Trends in management of patients with new-onset refractory status epilepticus (NORSE) from 2016 to 2023: An interim analysis.

In response to the evolving treatment landscape for new-onset refractory status epilepticus (NORSE) and the publication of consensus recommendations in 2022, we conducted a comparative analysis of NORSE management over time. Seventy-seven patients were enrolled by 32 centers, from July 2016 to August 2023, in the NORSE/FIRES biorepository at Yale. Immunotherapy was administered to 88% of patients after a median of 3 days, with 52% receiving second-line immunotherapy after a median of 12 days (anakinra 29%, rituximab 25%, and tocilizumab 19%). There was an increase in the use of second-line immunotherapies (odds ratio [OR] = 1.4, 95% CI = 1.1-1.8) and ketogenic diet (OR = 1.8, 95% CI = 1.3-2.6) over time. Specifically, patients from 2022 to 2023 more frequently received second-line immunotherapy (69% vs 40%; OR = 3.3; 95% CI = 1.3-8.9)-particularly anakinra (50% vs 13%; OR = 6.5; 95% CI = 2.3-21.0), and the ketogenic diet (OR = 6.8; 95% CI = 2.5-20.1)-than those before 2022. Among the 27 patients who received anakinra and/or tocilizumab, earlier administration after status epilepticus onset correlated with a shorter duration of status epilepticus (ρ = .519, p = .005). Our findings indicate an evolution in NORSE management, emphasizing the increasing use of second-line immunotherapies and the ketogenic diet. Future research will clarify the impact of these treatments and their timing on patient outcomes.

Comparative analysis of patients with new onset refractory status epilepticus preceded by fever (febrile infection-related epilepsy syndrome) versus without prior fever: An interim analysis.

Febrile infection-related epilepsy syndrome (FIRES) is a subset of new onset refractory status epilepticus (NORSE) that involves a febrile infection prior to the onset of the refractory status epilepticus. It is unclear whether FIRES and non-FIRES NORSE are distinct conditions. Here, we compare 34 patients with FIRES to 30 patients with non-FIRES NORSE for demographics, clinical features, neuroimaging, and outcomes. Because patients with FIRES were younger than patients with non-FIRES NORSE (median = 28 vs. 48 years old, p = .048) and more likely cryptogenic (odds ratio = 6.89), we next ran a regression analysis using age or etiology as a covariate. Respiratory and gastrointestinal prodromes occurred more frequently in FIRES patients, but no difference was found for non-infection-related prodromes. Status epilepticus subtype, cerebrospinal fluid (CSF) and magnetic resonance imaging findings, and outcomes were similar. However, FIRES cases were more frequently cryptogenic; had higher CSF interleukin 6, CSF macrophage inflammatory protein-1 alpha (MIP-1a), and serum chemokine ligand 2 (CCL2) levels; and received more antiseizure medications and immunotherapy. After controlling for age or etiology, no differences were observed in presenting symptoms and signs or inflammatory biomarkers, suggesting that FIRES and non-FIRES NORSE are very similar conditions.

Zebrafish models of candidate human epilepsy-associated genes provide evidence of hyperexcitability.

Hundreds of novel candidate human epilepsy-associated genes have been identified thanks to advancements in next-generation sequencing and large genome-wide association studies, but establishing genetic etiology requires functional validation. We generated a list of >2200 candidate epilepsy-associated genes, of which 81 were determined suitable for the generation of loss-of-function zebrafish models via CRISPR/Cas9 gene editing. Of those 81 crispants, 48 were successfully established as stable mutant lines and assessed for seizure-like swim patterns in a primary F2 screen. Evidence of seizure-like behavior was present in 5 (arfgef1, kcnd2, kcnv1, ubr5, wnt8b) of the 48 mutant lines assessed. Further characterization of those 5 lines provided evidence for epileptiform activity via electrophysiology in kcnd2 and wnt8b mutants. Additionally, arfgef1 and wnt8b mutants showed a decrease in the number of inhibitory interneurons in the optic tectum of larval animals. Furthermore, RNAseq revealed convergent transcriptional abnormalities between mutant lines, consistent with their developmental defects and hyperexcitable phenotypes. These zebrafish models provide strongest experimental evidence supporting the role of ARFGEF1, KCND2, and WNT8B in human epilepsy and further demonstrate the utility of this model system for evaluating candidate human epilepsy genes.

