Genetic Discoveries Drive Molecular Analyses and Targeted Therapeutic Options in the Epilepsies

Precision medicine for genetic epilepsy on the horizon: Recent advances, present challenges, and suggestions for continued progress

The genetic basis of many epilepsies is increasingly understood, giving rise to the possibility of precision treatments tailored to specific genetic etiologies. Despite this, current medical therapy for most epilepsies remains imprecise, aimed primarily at empirical seizure reduction rather than targeting specific disease processes. Intellectual and technological leaps in diagnosis over the past 10 years have not yet translated to routine changes in clinical practice. However, the epilepsy community is poised to make impressive gains in precision therapy, with continued innovation in gene discovery, diagnostic ability, and bioinformatics; increased access to genetic testing and counseling; fuller understanding of natural histories; agility and rigor in preclinical research, including strategic use of emerging model systems; and engagement of an evolving group of stakeholders (including patient advocates, governmental resources, and clinicians and scientists in academia and industry). In each of these areas, we highlight notable examples of recent progress, new or persistent challenges, and future directions. The future of precision medicine for genetic epilepsy looks bright if key opportunities on the horizon can be pursued with strategic and coordinated effort.

The Genetic Control of Stoichiometry Underlying Autism

Autism is a common and complex neurologic disorder whose scientific underpinnings have begun to be established in the past decade. The essence of this breakthrough has been a focus on families, where genetic analyses are strongest, versus large-scale, case-control studies. Autism genetics has progressed in parallel with technology, from analyses of copy number variation to whole-exome sequencing (WES) and whole-genome sequencing (WGS). Gene mutations causing complete loss of function account for perhaps one-third of cases, largely detected through WES. This limitation has increased interest in understanding the regulatory variants of genes that contribute in more subtle ways to the disorder. Strategies combining biochemical analysis of gene regulation, WGS analysis of the noncoding genome, and machine learning have begun to succeed. The emerging picture is that careful control of the amounts of transcription, mRNA, and proteins made by key brain genes-stoichiometry-plays a critical role in defining the clinical features of autism.

A Transcriptome-Based Drug Discovery Paradigm for Neurodevelopmental Disorders

Advances in genetic discoveries have created substantial opportunities for precision medicine in neurodevelopmental disorders. Many of the genes implicated in these diseases encode proteins that regulate gene expression, such as chromatin-associated proteins, transcription factors, and RNA-binding proteins. The identification of targeted therapeutics for individuals carrying mutations in these genes remains a challenge, as the encoded proteins can theoretically regulate thousands of downstream targets in a considerable number of cell types. Here, we propose the application of a drug discovery approach originally developed for cancer called "transcriptome reversal" for these neurodevelopmental disorders. This approach attempts to identify compounds that reverse gene-expression signatures associated with disease states. ANN NEUROL 2021;89:199-211.

Nonseizure consequences of Dravet syndrome, KCNQ2-DEE, KCNB1-DEE, Lennox-Gastaut syndrome, ESES: A functional framework

RATIONALE

Developmental epilepsies and encephalopathies (DEEs) are characterized by many severe developmental impairments, which are not well-described. A functional framework could facilitate understanding of their nature and severity and guide the selection instruments to measure improvements in therapeutic trials.

METHODS

An online survey administered through several parent-organized foundations utilized accepted functional classifications and questionnaires derived from common instruments to determine levels of mobility, fine motor, communication, and feeding functions. Statistical analyses focused on overall levels of function and across-group comparisons adjusted for age.

RESULTS

From 6/2018 to 2/2020, 252 parents provided information for one or more functional domains. Median age was 7.2 years (interquartile range (IQR): 3.9 to 11.8), and 128 (51%) were females. DEE groups were Dravet syndrome (N = 72), KCNQ2-DEE (N = 80), KCNB1-DEE, (N = 33), Lennox-Gastaut syndrome (LGS; N = 26), electrographic status epilepticus in sleep (ESES; N = 15), and others (N = 26). Overall, functional hand grasp was absent in 48 (20%). Of children ≥2 years old, 60/214 (28%) could not walk independently, 85 (40%) were dependent on someone else for feeding, and 153 (73%) did not effectively communicate with unfamiliar people. Impairments entailing absence or near absence of independent function (profound impairment) were observed in 0, 1, 2, 3, and 4 domains for 58 (25%), 78 (34%), 40 (17%), 33 (14%), and 22 (10%) children, respectively. After adjustment for age, impairment levels varied substantially across DEE group for mobility (p < 0.0001), feeding (p < 0.0001), communication (p < 0.0001), hand grasp (p < 0.0001), and number of profoundly impaired domains (p < 0.0001). Three or four profoundly affected domains were reported in 44% of KCNQ2-DEE participants, followed by LGS (29%), KCNB1-DEE (27%), ESES (7%), and Dravet syndrome (6%).

