TITLE:
Early Detection of Temporal Lobe Epilepsy: Identification of Novel Candidate Genes and Potential Biomarkers Using Integrative Genomics Analysis
AUTHORS:
Vishruth Nagam
KEYWORDS:
Temporal Lobe Epilepsy (TLE), Gene Expression, Fold Change Values, Gene Ontology, Candidate Genes, Keyword Search, Four Individual Donors, STRING Enriched Functions, Protein, Genes Highest Fold
JOURNAL NAME:
Open Journal of Genetics,
Vol.10 No.4,
December
30,
2020
ABSTRACT: Currently afflicting more than 50 million people worldwide, epilepsy is the spectrum disorder characterizing seizures that occur without other plausible medical explanations. Temporal lobe epilepsy (TLE) is one of the most common forms of epilepsy. Current clinical methods; including MRI scans, EEG tests, and doctor visits; can take upwards of several months to confirm a TLE diagnosis; during this time, patients may experience additional seizures and are at an increased risk for other psychiatric disorders. The purpose of this study is to identify candidate genetic biomarkers to facilitate the earlier detection and diagnosis of TLE through gene-based testing (e.g., genomic heatmap analysis or genetic and/or microarray testing). It was hypothesized that potential biomarkers could be identified by analyzing genes that are normally significantly overexpressed in the temporal lobe relative to the gray matter. Statistical and functional analysis was performed on significantly overexpressed genes (≥3.000 fold change) in the gene expression profiles of four donors without epilepsy. The experimental-evidence-based STRING protein interactions analysis showed associations between genes found in DAVID keyword search and other genes facilitating network interconnectivity. After evaluation of the genes’ STRING enriched functions, changes in the expression of the genes CAMK2A, NPY, DLG4, MEF2C, and MAPK7 were concluded to be potential biomarkers for TLE, confirming the original hypothesis. Specifically, the identification of MEF2C and MAPK7 for this purpose is relatively novel in the fields of bioinformatics and neurogenetics. Future work includes investigating the utility of the candidate genes in real-world gene-based diagnostic methods.