Identification of patients with epilepsy using automated electronic health records phenotyping.

OBJECTIVE: Unstructured data present in electronic health records (EHR) are a rich source of medical information; however, their abstraction is labor intensive. Automated EHR phenotyping (AEP) can reduce the need for manual chart review. We present an AEP model that is designed to automatically identify patients diagnosed with epilepsy. METHODS: The ground truth for model training and evaluation was captured from a combination of structured questionnaires filled out by physicians for a subset of patients and manual chart review using customized software. Modeling features included indicators of the presence of keywords and phrases in unstructured clinical notes, prescriptions for antiseizure medications (ASMs), International Classification of Diseases (ICD) codes for seizures and epilepsy, number of ASMs and epilepsy-related ICD codes, age, and sex. Data were randomly divided into training (70%) and hold-out testing (30%) sets, with distinct patients in each set. We trained regularized logistic regression and an extreme gradient boosting models. Model performance was measured using area under the receiver operating curve (AUROC) and area under the precision-recall curve (AUPRC), with 95% confidence intervals (CI) estimated via bootstrapping. RESULTS: Our study cohort included 3903 adults drawn from outpatient departments of nine hospitals between February 2015 and June 2022 (mean age = 47 ± 18 years, 57% women, 82% White, 84% non-Hispanic, 70% with epilepsy). The final models included 285 features, including 246 keywords and phrases captured from 8415 encounters. Both models achieved AUROC and AUPRC of 1 (95% CI = .99-1.00) in the hold-out testing set. SIGNIFICANCE: A machine learning-based AEP approach accurately identifies patients with epilepsy from notes, ICD codes, and ASMs. This model can enable large-scale epilepsy research using EHR databases.

A replicable, open-source, data integration method to support national practice-based research & quality improvement systems.

OBJECTIVES: The Epilepsy Learning Healthcare System (ELHS) was created in 2018 to address measurable improvements in outcomes for people with epilepsy. However, fragmentation of data systems has been a major barrier for reporting and participation. In this study, we aimed to test the feasibility of an open-source Data Integration (DI) method that connects real-life clinical data to national research and quality improvement (QI) systems. METHODS: The ELHS case report forms were programmed as EPIC SmartPhrases at Mass General Brigham (MGB) in December 2018 and subsequently as EPIC SmartForms in June 2021 to collect actionable, standardized, structured epilepsy data in the electronic health record (EHR) for subsequent pull into the external national registry of the ELHS. Following the QI methodology in the Chronic Care Model, 39 providers, epileptologists and neurologists, incorporated the ELHS SmartPhrase into their clinical workflow, focusing on collecting diagnosis of epilepsy, seizure type according to the International League Against Epilepsy, seizure frequency, date of last seizure, medication adherence and side effects. The collected data was stored in the Enterprise Data Warehouse (EDW) without integration with external systems. We developed and validated a DI method that extracted the data from EDW using structured query language and later preprocessed using text mining. We used the ELHS data dictionary to match fields in the preprocessed notes to obtain the final structured dataset with seizure control information. For illustration, we described the data curated from the care period of 12/2018-12/2021. RESULTS: The cohort comprised a total of 1806 patients with a mean age of 43 years old (SD: 17.0), where 57% were female, 80% were white, and 84% were non-Hispanic/Latino. Using our DI method, we automated the data mining, preprocessing, and exporting of the structured dataset into a local database, to be weekly accessible to clinicians and quality improvers. During the period of SmartPhrase implementation, there were 5168 clinic visits logged by providers documenting each patient's seizure type and frequency. During this period, providers documented 59% patients having focal seizures, 35% having generalized seizures and 6% patients having another type. Of the cohort, 45% patients had private insurance. The resulting structured dataset was bulk uploaded via web interface into the external national registry of the ELHS. CONCLUSIONS: Structured data can be feasibly extracted from text notes of epilepsy patients for weekly reporting to a national learning healthcare system.

