ArticleBriefings in bioinformatics2026
G2DR: a genotype-first framework for genetics-informed target prioritization and drug repurposing.
Article in Briefings in bioinformatics, 2026. 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
Human genetics offers a scalable route to therapeutic discovery, but practical frameworks that convert genotype-derived signal into ranked target and drug hypotheses remain limited, particularly when matched disease transcriptomics are unavailable. We present G2DR, a genotype-first computational prioritization framework that integrates genetically predicted gene expression, multi-method gene-level testing, pathway enrichment, network context, druggability, and multi-source drug-target evidence to generate hypotheses for downstream follow-up. In a migraine case study of 733 UK Biobank participants (53 cases, 680 controls) using stratified five-fold cross-validation, G2DR imputed genetically regulated expression across seven transcriptome-weight resources and ranked genes using a reproducibility-aware discovery score derived only from training and validation data, followed by a balanced integrated score for target selection. Internal held-out evaluation within the same UK Biobank-derived analytical framework achieved gene-level ROC-AUC of 0.775 and PR-AUC of 0.475 for recovery of test-significant genes, while retaining enrichment for curated migraine-associated biology. Mapping prioritized genes to compounds through Open Targets, DGIdb, and ChEMBL produced drug sets enriched for migraine-linked and literature-associated compounds relative to a global drug background. However, tiered benchmarking showed limited recovery of migraine-specific approved therapies, with stronger signal from mechanism-linked, off-label, and literature-associated pharmacological space. Directionality filtering further distinguished broadly recovered compounds from those with stronger mechanistic compatibility. G2DR is, therefore, best viewed as a modular framework for genetics-informed hypothesis generation in genotype-first settings, not as a clinically actionable target-identification or drug-recommendation system. Prioritized genes and compounds require independent validation.
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