An integrated systems-level framework for deciphering multidrug resistant epilepsy.

Epilepsy is a serious, common neurological disease - one in 26 people will develop epilepsy at some point in their life. Epilepsy has huge public health significance - it is the 5th most disabling disease in the World Health Organisation's rankings of disability by illness and accounts for 3% of all A&E attendances in the UK NHS alone. The greatest burden falls on the 20-30% of people with epilepsy who continue to have uncontrolled seizures despite all currently available antiepileptic drugs. These people are at a significantly increased risk of dying, as well as from other complications of their epilepsy such as memory and cognitive difficulties, and under and unemployment. Surprisingly, there has been no progress in improving seizure control in the last 50 years of anti-epileptic drug development, and none of the current antiepileptic drugs are disease modifying or curative. This absence of progress despite decades of research mandates a new scientific approach. Our project brings together three leading universities in the UK (Imperial College, University College London, Cambridge University) to combine data and expertise in order to address this major unmet clinical need. Our goal is ambitious - to find better drugs for treating epilepsy. Our project combines the largest and most comprehensive genetic datasets on drug response in epilepsy worldwide with proven "big-data" computational methods for working out how genes interact with each other to cause disease. Then, using the latest methods to connect disease mechanisms to drug targets, we aim to translate these insights to new therapies for people living with drug resistant epilepsy. Our project has the potential to transform the lives of people with drug resistant epilepsy, and to inform fundamental mechanisms of human brain function in health and disease generally.

Epilepsy is a common, serious neurological disease - it is the 5th most disabling disorder in the WHO's rankings of disability by illness and accounts for 3% of all A&E attendances in the UK NHS. The greatest burden falls on the 20-30% with multidrug resistant epilepsy (MDRE). There has been little progress in improving seizure control in the last 50 years of antiepileptic drug development and none of the current drugs are disease modifying or curative. This absence of progress despite decades of research mandates a new scientific approach. Systems-biological analyses provide powerful techniques for elucidating molecular processes and pathways underlying complex disease. In particular, we have established proof-of-concept for the use of gene regulatory network (regulome) approaches to new drug discovery, including the discovery of novel patented drugs and targets using these approaches. The recent development of methods to assay the transcriptomes of individual cells (single cell RNA-sequencing, scRNA-seq) now offers the opportunity to rapidly accelerate this progress by incorporating cell-type and disease-context specificity to our therapeutic predictions. In this application we start from the hypothesis that connecting genomic liability for MDRE to cellular transcriptomes of the human epileptic brain will identify cell-types and pathways fundamental to the genesis MDRE. Taking an integrative approach, we first evaluate how genomic loci implicated in susceptibility to MDRE map onto specific cell-types, gene networks and functional pathways and then, using knowledge of the cell-types and pathways perturbed in MDRE, we apply a cell-type specific regulome framework to the discovery of new druggable targets for MDRE. Our project has the potential to rapidly advance the discovery of new drugs for treatment resistant epilepsy, and will provide fundamental insights into cell variability and cell-type specific gene expression in the human brain in health and disease.

The research will advance scientific understanding of the mechanisms and pathways for multidrug resistant epilepsy specifically, and our understanding of the cellular taxonomy of the human brain generally. Outputs will also include datasets of critical value to the interpretation of neuropsychiatric GWAS including cell-type specific eQTLs from the human adult hippocampus and prefrontal cortex. As a consequence, and as detailed in in our Pathways to Impact and Academic Beneficiaries Statements, the advances in knowledge from this project will impact on scientific, clinical, commercial and wider public domains. These impacts will be realized during the course of the project and longer-term. A summary of the impacts is provided below. We also refer the reviewer to our Pathways to Impact and Academic Beneficiaries statements.

1. Pharmaceutical impact
Translational impacts include drug target discovery for disease modification in multidrug resistant epilepsy and biomarkers for patient stratification and small molecule high-throughput drug screening. The project has the potential to contribute to the development of new intellectual property with benefit to the nation's wealth, university and research sectors, and in this regard we highlight that a previous collaboration with UCB Pharma delivered a patented first in class novel drug target for epilepsy within 2-years of data generation, indicating that commercial impacts can expect to be realized in medium term time-frames using the approaches outlined in this application.

2. Scientific impact
In addition to impacts generated by the primary Aims of this project, knowledge and reagents generated during the course of the project will include important new data relating to single cell RNA-sequencing of the human brain, new genetic associations (common and rare variant) with multidrug resistant epilepsy, cell-type specific eQTLs from the epileptic and non-diseased adult human hippocampus and prefrontal cortex, and advances in methodology for scRNA-seq analysis. All primary single cell RNA-seq data and genetic association data will be made available to the research community according to our open access policy. We will coordinate with the Data Coordination Platform (DCP) of the Human Cell Atlas (HCA) to ensure that all data is validated, associated with high quality metadata and made available to the wider scientific community.

3. Clinical impact
The discovery of drugable pathways for multidrug resistant epilepsy would have a fundamental clinical impact. Improving treatments for epilepsy is a stated Pivotal Domain for epilepsy research by the International League Against Epilepsy, and is highlighted by patients themselves. Additionally, the discovery of new genetic associations with multidrug resistant epilepsy as well as understanding how polygenic risk maps on gene networks will aid the development of risk scores for patient stratification which may impact the design of future clinical trials for antiepileptic drug therapies and personalized medicine.

4. Patient and public impact
In our letter of support from the Chief Executive of The Epilepsy Society and our Public Patient Involvement statement we highlight the project's potential to enable the 120,000+ people in the UK and millions of others worldwide living with multidrug resistant epilepsy to lead full and rewarding lives. Our previous work showing how polygenic risk for human intelligence maps onto gene co-expression networks expressed in the human brain (Johnson et al., Nature Neuroscience 2016) generated substantial interest in the national press. The advances in how genes interact to alter human brain behaviour and disease arising from this project are likely to have a similar impact on the public imagination of brain sciences and computational biology and give hope to millions of people worldwide living with epilepsy.