Evidence map›Paper›PMID 40579353›Full record

ArticleNeurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics2025

Identification of plasma SEMA3E as the diagnostic biomarker for human epilepsy based on integrated bioinformatics analysis.

Xiaxin Yang, Jianhang Zhang, Si Chen, Zhong Yao, Shuo Xu

Abstract read
In one paragraph

Article in Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaxin YangDepartment of Neurology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Jianhang ZhangDepartment of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China.
Si ChenDepartment of Neurology, Qilu Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.
Zhong YaoDepartment of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China.
Shuo XuDepartment of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, Jinan, Shandong, China. Electronic address: xushuo@sdu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite advances in understanding epilepsy, challenges persist in identifying accessible and reliable biomarkers. In this study, an integrative analysis was conducted with transcriptomic data from both brain tissue and blood of epilepsy patients to identify common differentially expressed genes (DEGs). Using weighted gene co-expression network analysis (WGCNA), least absolute shrinkage and selection operator (LASSO) regression, and logistic regression, a robust epilepsy gene signature was constructed, and a hub gene associated with seizure frequency was identified. Single-cell RNA analysis, functional investigation, and clinical verification were subsequently conducted. Herein, we reported that the hub gene SEMA3E was significantly upregulated in both peripheral blood and epileptic brain tissue, with a positive correlation to seizure frequency. Subsequent analysis revealed that SEMA3E was enriched in excitatory neurons with NRP1 and VEGFR2, contributing to epileptogenesis by enhancing axonal growth. Clinical validation demonstrated that plasma SEMA3E levels were significantly elevated in epilepsy patients and correlated with specific clinical features. Unlike tissue biomarkers, blood-based SEMA3E exhibits advantages such as non-invasiveness and cost-effectiveness, making it suitable for large-scale screening and monitoring. This study highlights SEMA3E as a promising biomarker and therapeutic target for epilepsy, offering novel insights into its molecular and clinical relevance.

Indexed as

Computational BiologyEpilepsySemaphorinsAdultBiomarkersFemaleHumansMaleBiomarkersSEMA3E protein, humanSemaphorinsBioinformatic analysisBiomarkerEpilepsyExcitatory neuronsSEMA3E

Identifiers

PMID40579353
PMCPMC12491810

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.