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

IF 4.8 1区 医学 Q1 NEUROSCIENCES
Jianwei Shi, Jing Xie, Yanfeng Yang, Bin Fu, Zuliang Ye, Ting Tang, Quanlei Liu, Jinkun Xu, Penghu Wei, Yongzhi Shan, Guoguang Zhao
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Abstract

Background

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

Methods

We 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.

Results

We 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.

Conclusions

This 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.

Abstract Image

综合孟德尔随机化和单细胞转录组学分析确定癫痫的关键血液生物标志物和潜在机制。
背景:癫痫具有遗传易感性,但癫痫的病因和免疫环境的动态尚不完全清楚。方法:对癫痫患者外周血样本进行分析,通过孟德尔随机化、eQTLGen和全基因组关联研究,确定与癫痫风险相关的关键基因。采用CIBERSORT方法探讨癫痫患者外周免疫环境的组成。建立癫痫小鼠模型,通过单细胞分析验证关键基因在转录组学和蛋白质组学水平的表达。验证了相关通路。最后,我们建立了癫痫患者抗癫痫药物反应的预测模型。结果:我们发现CDC25B、DNMT1、GZMA、MTX1和SSH2表达降低癫痫风险,而FGD3、RAF1和SH3BP5L表达增加癫痫风险。癫痫患者表现出外周免疫谱的改变,特别是激活肥大细胞增加,CD4记忆激活T细胞和γδ T细胞减少。8个基因与这种免疫环境显著相关。在动物模型中,海马中FGD3、SSH2和DNMT1 mRNA和蛋白水平均上调。FGD3和SSH2在小胶质细胞中特异性升高,主要与肌动蛋白调节有关。将训练好的预测模型部署到在线平台上。结论:本研究阐明了与癫痫相关的关键基因,描绘了癫痫免疫景观,并强调了这些区域之间的相互作用,为潜在的癫痫机制和治疗提供了见解。
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来源期刊
CNS Neuroscience & Therapeutics
CNS Neuroscience & Therapeutics 医学-神经科学
CiteScore
7.30
自引率
12.70%
发文量
240
审稿时长
2 months
期刊介绍: CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.
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