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More than 100 genetic etiologies have been identified in developmental and epileptic encephalopathies (DEEs), but correlating genetic findings with clinical features at scale has remained a hurdle because of a lack of frameworks for analyzing heterogenous clinical data. Here, we analyzed 31,742 Human Phenotype Ontology (HPO) terms in 846 individuals with existing whole-exome trio data and assessed associated clinical features and phenotypic relatedness by using HPO-based semantic similarity analysis for individuals with de novo variants in the same gene. Gene-specific phenotypic signatures included associations of SCN1A with "complex febrile seizures" (HP: 0011172; p = 2.1 × 10-5) and "focal clonic seizures" (HP: 0002266; p = 8.9 × 10-6), STXBP1 with "absent speech" (HP: 0001344; p = 1.3 × 10-11), and SLC6A1 with "EEG with generalized slow activity" (HP: 0010845; p = 0.018). Of 41 genes with de novo variants in two or more individuals, 11 genes showed significant phenotypic similarity, including SCN1A (n = 16, p < 0.0001), STXBP1 (n = 14, p = 0.0021), and KCNB1 (n = 6, p = 0.011). Including genetic and phenotypic data of control subjects increased phenotypic similarity for all genetic etiologies, whereas the probability of observing de novo variants decreased, emphasizing the conceptual differences between semantic similarity analysis and approaches based on the expected number of de novo events. We demonstrate that HPO-based phenotype analysis captures unique profiles for distinct genetic etiologies, reflecting the breadth of the phenotypic spectrum in genetic epilepsies. Semantic similarity can be used to generate statistical evidence for disease causation analogous to the traditional approach of primarily defining disease entities through similar clinical features.

The developmental and epileptic encephalopathies (DEEs) are heterogeneous disorders with a strong genetic contribution, but the underlying genetic etiology remains unknown in a significant proportion of individuals. To explore whether statistical support for genetic etiologies can be generated on the basis of phenotypic features, we analyzed whole-exome sequencing data and phenotypic similarities by using Human Phenotype Ontology (HPO) in 314 individuals with DEEs. We identified a de novo c.508C>T (p.Arg170Trp) variant in AP2M1 in two individuals with a phenotypic similarity that was higher than expected by chance (p = 0.003) and a phenotype related to epilepsy with myoclonic-atonic seizures. We subsequently found the same de novo variant in two individuals with neurodevelopmental disorders and generalized epilepsy in a cohort of 2,310 individuals who underwent diagnostic whole-exome sequencing. AP2M1 encodes the μ-subunit of the adaptor protein complex 2 (AP-2), which is involved in clathrin-mediated endocytosis (CME) and synaptic vesicle recycling. Modeling of protein dynamics indicated that the p.Arg170Trp variant impairs the conformational activation and thermodynamic entropy of the AP-2 complex. Functional complementation of both the μ-subunit carrying the p.Arg170Trp variant in human cells and astrocytes derived from AP-2μ conditional knockout mice revealed a significant impairment of CME of transferrin. In contrast, stability, expression levels, membrane recruitment, and localization were not impaired, suggesting a functional alteration of the AP-2 complex as the underlying disease mechanism. We establish a recurrent pathogenic variant in AP2M1 as a cause of DEEs with distinct phenotypic features, and we implicate dysfunction of the early steps of endocytosis as a disease mechanism in epilepsy.

