Jul 2026· Current Cancer Drug Targets· Vol 26· 0 citations
Medicine
TL;DR
These findings support a neuroimmune model in which pleiotropic germline variants act via microglia and excitatory neurons to link seizure biology with tumor immunity and prognosis, and reveal a common genetic architecture between glioma and epilepsy.
Abstract
Background
Glioma-Related Epilepsy (GRE) is a hallmark comorbidity of Low-Grade Glioma (LGG), yet the cellular and molecular mechanisms through which germline epilepsy susceptibility converges with tumor biology to shape clinical outcomes remain poorly understood.
Methods
Genome-Wide Association Studies (GWAS), expression quantitative trait loci (eQTL) data, single-cell RNA sequencing, and spatial transcriptomics were integrated. Causal inference, phenotype-driven single-cell analyses, and machine learning were applied to identify genetically informed cellular mechanisms underlying GRE.
Results
A total of 68 germline loci shared by glioma and epilepsy (FDRIVW < 0.05) were integrated, with microglia and excitatory neurons as the principal mediating cell types. Four seizure-associated genes (WFIKKN1, WDSUB1, SPARCL1, and CALD1) were subsequently identified in TCGA-LGG, with high-confidence enhancer-promoter support for three of them (colco.PP4 > 0.9). A four-gene signature consistently stratified overall survival across three independent cohorts (TCGA-LGG, CGGA_325, and GSE16011) and correlated with immune checkpoint gene expression. High-risk patients showed higher sensitivity to cyclopamine, according to in silico drug response.
Discussion
These findings support a neuroimmune model in which pleiotropic germline variants act via microglia and excitatory neurons to link seizure biology with tumor immunity and prognosis. At the same time, in silico therapeutic predictions require functional and multi-ancestry validation.
Conclusion
These results reveal a common genetic architecture between glioma and epilepsy, offering candidate biomarkers and therapeutic strategies for the management of GRE.
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, accounting for 60–70% of all dementia cases. The limitations of current therapies and the complexity of its multifaceted pathological mechanisms underscore the urgent need to identify candidate therapeutic targets.
This study aims to systematically identify brain cell type-specific candidate druggable targets for Alzheimer's disease by integrating brain single-cell expression quantitative trait loci (sc-eQTL) data with large-scale genome-wide association studies (GWAS) using Mendelian randomization (MR) and colocalization analysis.
This study integrates sc-eQTL data with large-scale GWAS to systematically assess the causal relationships between gene expression in eight brain cell types and AD risk using MR analysis and colocalization analysis. Target functionality was further analyzed through KEGG pathway analysis and the STRING protein interaction network.
MR analysis prioritized 46 genetically supported candidate druggable genes (FDR < 0.05), of which 10 gene–cell type pairs corresponding to 9 unique genes showed colocalization support. Cell type-specific analysis suggested that these genetically supported associations were restricted to specific brain cell types. Protein–protein interaction analysis with clinical AD drug targets showed that 13% of the candidate targets (6/46) had direct network connections with approved AD drug targets, suggesting potential pharmacological relevance.
This study provides a brain cell type-resolved genetic prioritization framework for AD, nominating genetically supported candidate druggable targets and linking them to neurodegenerative and immune-related pathways. This framework may help generate hypotheses for future experimental validation and drug development.
Renjun Huang, Liqing Guan, Yang Chen et al.· Journal of Alzheimer's Disea...· 0 citations
This review synthesizes contemporary insights into the genetic and molecular pathophysiology of seizures and epilepsy, with emphasis on mechanisms that destabilize excitation–inhibition balance, promote epileptogenesis, and drive pharmacoresistance and supports more refined approaches to epilepsy classification and future precision medicine strategies.
Mohammad Reza Seyedtaghia, Jina Babanzadeh, Marcello Scala et al.· Epilepsia Open· 0 citations
Summary Breast cancer (BC) and psychiatric disorders are epidemiologically linked, raising the possibility of shared genetic influences. Based on the summary statistics from the genome-wide association studies (GWAS), the genetic correlation and overlap between psychiatric disorders and BC were investigated. Shared pleiotropic loci and genes were identified via cross-trait analyses. Functional annotations and tissue-specific enrichment were carried out to determine potential associations. A total of 7,274 pleiotropic single nucleotide polymorphisms (SNPs) were identified by cross-trait analyses. Furthermore, 156 shared genomic risk loci were identified by annotation, of which 19 passed the colocalization test. The gene-level analysis discovered 142 pleiotropic genes, among which MRTFA and FGFR2 were identified in most trait pairs. Pathway enrichment highlighted positive regulation of RNA. Finally, protein quantitative trait locus (pQTL)-based summary-data-based Mendelian randomization (SMR) analyses further prioritized plasma proteins associated with both phenotypes. These findings delineate a common genetic basis for BC and psychiatric conditions, offering insights into their comorbidity.
