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Войти в исследования European journal of pharmacology · 2026
Cerebrospinal fluid metabolites and brain imaging in epilepsy subtypes: Mendelian randomization and multi-omics analysis.
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Sun Huaiyu, Li Xuewei, Zhao Weixuan, Meng Hongmei, Zhang Wuqiong
Аннотация
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.
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.