A systems-level framework for anti-epilepsy drug discovery

Neuropharmacology. 2020 Jun 15:170:107868. doi: 10.1016/j.neuropharm.2019.107868. Epub 2019 Nov 28.

Abstract

Modern anti-seizure drug development yielded benefits in terms of improved pharmacokinetics, safety and tolerability profiles, but offered no advances in efficacy compared to previous older generations of anti-seizure drugs. Despite significant advances in our understanding of the genetic bases to epilepsy, and a welcome renewed interest on the severe monogenic epilepsies, modern genetics has yet to directly inform more effective or disease-modifying anti-seizure drugs. Here, we describe a new approach to the identification of novel disease modifying anti-epilepsy drugs. The systems genetics approach aims to first identify pathophysiological mechanisms by integrating polygenic risk with cellular gene expression profiles and then to relate these molecular mechanisms to druggable targets using a gene regulatory (regulome) framework. The approach offers an exciting and flexible framework for future drug discovery in epilepsy, and is applicable to any disease for which appropriate cell-type and disease-context specific data exist. This article is part of the special issue entitled 'New Epilepsy Therapies for the 21st Century - From Antiseizure Drugs to Prevention, Modification and Cure of Epilepsy'.

Keywords: Disease modification; Drug discovery; Epilepsy; Gene regulatory network; Integrative genomics; Network; RNA-seq; Regulome; Single-cell; Systems genetics; Transcriptomics; scRNA-seq; snRNA-seq.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Anticonvulsants / pharmacology
  • Anticonvulsants / therapeutic use*
  • Drug Discovery / methods*
  • Drug Discovery / trends
  • Epilepsy / diagnosis
  • Epilepsy / drug therapy*
  • Epilepsy / genetics*
  • Gene Regulatory Networks / drug effects
  • Gene Regulatory Networks / genetics
  • Humans
  • Sequence Analysis, DNA / methods
  • Sequence Analysis, RNA / methods
  • Systems Analysis*

Substances

  • Anticonvulsants