Bioinformatic analysis identified common pathogenetic processes between epilepsy and COVID-19.

Area of Science:

• Neurology
• Infectious Diseases
• Bioinformatics

Background:

• Long COVID (post-acute COVID-19 syndrome) presents neurological manifestations, including epilepsy and seizures.
• COVID-19 increases epilepsy prevalence and mortality, and exacerbates seizures in existing epilepsy patients.
• The molecular mechanisms linking COVID-19 to epilepsy remain largely unknown.

Purpose of the Study:

• To elucidate the molecular mechanisms and biological processes underlying COVID-19-induced epilepsy using bioinformatic approaches.
• To identify shared genes and pathways between COVID-19 and epilepsy.

Main Methods:

• Utilized weighted gene co-expression network analysis (WGCNA) on gene expression datasets from COVID-19 and epilepsy patients.
• Constructed a protein-protein interaction (PPI) network to identify hub genes.
• Performed functional enrichment and immune cell infiltration analyses.

Main Results:

• Identified 373 common genes between COVID-19 and epilepsy, primarily involved in immune responses.
• Highlighted abnormal lipid metabolism as a crucial factor in the interplay between COVID-19 and epilepsy.
• Discovered CD38 and PRKCA as potential shared diagnostic markers and found activated dendritic cells correlated with disease phenotypes.

Conclusions:

• Revealed potential molecular mechanisms driving COVID-19-related epilepsy.
• Provided novel insights for the prevention, diagnosis, and clinical management of COVID-19-associated epilepsy.