Identification and enrichment of potential pathways in the buffy coat of patients with DRE using non-targeted metabolomics integrated with GEO Datasets

利用非靶向代谢组学结合GEO数据集,鉴定和富集DRE患者白细胞层中的潜在通路

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Abstract

BACKGROUND: This study aims to identify potential biomarkers in the buffy coat of drug-resistant epilepsy (DRE) patients with mesial temporal lobe epilepsy and to elucidate associated pathways. METHODS: A comprehensive non-targeted metabolomic and Gene Expression Omnibus (GEO) datasets analysis was first performed on buffy coat from DRE patients and non-epilepsy (CON) patients. Potential enriched biomarkers and pathways were integrated with gene expression profiles from GEO datasets to identify robust biomarkers. RESULTS: In the DRE group, there were 15 patients (10 males and 5 females), with an average age of (37.67 ± 15.53) years. In the CON group, there were 10 patients (7 males and 3 females), with an average age of (51.60 ± 18.20) years. A total of 27 potential biomarkers were identified, including 7 down-regulated and 8 up-regulated. Additionally, 9 potential pathways related to DRE were identified. Notably, purine metabolism, tryptophan metabolism and aminoacyl-tRNA metabolism were closely related to DRE. Purine metabolism was up-regulated, while aminoacyl-tRNA and tryptophan metabolism were down-regulated. CONCLUSIONS: The integration of metabolomic data with GEO datasets analysis offers a new strategy to identify robust biomarkers and pathways. The findings obtained from the buffy coat analysis offer potential insights for the diagnosis and treatment of DRE.

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