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Tuberous sclerosis complex (TSC) is a rare genetic disorder caused by mutations in the TSC1 or TSC2 genes, which encode proteins that antagonise the mammalian isoform of the target of rapamycin complex 1 (mTORC1) – a key mediator of cell growth and metabolism. TSC is characterised by the development of benign tumours in multiple organs, together with neurological manifestations including epilepsy and TSC-associated neuropsychiatric disorders (TAND). Epilepsy occurs frequently and is associated with significant morbidity and mortality; however, the management is challenging due to the intractable nature of the seizures. Preventative epilepsy treatment is a key aim, especially as patients with epilepsy may be at a higher risk of developing severe cognitive and behavioural impairment. Vigabatrin given preventatively reduces the risk and severity of epilepsy although the benefits for TAND are inconclusive. These promising results could pave the way for evaluating other treatments in a preventative capacity, especially those that may address the underlying pathophysiology of TSC, including everolimus, cannabidiol and the ketogenic diet (KD). Everolimus is an mTOR inhibitor approved for the adjunctive treatment of refractory TSC-associated seizures that has demonstrated significant reductions in seizure frequency compared with placebo, improvements that were sustained after 2 years of treatment. Highly purified cannabidiol, recently approved in the US as Epidiolex® for TSC-associated seizures in patients ⩾1 years of age, and the KD, may also participate in the regulation of the mTOR pathway. This review focusses on the pivotal clinical evidence surrounding these potential targeted therapies that may form the foundation of precision medicine for TSC-associated epilepsy, as well as other current treatments including anti-seizure drugs, vagus nerve stimulation and surgery. New future therapies are also discussed, together with the potential for preventative treatment with targeted therapies. Due to advances in understanding the molecular genetics and pathophysiology, TSC represents a prototypic clinical syndrome for studying epileptogenesis and the impact of precision medicine.
Current anti-epileptic drugs (AEDs) act on a limited set of neuronal targets, are ineffective in a third of patients with epilepsy, and do not show disease-modifying properties. MicroRNAs are small noncoding RNAs that regulate levels of proteins by post-transcriptional control of mRNA stability and translation. MicroRNA-134 is involved in controlling neuronal microstructure and brain excitability and previous studies showed that intracerebroventricular injections of locked nucleic acid (LNA), cholesterol-tagged antagomirs targeting microRNA-134 (Ant-134) reduced evoked and spontaneous seizures in mouse models of status epilepticus. Translation of these findings would benefit from evidence of efficacy in non-status epilepticus models and validation in another species. Here, we report that electrographic seizures and convulsive behavior are strongly reduced in adult mice pre-treated with Ant-134 in the pentylenetetrazol model. Pre-treatment with Ant-134 did not affect the severity of status epilepticus induced by perforant pathway stimulation in adult rats, a toxin-free model of acquired epilepsy. Nevertheless, Ant-134 post-treatment reduced the number of rats developing spontaneous seizures by 86% in the perforant pathway stimulation model and Ant-134 delayed epileptiform activity in a rat ex vivo hippocampal slice model. The potent anticonvulsant effects of Ant-134 in multiple models may encourage pre-clinical development of this approach to epilepsy therapy.
Plasticity supports the remarkable adaptability and robustness of cortical processing. It allows the brain to learn and remember patterns in the sensory world, to refine motor control, to predict and obtain reward, or to recover function after injury. Behind this great flexibility hide a range of plasticity mechanisms, affecting different aspects of neuronal communication. However, little is known about the precise computational roles of some of these mechanisms. Here, we show that the interaction between spike-timing dependent plasticity (STDP), intrinsic plasticity and synaptic scaling enables neurons to learn efficient representations of their inputs. In the context of reward-dependent learning, the same mechanisms allow a neural network to solve a working memory task. Moreover, although we make no any apriori assumptions on the encoding used for representing inputs, the network activity resembles that of brain regions known to be associated with working memory, suggesting that reward-dependent learning may be a central force in working memory development. Lastly, we investigated some of the clinical implications of synaptic scaling and showed that, paradoxically, there are situations in which the very mechanisms that normally are required to preserve the balance of the system, may act as a destabilizing factor and lead to seizures. Our model offers a novel explanation for the increased incidence of seizures following chronic inflammation.