Glioblastoma (GBM) is one of the most lethal central nervous system malignancies, characterized by complex inflammatory responses and metabolic reprogramming. However, the causal relationships between inflammatory factors, metabolites, and GBM risk remain largely unclear. We conducted a 3-stage Mendelian randomization analysis using data from the FinnGen biobank (341 GBM cases and 314,193 controls) and genome-wide association studies of 91 inflammatory factors and 1400 metabolites. For instrument variable selection, we applied a stringent threshold (P < 1 × 10-5) and performed linkage disequilibrium pruning (r2 < 0.001). We employed inverse variance weighted method as the primary analysis, supplemented with weighted median, simple mode, and weighted mode methods. Sensitivity analyses included heterogeneity tests, pleiotropy assessments, and leave-one-out analyses. Mediation analysis was performed to explore the metabolic pathways linking inflammatory factors to GBM risk. We identified 4 inflammatory factors causally associated with GBM risk: CCL25 (OR = 1.24, 95% CI = 1.02-1.51), M-CSF1 (OR = 1.70, 95% CI = 1.09-2.68), and IL-33 (OR = 1.61, 95% CI = 1.01-2.56) showed risk-increasing effects, while FGF21 (OR = 0.57, 95% CI = 0.37-0.89) demonstrated protective effects. Among 1400 metabolites, 23 showed significant causal associations with GBM risk across multiple statistical methods. The strongest evidence was found for phospholipid metabolism (1-stearoyl-2-oleoyl-GPE, OR = 1.21, 95% CI = 1.08-1.36) and energy metabolism (cAMP/taurocholate ratio, OR = 0.85, 95% CI = 0.77-0.94). Mediation analysis revealed 21 inflammatory factor-metabolite-GBM pathways, with FGF21 showing the most extensive metabolic regulatory network (12 pathways), followed by M-CSF1 (7 pathways) and CCL25 (2 pathways). Our study establishes a causal framework linking peripheral inflammatory factors and metabolic reprogramming to GBM risk, with FGF21 emerging as a potential protective factor. These findings provide novel therapeutic targets and contribute to the development of precision medicine strategies for GBM.
Yang et al. (Fri,) studied this question.