Mosaic and non-mosaic protocadherin 19 mutation leads to neuronal hyperexcitability in zebrafish.

Epilepsy is one of the most common neurological disorders. The X-linked gene PCDH19 is associated with sporadic and familial epilepsy in humans, typically with early-onset clustering seizures and intellectual disability in females but not in so-called 'carrier' males, suggesting that mosaic PCDH19 expression is required to produce epilepsy. To characterize the role of loss of PCDH19 function in epilepsy, we generated zebrafish with truncating pcdh19 variants. Evaluating zebrafish larvae for electrophysiological abnormalities, we observed hyperexcitability phenotypes in both mosaic and non-mosaic pcdh19+/- and pcdh19-/- mutant larvae. Thus, we demonstrate that the key feature of epilepsy-network hyperexcitability-can be modeled effectively in zebrafish, even though overt spontaneous seizure-like swim patterns were not observed. Further, zebrafish with non-mosaic pcdh19 mutation displayed reduced numbers of inhibitory interneurons suggesting a potential cellular basis for the observed hyperexcitability. Our findings in both mosaic and non-mosaic pcdh19 mutant zebrafish challenge the prevailing theory that mosaicism governs all PCDH19-related phenotypes and point to interneuron-mediated mechanisms underlying these phenotypes.

Telemedicine Can Support Measurable and High-Quality Epilepsy Care During the COVID-19 Pandemic.

Routine outpatient epilepsy care has shifted from in-person to telemedicine visits in response to safety concerns posed by the coronavirus disease 2019 (COVID-19) pandemic. But whether telemedicine can support and maintain standardized documentation of high-quality epilepsy care remains unknown. In response, the authors conducted a quality improvement study at a level 4 epilepsy center between January 20, 2019, and May 31, 2020. Weekly average completion proportion of standardized documentation used by a team of neurologists for adult patients for the diagnosis of epilepsy, seizure classification, and frequency were analyzed. By December 15, 2019, a 94% average weekly completion proportion of standardized epilepsy care documentation was achieved that was maintained through May 31, 2020. Moreover, during the period of predominately telemedicine encounters in response to the pandemic, the completion proportion was 90%. This study indicates that high completion of standardized documentation of seizure-related information can be sustained during telemedicine appointments for routine outpatient epilepsy care at a level 4 epilepsy center.

Uridine-responsive epileptic encephalopathy due to inherited variants in CAD: A Tale of Two Siblings.

We report two siblings with intractable epilepsy, developmental regression, and progressive cerebellar atrophy due to biallelic variants in the gene CAD. For the affected girl, uridine started at age 5 resulted in dramatic improvements in seizure control and development, cessation of cerebellar atrophy, and resolution of hematological abnormalities. Her older brother had a more severe course and only modest response to uridine started at 14 years old. Treatment of this progressive condition via uridine supplementation provides an example of precision diagnosis and treatment using clear outcome measures and biomarkers to monitor efficacy.

Loss of MeCP2 Function Across Several Neuronal Populations Impairs Breathing Response to Acute Hypoxia.

