Autoregulatory Gene Therapy as a Treatment for Focal Epilepsy

What's the science?

Patients with epilepsy often do not respond to anti-epileptic drugs and continue to experience seizures. Drug-resistance is especially common when seizures arise from a specific region of the brain (focal epilepsy). Further, anti-epileptic drugs are not selective for the neurons which cause seizures. Viral mediated gene therapy, where new DNA is carried by a viral vector and inserted into cells, could potentially be used to selectively modify neuron populations that cause seizures. Gene therapy has shown promise in animal models; however, most therapies have been irreversible. This week in Nature Medicine, Lieb and colleagues use an autoregulating viral-mediated gene therapy treatment in rats to test whether it is tolerated and reduces seizures.

How did they do it?

They designed a viral plasmid containing a gene encoding a glutamate-gated chloride channel that detects excessive glutamate (an excitatory neurotransmitter) release from neurons and inhibits neurons in a self-regulating manner. Glutamate release is increased in epilepsy resulting in heightened neural activity, so inhibiting this process can reduce seizures. Adult rats were injected with pilocarpine, a seizure inducing drug, before injection of the viral vector containing the glutamate sensitive channel or a control vector, and then again two weeks later. Both of these were administered to the primary motor cortex of the rats. An electrode was also placed in the motor cortex to record the electroencephalogram (EEG) to detect seizure activity. Comparing the effect of pilocarpine before and after treatment revealed the effect of gene therapy on seizure activity. They then tested the effect of gene therapy on a model of chronic focal epilepsy where seizures occur spontaneously for several weeks after injecting tetanus toxin into the visual cortex of rats. They did this by comparing the frequency of seizures before and after treatment. Finally, they performed a series of behavioral experiments to test whether motor coordination was altered by the gene therapy treatment administered to the primary motor cortex (i.e. whether it was well tolerated).

What did they find?

Rats injected with the viral DNA encoding the glutamate sensitive channel showed a reduction in frequency and amplitude of seizure-related activity (induced by pilocarpine in the motor cortex), when compared to rats injected with the control virus. The frequency of spontaneous seizures was also reduced after introducing the glutamate sensitive channel in a chronic model of focal epilepsy. However, there was no effect on seizure duration or intensity in the chronic epilepsy model, or on the background EEG. These results suggest that the gene therapy was effective in inhibiting both pilocarpine-evoked seizure-related activity and the number of spontaneous seizures in a chronic focal seizure model. After testing for effects of gene therapy on motor coordination, there was no difference between control rats and those rats treated with the viral injection of the glutamate sensitive channel, demonstrating that the gene therapy was well tolerated.

What's the impact?

This is the first study to demonstrate how gene therapy can be used to express an autoregulating channel that responds to excessive glutamate release to reduce seizures. This gene therapy was well-tolerated and able to inhibit neurons to reduce seizure related activity and reduce the number of seizures in a chronic model of focal epilepsy. This study shows that gene therapy could potentially be used to apply selective treatment to specific brain regions causing seizures. Further research will be needed to ensure that this gene therapy can be well tolerated in humans.

Lieb et al., Biochemical autoregulatory gene therapy for focal epilepsy. Nature Medicine (2018). Access the original scientific publication here.

MicroRNAs Cause Astrocyte Dysfunction in ALS

What's the science?

ALS is a devastating disease where motor neurons degenerate over time. Astrocytes which normally support neurons function abnormally in ALS and play a role in ongoing cell death. MicroRNAs are naturally occurring small pieces of non-coding RNA that regulate (and often inhibit) the production of proteins in cells. One type of microRNA called miR-218 has recently been shown to be higher in motor neurons in ALS and is released from the neuron into the cerebrospinal fluid. This microRNA, which is released from dying neurons, could communicate with astrocytes to cause dysfunction. This week in Brain Hoye and colleagues examine whether microRNA released from neurons are taken up by astrocytes and regulate their protein expression.

How did they do it?

They identified potential targets that microRNA miR-218 might bind to or regulate in astrocytes to affect their function. They did this by looking for genes with enriched (i.e. higher) expression in astrocytes. They identified EAAT2, a glutamate reuptake transporter that is enriched in healthy astrocytes but lost in ALS. They injected cells with either random microRNA or miR-218 (specifically released from motor neurons in ALS) to see whether it would affect EAAT2 expression. They then assessed whether miR-218 is taken up by astrocytes using a sensor they developed and whether it is free, protein bound, or encapsulated in vesicles. Finally, they tested whether any potentially pathological effects of miR-218 on astrocyte EAAT2 expression could be altered using antisense oligonucleotide therapy.

What did they find?

They found that miR-218 infected cells had reduced production of EAAT2 (measured with western blot) demonstrating that it can repress translation of this glutamate transporter in astrocytes. They then developed a ‘sensor’ to confirm that miR-218 is taken up by astrocytes. They found that the majority of miR-218 is protein bound in the cerebrospinal fluid (after it is released from the cell). They then tested whether they could block the miR-218 induced repression of EAAT2 expression in astrocytes using antisense oligonucleotides. They applied media from sporadic ALS patient iPSC-derived motor neurons to primary astrocytes that contained miR-218 with and without antisense oligonucleotides (a type of therapy for regulating protein production), and found that EAAT2 repression was blocked by antisense oligonucleotides. They then followed up by testing in a mouse model of ALS whether inhibiting miR-218 would block EAAT2 suppression. SOD1 mice (a mouse model of ALS) were treated with either antisense oligonucleotides or saline, and they found that the mice treated with the antisense oligonucleotides had less miR-218 activity in their brains. It also reduced astrogliosis (an abnormal increase in number of astrocytes) in ALS model mice.