CONCLUSIONS

Many children with DEEs experience severe functional impairments, and few children have typical function. As precision therapies will emphasize nonseizures consequences of DEEs, understanding the nature of abilities and impairments will be critical to selecting appropriate outcome measures in therapeutic trials.

Calcium imaging and dynamic causal modelling reveal brain-wide changes in effective connectivity and synaptic dynamics during epileptic seizures

Pathophysiological explanations of epilepsy typically focus on either the micro/mesoscale (e.g. excitation-inhibition imbalance), or on the macroscale (e.g. network architecture). Linking abnormalities across spatial scales remains difficult, partly because of technical limitations in measuring neuronal signatures concurrently at the scales involved. Here we use light sheet imaging of the larval zebrafish brain during acute epileptic seizure induced with pentylenetetrazole. Spectral changes of spontaneous neuronal activity during the seizure are then modelled using neural mass models, allowing Bayesian inference on changes in effective network connectivity and their underlying synaptic dynamics. This dynamic causal modelling of seizures in the zebrafish brain reveals concurrent changes in synaptic coupling at macro- and mesoscale. Fluctuations of both synaptic connection strength and their temporal dynamics are required to explain observed seizure patterns. These findings highlight distinct changes in local (intrinsic) and long-range (extrinsic) synaptic transmission dynamics as a possible seizure pathomechanism and illustrate how our Bayesian model inversion approach can be used to link existing neural mass models of seizure activity and novel experimental methods.

A survey of antiepileptic drug responses identifies drugs with potential efficacy for seizure control in Wolf-Hirschhorn syndrome

Seizures are present in over 90% of infants and children with Wolf-Hirschhorn syndrome (WHS). When present, they significantly affect quality of life. The goal of this study was to use caregiver reports to describe the comparative efficacies of commonly used antiepileptic medications in a large population of individuals with WHS. A web-based, confidential caregiver survey was developed to capture seizure semiology and a chronologic record of seizure treatments as well as responses to each treatment. Adverse events for each drug were also cataloged. We received 141 complete survey responses (47% response rate) describing the seizures of individuals ranging in age from 4months to 61years (90 females: 51 males). Using the Early Childhood Epilepsy Severity Scale (E-Chess), WHS-associated seizures are demonstrably severe regardless of deletion size. The best-performing antiepileptic drugs (AEDs) for controlling seizures in this cohort were broad spectrum drugs clobazam, levetiracetam, and lamotrigine; whereas, the three commonly used carboxamide class drugs: carbamazepine, phenytoin, and oxcarbazepine, were reported to have little effect on, or even exacerbate, seizures. The carboxamide class drugs, along with phenobarbital and topiramate, were also associated with the highest rate of intolerance due to cooccurrence of adverse events. Levetiracetam, clobazam, and clonazepam demonstrated higher tolerability and comparatively less severe adverse events (Wilcoxon rank sum comparison between performance of levetiracetam and carboxamide class drugs gives a p<0.0001 after multiple comparison adjustment). This is the largest survey to date assessing WHS seizures. This study design is susceptible to possible bias, as the data are largely drawn from caregiver report and investigators had limited access to medical records. Despite this, our data suggest that the genetic etiology of seizures, together with an accurate electroclinical delineation, are important components of drug selection, even in contiguous gene syndromes which may have complex seizure etiologies.

Drug development in the era of precision medicine

For the past three decades, the use of genomics to inform drug discovery and development pipelines has generated both excitement and scepticism. Although earlier efforts successfully identified some new drug targets, the overall clinical efficacy of developed drugs has remained unimpressive, owing in large part to the heterogeneous causes of disease. Recent technological and analytical advances in genomics, however, have now made it possible to rapidly identify and interpret the genetic variation underlying a single patient's disease, thereby providing a window into patient-specific mechanisms that cause or contribute to disease, which could ultimately enable the 'precise' targeting of these mechanisms. Here, we first examine and highlight the successes and limitations of the earlier phases of genomics in drug discovery and development. We then review the current major efforts in precision medicine and discuss the potential broader utility of mechanistically guided treatments going forward.