The Human Phenotype Ontology (HPO, https://hpo.jax.org) was launched in 2008 to provide a comprehensive logical standard to describe and computationally analyze phenotypic abnormalities found in human disease. The HPO is now a worldwide standard for phenotype exchange. The HPO has grown steadily since its inception due to considerable contributions from clinical experts and researchers from a diverse range of disciplines. Here, we present recent major extensions of the HPO for neurology, nephrology, immunology, pulmonology, newborn screening, and other areas. For example, the seizure subontology now reflects the International League Against Epilepsy (ILAE) guidelines and these enhancements have already shown clinical validity. We present new efforts to harmonize computational definitions of phenotypic abnormalities across the HPO and multiple phenotype ontologies used for animal models of disease. These efforts will benefit software such as Exomiser by improving the accuracy and scope of cross-species phenotype matching. The computational modeling strategy used by the HPO to define disease entities and phenotypic features and distinguish between them is explained in detail.We also report on recent efforts to translate the HPO into indigenous languages. Finally, we summarize recent advances in the use of HPO in electronic health record systems.

Objective:To assess the rapid implementation of child neurology telehealth outpatient care with the onset of the COVID-19 pandemic in March 2020.Methods:This was a cohort study with retrospective comparison of 14,780 in-person encounters and 2,589 telehealth encounters including 2,093 audio-video telemedicine and 496 scheduled telephone encounters between 10/1/19 and 4/24/2020. We compared in-person and telehealth encounters for patient demographics and diagnoses. For audio-video telemedicine encounters, we analyzed questionnaire responses addressing provider experience, follow-up plans, technical quality, need for in-person assessment, and parent/caregiver satisfaction. We performed manual reviews of encounters flagged as concerning by providers.Results:There were no differences in patient age and major ICD10 codes before and after transition. Clinicians considered telemedicine satisfactory in 93% (1200/1286) of encounters and suggested telemedicine as a component for follow-up care in 89% (1144/1286) of encounters. Technical challenges were reported in 40% (519/1314) of encounters. In-person assessment was considered warranted following 5% (65/1285) of encounters. Patients/caregivers indicated interest in telemedicine for future care in 86% (187/217) of encounters. Participation in telemedicine encounters compared to telephone encounters was less frequent amongst patients in racial or ethnic minority groups.Conclusions:We effectively converted most of our outpatient care to telehealth encounters, including mostly audio-video telemedicine encounters. Providers rated the vast majority of telemedicine encounters to be satisfactory, and only a small proportion of encounters required short-term in-person follow-up. These findings suggest telemedicine is feasible and effective for a large proportion of child neurology care. Additional strategies are needed to ensure equitable telemedicine utilization.

Disease-causing variants in STXBP1 are among the most common genetic causes of neurodevelopmental disorders. However, the phenotypic spectrum in STXBP1-related disorders is wide and clear correlations between variant type and clinical features have not been observed so far. Here, we harmonized clinical data across 534 individuals with STXBP1-related disorders and analysed 19 973 derived phenotypic terms, including phenotypes of 253 individuals previously unreported in the scientific literature. The overall phenotypic landscape in STXBP1-related disorders is characterized by neurodevelopmental abnormalities in 95% and seizures in 89% of individuals, including focal-onset seizures as the most common seizure type (47%). More than 88% of individuals with STXBP1-related disorders have seizure onset in the first year of life, including neonatal seizure onset in 47%. Individuals with protein-truncating variants and deletions in STXBP1 (n = 261) were almost twice as likely to present with West syndrome and were more phenotypically similar than expected by chance. Five genetic hotspots with recurrent variants were identified in more than 10 individuals, including p.Arg406Cys/His (n = 40), p.Arg292Cys/His/Leu/Pro (n = 30), p.Arg551Cys/Gly/His/Leu (n = 24), p.Pro139Leu (n = 12), and p.Arg190Trp (n = 11). None of the recurrent variants were significantly associated with distinct electroclinical syndromes, single phenotypic features, or showed overall clinical similarity, indicating that the baseline variability in STXBP1-related disorders is too high for discrete phenotypic subgroups to emerge. We then reconstructed the seizure history in 62 individuals with STXBP1-related disorders in detail, retrospectively assigning seizure type and seizure frequency monthly across 4433 time intervals, and retrieved 251 anti-seizure medication prescriptions from the electronic medical records. We demonstrate a dynamic pattern of seizure control and complex interplay with response to specific medications particularly in the first year of life when seizures in STXBP1-related disorders are the most prominent. Adrenocorticotropic hormone and phenobarbital were more likely to initially reduce seizure frequency in infantile spasms and focal seizures compared to other treatment options, while the ketogenic diet was most effective in maintaining seizure freedom. In summary, we demonstrate how the multidimensional spectrum of phenotypic features in STXBP1-related disorders can be assessed using a computational phenotype framework to facilitate the development of future precision-medicine approaches.

