ArticleDiscover oncology2025
Genetic evidence for causal association between platelet count and glioma risk through Mendelian randomization analysis.
Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundGlioma is the most common primary brain tumor in adults, with glioblastoma (GBM) being the most aggressive subtype. The causal relationship between platelet count and glioma risk remains unclear. This study aimed to evaluate this relationship using Mendelian randomization (MR) methodology.
methodsWe performed MR analysis using 707 platelet count-associated SNPs as instrumental variables, validated by three statistical methods (IVW radial, Maximum likelihood, and MR IVW). Genome-wide association study (GWAS) identified glioma susceptibility loci. We also measured mRNA expression of 4 platelet-related genes (THPO, GP6, ITGA2B, MPL) in glioma cell lines (U87-MG and U251-MG) and normal astrocytes (NHA) using qRT-PCR.
resultsMR analysis demonstrated that genetically determined increased platelet count significantly reduces glioma risk (OR: 0.721-0.724, 95% CI: 0.554-0.938, P < 0.05), representing approximately 27-28% risk reduction per standard deviation increase. GWAS identified multiple susceptibility loci across chromosomes 1, 5, 7, 8, 9, 11, 16, and 20. This protective association was confirmed in GBM subtype analysis (OR: 0.65-0.95). All 4 platelet-related genes showed significant downregulation in glioma cells compared to normal astrocytes (P < 0.001), with expression ranging from 0.31 to 0.48-fold of controls.
conclusionsThis study establishes a causal relationship between platelet count and glioma risk through genetic evidence. Increased platelet count confers protection against glioma, including GBM. Suppressed expression of platelet-related genes in glioma cells supports this finding. These results provide new insights into glioma pathogenesis and suggest potential for platelet-based prevention strategies and biomarker development.
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