Integrating exposome data with multi-omics and AI for diffuse glioma biomarker discovery

Review argues for systematically integrating environmental, occupational, and lifestyle exposures with AI and multi-omics to improve diffuse glioma biomarker discovery, proposing applications in high-risk surveillance, recurrence monitoring, and treatment-toxicity reduction, whi…

• The synthesis addresses five dimensions: limits of AI models lacking exposure data, glioma-relevant exposures by evidence strength, mechanistic conduits (genotoxic, epigenetic, vascular, neuroimmune), computational strategies for multi-scale data integration, and translational applications in surveillance and trial stratification.
• Current evidence does not support population-level glioma screening based on environmental exposures; the review maintains conservative boundaries between established findings, mechanistic hypotheses, and future clinical implementation.

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