Identyfikacja markerów biologicznych związanych z dysfunkcją mitochondriów i analiza nacieku komórek immunologicznych w epilepsji
Identification of Mitochondrial Dysfunction-Related Candidate Biomarkers and Analysis of the Immune Cell Infiltration in Epilepsy
W skrócie
Badacze odkryli trzy białka (Nubpl, Tspo i Idi1), które mogą być odpowiedzialne za zaburzenia działania mitochondriów (organelli dostarczających energię komórkom) u pacjentów z epilepsją. Białka Nubpl i Tspo były podwyższone u chorych i wiąże się z nimi nieprawidłowa aktywność komórek odpornościowych, szczególnie komórek tłumiących i regulatorowych, które mogą sprzyjać rozwojowi i utrzymywaniu się padaczki. Wyniki sugerują, że dysfunkcja mitochondriów przyczynia się do epilepsji poprzez zaburzenia zarówno energetyczne komórek, jak i poprzez wpływ na układ immunologiczny, co otwiera nowe możliwości leczenia.
Oryginalny abstract (angielski)
Epilepsy is a severe neurological disorder with complex pathogenesis. Mitochondrial dysfunction (MitD) is increasingly recognized as a key driver of epileptogenesis and seizure generation, contributing to neuronal hyperexcitability and network instability. However, the potential mechanisms linking MitD to epilepsy remain incompletely understood. This study aimed to identify MitD-related biomarkers in epilepsy and investigate their associations with alterations in the immune cell infiltration landscape during epileptogenesis. On the basis of the GSE47752 dataset, differential expression analysis was performed to identify differentially expressed genes (DEGs) between the control group and epilepsy groups in the early phase after status epilepticus (SE). The intersection of DEGs across time points yielded core DEGs, which were further intersected with MitD-related genes (MDRGs) to obtain MitD-related differentially expressed genes (MDR-DEGs). Multiple machine learning algorithms (LASSO, Boruta, XGBoost, and SVM-RFE) were applied to identify robust candidate biomarkers through consensus feature selection strategies, prioritizing genes with high stability across different algorithms. Importantly, immune infiltration was analyzed via the single-sample gene set enrichment analysis (ssGSEA) algorithm to characterize the immunological microenvironment in epilepsy. Finally, the expression of candidate biomarkers was validated via RT-qPCR in hippocampal tissues from a lithium-pilocarpine (Li-Pilo) rat model. Machine learning consensus pinpointed three candidate biomarkers: Idi1, Nubpl, and Tspo. Single-gene gene set enrichment analysis (GSEA) revealed that Nubpl and Tspo were significantly enriched in the complement and coagulation cascades pathway. Immune infiltration analysis revealed a substantial increase in the abundance of myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs). The expression of Nubpl and Tspo was strongly positively correlated with that of most of these differentially infiltrated immune cell subsets. RT-qPCR confirmed that Nubpl and Tspo mRNA levels were significantly elevated in the early phase post-SE compared with those in controls, whereas the change in Idi1 expression was not statistically significant. Nubpl and Tspo were identified as key candidate biomarkers associated with MitD in epilepsy. The candidate biomarkers may contribute to epileptogenesis not only through direct mitochondrial pathways but also through crosstalk between complement and coagulation cascades and immune cell dynamics. These findings offer novel insights into the integrative molecular and immunological mechanisms linking MitD to epilepsy, highlighting potential therapeutic targets.