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Researchers Identify New Epilepsy Gene Network

Summary: Researchers have identified a network of 320 genes they believe to be associated with epilepsy.

Source: Imperial College London.

Scientists have discovered a gene network in the brain associated with epilepsy.

The team, led by scientists at Imperial College London, believe the discovery may lead to more treatments for the condition.

The study, published in the journal Genome Biology, has revealed an ‘epileptic network’ of 320 genes, called M30, that is associated with the condition. The genes in the network are thought to be involved in how brain cells communicate with each other.

The results suggest that when this network malfunctions, it triggers epilepsy. Finding medications that restore this network to normal could provide desperately needed new treatments, explained Professor Michael Johnson, senior author of the research from the Department of Medicine at Imperial.

“Epilepsy is one of the most common serious neurological diseases worldwide. Yet despite almost 30 different drugs licensed for the condition, a third of people with epilepsy continue to suffer from uncontrolled epileptic seizures – despite taking medication.

“In fact, very little progress in finding more effective drugs for epilepsy has been made in the past 100 years.”

He added that many drug companies have stopped their research into finding new medicines for epilepsy.

“But the discovery of this network of genes linked to epilepsy opens avenues for finding new treatments. This uses an approach that is entirely different to the past 100 years of anti-epilepsy drug development.”

Interestingly, the network seems to malfunction in epilepsy caused by genetic causes, as well as epilepsy triggered by brain injury such as following stroke or infection.

Epilepsy affects around half a million people in the UK, and over 50 million worldwide. The condition triggers seizures, which can cause a range of symptoms – from an odd sensation or a trance-like state, to severe convulsions and loss of consciousness. Seizures are thought to be caused by brain cells sending faulty signals to each other.

In most people with epilepsy, the disease is thought to be caused by their genes. However, one third of cases are triggered by damage to the brain from causes such as head injury, stroke, tumours or infection.

In the new research, which was conducted in collaboration with Duke-NUS Medical School in Singapore, scientists used computational techniques to scan thousands of genes and mutations associated with epilepsy. They also looked at data from healthy human brains, to identify networks of genes that seem to work together, and were associated with the disease.

The scientists also used data from mice to confirm that malfunctions in this network triggered seizures.

The team then computationally analysed 1,300 known drugs to predict which ones could help restore the gene network to normal.

One of the drugs found was a known epilepsy treatment, called valproic acid.

New treatments

The team’s analyses also pointed to many other drugs not previously considered as conventional anti-epilepsy medications.

One of these was withaferin A, a compound derived from a plant known as Indian ginseng that has been used in Ayurvedic medicine for centuries to treat a range of diseases, including epilepsy.

Image shows a brain made up of network nodes.

In most people with epilepsy, the disease is thought to be caused by their genes. However, one third of cases are triggered by damage to the brain from causes such as head injury, stroke, tumours or infection. NeuroscienceNews.com image is adapted from the Imperial College London press release.

Professor Johnson explained that finding other compounds that restore the activity of the network could lead to potential new treatments.

He added that the method used in this study, called ‘network biology’ – where computer systems are used to identify gene networks that work together to underpin disease – may also help find treatments for other conditions.

“Until recently we have been looking for individual genes associated with diseases, which drug companies then target with treatments. However, we are increasingly aware that genes don’t work in isolation. Identifying groups of genes that work together, and then targeting these networks of genes, may lead to more effective treatments. Our proof of concept study suggests this network biology approach could help us identify new medications for epilepsy, and the methods can also be applied to other diseases.”

About this neuroscience research article

Funding: The research was funded by the European Union’s Seventh Framework Programme, and the National Institute for Health Research Imperial Biomedical Research Centre.

Source: Kate Wighton – Imperial College London
Image Source: NeuroscienceNews.com image is adapted from the Imperial College London press release.
Original Research: Full open access research for “Rare and common epilepsies converge on a shared gene regulatory network providing 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 in Genome Biology. Published online December 13 2016 doi:10.1186/s13059-016-1097-7

Cite This NeuroscienceNews.com Article
Imperial College London “Researchers Identify New Epilepsy Gene Network.” NeuroscienceNews. NeuroscienceNews, 13 December 2016.
<http://neurosciencenews.com/epilepsy-gene-network-5741/>.
Imperial College London (2016, December 13). Researchers Identify New Epilepsy Gene Network. NeuroscienceNew. Retrieved December 13, 2016 from http://neurosciencenews.com/epilepsy-gene-network-5741/
Imperial College London “Researchers Identify New Epilepsy Gene Network.” http://neurosciencenews.com/epilepsy-gene-network-5741/ (accessed December 13, 2016).

Abstract

Rare and common epilepsies converge on a shared gene regulatory network providing opportunities for novel antiepileptic drug discovery

Background
The relationship between monogenic and polygenic forms of epilepsy is poorly understood and the extent to which the genetic and acquired epilepsies share common pathways is unclear. Here, we use an integrated systems-level analysis of brain gene expression data to identify molecular networks disrupted in epilepsy.

Results
We identified a co-expression network of 320 genes (M30), which is significantly enriched for non-synonymous de novo mutations ascertained from patients with monogenic epilepsy and for common variants associated with polygenic epilepsy. The genes in the M30 network are expressed widely in the human brain under tight developmental control and encode physically interacting proteins involved in synaptic processes. The most highly connected proteins within the M30 network were preferentially disrupted by deleterious de novo mutations for monogenic epilepsy, in line with the centrality-lethality hypothesis. Analysis of M30 expression revealed consistent downregulation in the epileptic brain in heterogeneous forms of epilepsy including human temporal lobe epilepsy, a mouse model of acquired temporal lobe epilepsy, and a mouse model of monogenic Dravet (SCN1A) disease. These results suggest functional disruption of M30 via gene mutation or altered expression as a convergent mechanism regulating susceptibility to epilepsy broadly. Using the large collection of drug-induced gene expression data from Connectivity Map, several drugs were predicted to preferentially restore the downregulation of M30 in epilepsy toward health, most notably valproic acid, whose effect on M30 expression was replicated in neurons.

Conclusions
Taken together, our results suggest targeting the expression of M30 as a potential new therapeutic strategy in epilepsy.

“Rare and common epilepsies converge on a shared gene regulatory network providing 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 in Genome Biology. Published online December 13 2016 doi:10.1186/s13059-016-1097-7

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