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With the increased power now available in sequencing and genomic technologies has come the realization that within an organism, individual cellular genomes can diverge from one another. Poduri et al. (p. 10.1126/science.1237758 ) review how de novo mutations, which arise in the parental germ line, or during development of the child, are the cause of a variety of neurodevelopmental disorders. Genetic mutations causing human disease are conventionally thought to be inherited through the germ line from one’s parents and present in all somatic (body) cells, except for most cancer mutations, which arise somatically. Increasingly, somatic mutations are being identified in diseases other than cancer, including neurodevelopmental diseases. Somatic mutations can arise during the course of prenatal brain development and cause neurological disease—even when present at low levels of mosaicism, for example—resulting in brain malformations associated with epilepsy and intellectual disability. Novel, highly sensitive technologies will allow more accurate evaluation of somatic mutations in neurodevelopmental disorders and during normal brain development.

A recent study describes the yield and clinical utility of epilepsy gene panel testing in a cohort of adults with epilepsy and intellectual disability. These findings are similar to those in children with developmental epileptic encephalopathies and support the utility of testing in this subgroup of adults with epilepsy.

Somatic mutations can cause brain malformations but may escape detection if their prevalence in blood is low. The authors of this study used deep-coverage targeting sequencing to gauge the extent to which somatic mutations cause relatively common forms of brain malformation. Somatic mutation, a postzygotic event, leads to two or more populations of cells with distinct genotypes in an organism, despite development from a single fertilized egg. 1 , 2 Although the role of somatic mutation in cancer cells is well established, 3 an analogous role for somatic mutations that occur randomly during the normal mitotic cell divisions of embryonic development — and that are therefore present in clones of cells in one or more tissues of the body — has been recognized only recently. Somatic mutations have been described in several noncancerous disorders, including the McCune–Albright syndrome, 4 the Sturge–Weber syndrome, 5 the Proteus syndrome, . . .

Purpose Neurodevelopmental disabilities are common and genetically heterogeneous. We identified a homozygous variant in the gene encoding UFM1-specific peptidase 2 ( UFSP2 ), which participates in the UFMylation pathway of protein modification. UFSP2 variants are implicated in autosomal dominant skeletal dysplasias, but not neurodevelopmental disorders. Homozygosity for the variant occurred in eight children from four South Asian families with neurodevelopmental delay and epilepsy. We describe the clinical consequences of this variant and its effect on UFMylation. Methods Exome sequencing was used to detect potentially pathogenic variants and identify shared regions of homozygosity. Immunoblotting assessed protein expression and post-translational modifications in patient-derived fibroblasts. Results The variant (c.344T>A; p.V115E) is rare and alters a conserved residue in UFSP2. Immunoblotting in patient-derived fibroblasts revealed reduced UFSP2 abundance and increased abundance of UFMylated targets, indicating the variant may impair de-UFMylation rather than UFMylation. Reconstituting patient-derived fibroblasts with wild-type UFSP2 reduced UFMylation marks. Analysis of UFSP2’s structure indicated that variants observed in skeletal disorders localize to the catalytic domain, whereas V115 resides in an N-terminal domain possibly involved in substrate binding. Conclusion Different UFSP2 variants cause markedly different diseases, with homozygosity for V115E causing a severe syndrome of neurodevelopmental disability and epilepsy.

