Search PubMed⌕ Search
Home/Archive/PubMed

PubMed · 38905914

Exploring correlations between immune cell phenotypes and the risk of epilepsy: A bidirectional Mendelian randomization study.

Zhiqing Chen·Huaiyu Sun·Wuqiong Zhang·Shuai Hou·Xi Yang·Jingqi Lin·Xiaohui Ma·Hongmei Meng
View original source ↗Export metadata ↓

Abstract

BACKGROUND: Neuroinflammation plays an important pathophysiological role in epilepsy; however, the precise connection between immune cells and epilepsy remains unclear. This study used Mendelian randomization (MR) to analyze the causal relationship between 731 immune cell traits and epilepsy. METHODS: Based on data from a genome-wide association study (GWAS), a bidirectional two-sample MR analysis was conducted to investigate the potential influence of immune cell phenotypes on epilepsy. Five MR methods were used to analyze the results, with the inverse variance weighted (IVW) method as the primary method, and the results were corrected using the false discovery rate (FDR) method. Sensitivity analyses were performed to test for heterogeneity and horizontal pleiotropy. RESULTS: After correction for FDR, four immune traits remained significantly associated with epilepsy risk: CD25 expression on memory (OR = 1.04, 95 % CI = 1.02 ∼ 1.06,P = 2.55 × 10-4), IgD+CD38dim (OR = 1.05, 95 % CI = 1.02 ∼ 1.08, P = 4.73 × 10-4), CD24+CD27+ (OR = 1.04, 95 % CI = 1.02 ∼ 1.06, P = 4.82 × 10-4), and IgD-CD38dim (OR = 1.04, 95 % CI = 1.02 ∼ 1.06, P = 1.04 × 10-3) B cells. The risk of generalized epilepsy was significantly associated with two immune cell traits, whereas that of focal epilepsy was significantly associated with seven immune cell traits. Furthermore, immune cell phenotypes are not affected by genetically predicted epilepsy. CONCLUSION: This MR study affirms the causal connection between circulating immune cells and epilepsy, offering guidance for further understanding of the immune mechanisms that underlie epilepsy and the discovery of novel targets for therapy.

Explore related subjects

HumansMendelian Randomization AnalysisEpilepsyGenome-Wide Association StudyPhenotypeGenetic Predisposition to DiseasePolymorphism, Single NucleotideImmune cellsMendelian randomizationNeuroinflammationJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zhiqing Chen, Huaiyu Sun, Wuqiong Zhang, Shuai Hou, Xi Yang, Jingqi Lin, Xiaohui Ma, Hongmei Meng. 2024-06-20. Exploring correlations between immune cell phenotypes and the risk of epilepsy: A bidirectional Mendelian randomization study.. https://doi.org/10.1016/j.yebeh.2024.109896

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2027

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗
PubMed2027

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗
PubMed2027

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