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

Y.-Z. Liu, T. Jiang, C.-L. Jiang

National Engineering Laboratory for AIDS Vaccine, School of Life Sciences, Jilin University, Changchun, China. jiangcl@jlu.edu.cn

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• Bioinformatics
• Infectious Diseases

OBJECTIVE: With the ongoing progression of SARS-CoV-2-induced COVID-19, the post-acute COVID-19 syndrome (long COVID) has garnered increasing attention as a novel multisystem disorder. Long COVID-19 has been shown to impact the nervous system, leading to various neurological manifestations, including epilepsy and seizures. Current studies have reported a significant increase in the prevalence and mortality rate of epilepsy in COVID-19 patients. Additionally, COVID-19 exacerbates seizures in patients with epilepsy. However, the mechanisms underlying the impact of COVID-19 on epilepsy remain elusive. This research focused on further identifying and elucidating the molecular mechanisms and biological processes underlying the induction of epilepsy by COVID-19 through bioinformatic methods.

MATERIALS AND METHODS: We retrieved four gene expression datasets related to COVID-19 and epilepsy patients from the GEO and ArrayExpress databases. By crossing the major modules of weighted gene co-expression network analysis (WGCNA), the commonly expressed genes of epilepsy and COVID-19 were identified. By establishing the protein-protein interaction (PPI) network of the common genes, 20 hub genes were recognized through CytoHubba. Furthermore, functional enrichment and immune cell infiltration analyses were conducted to explore the potential mechanisms of COVID-19-related epilepsy.

RESULTS: We identified a total of 373 common genes between the two diseases. The functional enrichment analysis revealed that the common genes were mainly involved in biological processes related to the immune response. Further analysis of the Hub genes revealed the important role of abnormal lipid metabolism in the crosstalk between COVID-19 and epilepsy. LASSO regression identified CD38 and PRKCA as the potential shared diagnostic candidates, which also exhibited excellent diagnostic value in the validation dataset. The immune infiltration analysis showed that activated dendritic cells (DCs) were positively correlated with the phenotypes of both diseases.

CONCLUSIONS: This research revealed the potential mechanisms of COVID-19-related epilepsy, providing novel insights for the prevention, diagnosis, and clinical management strategies of COVID-19-related epilepsy.

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