Rett Syndrome (RTT) is a neurodevelopmental disorder caused by loss of function of the transcriptional regulator Methyl-CpG-Binding Protein 2 (MeCP2). In addition to the characteristic loss of hand function and spoken language after the first year of life, people with RTT also have a variety of physiological and autonomic abnormalities including disrupted breathing rhythms characterized by bouts of hyperventilation and an increased frequency of apnea. These breathing abnormalities, that likely involve alterations in both the circuitry underlying respiratory pace making and those underlying breathing response to environmental stimuli, may underlie the sudden unexpected death seen in a significant fraction of people with RTT. In fact, mice lacking MeCP2 function exhibit abnormal breathing rate response to acute hypoxia and maintain a persistently elevated breathing rate rather than showing typical hypoxic ventilatory decline that can be observed among their wild-type littermates. Using genetic and pharmacological tools to better understand the course of this abnormal hypoxic breathing rate response and the neurons driving it, we learned that the abnormal hypoxic breathing response is acquired as the animals mature, and that MeCP2 function is required within excitatory, inhibitory, and modulatory populations for a normal hypoxic breathing rate response. Furthermore, mice lacking MeCP2 exhibit decreased hypoxia-induced neuronal activity within the nucleus tractus solitarius of the dorsal medulla. Overall, these data provide insight into the neurons driving the circuit dysfunction that leads to breathing abnormalities upon loss of MeCP2. The discovery that combined dysfunction across multiple neuronal populations contributes to breathing dysfunction may provide insight into sudden unexpected death in RTT.

Accuracy of ICD-10-CM claims-based definitions for epilepsy and seizure type.

OBJECTIVE: To evaluate the accuracy of ICD-10-CM claims-based definitions for epilepsy and classifying seizure types in the outpatient setting. METHODS: We reviewed electronic health records (EHR) for a cohort of adults aged 18+ years seen by six neurologists who had an outpatient visit at a level 4 epilepsy center between 01/2019-09/2019. The neurologists used a standardized documentation template to capture the diagnosis of epilepsy (yes/no/unsure), seizure type (focal/generalized/unknown), and seizure frequency in the EHR. Using linked ICD-10-CM codes assigned by the provider, we assessed the accuracy of claims-based definitions for epilepsy, focal seizure type, and generalized seizure type against the reference-standard EHR documentation by estimating sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV). RESULTS: There were 673 eligible outpatient encounters. After review of EHRs for standardized documentation, an analytic sample consisted of 520 encounters representing 402 unique patients. In the EHR documentation, 93.5 % (n = 486/520) of encounters were with patients with a diagnosis of epilepsy. Of those, 66.0 % (n = 321/486) had ≥1 focal seizure, 41.6 % (n = 202/486) had ≥1 generalized seizure, and 7% (n = 34/486) had ≥1 unknown seizure. An ICD-10-CM definition for epilepsy (i.e., ICD-10 G40.X) achieved Sn = 84.4 % (95 % CI 80.8-87.5%), Sp = 79.4 % (95 % CI 62.1-91.3%), PPV = 98.3 % (95 % CI 96.6-99.3%), and NPV = 26.2 % (95 % CI 18.0-35.8%). The classification of focal vs generalized/unknown seizures achieved Sn = 69.8 % (95 % CI 64.4-74.8%), Sp = 79.4 % (95 % CI 72.4-85.3%), PPV = 86.8 % (95 % CI 82.1-90.7%), and NPV = 57.5 % (95 % CI 50.8-64.0%). CONCLUSIONS: Claims-based definitions using groups of ICD-10-CM codes assigned by neurologists in routine outpatient clinic visits at a level 4 epilepsy center performed well in discriminating between patients with and without a diagnosis of epilepsy and between seizure types.

Neurexophilin4 is a selectively expressed α-neurexin ligand that modulates specific cerebellar synapses and motor functions.

Neurexophilins are secreted neuropeptide-like glycoproteins, and neurexophilin1 and neurexophilin3 are ligands for the presynaptic cell adhesion molecule α-neurexin. Neurexophilins are more selectively expressed in the brain than α-neurexins, however, which led us to ask whether neurexophilins modulate the function of α-neurexin in a context-specific manner. We characterized the expression and function of neurexophilin4 in mice and found it to be expressed in subsets of neurons responsible for feeding, emotion, balance, and movement. Deletion of Neurexophilin4 caused corresponding impairments, most notably in motor learning and coordination. We demonstrated that neurexophilin4 interacts with α-neurexin and GABAARs in the cerebellum. Loss of Neurexophilin4 impaired cerebellar Golgi-granule inhibitory neurotransmission and synapse number, providing a partial explanation for the motor learning and coordination deficits observed in the Neurexophilin4 null mice. Our data illustrate how selectively expressed Neurexophilin4, an α-neurexin ligand, regulates specific synapse function and modulates cerebellar motor control.