Technologies for mapping the spatial and temporal patterns of neural activity have advanced our understanding of brain function in both health and disease. An important application of these technologies is the discovery of next-generation neurotherapeutics for neurological and psychiatric disorders. Here, we describe an in vivo drug screening strategy that combines high-throughput technology to generate large-scale brain activity maps (BAMs) with machine learning for predictive analysis. This platform enables evaluation of compounds’ mechanisms of action and potential therapeutic uses based on information-rich BAMs derived from drug-treated zebrafish larvae. From a screen of clinically used drugs, we found intrinsically coherent drug clusters that are associated with known therapeutic categories. Using BAM-based clusters as a functional classifier, we identify anti-seizure-like drug leads from non-clinical compounds and validate their therapeutic effects in the pentylenetetrazole zebrafish seizure model. Collectively, this study provides a framework to advance the field of systems neuropharmacology. A major goal in neuropharmacology is to develop new tools to effectively test the therapeutic potential of pharmacological agents to treat neurological and psychiatric conditions. Here, authors present an in vivo drug screening system that generates large-scale brain activity maps to be used with machine learning to predict the therapeutic potential of clinically relevant drug leads.

Objective KCNQ2‐associated developmental and epileptic encephalopathies (DEE) present with seizures and developmental impairments. The relation between seizures and functional impairments in affected children and the relation of a specific genetic variant to seizure control remains unknown. Methods Parents of children with documented KCNQ2 variants who participated in a structured, online natural history survey provided information about seizure history, functional mobility, hand use, communication function, and feeding independence. Bivariate analyses were performed with nonparametric methods and logistic regression was used for multivariable analyses. Results Thirty‐nine children (20, 51% girls, median age 4.5 years, interquartile range (IQR) 1.9—19.3) had a median age of seizure onset of 1 day (IQR 1—3 days). The most common seizure types were bilateral tonic‐clonic (N = 72, 28%) and bilateral tonic (N = 13, 33%). Time since last seizure was <6 months (N = 18, 46%), 6–23 months (N = 11, 28%), and ≥24 months (N = 10 26%). Severe functional impairment was reported for mobility (62%), hand grasp (31%), feeding (59%), and communication (77%). Twenty‐eight (72%) were impaired in ≥2 domains. There were only weak and inconsistent associations between seizure recency and individual impairments or number of impairments after adjustment for other factors. The functional location of the variants within the Kv7.2 protein was not associated with seizure control. Interpretation Seizures in KCNQ2‐DEE are often well‐controlled, but children have severe impairments regardless. With the increased potential for precision therapies targeting the Kv7.2 channel or the KCNQ2 gene itself, identifying the most relevant and sensitive clinical endpoints will be critical to ensure successful trials of new therapies.

Care advances in the United States (US) have led to improved survival of children with neurological impairment (NI). Children with NI may account for an increasing proportion of hospital resources. However, this assumption has not been tested at a national level. We conducted a study of 25,747,016 US hospitalizations of children recorded in the Kids' Inpatient Database (years 1997, 2000, 2003, and 2006). Children with NI were identified with International Classification of Diseases, 9th Revision, Clinical Modification diagnoses resulting in functional and/or intellectual impairment. We assessed trends in inpatient resource utilization for children with NI with a Mantel-Haenszel chi-square test using all 4 y of data combined. Across the 4 y combined, children with NI accounted for 5.2% (1,338,590) of all hospitalizations. Epilepsy (52.2% [n = 538,978]) and cerebral palsy (15.9% [n = 164,665]) were the most prevalent NI diagnoses. The proportion of hospitalizations attributable to children with NI did not change significantly (p = 0.32) over time. In 2006, children with NI accounted for 5.3% (n = 345,621) of all hospitalizations, 13.9% (n = 3.4 million) of bed days, and 21.6% (US$17.7 billion) of all hospital charges within all hospitals. Over time, the proportion of hospitalizations attributable to children with NI decreased within non-children's hospitals (3.0% [n = 146,324] in 1997 to 2.5% [n = 113,097] in 2006, p<.001) and increased within children's hospitals (11.7% [n = 179,324] in 1997 to 13.5% [n = 209,708] in 2006, p<0.001). In 2006, children with NI accounted for 24.7% (2.1 million) of bed days and 29.0% (US$12.0 billion) of hospital charges within children's hospitals. Children with NI account for a substantial proportion of inpatient resources utilized in the US. Their impact is growing within children's hospitals. We must ensure that the current health care system is staffed, educated, and equipped to serve this growing segment of vulnerable children.

