Evidence map›Paper›PMID 39753851›Full record

ArticleCNS neuroscience & therapeutics2025

Integrated Mendelian Randomization and Single-Cell Transcriptomics Analysis Identifies Critical Blood Biomarkers and Potential Mechanisms in Epilepsy.

Jianwei Shi, Jing Xie, Yanfeng Yang, Bin Fu, Zuliang Ye, Ting Tang, Quanlei Liu, Jinkun Xu, Penghu Wei, Yongzhi Shan and 1 more

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. GABACellular and molecular neurobiology · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Jianwei ShiDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-9887-044X
Jing XieDeanery of Biomedical Sciences, Edinburgh Medical School, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh, UK.
Yanfeng YangDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Bin FuChina International Neuroscience Institute, Beijing, China.
Zuliang YeDepartment of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.
Ting TangDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-5952-4023
Quanlei LiuDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Jinkun XuDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.
Penghu WeiDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-4529-7691
Yongzhi ShanDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0000-0001-5510-1026
Guoguang ZhaoDepartment of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-7569-5252

Funding

Beijing Municipal Health Commission 11000022T000000444685Beijing Municipal Health Commission 11000023T000002036286National Natural Science Foundation of China 82030037
6 · The paper itself

Abstract

backgroundEpilepsy has a genetic predisposition, yet causal factors and the dynamics of the immune environment in epilepsy are not fully understood.

methodsWe analyzed peripheral blood samples from epilepsy patients, identifying key genes associated with epilepsy risk through Mendelian randomization, using eQTLGen and genome-wide association studies. The peripheral immune environment's composition in epilepsy was explored using CIBERSORT. An epilepsy mouse model was established to validated the expression of key genes at the transcriptomic and proteomic levels through single-cell analysis. Relevant pathways were verified. Finally, we developed a predictive model for antiepileptic drug response in epilepsy patients.

resultsWe found that CDC25B, DNMT1, GZMA, MTX1, and SSH2 expression decreases epilepsy risk, whereas FGD3, RAF1, and SH3BP5L increase it. Epilepsy patients exhibited an altered peripheral immune profile, notably with increased activated mast cells and decreased CD4 memory activated T cells and γδ T cells. Eight genes were significantly related to this immune environment. In the animal model, FGD3, SSH2, and DNMT1 were upregulated at both mRNA and protein levels in the hippocampus. FGD3 and SSH2 are specifically elevated in microglia and are primarily associated with actin regulation. The trained predictive model was deployed on an online platform.

conclusionsThis study elucidates key genes linked to epilepsy, delineates the epilepsy immune landscape, and highlights the interaction between these domains, providing insights into potential epilepsy mechanisms and treatments.

Indexed as

BiomarkersEpilepsyMendelian Randomization AnalysisAnimalsAnticonvulsantsDNA (Cytosine-5-)-Methyltransferase 1FemaleGene Expression ProfilingGenome-Wide Association StudyHumansMaleMiceMice, Inbred C57BLMicrofilament ProteinsSingle-Cell AnalysisTranscriptomeAnticonvulsantsBiomarkersDNA (Cytosine-5-)-Methyltransferase 1DNMT1 protein, humanDnmt1 protein, mouseMicrofilament Proteinsepilepsykey genesmendelian randomizationrisk incidencesingle‐cell transcriptomics

Identifiers

PMID39753851
PMCPMC11702437

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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.