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免疫细胞特征与多种恶性和非恶性中枢神经系统疾病风险之间的因果关联:孟德尔随机化和单细胞转录组分析

Causal Association Between Immune Cell Traits and Risk of Multiple Malignant and Nonmalignant CNS Diseases: A Mendelian Randomization and Single-Cell Transcriptomic Analysis.

作者信息

Ke Shanbao, Yan Junya, Li Baiyu, Feng Xiao

机构信息

Department of Oncology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital, Henan University People's Hospital, Zhengzhou, China.

出版信息

Brain Behav. 2025 Aug;15(8):e70632. doi: 10.1002/brb3.70632.

Abstract

BACKGROUND

The influence of immune cell traits (ICTs) on the onset of multiple brain diseases has been previously investigated; however, it is limited by the sample size or colocalization evidence. Besides, the impact remains inconclusive.

METHODS

We performed a Mendelian randomization (MR) study to elucidate the causal correlation between significant ICTs and diverse brain disorders and explored the biomarkers linked to glioblastoma (GBM), a form of solid tumor, by integrating expression quantitative trait locus (eQTL) and single-cell RNA sequencing (scRNA-seq) analyses. The nonnegative matrix factorization (NMF) method was utilized to reclassify malignant cells into distinct cell states. Related functional analyses at the scRNA-seq level were also performed.

RESULTS

We examined 731 ICTs across 13 brain disorders; impacts from these ICTs varied a lot across different brain diseases. Such ICTs mainly involved T/natural killer (NK) cell activation, B cell differentiation, and myeloid cell suppression or activation. Pleiotropy or heterogeneity in current results has been checked and excluded via sensitivity analyses. Specifically, colocalization analyses demonstrated protective roles of distinct ICTs in T/B/NK cell panels for amyotrophic lateral sclerosis (ALS) and GBM, while myeloid and human leukocyte antigen (HLA)-associated traits were associated with increased risk of Alzheimer's disease (AD), and then two memory cell traits were linked to the increased risk of major depressive disease (MDD). By NMF, we identified six distinct cell states within GBM cells. Furthermore, we established an eight-marker glioblastoma risk signature (GBRS) using scRNA-seq and eQTL data, with higher GBRS scores observed in the NFkB cluster and EGFR cluster, indicating their highlighted aggression among malignant cells. Epigallocatechin gallate could be an effective treatment candidate targeting the EGFR cluster via markers of SQLE and VCP.

CONCLUSION

Our findings identified causal effects of distinct ICTs on both malignant and nonmalignant brain diseases and underscored the pivotal role of neuroinflammation in their etiology. With combined evidence from eQTL and scRNA-seq, GBM could be better characterized and managed.

摘要

背景

免疫细胞特征(ICTs)对多种脑部疾病发病的影响此前已被研究;然而,该研究受样本量或共定位证据的限制。此外,其影响仍无定论。

方法

我们进行了一项孟德尔随机化(MR)研究,以阐明显著的ICTs与多种脑部疾病之间的因果关系,并通过整合表达定量性状位点(eQTL)和单细胞RNA测序(scRNA-seq)分析,探索与胶质母细胞瘤(GBM,一种实体瘤形式)相关的生物标志物。利用非负矩阵分解(NMF)方法将恶性细胞重新分类为不同的细胞状态。还在scRNA-seq水平上进行了相关的功能分析。

结果

我们研究了13种脑部疾病中的731种ICTs;这些ICTs对不同脑部疾病的影响差异很大。此类ICTs主要涉及T/自然杀伤(NK)细胞活化、B细胞分化以及髓样细胞抑制或活化。通过敏感性分析检查并排除了当前结果中的多效性或异质性。具体而言,共定位分析表明,不同的ICTs在T/B/NK细胞组中对肌萎缩侧索硬化症(ALS)和GBM具有保护作用,而髓样和人类白细胞抗原(HLA)相关特征与阿尔茨海默病(AD)风险增加有关,另外两种记忆细胞特征与重度抑郁症(MDD)风险增加有关。通过NMF,我们在GBM细胞中鉴定出六种不同的细胞状态。此外,我们利用scRNA-seq和eQTL数据建立了一个八标志物胶质母细胞瘤风险特征(GBRS),在NFkB簇和EGFR簇中观察到较高的GBRS评分,表明它们在恶性细胞中具有更强的侵袭性。表没食子儿茶素 gallate可能是一种通过SQLE和VCP标志物靶向EGFR簇的有效治疗候选药物。

结论

我们的研究结果确定了不同的ICTs对恶性和非恶性脑部疾病的因果影响,并强调了神经炎症在其病因学中的关键作用。结合eQTL和scRNA-seq的证据,可以更好地对GBM进行特征描述和管理。

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