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Abstract
The identification of drug targets is highly challenging, particularly for diseases of the brain. To address this problem, we developed and experimentally validated a general computational framework for drug target discovery that combines gene regulatory information with causal reasoning (“Causal Reasoning Analytical Framework for Target discovery”—CRAFT). Using a systems genetics approach and starting from gene expression data from the target tissue, CRAFT provides a predictive framework for identifying cell membrane receptors with a direction-specified influence over disease-related gene expression profiles. As proof of concept, we applied CRAFT to epilepsy and predicted the tyrosine kinase receptor Csf1R as a potential therapeutic target. The predicted effect of Csf1R blockade in attenuating epilepsy seizures was validated in three pre-clinical models of epilepsy. These results highlight CRAFT as a systems-level framework for target discovery and suggest Csf1R blockade as a novel therapeutic strategy in epilepsy. CRAFT is applicable to disease settings other than epilepsy.
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1 Division of Brain Sciences, Imperial College London, London, UK
2 UCB Pharma, Braine-l’Alleud, Belgium
3 Clarivate Analytics (formerly the IP & Science Business of Thomson Reuters), Carlsbad, CA, USA
4 Division of Brain Sciences, Imperial College London, London, UK; UFR de Santé, Médecine et Biologie Humaine, Sorbonne Paris Cité, Université Paris 13, Bobigny, France; PROTECT, INSERM, Sorbonne Paris Cité, Université Paris Diderot, Paris, France
5 PROTECT, INSERM, Sorbonne Paris Cité, Université Paris Diderot, Paris, France
6 PROTECT, INSERM, Sorbonne Paris Cité, Université Paris Diderot, Paris, France; School of Biomedical Engineering & Imaging Sciences, Centre for the Developing Brain, King’s College London, London, UK
7 Centre for Complement and Inflammation Research, Imperial College London, London, UK
8 Duke-NUS Medical School, Centre for Computational Biology, Singapore, Republic of Singapore; Faculty of Medicine, MRC Clinical Sciences Centre, Imperial College London, London, UK