Metabolity płynu mózgowo-rdzeniowego i obrazowanie mózgu w różnych typach epilepsji: randomizacja Mendela i analiza wielu danych biologicznych
Cerebrospinal Fluid Metabolites and Brain Imaging in Epilepsy Subtypes: Mendelian Randomization and Multi-Omics Analysis
W skrócie
Badacze zbadali powiązania między substancjami w płynie dookoła mózgu, obrazami mózgu oraz epilepsją, aby znaleźć geny i możliwe leki, które mogą pomóc w leczeniu. Znaleźli 14 substancji chroniących przed ogniskową epilepsją i zidentyfikowali trzy główne geny (DAB1, ITGA8, RORA), które mogą odpowiadać za uszkodzenia określonych komórek mózgu. Odkrycia sugerują, że zmiany metaboliczne i strukturalne w mózgu mogą pojawiać się wcześniej niż symptomy epilepsji i mogą być ważnym kierunkiem dla nowych sposobów leczenia.
Oryginalny abstract (angielski)
BACKGROUND: Epilepsy is a complex neurological disorder significantly influenced by genetic factors. Observational studies can identify associations, but cannot establish causality. Mendelian randomization (MR) offers a robust tool for identifying etiology. Therefore, using multi-omics, we explored genetically proxied associations among cerebrospinal fluid metabolites, neuroimaging phenotypes, and epilepsy to prioritize candidate genes and potential therapeutic targets. METHODS: Leveraging data from genome-wide association studies, gene expression databases, and the UK Biobank, we performed two-sample MR analyses. Immune infiltration was assessed using multiple algorithms, transcription factors predicted using RcisTarget, and key genes prioritized through single-nucleotide polymorphism annotation and localization using single-cell RNA sequencing. RESULTS: We identified genetically proxied associations between 14 cerebrospinal fluid metabolites and focal epilepsy (11 protective, three risk-associated), with 13 confirmed using reverse MR. Additionally, 259 neuroimaging phenotypes showed significant associations with focal epilepsy. DAB1, ITGA8, and RORA were the top-ranked genes, localized to inhibitory neurons, oligodendrocyte precursor cells, and astrocytes, respectively. DISCUSSION: These findings demonstrate cell-specific pathology beyond standard neuronal activity. Mechanistically, DAB1 contributes to defects in inhibitory circuits, potentially disrupting excitation-inhibition balance, ITGA8 to matrix or myelin abnormalities in oligodendrocyte precursor cells, and RORA to astrocyte-mediated metabolic regulation and neuroinflammation. These robust metabolic and structural associations suggest that these features may represent early endophenotypes preceding clinical symptoms. CONCLUSION: By integrating multi-omics data, we identified a candidate gene-metabolite-imaging feature network potentially involved in epileptogenesis. The prioritized glial and neuronal targets offer hypothesis-generating insights for future mechanistic studies, precision medicine approaches, and translational research in epilepsy.