-β signal are relevant to the high seizure frequency, the unfolded protein response and MYC-target are mostly expressed in patients with low-frequency seizures. Genes with high gene significance(GS) values that were correlated with seizure frequency include OSR2, CABP4, CAPSL, CYP4F8, and FRK in the pink module, and SH3GLB2, CHAC1 and DDX23 in the yellow module. The occurrence of EZ and IZ act on different biological mechanisms. The upregulated genes associated with seizure frequency include OSR2, CABP4, CAPSL, CYP4F8, and FRK, and the downregulated genes include SH3GLB2, CHAC1 and DDX23. The evidence of key genes and differential pathways obtained by WGCNA and GSVA may be biomarkers for novel preventive and pharmacological interventions in clinical practice.