Background and ObjectivesClinical manifestations in STXBP1 developmental and epileptic encephalopathy (DEE) vary in severity and outcome, and the genotypic spectrum is diverse. We aim to trace the neurodevelopmental trajectories in individuals with STXBP1-DEE and dissect the relationship between neurodevelopment and epilepsy.MethodsRetrospective standardized clinical data were collected through international collaboration. A composite neurodevelopmental score system compared the developmental trajectories in STXBP1-DEE.ResultsForty-eight patients with de novo STXBP1 variants and a history of epilepsy were included (age range at the time of the study: 10 months to 35 years, mean 8.5 years). At the time of inclusion, 65% of individuals (31/48) had active epilepsy, whereas 35% (17/48) were seizure free, and 76% of those (13/17) achieved remission within the first year of life. Twenty-two individuals (46%) showed signs of developmental impairment and/or neurologic abnormalities before epilepsy onset. Age at seizure onset correlated with severity of developmental outcome and the developmental milestones achieved, with a later seizure onset associated with better developmental outcome. In contrast, age at seizure remission and epilepsy duration did not affect neurodevelopmental outcomes. Overall, we did not observe a clear genotype-phenotype correlation, but monozygotic twins with de novo STXBP1 variant showed similar phenotype and parallel disease course.DiscussionThe disease course in STXBP1-DEE presents with 2 main trajectories, with either early seizure remission or drug-resistant epilepsy, and a range of neurodevelopmental outcomes from mild to profound intellectual disability. Age at seizure onset is the only epilepsy-related feature associated with neurodevelopment outcome. These findings can inform future dedicated natural history studies and trial design.

Purpose Pathogenic variants in SCN2A cause a wide range of neurodevelopmental phenotypes. Reports of genotype–phenotype correlations are often anecdotal, and the available phenotypic data have not been systematically analyzed. Methods We extracted phenotypic information from primary descriptions of SCN2A-related disorders in the literature between 2001 and 2019, which we coded in Human Phenotype Ontology (HPO) terms. With higher-level phenotype terms inferred by the HPO structure, we assessed the frequencies of clinical features and investigated the association of these features with variant classes and locations within the NaV1.2 protein. Results We identified 413 unrelated individuals and derived a total of 10,860 HPO terms with 562 unique terms. Protein-truncating variants were associated with autism and behavioral abnormalities. Missense variants were associated with neonatal onset, epileptic spasms, and seizures, regardless of type. Phenotypic similarity was identified in 8/62 recurrent SCN2A variants. Three independent principal components accounted for 33% of the phenotypic variance, allowing for separation of gain-of-function versus loss-of-function variants with good performance. Conclusion Our work shows that translating clinical features into a computable format using a standardized language allows for quantitative phenotype analysis, mapping the phenotypic landscape of SCN2A-related disorders in unprecedented detail and revealing genotype–phenotype correlations along a multidimensional spectrum.

Febrile infection‐related epilepsy syndrome (FIRES) is a devastating epilepsy characterized by new‐onset refractory status epilepticus with a prior febrile infection. We performed exome sequencing in 50 individuals with FIRES, including 27 patient–parent trios and 23 single probands, none of whom had pathogenic variants in established genes for epilepsies or neurodevelopmental disorders. We also performed HLA sequencing in 29 individuals with FIRES and 529 controls, which failed to identify prominent HLA alleles. The genetic architecture of FIRES is substantially different from other developmental and epileptic encephalopathies, and the underlying etiology remains elusive, requiring novel approaches to identify the underlying causative factors.

Making a specific diagnosis in neurodevelopmental disorders is traditionally based on recognizing clinical features of a distinct syndrome, which guides testing of its possible genetic etiologies. Scalable frameworks for genomic diagnostics, however, have struggled to integrate meaningful measurements of clinical phenotypic features. While standardization has enabled generation and interpretation of genomic data for clinical diagnostics at unprecedented scale, making the equivalent breakthrough for clinical data has proven challenging. However, increasingly clinical features are being recorded using controlled dictionaries with machine readable formats such as the Human Phenotype Ontology (HPO), which greatly facilitates their use in the diagnostic space. Improving the tractability of large-scale clinical information will present new opportunities to inform genomic research and diagnostics from a clinical perspective. Here, we describe novel approaches for computational phenotyping to harmonize clinical features, improve data translation through revising domain-specific dictionaries, quantify phenotypic features, and determine clinical relatedness. We demonstrate how these concepts can be applied to longitudinal phenotypic information, which represents a critical element of developmental disorders and pediatric conditions. Finally, we expand our discussion to clinical data derived from electronic medical records, a largely untapped resource of deep clinical information with distinct strengths and weaknesses.

Objective: STXBP1-related disorders are rare genetic epilepsies and neurodevelopmental disorders, but the impact of symptoms across clinical domains is poorly understood. Disease concept models are formal frameworks to assess the lived experience of individuals and their families and provide a basis for generating outcome measures. Methods:We conducted semistructured, qualitative interviews with 19 caregivers of 16 individuals with STXBP1-related disorders and 7 healthcare professionals. We systematically coded themes using NVivo software and grouped concepts into the domains of symptoms, symptom impact, and caregiver impact. We quantified the frequency of concepts throughout the lifespan and across clinical subgroups stratified by seizure history and developmental trajectories. Results: Over 25 hours of interviews, we coded a total of 3626 references to 38 distinct concepts. In addition to well-recognized clinical features such as developmental delay (n = 240 references), behavior (n = 201), and seizures (n = 147), we identified previously underrepresented symptoms including gastrointestinal (n = 68) and respiratory symptoms (n = 24) and pain (n = 30). The most frequently referenced symptom impacts were autonomy (n = 96), socialization (n = 64), and schooling (n = 61). Emotional impact (n = 354), support (n = 200), and daily life