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  • Final Report Summary - IGENEE (Identification of pathways and genetic drivers for childhood epileptic encephalopathies by integrating whole-exome sequencing and gene network approaches)

Final Report Summary - IGENEE (Identification of pathways and genetic drivers for childhood epileptic encephalopathies by integrating whole-exome sequencing and gene network approaches)

The objective of the iGENEE project (Integrated Genetic Networks for Epileptic Encephalopathies) was the identification of pathways and genetic drivers for childhood epileptic encephalopathies (EE) by integrating whole-exome sequencing and gene network approaches. The project was supervised by Dr Petretto, Senior Lecturer at Imperial College London and Associate Professor at Duke National University of Singapore, and co-supervised by Professor Johnson, Deputy Head of the Centre for Clinical Translation of Brain Sciences, at Imperial College London.

The researcher built gene co-expression networks from human brain transcriptomes to identify gene networks from various brain regions (UK Brain Expression Consortium dataset). These gene networks were connected to EE using data on DNA mutations that underlie EE susceptibility. The analytical tools and computational methods that have been developed by the researcher for this part of the iGENEE project benefited another research project in the group. The application of these approaches to different genomic datasets allowed the researcher to expand the “disease spectrum” of the iGENEE project to other neurodevelopmental diseases for which exome sequencing data were available (namely, autism spectrum disorder, schizophrenia and intellectual disabilities). The researcher’s contribution to this work has been recognised as joint-second author in a original research manuscript published in Nature Neuroscience in 2016 (doi:10.1038/nn.4205).
http://www.nature.com/neuro/journal/vaop/ncurrent/full/nn.4205.html.

As part of the main research activity of the iGENEE project, the researcher identified a novel gene co-expression network of 320 genes (M30), which is significantly enriched for non-synonymous de novo mutations ascertained from patients with EE, and also for common variants associated with polygenic epilepsy. Further analyses suggested that functional disruption of this gene network by means of gene mutations and/or altered expression in different experimental models of epilepsy can represent a novel convergent mechanism for the regulation of epilepsy susceptibility, which was not previously appreciated. These results oriented the work towards another hypothesis: could the identified disease-network be targeted as a novel therapeutic strategy?
Using the large collection of drug-induced gene expression data from Connectivity Map (CMap), the researcher predicted several drugs that preferentially restore the down-regulation of gene network in epilepsy toward its healthy state, most notably valproic acid, an established antiepileptic medication with a broad spectrum of clinical efficacy. The identification of this disease-gene network in the brain as a potential therapeutic target in epilepsy represents a proof of concept for drug prioritisation using network based in epilepsy. These results have been reported in a research manuscript (currently under revision for Genome Biology) entitled: “Rare and common epilepsies converge on a shared gene regulatory network: opportunities for novel antiepileptic drug discovery” by Andree Delahaye-Duriez, Prashant Srivastava, Kirill Shkura, Sarah R. Langley, Liisi Laaniste, Aida Moreno-Moral, Bénédicte Danis, Manuela Mazzuferi, Patrik Foerch, Elena V. Gazina, Kay Richards, Steven Petrou, Rafal M. Kaminski, Enrico Petretto and Michael R. Johnson.

The code of R functions newly created for this study by the researched will be provided as a easy-to-use R package at https://github.com/adelahay/BrainCell. This repository will be made public upon publication acceptance.

For the last part of the iGENEE project, the researcher use gene mapping approaches to identify key regulatory genes of the epilepsy-associated gene co-expression network described above. Using Sparse Bayesian Regression models on all expression levels of the gene network and thousands of genetic predictors (i.e., SNPs) genome-wide, the aim of was to pinpoint “hotspots” in the genome for the regulation the disease-associated co-expression network; using this approach the researcher identified three candidate genetic regulators. Experimental validation of these candidate genetic regulators is in progress in collaboration with INSERM U1141 laboratory in Paris, where the researcher now conducts her research activity since the end of the Marie Sklodowska Curie fellowship.

Through the development of the iGENEE project, the researcher developed expertise in bioinformatics and statistical genomics (using and coding in several computing languages: R, Matlab, bash; experience in analyzing and integrating several types of large scale datasets: e.g., gene expression data, whole-exome-sequencing, genome-wide genotype SNP data, phenotype and covariates; data management; usage of different computing systems for parallelisation of calculations using high performance computer cluster).

The impact of this fellowship is highly positive not only for the researcher’s career but also through the development of lasting collaboration between UK (Imperial College London), France (INSERM in Paris) and now extended to Singapore (Duke-National University of Singapoer) where Dr Petretto recently relocated to. The researcher has come back to her position of Associate Professor in Paris 13 University on the 1st of September 2016, and was offered the title of Honorary Clinical Senior lecturer at Imperial College to reinforce these collaborations. Together they will set up new collaborative projects including collaborative applications for Horizon 2020 and other EU Funding opportunities.

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IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE
United Kingdom
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