Genetic rodent models of brain disorders: Perspectives on experimental approaches and therapeutic strategies.

Neurobehavioral disorders comprised of neurodegenerative, neurodevelopmental, and psychiatric disorders together represent leading causes of morbidity and mortality. Despite significant academic research and industry efforts to elucidate the disease mechanisms operative in these disorders and to develop mechanism-based therapies, our understanding remains incomplete and our access to tractable therapeutic interventions severely limited. The magnitude of these short-comings can be measured by the growing list of disappointing clinical trials based on initially promising compounds identified in genetic animal models. This review and commentary will explore why this may be so, focusing on the central role that genetic models of neurobehavioral disorders have come to occupy in current efforts to identify disease mechanisms and therapies. In particular, we will highlight the unique pitfalls and challenges that have hampered success in these models as compared to genetic models of non-neurological diseases as well as to symptom-based models of the early 20th century that led to the discovery of all major classes of psychoactive pharmaceutical compounds still used today. Using examples from specific genetic rodent models of human neurobehavioral disorders, we will highlight issues of reproducibility, construct validity, and translational relevance in the hopes that these examples will be instructive toward greater success in future endeavors. Lastly, we will champion a two-pronged approach toward identifying novel therapies for neurobehavioral disorders that makes greater use of the historically more successful symptom-based approaches in addition to more mechanism-based approaches.

Loss of MeCP2 in the rat models regression, impaired sociability and transcriptional deficits of Rett syndrome.

Mouse models of the transcriptional modulator Methyl-CpG-Binding Protein 2 (MeCP2) have advanced our understanding of Rett syndrome (RTT). RTT is a 'prototypical' neurodevelopmental disorder with many clinical features overlapping with other intellectual and developmental disabilities (IDD). Therapeutic interventions for RTT may therefore have broader applications. However, the reliance on the laboratory mouse to identify viable therapies for the human condition may present challenges in translating findings from the bench to the clinic. In addition, the need to identify outcome measures in well-chosen animal models is critical for preclinical trials. Here, we report that a novel Mecp2 rat model displays high face validity for modelling psychomotor regression of a learned skill, a deficit that has not been shown in Mecp2 mice. Juvenile play, a behavioural feature that is uniquely present in rats and not mice, is also impaired in female Mecp2 rats. Finally, we demonstrate that evaluating the molecular consequences of the loss of MeCP2 in both mouse and rat may result in higher predictive validity with respect to transcriptional changes in the human RTT brain. These data underscore the similarities and differences caused by the loss of MeCP2 among divergent rodent species which may have important implications for the treatment of individuals with disease-causing MECP2 mutations. Taken together, these findings demonstrate that the Mecp2 rat model is a complementary tool with unique features for the study of RTT and highlight the potential benefit of cross-species analyses in identifying potential disease-relevant preclinical outcome measures.

Female Mecp2(+/-) mice display robust behavioral deficits on two different genetic backgrounds providing a framework for pre-clinical studies.

Rett syndrome (RTT) is an X-linked neurological disorder caused by mutations in the gene encoding the transcriptional modulator methyl-CpG-binding protein 2 (MeCP2). Typical RTT primarily affects girls and is characterized by a brief period of apparently normal development followed by the loss of purposeful hand skills and language, the onset of anxiety, hand stereotypies, autistic features, seizures and autonomic dysfunction. Mecp2 mouse models have extensively been studied to demonstrate the functional link between MeCP2 dysfunction and RTT pathogenesis. However, the majority of studies have focused primarily on the molecular and behavioral consequences of the complete absence of MeCP2 in male mice. Studies of female Mecp2(+/-) mice have been limited because of potential phenotypic variability due to X chromosome inactivation effects. To determine whether reproducible and reliable phenotypes can be detected Mecp2(+/-) mice, we analyzed Mecp2(+/-) mice of two different F1 hybrid isogenic backgrounds and at young and old ages using several neurobehavioral and physiological assays. Here, we report a multitude of phenotypes in female Mecp2(+/-) mice, some presenting as early as 5 weeks of life. We demonstrate that Mecp2(+/-) mice recapitulate several aspects of typical RTT and show that mosaic expression of MeCP2 does not preclude the use of female mice in behavioral and molecular studies. Importantly, we uncover several behavioral abnormalities that are present in two genetic backgrounds and report on phenotypes that are unique to one background. These findings provide a framework for pre-clinical studies aimed at improving the constellation of phenotypes in a mouse model of RTT.