Canzhou Wang, Jingxi Hu, Yan Lei et al.· iScience· 0 citations
BACKGROUND
Observational studies link hyperthyroidism to increased prostate cancer (PCa) risk, but causality and mechanisms remain unclear. Graves' disease (GD), the primary cause of hyperthyroidism, involves chronic immune dysregulation that may influence PCa through shared immune pathways.
METHODS
We performed bidirectional two-sample Mendelian randomization (MR) using IEU Open GWAS data, then integrated differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning on Gene Expression Omnibus (GEO) datasets to identify shared gene, validated by ROC curves, and analyzed immune profilesusing ssGSEA.
RESULTS
MR analysis indicated that genetic predisposition to GD significantly reduced PCa risk (OR = 0.997, 95% CI = 0.996-0.999, p = 0.004), with consistentsensitivity and no reverse causality. Four key genes (BTG2, JUN, JUNB, FOS) were identified as robust shared genes with high predictive accuracy in external validation. Immune profiles analysis revealed disease-specific associations of these genes: BTG2 and JUNB correlated with memory CD8 T cells in GD, whereas all four genes correlated with dendritic cells, mast cells and NK cells in PCa.
CONCLUSION
This study provided novel insights into the protective effect of GD against PCa and identified shared genes and immune mechanisms, offering a deeper understanding of the common mechanisms between GD and PCa.
Mingshun Zuo, Yuanjian Liao, Qiang Xu et al.· The Aging Male· 0 citations
Background This study aimed to systematically characterize genetically links and Mediation mechanism between glioma susceptibility and brain microstructure, cross-compartment metabolic profiles, and region-specific gene expression, followed by functional validation. Methods Using GWAS data from 12,488 glioma cases and 18,169 controls, we performed two-sample MR (TSMR) and summary data-based MR (SMR) analyses. We evaluated 587 brain imaging-derived phenotypes (IDPs) from diffusion and structural MRI; levels of 962 brain tissue metabolites, 440 cerebrospinal fluid (CSF) metabolites, and 1,400 plasma metabolites; and eQTL based gene expression across 13 brain regions. A two-step MR design was employed for mediation analysis, and the key gene identified, HEATR3, underwent clinical correlation and in vitro functional validation. Results TSMR identified 6 IDPs significantly associated with all glioma subtypes. Specifically, elevated intracellular volume fraction (ICVF) in the corpus callosum and cingulum increased risk, while increased mean diffusivity (MD) in the posterior limb of the right internal capsule was protective. Integrated SMR and TSMR revealed that elevated HEATR3 expression across all 13 brain regions significantly increases glioma risk. Functional experiments confirmed HEATR3 is upregulated in glioma, correlates with poor patient prognosis, and promotes malignant progression in vitro. Mediation analysis showed that HEATR3’s effect on glioma risk is partially mediated by specific white matter IDPs. Metabolic analysis revealed that higher levels of orotate—a product of de novo pyrimidine synthesis—in plasma, CSF, and brain tissue significantly increase GBM risk. Mediation analysis suggested that the effect of plasma orotate on glioma risk is partially mediated by the ICVF in the right cingulum hippocampus. Enrichment analyses indicated that significant regional genes are heavily involved in DNA metabolism and cell cycle pathways. Conclusion This study provides robust multi-layered evidence for the causal roles of white matter microstructural abnormalities, metabolic dysregulation, and regional gene expression in glioma development. These findings offer novel genetic insights and potential therapeutic targets for precision medicine in glioma.
Yufan Wu, Xuezhen Wang, Xinkai Wang et al.· Frontiers in Immunology· 0 citations
Schizophrenia (SCZ) is a highly heritable and complex neuropsychiatric disorder. Emerging evidence implicates dysregulated brain iron, particularly in subcortical regions, in SCZ pathophysiology. Here, we systematically dissected the shared genetic architecture between SCZ and subcortical brain susceptibility phenotypes by integrating large-scale genome-wide association study (GWAS) data with quantitative susceptibility mapping (QSM) phenotypes across 16 subcortical regions. Using the MiXeR framework, we quantified the extent and pattern of shared genetic overlap between SCZ and each QSM phenotype, revealing the strongest overlap in the left and right nucleus accumbens. Conditional and conjunction false discovery rate analyses identified 666 unique shared SNPs. Functional annotation highlighted enrichment in pathways related to synaptic function and neuronal development, with pronounced expression in neurons. Additionally, we characterized their spatio-temporal expression patterns of shared genes and identified 89 significant expression-trait associations linked to SCZ-related phenotypes. Furthermore, the virtual drug screen identified 691 potential protein-drug pairs that may contribute to both iron regulation and SCZ. Our findings provide new insights into the complex interaction between subcortical brain susceptibility phenotypes and SCZ, highlighting pathways that may offer novel therapeutic strategies for SCZ and related brain susceptibility-associated conditions.
Yingying Xie, Jiaojiao Du, Yao Zhao et al.· Schizophrenia· 0 citations