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Cornu, H.

Publications and source records attributed to Cornu, H..

2 recordsLinked to original sources

The Human Pleiotropic Map of GWAS Associations and Therapeutic Implications

Genetic support for drug targets substantially increases clinical success rates, establishing genome-wide association studies (GWAS) as central to therapeutic hypothesis generation. However, the same genetic evidence that reveals causal gene-disease relationships simultaneously exposes organism-level safety liabilities--a dimension requiring principled, genome-wide quantification. Here we systematically analyse 100,526 GWAS to yield 789,453 credible sets and gene prioritisations for 15,641 genes, with discovery showing no saturation as GWAS expand and increase diversity. We find that 64% of GWAS-implicated genes are pleiotropic, associated with traits across multiple diseases and showing a non-linear relationship between the degree of pleiotropy and clinical success. Highly pleiotropic genes--concentrated in immune, inflammatory, and oncogenic signalling programmes--are enriched in safety-terminated clinical programmes, mouse lethal knockouts, and cancer driver genes, establishing gene-level pleiotropy as a potential measure of genetically-informed organism-level safety liability. Protein-altering variant (PAV) support amplifies therapeutic signal (OR = 6.0), yet PAV targets show higher average pleiotropy, introducing a competing safety liability. Combining PAV support with intermediate pleiotropy (2-5 therapeutic areas) resolves this tension, yielding OR = 10.3 and relative success = 4.8--a profile already satisfied by 52 approved therapies. As GWAS continue to expand in scale and resolution, these findings lay the groundwork for increasingly sophisticated target discovery strategies that yield safer and more effective therapeutic hypotheses.

genomics↗

Associations on the Fly, a new feature aiming to facilitate exploration of the Open Targets Platform evidence

MotivationThe Open Targets Platform (https://platform.opentargets.org) is a unique, comprehensive, open-source resource supporting systematic identification and prioritisation of targets for drug discovery. The Platform combines, harmonises and integrates data from >20 diverse sources to provide target-disease associations, covering evidence derived from genetic associations, somatic mutations, known drugs, differential expression, animal models, pathways and systems biology. An in-house target identification scoring framework weighs the evidence from each data source and type, contributing to an overall score for each of the 7.8M target-disease associations. However, the previous infrastructure did not allow user-led dynamic adjustments in the contribution of different evidence types for target prioritisation, a limitation frequently raised by our user community. Furthermore, the previous Platform user interface did not support navigation and exploration of the underlying target-disease evidence on the same page, occasionally making the user journey counterintuitive. ResultsHere, we describe "Associations on the Fly" (AOTF), a new Platform feature - developed as part of a wider product refactoring project - to enable formulation of more flexible and impactful therapeutic hypotheses through dynamic adjustment of the weight of contributing evidence from each source, altering the prioritisation of targets. Availability and implementationAll Open Targets code is available as open source: [https://github.com/opentargets]. This tool was implemented using React v18 and its code is accessible here: [https://github.com/opentargets/ot-ui-apps]. The tools described in the paper are accessible through the Open Targets Platform web interface [https://platform.opentargets.org/] and GraphQL API (https://platform-docs.opentargets.org/data-access/graphql-api). Data is available for download here: [https://platform.opentargets.org/downloads] and from the EMBL-EBI FTP: [https://ftp.ebi.ac.uk/pub/databases/opentargets/platform/]. Supplementary informationAdditional information on this tool can be found on the Platform documentation pages [https://platform-docs.opentargets.org/web-interface, https://platform-docs.opentargets.org/web-interface/associations-on-the-fly, https://platform-docs.opentargets.org/target-prioritisation] and training video [https://youtu.be/2A9bksboAag]. ContactAnnalisa Buniello, EMBL-EBI, buniello@ebi.ac.uk

bioinformatics↗