Crh and Oprm1 mediate anxiety-related behavior and social approach in a mouse model of MECP2 duplication syndrome.

Genomic duplications spanning Xq28 are associated with a spectrum of phenotypes, including anxiety and autism. The minimal region shared among affected individuals includes MECP2 and IRAK1, although it is unclear which gene when overexpressed causes anxiety and social behavior deficits. We report that doubling MECP2 levels causes heightened anxiety and autism-like features in mice and alters the expression of genes that influence anxiety and social behavior, such as Crh and Oprm1. To test the hypothesis that alterations in these two genes contribute to heightened anxiety and social behavior deficits, we analyzed MECP2 duplication mice (MECP2-TG1) that have reduced Crh and Oprm1 expression. In MECP2-TG1 animals, reducing the levels of Crh or its receptor, Crhr1, suppressed anxiety-like behavior; in contrast, reducing Oprm1 expression improved abnormal social behavior. These data indicate that increased MeCP2 levels affect molecular pathways underlying anxiety and social behavior and provide new insight into potential therapies for MECP2-related disorders.

Adult neural function requires MeCP2.

Rett syndrome (RTT) is a postnatal neurological disorder caused by mutations in MECP2, encoding the epigenetic regulator methyl-CpG-binding protein 2 (MeCP2). The onset of RTT symptoms during early life together with findings suggesting neurodevelopmental abnormalities in RTT and mouse models of RTT raised the question of whether maintaining MeCP2 function exclusively during early life might protect against disease. We show by using an inducible model of RTT that deletion of Mecp2 in adult mice recapitulates the germline knock-out phenotype, underscoring the ongoing role of MeCP2 in adult neurological function. Moreover, unlike the effects of other epigenetic instructions programmed during early life, the effects of early MeCP2 function are lost soon after its deletion. These findings suggest that therapies for RTT must be maintained throughout life.

The locus encoding an oligomorphic family of MHC-A alleles (Mane-A*06/Mamu-A*05) is present at high frequency in several macaque species.

Several macaques species are used for HIV pathogenesis and vaccine studies, and the characterization of their major histocompatibility complex (MHC) class I genes is required to rigorously evaluate the cellular immune responses induced after immunization and/or infection. In this study, we demonstrate that the gene expressing the Mane-A*06 allele of pig-tailed macaques is an orthologue of the locus encoding the Mamu-A*05 allele family in rhesus macaques. Analysis of the distribution of this locus in a cohort of 63 pig-tailed macaques revealed that it encodes an oligomorphic family of alleles, highly prevalent (90%) in the pig-tailed macaque population. Similarly, this locus was very frequently found (62%) in a cohort of 80 Indian rhesus macaques. An orthologous gene was also detected in cynomolgus monkeys originating from four different geographical locations, but was absent in two African monkey species. Expression analysis in pig-tailed macaques revealed that the Mane-A*06 alleles encoded by this locus are transcribed at 10- to 20-fold lower levels than other MHC-A alleles (Mane-A*03 or Mane-A*10). Despite their conservation and high prevalence among Asian macaque species, the alleles of the Mane-A*06 family and, by extension their orthologues in rhesus and cynomolgus monkeys, may only modestly contribute to cellular immune responses in macaques because of their low level of expression.