A new method that involves marking DNA by changing its sequence may provide a more accurate understanding of developmental disorders and cancer in models of disease. Human genetic variation in both health and disease can arise through inherited germline genetic variants, changes that form the basis of inherited genetic traits. It has become increasingly recognized that genetic variation may also arise spontaneously during development. Spontaneous genetic variants may arise at the gamete or zygote stage, leading to an organism in which every cell carries the variant, an event that can in turn have widespread effects. Variants that occur early during postzygotic development may result in a mosaic pattern that may affect most, but not all, organ systems. When variants arise later in development, they may be . . .

Sudden Infant Death syndrome (SIDS) is a diagnosis of exclusion. Decades of research have made steady gains in understanding plausible mechanisms of terminal events. Current evidence suggests SIDS includes heterogeneous biological conditions, such as metabolic, cardiac, neurologic, respiratory, and infectious conditions. Here we review genetic studies that address each of these areas in SIDS cases and cohorts, providing a broad view of the genetic underpinnings of this devastating phenomenon. The current literature has established a role for monogenic genetic causes of SIDS mortality in a subset of cases. To expand upon our current knowledge of disease-causing genetic variants in SIDS cohorts and their mechanisms, future genetic studies may employ functional assessments of implicated variants, broader genetic tests, and the inclusion of parental genetic data and family history information.

Importance Genomic advances inform our understanding of epilepsy and can be translated to patients as precision diagnoses that influence clinical treatment, prognosis, and counseling. Objective To delineate the genetic landscape of pediatric epilepsy and clinical utility of genetic diagnoses for patients with epilepsy. Design, Setting, and Participants This cohort study used phenotypic data from medical records and treating clinicians at a pediatric hospital to identify patients with unexplained pediatric-onset epilepsy. Exome sequencing was performed for 522 patients and available biological parents, and sequencing data were analyzed for single nucleotide variants (SNVs) and copy number variants (CNVs). Variant pathogenicity was assessed, patients were provided with their diagnostic results, and clinical utility was evaluated. Patients were enrolled from August 2018 to October 2021, and data were analyzed through December 2022. Exposures Phenotypic features associated with diagnostic genetic results. Main Outcomes and Measures Main outcomes included diagnostic yield and clinical utility. Diagnostic findings included variants curated as pathogenic, likely pathogenic (PLP), or diagnostic variants of uncertain significance (VUS) with clinical features consistent with the involved gene’s associated phenotype. The proportion of the cohort with diagnostic findings, the genes involved, and their clinical utility, defined as impact on clinical treatment, prognosis, or surveillance, are reported. Results A total of 522 children (269 [51.5%] male; mean [SD] age at seizure onset, 1.2 [1.4] years) were enrolled, including 142 children (27%) with developmental epileptic encephalopathy and 263 children (50.4%) with intellectual disability. Of these, 100 participants (19.2%) had identifiable genetic explanations for their seizures: 89 participants had SNVs (87 germline, 2 somatic mosaic) involving 69 genes, and 11 participants had CNVs. The likelihood of identifying a genetic diagnosis was highest in patients with intellectual disability (adjusted odds ratio [aOR], 2.44; 95% CI, 1.40-4.26), early onset seizures (aOR, 0.93; 95% CI, 0.88-0.98), and motor impairment (aOR, 2.19; 95% CI 1.34-3.58). Among 43 patients with apparently de novo variants, 2 were subsequently determined to have asymptomatic parents harboring mosaic variants. Of 71 patients who received diagnostic results and were followed clinically, 29 (41%) had documented clinical utility resulting from their genetic diagnoses. Conclusions and Relevance These findings suggest that pediatric-onset epilepsy is genetically heterogeneous and that some patients with previously unexplained pediatric-onset epilepsy had genetic diagnoses with direct clinical implications.