Combined transcriptomics and proteomics forecast analysis for potential biomarker in the acute phase of temporal lobe epilepsy

Abstract

BackgroundTemporal lobe epilepsy (TLE) is a common chronic episodic illness of the nervous system. However, the precise mechanisms of dysfunction and diagnostic biomarkers in the acute phase of TLE are uncertain and hard to diagnose. Thus, we intended to qualify potential biomarkers in the acute phase of TLE for clinical diagnostics and therapeutic purposes.MethodsAn intra-hippocampal injection of kainic acid was used to induce an epileptic model in mice. First, with a TMT/iTRAQ quantitative labeling proteomics approach, we screened for differentially expressed proteins (DEPs) in the acute phase of TLE. Then, differentially expressed genes (DEGs) in the acute phase of TLE were identified by linear modeling on microarray data (limma) and weighted gene co-expression network analysis (WGCNA) using the publicly available microarray dataset GSE88992. Co-expressed genes (proteins) in the acute phase of TLE were identified by overlap analysis of DEPs and DEGs. The least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) algorithms were used to screen Hub genes in the acute phase of TLE, and logistic regression algorithms were applied to develop a novel diagnostic model for the acute phase of TLE, and the sensitivity of the diagnostic model was validated using receiver operating characteristic (ROC) curves.ResultsWe screened a total of 10 co-expressed genes (proteins) from TLE-associated DEGs and DEPs utilizing proteomic and transcriptome analysis. LASSO and SVM-RFE algorithms for machine learning were applied to identify three Hub genes: Ctla2a, Hapln2, and Pecam1. A logistic regression algorithm was applied to establish and validate a novel diagnostic model for the acute phase of TLE based on three Hub genes in the publicly accessible datasets GSE88992, GSE49030, and GSE79129.ConclusionOur study establishes a reliable model for screening and diagnosing the acute phase of TLE that provides a theoretical basis for adding diagnostic biomarkers for TLE acute phase genes.

Integrating Proteomics and Transcriptomics Reveals the Potential Pathways of Hippocampal Neuron Apoptosis in Dravet Syndrome Model Mice

“…These results suggest that DEGs may be involved in the apoptosis of hippocampal neurons in Scn1a mice. The KEGG results show that the DEPs play a role in synaptic function, neurotransmission, the cell cycle, and immune function, and that the DEGs play a role in neurotransmission, the cell cycle, apoptosis, and neuroinflammation, which is consistent with the results of Huang et al [41].…”

Low-density lipoprotein receptor-related protein-1 (LRP1) in the glial lineage modulates neuronal excitability

“…This opens the perspective that seizures may be rooted in a neurodevelopmental deficit affecting the neural stem cell compartment. The identification of the genes and pathways involved may in the future benefit from the application of genomic and transcriptomic strategies to the mouse model ( Busch et al, 2022 ; Lariviere et al, 2022 ; Pai et al, 2022 ; Assis-Mendonca et al, 2023 ; Chung et al, 2023 ; Huang et al, 2023 ).…”