Clinical approach to the diagnosis of autoimmune encephalitis in the pediatric patient.
Neurology(R) neuroimmunology & neuroinflammation
Cellucci, T., Van Mater, H., Graus, F., Muscal, E., Gallentine, W., Klein-Gitelman, M. S., Benseler, S. M., Frankovich, J., Gorman, M. P., Van Haren, K., Dalmau, J., Dale, R. C.
2020; 7 (2)
Abstract
OBJECTIVE: Autoimmune encephalitis (AE) is an important and treatable cause of acute encephalitis. Diagnosis of AE in a developing child is challenging because of overlap in clinical presentations with other diseases and complexity of normal behavior changes. Existing diagnostic criteria for adult AE require modification to be applied to children, who differ from adults in their clinical presentations, paraclinical findings, autoantibody profiles, treatment response, and long-term outcomes.METHODS: A subcommittee of the Autoimmune Encephalitis International Working Group collaborated through conference calls and email correspondence to consider the pediatric-specific approach to AE. The subcommittee reviewed the literature of relevant AE studies and sought additional input from other expert clinicians and researchers.RESULTS: Existing consensus criteria for adult AE were refined for use in children. Provisional pediatric AE classification criteria and an algorithm to facilitate early diagnosis are proposed. There is also discussion about how to distinguish pediatric AE from conditions within the differential diagnosis.CONCLUSIONS: Diagnosing AE is based on the combination of a clinical history consistent with pediatric AE and supportive diagnostic testing, which includes but is not dependent on antibody testing. The proposed criteria and algorithm require validation in prospective pediatric cohorts.
View details for DOI 10.1212/NXI.0000000000000663
View details for PubMedID 31953309
Abstract
Phenotypic and biological characterization of rare monogenic disorders represents 1 of the most important avenues toward understanding the mechanisms of human disease. Among patients with SH3 and multiple ankyrin repeat domains 3 (SHANK3) mutations, a subset will manifest neurologic regression, psychosis, and mood disorders. However, which patients will be affected, when, and why are important unresolved questions. Authors of recent studies suggest neuronal SHANK3 expression is modulated by both inflammatory and hormonal stimuli. In this case series, we describe 4 independent clinical observations of an immunotherapy responsive phenotype of peripubertal-onset neuropsychiatric regression in 4 girls with pathogenic SHANK3 mutations. Each child exhibited a history of stable, mild-to-moderate lifelong developmental disability until 12 to 14 years of age, at which time each manifested a similar, subacute-onset neurobehavioral syndrome. Symptoms included mutism, hallucinations, insomnia, inconsolable crying, obsessive-compulsive behaviors, loss of self-care, and urinary retention and/or incontinence. Symptoms were relatively refractory to antipsychotic medication but improved after immunomodulatory treatment. All 4 patients exhibited chronic relapsing courses during a period of treatment and follow-up ranging from 3 to 6 years. Two of the 4 girls recovered their premorbid level of functioning. We briefly review the scientific literature to offer a conceptual and molecular framework for understanding these clinical observations. Future clinical and translational investigations in this realm may offer insights into mechanisms and therapies bridging immune function and human behavior.
View details for DOI 10.1542/peds.2019-1490
View details for PubMedID 32015180
Abstract
The use of whole-exome and whole-genome sequencing has been a catalyst for a genotype-first approach to diagnostics. Under this paradigm, we have implemented systematic sequencing of neonates and young children with a suspected genetic disorder. Here, we report on two families with recessive mutations in NCAPG2 and overlapping clinical phenotypes that include severe neurodevelopmental defects, failure to thrive, ocular abnormalities, and defects in urogenital and limb morphogenesis. NCAPG2 encodes a member of the condensin II complex, necessary for the condensation of chromosomes prior to cell division. Consistent with a causal role for NCAPG2, we found abnormal chromosome condensation, augmented anaphase chromatin-bridge formation, and micronuclei in daughter cells of proband skin fibroblasts. To test the functional relevance of the discovered variants, we generated an ncapg2 zebrafish model. Morphants displayed clinically relevant phenotypes, such as renal anomalies, microcephaly, and concomitant increases in apoptosis and altered mitotic progression. These could be rescued by wild-type but not mutant human NCAPG2 mRNA and were recapitulated in CRISPR-Cas9 F0 mutants. Finally, we noted that the individual with a complex urogenital defect also harbored a heterozygous NPHP1 deletion, a common contributor to nephronophthisis. To test whether sensitization at the NPHP1 locus might contribute to a more severe renal phenotype, we co-suppressed nphp1 and ncapg2, which resulted in significantly more dysplastic renal tubules in zebrafish larvae. Together, our data suggest that impaired function of NCAPG2 results in a severe condensinopathy, and they highlight the potential utility of examining candidate pathogenic lesions beyond the primary disease locus.
