A genetics-led approach defines the drug target landscape of 30 immune-related traits
Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection1. Drug targets with genetic support are more likely to be therapeutically valid2,3, but the translational use of genome-scale data such as from genome-wide associat...
| Auteurs principaux: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Journal article |
| Langue: | English |
| Publié: |
Springer Nature
2019
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| _version_ | 1826295185322016768 |
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| author | Fang, H De Wolf, H Knezevic, B Burnham, K Osgood, J Sanniti, A Lledó Lara, A Kasela, S De Cesco, S Wegner, J Handunnetthi, L McCann, F Chen, L Sekine, T Brennan, P Marsden, B Damerell, D O’Callaghan, C Bountra, C Bowness, P Sundström, Y Milani, L Berg, L Göhlmann, H Peeters, P Fairfax, B Sundström, M Knight, J |
| author_facet | Fang, H De Wolf, H Knezevic, B Burnham, K Osgood, J Sanniti, A Lledó Lara, A Kasela, S De Cesco, S Wegner, J Handunnetthi, L McCann, F Chen, L Sekine, T Brennan, P Marsden, B Damerell, D O’Callaghan, C Bountra, C Bowness, P Sundström, Y Milani, L Berg, L Göhlmann, H Peeters, P Fairfax, B Sundström, M Knight, J |
| author_sort | Fang, H |
| collection | OXFORD |
| description | Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection1. Drug targets with genetic support are more likely to be therapeutically valid2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging4,5,6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority index) successfully identifies current therapeutics, predicts activity in high-throughput cellular screens (including L1000, CRISPR, mutagenesis and patient-derived cell assays), enables prioritization of under-explored targets and allows for determination of target-level trait relationships. The priority index is an open-access, scalable system accelerating early-stage drug target selection for immune-mediated disease. |
| first_indexed | 2024-03-07T03:57:09Z |
| format | Journal article |
| id | oxford-uuid:c342a24b-7cbd-4e4c-a667-0c798e7a92d6 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T03:57:09Z |
| publishDate | 2019 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | oxford-uuid:c342a24b-7cbd-4e4c-a667-0c798e7a92d62022-03-27T06:15:14ZA genetics-led approach defines the drug target landscape of 30 immune-related traitsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c342a24b-7cbd-4e4c-a667-0c798e7a92d6EnglishSymplectic Elements at OxfordSpringer Nature2019Fang, HDe Wolf, HKnezevic, BBurnham, KOsgood, JSanniti, ALledó Lara, AKasela, SDe Cesco, SWegner, JHandunnetthi, LMcCann, FChen, LSekine, TBrennan, PMarsden, BDamerell, DO’Callaghan, CBountra, CBowness, PSundström, YMilani, LBerg, LGöhlmann, HPeeters, PFairfax, BSundström, MKnight, J Most candidate drugs currently fail later-stage clinical trials, largely due to poor prediction of efficacy on early target selection1. Drug targets with genetic support are more likely to be therapeutically valid2,3, but the translational use of genome-scale data such as from genome-wide association studies for drug target discovery in complex diseases remains challenging4,5,6. Here, we show that integration of functional genomic and immune-related annotations, together with knowledge of network connectivity, maximizes the informativeness of genetics for target validation, defining the target prioritization landscape for 30 immune traits at the gene and pathway level. We demonstrate how our genetics-led drug target prioritization approach (the priority index) successfully identifies current therapeutics, predicts activity in high-throughput cellular screens (including L1000, CRISPR, mutagenesis and patient-derived cell assays), enables prioritization of under-explored targets and allows for determination of target-level trait relationships. The priority index is an open-access, scalable system accelerating early-stage drug target selection for immune-mediated disease. |
| spellingShingle | Fang, H De Wolf, H Knezevic, B Burnham, K Osgood, J Sanniti, A Lledó Lara, A Kasela, S De Cesco, S Wegner, J Handunnetthi, L McCann, F Chen, L Sekine, T Brennan, P Marsden, B Damerell, D O’Callaghan, C Bountra, C Bowness, P Sundström, Y Milani, L Berg, L Göhlmann, H Peeters, P Fairfax, B Sundström, M Knight, J A genetics-led approach defines the drug target landscape of 30 immune-related traits |
| title | A genetics-led approach defines the drug target landscape of 30 immune-related traits |
| title_full | A genetics-led approach defines the drug target landscape of 30 immune-related traits |
| title_fullStr | A genetics-led approach defines the drug target landscape of 30 immune-related traits |
| title_full_unstemmed | A genetics-led approach defines the drug target landscape of 30 immune-related traits |
| title_short | A genetics-led approach defines the drug target landscape of 30 immune-related traits |
| title_sort | genetics led approach defines the drug target landscape of 30 immune related traits |
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