Felici B et al., Cell Genomics - A concise review of how post-GWAS methods are being used to move from statistical associations to translational insights by integrating drug-target prioritization, single-cell resolution of regulatory mechanisms, and imaging-derived organ phenotypes. Key terms: GWAS, drug discovery, single-cell, imaging genetics, polygenic scores. Study Highlights: This review synthesizes recent advances in translating GWAS findings into therapeutic targets, single-cell resolved mechanisms, and imaging-derived organ phenotypes. It outlines methods including fine-mapping, sc-eQTL mapping, colocalization, imaging GWAS, and Mendelian randomization to link variants to genes, cell types, proteins, and organ function. Case studies show genetics-informed target prioritization and drug repurposing, and the use of imaging IDPs and polygenic scores to refine discovery and prediction. The authors emphasize key challenges such as limited ancestry diversity, small single-cell cohorts, and difficulty inferring causality across biological scales. Conclusion: Integrating GWAS with single-cell and imaging data can accelerate target prioritization and translational discovery, but progress depends on larger, diverse cohorts and improved causal, multi-modal frameworks. Music: Enjoy the music based on this article at the end of the episode. Article title: Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging First author: Felici B Journal: Cell Genomics DOI: 10.1016/j.xgen.2026.101282 Reference: Felici B, Chen S, Yuan M, Jiang X, Ip S, Rudd JHF, Inouye M. Translating genome-wide association studies at multiple scales: Drug target prioritization, cellular architectures, and organ imaging. Cell Genomics. 2026;6:101282. doi:10.1016/j.xgen.2026.101282 License: This episode is based on an open-access article published under the Creative Commons Attribution 4.0 International License (CC BY 4.0) – https://creativecommons.org/licenses/by/4.0/ Support: Base by Base is independent and ad-free — no sponsors, no paywall. If an episode was worth your time, chip in and keep the papers audited and the original songs coming: ❤️ Support monthly: https://buy.stripe.com/cNifZhclVebvagk2JDgEg01 ☕ One-time donation: https://donate.stripe.com/7sY4gz71B2sN3RWac5gEg00 More at basebybase.com On PaperCast Base by Base you'll discover the latest in genomics, functional genomics, structural genomics, and proteomics. Episode link: https://basebybase.com/episodes/translating-gwas-multiple-scales QC: This episode was checked against the original article PDF and publication metadata for the episode release published on 2026-07-18. QC Scope: - article metadata and core scientific claims from the narration - excludes analogies, intro/outro, and music - transcript coverage: Assessed the transcript's coverage of the multi-scale GWAS translation framework, including cellular and imaging scales, concrete gene/target examples, pharmacogenomics, noncoding variants, brain-heart axis, perturb-seq and AI modeling, and limitations; cross-checked against the canonical text for consistency and accur - transcript topics: Multi-scale genomics framework (molecular, cellular, organ); Single-cell omics and scQTL causal inference; Imaging genetics and imaging-derived phenotypes (IDPs); Genetic target examples: PCSK9, ANGPTL3, TYK2, BCL11A; Non-coding regulatory variants and gene regulation; Brain-heart-eye axis and cross-organ pleiotropy QC Summary: - factual score: 10/10 - metadata score: 10/10 - supported core claims: 8 - claims flagged for review: 0 - metadata checks passed: 4 - metadata issues found: 0 Metadata Audited: - article_doi - article_t...