View details for DOI 10.1016/j.ajhg.2018.11.017
View details for Web of Science ID 000454775500011
View details for PubMedID 30609410
Abstract
PurposeAs part of the Epilepsy Genetics Initiative, we re-evaluated clinically generated exome sequence data from 54 epilepsy patients and their unaffected parents to identify molecular diagnoses not provided in the initial diagnostic interpretation.MethodsWe compiled and analyzed exome sequence data from 54 genetically undiagnosed trios using a validated analysis pipeline. We evaluated the significance of the genetic findings by reanalyzing sequence data generated at Ambry Genetics, and from a number of additional case and control cohorts.ResultsIn 54 previously undiagnosed trios, we identified two de novo missense variants in SCN8A in the highly expressed alternative exon 5 A-an exon only recently added to the Consensus Coding Sequence database. One additional undiagnosed epilepsy patient harboring a de novo variant in exon 5 A was found in the Ambry Genetics cohort. Missense variants in SCN8A exon 5 A are extremely rare in the population, further supporting the pathogenicity of the de novo alterations identified.ConclusionThese results expand the range of SCN8A variants in epileptic encephalopathy patients and illustrate the necessity of ongoing reanalysis of negative exome sequences, as advances in the knowledge of disease genes and their annotations will permit new diagnoses to be made.
View details for DOI 10.1038/gim.2017.100
View details for Web of Science ID 000425939300013
View details for PubMedID 29121005
View details for PubMedCentralID PMC5823708
Abstract
Electrographic seizures are common in encephalopathic critically ill children, but identification requires continuous EEG monitoring (CEEG). Development of a seizure prediction model would enable more efficient use of limited CEEG resources. We aimed to develop and validate a seizure prediction model for use among encephalopathic critically ill children.We developed a seizure prediction model using a retrospectively acquired multi-center database of children with acute encephalopathy without an epilepsy diagnosis, who underwent clinically indicated CEEG. We performed model validation using a separate prospectively acquired single center database. Predictor variables were chosen to be readily available to clinicians prior to the onset of CEEG and included: age, etiology category, clinical seizures prior to CEEG, initial EEG background category, and inter-ictal discharge category.The model has fair to good discrimination ability and overall performance. At the optimal cut-off point in the validation dataset, the model has a sensitivity of 59% and a specificity of 81%. Varied cut-off points could be chosen to optimize sensitivity or specificity depending on available CEEG resources.Despite inherent variability between centers, a model developed using multi-center CEEG data and few readily available variables could guide the use of limited CEEG resources when applied at a single center. Depending on CEEG resources, centers could choose lower cut-off points to maximize identification of all patients with seizures (but with more patients monitored) or higher cut-off points to reduce resource utilization by reducing monitoring of lower risk patients (but with failure to identify some patients with seizures).
View details for DOI 10.1016/j.seizure.2014.09.013
View details for Web of Science ID 000349881100019
View details for PubMedCentralID PMC4315714
Abstract
Electrographic seizures are common in encephalopathic critically ill children, but identification requires continuous EEG monitoring (CEEG). Development of a seizure prediction model would enable more efficient use of limited CEEG resources. We aimed to develop and validate a seizure prediction model for use among encephalopathic critically ill children.We developed a seizure prediction model using a retrospectively acquired multi-center database of children with acute encephalopathy without an epilepsy diagnosis, who underwent clinically indicated CEEG. We performed model validation using a separate prospectively acquired single center database. Predictor variables were chosen to be readily available to clinicians prior to the onset of CEEG and included: age, etiology category, clinical seizures prior to CEEG, initial EEG background category, and inter-ictal discharge category.The model has fair to good discrimination ability and overall performance. At the optimal cut-off point in the validation dataset, the model has a sensitivity of 59% and a specificity of 81%. Varied cut-off points could be chosen to optimize sensitivity or specificity depending on available CEEG resources.Despite inherent variability between centers, a model developed using multi-center CEEG data and few readily available variables could guide the use of limited CEEG resources when applied at a single center. Depending on CEEG resources, centers could choose lower cut-off points to maximize identification of all patients with seizures (but with more patients monitored) or higher cut-off points to reduce resource utilization by reducing monitoring of lower risk patients (but with failure to identify some patients with seizures).
View details for DOI 10.1016/j.seizure.2014.09.013
View details for PubMedID 25458097
View details for PubMedCentralID PMC4315714
Abstract
The cerebral organization of language in epilepsy patients has been studied with invasive procedures such as Wada testing and electrical cortical stimulation mapping and more recently with noninvasive neuroimaging techniques, such as functional MRI. In the setting of a chronic seizure disorder, clinical variables have been shown to contribute to cerebral language reorganization underscoring the need for language lateralization and localization procedures. We present a 14-year-old pediatric patient with a refractory epilepsy disorder who underwent two neurosurgical resections of a left frontal epileptic focus separated by a year. He was mapped extraoperatively through a subdural grid using cortical stimulation to preserve motor and language functions. The clinical history and extensive workup prior to surgery is discussed as well as the opportunity to compare the cortical maps for language, motor, and sensory function before each resection. Reorganization in cortical tongue sensory areas was seen concomitant with a new zone of ictal and interictal activity in the previous tongue sensory area. Detailed neuropsychological data is presented before and after any surgical intervention to hypothesize about the extent of reorganization between epochs. We conclude that intrahemispheric cortical plasticity does occur following frontal lobe resective surgery in a teenager with medically refractory seizures.
View details for DOI 10.3390/brainsci3041597
View details for PubMedID 24961623
View details for PubMedCentralID PMC4061887