Astrocyte, Servier Medical Art, image by BrainPost, CC BY-SA 3.0

What's the impact?

This is the first study to demonstrate that a microRNA (miR-218) release from dying motor neurons results in the repression of glutamate transporter (EAAT2) expression. Further, this study shows that blocking this repression using antisense oligonucleotides can reverse the effects of this microRNA on causing potentially damaging effects on astrocytes. Importantly, this study suggests that microRNAs play an important role in affecting astrocytes that contribute to ongoing neurodegeneration in ALS.

Hoye et al., Motor neuron-derived microRNAs cause astrocyte dysfunction in amyotrophic lateral sclerosis. Brain (2018). Access the original scientific publication here.

A Neural Basis for Episodic Memory Deficits in Older Adults

What's the science?

Episodic memory, in which an individual uses contextual details to recall an entire event (as opposed to simply recalling a fact) is disproportionately affected in older adults. Older adults have been found to engage in a process known as ‘hyper-binding’, in which they remember additional irrelevant features while encoding the relationship between an item and its context (forming an episodic memory). Older adults may have to work harder to recall information. However, we don’t know what is happening in the brain when the memory is being encoded in older adults. This week in NeuroImage, Powell and colleagues had young and older adults perform an encoding task while EEG was recorded in order to understand how aging affects episodic memory encoding.

How did they do it?

22 young (18-35) and 21 older (60-80 years) participated in the study. Over a series of mini blocks of trials within four larger blocks, participants were presented with 288 images of objects flanked by a coloured square on one side and a scene on the other side. During the memory encoding phase of the experiment, for each mini block, the ‘target context’ (i.e. the association between the object and either a color or scene) was manipulated: Participants were asked to judge either a) whether the color of the square was a color likely to be associated with the the object or b) whether the object was likely to be found in the scene. In sum, in each trial they were required to memorize either the color or scene associated with the object while the other acted as a distractor. During the test phase of the experiment, the 288 images were presented interspersed with 144 new images/objects. Participants were first asked to recall whether the images were new or old (whether they had seen them before), and, if they correctly guessed old, whether the colour and the scene matched the object as it had originally been presented. Sometimes, the target context matched the image, sometimes the distractor matched the image, and sometimes both matched the image.

Multi-voxel pattern analysis (MVPA; a pattern classification technique) was used to predict the target context of a given trial based on the pattern of brain activity during encoding. The data were divided into bins by frequency (3-80 Hz) and time during the trial (0-2000 ms) and the MVPA classifier was able to ‘learn’ which target context (colour vs. scene) was presented during the memory encoding period. The purpose of the classifier was to see whether EEG oscillatory power could predict selective attention to the target context feature (color or scene). A follow-up analysis/classification was performed in which data was binned into delta, theta, alpha, beta, and gamma frequency bands (different frequencies of brain activation measured by EEG). The relationship between classifier accuracy (correct identification of scene vs. colour as the target context during encoding) and participant accuracy of the target context and distractor during the test phase was explored.

What did they find?

Context memory was worse in older adults compared to young adults, suggesting hyper-binding of both the target and distractor during encoding. Older adults were also more likely to correctly identify the target context if the distractor context also matched the original image, further suggesting hyper-binding. The peak frequency (of brain activity) and time period in which the classifier (which uses brain activity to predict attention to target context) correctly identified the target context presented (colour vs. scene) were 2-20 Hz and 300-1200 ms respectively. When the classifier was run with the data divided into frequency bins, a positive relationship between beta band power and the correct identification of the target context was observed. A negative relationship between beta and alpha band power and correct identification of the distractor (i.e. lower beta and alpha band power, better distractor identification) were found. This indicates that the classifier ‘learned’ the brain activity pattern and used it to correctly identify the target context (color vs. scene) better on trials in which the individuals later recalled the target context correctly (demonstrating better selective attention), but had poor accuracy on trials for which the participant correctly identified the distractor. There was no relationship with age, which suggests that there were no differences between classifier performance across age groups. Electrodes located over the cortex contralateral to the location of the target context exhibited better performance. Therefore, a follow-up analysis was performed using only the contralateral electrodes: greater decline from 0-500 ms to 500-100 ms in classifier accuracy was associated with poorer target context accuracy and better distractor accuracy, suggesting poor selective attention and greater hyper-binding was associated with worse classification performance. This result was driven by the older adults group and could reflect a shift in attention away from target and towards distractor that may result in greater hyper-binding.  

What's the impact?

This is the first study to examine age-related changes in memory encoding using a pattern classification of EEG oscillatory activity. Target context was predicted by alpha and beta power features of the classifier, which play roles in behavioural inhibition and attention respectively. Poor selective attention or poor inhibition of a distractor may underlie episodic memory deficits in older adults. These finding improve our understanding of episodic memory impairment associated with aging.

Powell et al., Decoding selective attention to context memory: An aging study. NeuroImage (2018). Access the original scientific publication here.