Aim: To differentiate phenotypic features of individuals with CDKL5 deficiency disorder (CDD) from those of individuals with other infantile‐onset epilepsies. Method: We performed a retrospective cohort study and ascertained individuals with CDD and comparison individuals with infantile‐onset epilepsy who had epilepsy gene panel testing. We reviewed records, updated variant classifications, and compared phenotypic features. Wilcoxon rank‐sum tests and χ2 or Fisher's exact tests were performed for between‐cohort comparisons. Results: We identified 137 individuals with CDD (110 females, 80.3%; median age at last follow‐up 3 year 11 months) and 313 individuals with infantile‐onset epilepsies (156 females, 49.8%; median age at last follow‐up 5 years 2 months; 35% with genetic diagnosis). Features reported significantly more frequently in the CDD group than in the comparison cohort included developmental and epileptic encephalopathy (81% vs 66%), treatment‐resistant epilepsy (95% vs 71%), sequential seizures (46% vs 6%), epileptic spasms (66% vs 42%, with hypsarrhythmia in 30% vs 48%), regression (52% vs 29%), evolution to Lennox–Gastaut syndrome (23% vs 5%), diffuse hypotonia (72% vs 36%), stereotypies (69% vs 11%), paroxysmal movement disorders (29% vs 17%), cerebral visual impairment (94% vs 28%), and failure to thrive (38% vs 22%). Interpretation: CDD, compared with other suspected or confirmed genetic epilepsies presenting in the first year of life, is more often characterized by a combination of treatment‐resistant epilepsy, developmental and epileptic encephalopathy, sequential seizures, spasms without hypsarrhythmia, diffuse hypotonia, paroxysmal movement disorders, cerebral visual impairment, and failure to thrive. Defining core phenotypic characteristics will improve precision diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Background: Extensive literature documents the adverse sequelae of delayed diagnosis of slipped capital femoral epiphysis (SCFE), including worsening deformity and surgical complications. Less is known about predictors of delayed diagnosis of SCFE, particularly the effects of social determinants of health. The purpose of this study was to evaluate the impact of insurance type, family structure, and neighborhood-level socioeconomic vulnerability on the delay of SCFE diagnosis. Methods: We reviewed medical records of patients who underwent surgical fixation for stable SCFE at a tertiary pediatric hospital from 2002 to 2021. We abstracted data on demographic characteristics, insurance status, family structure, home address, and symptom duration. We measured diagnostic delay in weeks from the date of symptom onset to diagnosis. We then geocoded patient addresses to determine their Census tract-level U.S. Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI), using U.S. Census and American Community Survey data. We performed 3 separate logistic regression models to examine the effects of (1) insurance status, (2) family structure, and (3) SVI on a delay of ≥12 weeks (reference, <12 weeks). We adjusted for age, sex, weight status, number of siblings, and calendar year. Results: We identified 351 patients with SCFE; 37% (129) had a diagnostic delay of ≥12 weeks. In multivariable logistic regression models, patients with public insurance were more likely to have a delay of ≥12 weeks than patients with private insurance (adjusted odds ratio [OR], 1.83 [95% confidence interval (CI), 1.12 to 2.97]; p = 0.015) and patients from single-guardian households were more likely to have a delay of ≥12 weeks than patients from multiguardian households (adjusted OR, 1.95 [95% CI, 1.11 to 3.45]; p = 0.021). We did not observe a significant increase in the odds of delay among patients in the highest quartile of overall SVI compared with patients from the lower 3 quartiles, in both the U.S. comparison (adjusted OR, 1.43 [95% CI, 0.79 to 2.58]; p = 0.24) and the Massachusetts comparison (adjusted OR, 1.45 [95% CI, 0.79 to 2.66]; p = 0.23). Conclusions: The delay in diagnosis of SCFE remains a concern, with 37% of patients with SCFE presenting with delay of ≥12 weeks. Public insurance and single-guardian households emerged as independent risk factors for diagnostic delay. Interventions to reduce delay may consider focusing on publicly insured patients and those from single-guardian households. [ABSTRACT FROM AUTHOR]

Epilepsy, defined by the occurrence of two or more unprovoked seizures or one unprovoked seizure with a propensity for others, affects 0.64% of the population and can lead to significant morbidity and mortality. A majority of unexplained epilepsy (seizures not attributed to an acquired etiology, such as trauma or infection) is estimated to have an underlying genetic etiology. Despite rapid progress in understanding of the genetic underpinnings of the epilepsies, there are no recent evidence‐based guidelines for genetic testing and counseling for this population. This practice guideline provides evidence‐based recommendations for approaching genetic testing in the epilepsies using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision framework. We used evidence from a recent systematic evidence review and meta‐analysis of diagnostic yield of genetic tests in patients with epilepsy. We also compiled data from other sources, including recently submitted conference abstracts and peer‐reviewed journal articles. We identified and prioritized outcomes of genetic testing as critical, important or not important and based our recommendations on outcomes deemed critical and important. We considered the desirable and undesirable effects, value and acceptability to relevant stakeholders, impact on health equity, cost‐effectiveness, certainty of evidence, and feasibility of the interventions in individuals with epilepsy. Taken together, we generated two clinical recommendations: (1) Genetic testing is strongly recommended for all individuals with unexplained epilepsy, without limitation of age, with exome/genome sequencing and/or a multi‐gene panel (>25 genes) as first‐tier testing followed by chromosomal microarray, with exome/genome sequencing conditionally recommended over multi‐gene panel. (2) It is strongly recommended that genetic tests be selected, ordered, and interpreted by a qualified healthcare provider in the setting of appropriate pre‐test and post‐test genetic counseling. Incorporation of genetic counselors into neurology practices and/or referral to genetics specialists are both useful models for supporting providers without genetics expertise to implement these recommendations. [ABSTRACT FROM AUTHOR]

