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Nat Genet. 2019 Jul;51(7):1082-1091. doi: 10.1038/s41588-019-0456-1. Epub 2019 Jun 28.

A genetics-led approach defines the drug target landscape of 30 immune-related traits.

Author information

1
Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
2
Janssen Research & Development, Beerse, Belgium.
3
Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.
4
Alzheimer's Research UK Oxford Drug Discovery Institute, Target Discovery Institute, University of Oxford, Oxford, UK.
5
Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK.
6
Botnar Research Centre, University of Oxford, Oxford, UK.
7
Structural Genomics Consortium, University of Oxford, Oxford, UK.
8
NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK.
9
Structural Genomics Consortium, Department of Medicine, Karolinska University Hospital and Karolinska Institutet, Stockholm, Sweden.
10
Department of Oncology, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
11
Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK. julian@well.ox.ac.uk.
12
NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, UK. julian@well.ox.ac.uk.

Abstract

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 challenging4-6. 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.

PMID:
31253980
DOI:
10.1038/s41588-019-0456-1

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