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Much of the field of epilepsy still harbors long-held ideas about what creates the patterns of neural electrophysiology that results in focal seizures, a lot of which has not been experimentally established. Much of this activity may have the spatiotemporal characteristics that would be unlikely to be captured with standard imaging protocols. Better understanding of these mechanisms will not only better reveal the underlying... more »

The American Epilepsy Society suggests that this priority be merged with priority (#1).

It is indeed a high priority to make models in cells and multiple organisms (fly, fish, mouse) that actually replicate the human mechanisms, e.g., gene knockout may not be the same as gene inactivation from a missense variant. All models have REAL human relevance, it is just HOW relevant. Another way to say it might be: Develop cell... more »

The American Epilepsy Society does not recommend this for the top 4-5 priorities for the field. It should instead be a goal for 5-10 years from now, after the ability to develop improved models (priority #1 above) is achieved.

There are a myriad of known gene variants found within intronic or untranslated gene regions or at splice-sites that will require functional validation in vitro by expression of the variant in... more »

The American Epilepsy Society considers comorbidities of epilepsy a high priority endeavor. Patients themselves, often independent of actual seizure frequency, remain underemployed or underachieving because comorbidities affect function in equal or greater measure than epilepsy itself. Furthermore, accumulating evidence finds that comorbidities and epilepsy have bilateral interactions; improvement in one comorbid domain... more »

The American Epilepsy Society agrees that topic is a VERY high priority. We suggest a revision to include "onset of epilepsy" in its scope.

To date there have been numerous studies and meta-analyses on epilepsy biomarkers. Biomarkers for epilepsy versus seizure have often been blurred but should be considered distinct. Clinically useful biomarkers for seizures (i.e., a blood test), would have great value in the emergency... more »

The American Epilepsy Society views this topic as a high priority that should encompass strategy to incorporate the expertise from experts in immunology and neuroimmunology. Some revisions would help to ensure its transformative nature.

This focus should be on epilepsy alone, as the co-morbidities add a level of complexity that may make progress slow.

With genetic and epigenetic mechanisms represented strongly in other... more »

AES believes this is high public health priority as it will save lives i.e., to identify patients at higher risk for SUDEP and thus particularly in need of pharmaco-treatments or preventative devices (AICD) or patient surveillance. It will, however, be a major challenge due to ascertainment and low (sporadic) sample size worldwide. A genetic approach to identify genes associated with SUDEP is laudable though it seems... more »

The American Epilepsy Society considers this a high priority. As in human cancer, there will likely be common and overarching processes or mechanisms that lead to the establishment of the epileptic network. By analogy, all cancers stem from abnormally exuberant cell proliferation, and epilepsy reflects abnormal synchrony of neural networks. But the processes and mechanisms leading to seizures in SCN1A may be very different... more »

This should be a clear mandate for future and collaborative investigation in epilepsy, as it provides an opportunity to bring in scientists from disciplines outside of the epilepsy field.

The AES views this as the most important research endeavor for the next 5 years. We suggest a revision to explicitly state that new models must mimic human etiologies.

 

The lowest hanging fruit for epilepsy models is to use CRISPR-knock-in (KI) strategies to create mice expressing human gene variants rather than simply presuming gene knockout or over-expression will accurately model a loss- or gain-of-function mutation.... more »

Antiseizure medicines (ASMs) are one of the most commonly used teratogens. The current benchmarks include impact of epilepsy on women's health outcomes and health of their offspring (fetal and neonatal development, but progress is slow and the risks of fetal exposure for most ASMs remain unknown. Integrated basic and clinical research is needed to fully delineate risks and underlying mechanisms for ASM-induced anatomical... more »

Epilepsy patients' research data are typically collected and stored in standalone de-identified database silos, making it impossible to merge or compare data across disparate research studies or give feedback to the patient. A patient-generated clinical research ID (CRID) could be used to merge and share data across different research studies for the same patient without revealing PHI/PII data. CRID enables a secure two-way... more »

This priority will transform epilepsy research by integrating modern science into modern care for patients with epilepsy.

For example, a patient with as yet unexplained non-acquired epilepsy should be considered to have genetic epilepsy until proven otherwise and appropriately evaluated. If the first line of evaluation is unrevealing he or she should have an iterative re-analysis of cause in tandem with empiric therapy.... more »

More substantive research priorities, however well framed and targeted, can not alone overcome the inefficiencies and silo-ed structure for clinical care and research in the epilepsies.

By integrating clinical care and research—the standard for decades in pediatric oncology—we will get on a path where we will start seeing improvements in the quality of life for all those living with and too often dying from epilepsy.... more »

Most epilepsy-related Machine Learning (ML) tools tend to focus on seizure detection using readily available EEG "training" datasets. ML has potentially many other epilepsy-related use cases beyond seizure detection that are yet to be discovered, but the lack of "training" data is likely hindering its use. If tools could be developed to help identify and generate new "training" data from existing epilepsy datasets, ML... more »