ABSTRACT Planktonic larvae of resident, oyster reef-associated decapods and fishes are subject to variable transport and retention whenever estuarine circulation is altered by freshwater inflow. Because freshwater inflow has the [...]

Abstract Background Maternal smoking is a risk factor for pediatric lung disease, including asthma. Animal models suggest that maternal smoking causes defective alveolarization in the offspring. Retinoic acid signaling modulates both lung development and postnatal immune function. Thus, abnormalities in this pathway could mediate maternal smoking effects. We tested whether maternal smoking disrupts retinoic acid pathway expression and functioning in a murine model. Methods Female C57Bl/6 mice with/without mainstream cigarette smoke exposure (3 research cigarettes a day, 5 days a week) were mated to nonsmoking males. Cigarette smoke exposure continued throughout the pregnancy and after parturition. Lung tissue from the offspring was examined by mean linear intercept analysis and by quantitative PCR. Cell culture experiments using the type II cell-like cell line, A549, tested whether lipid-soluble cigarette smoke components affected binding and activation of retinoic acid response elements in vitro. Results Compared to tobacco-naïve mice, juvenile mice with tobacco toxin exposure had significantly (P Conclusions A murine model of maternal cigarette smoking causes abnormal alveolarization in association with altered retinoic acid pathway element expression in the offspring. An in vitro cell culture model shows that lipid-soluble components of cigarette smoke decrease retinoic acid response element activation. It is feasible that disruption of retinoic acid signaling contributes to the pediatric lung dysfunction caused by maternal smoking.

Objective: We aimed to characterize the phenotypic spectrum and functional consequences associated with variants in the gene GABRB2, coding for the γ-aminobutyric acid type A (GABAA ) receptor subunit β2.Methods: We recruited and systematically evaluated 25 individuals with variants in GABRB2, 17 of whom are newly described and 8 previously reported with additional clinical data. Functional analysis was performed using a Xenopus laevis oocyte model system.Results: Our cohort of 25 individuals from 22 families with variants in GABRB2 demonstrated a range of epilepsy phenotypes from genetic generalized epilepsy to developmental and epileptic encephalopathy. Fifty-eight percent of individuals had pharmacoresistant epilepsy; response to medications targeting the GABAergic pathway was inconsistent. Developmental disability (present in 84%) ranged from mild intellectual disability to severe global disability; movement disorders (present in 44%) included choreoathetosis, dystonia, and ataxia. Disease-associated variants cluster in the extracellular N-terminus and transmembrane domains 1-3, with more severe phenotypes seen in association with variants in transmembrane domains 1 and 2 and the allosteric binding site between transmembrane domains 2 and 3. Functional analysis of 4 variants in transmembrane domains 1 or 2 (p.Ile246Thr, p.Pro252Leu, p.Ile288Ser, p.Val282Ala) revealed strongly reduced amplitudes of GABA-evoked anionic currents.Interpretation: GABRB2-related epilepsy ranges broadly in severity from genetic generalized epilepsy to developmental and epileptic encephalopathies. Developmental disability and movement disorder are key features. The phenotypic spectrum is comparable to other GABAA receptor-encoding genes. Phenotypic severity varies by protein domain. Experimental evidence supports loss of GABAergic inhibition as the mechanism underlying GABRB2-associated neurodevelopmental disorders. ANN NEUROL 2021;89:573-586. [ABSTRACT FROM AUTHOR]