Healthcare utilization and clinical characteristics of genetic epilepsy in electronic health records.

Understanding the clinical characteristics and medical treatment of individuals affected by genetic epilepsies is instrumental in guiding selection for genetic testing, defining the phenotype range of these rare disorders, optimizing patient care pathways and pinpointing unaddressed medical need by quantifying healthcare resource utilization. To date, a matched longitudinal cohort study encompassing the entire spectrum of clinical characteristics and medical treatment from childhood through adolescence has not been performed. We identified individuals with genetic and non-genetic epilepsies and onset at ages 0-5 years by linkage across the Cleveland Clinic Health System. We used natural language processing to extract medical terms and procedures from longitudinal electronic health records and tested for cross-sectional and temporal associations with genetic epilepsy. We implemented a two-stage design: in the discovery cohort, individuals were stratified as being 'likely genetic' or 'non-genetic' by a natural language processing algorithm, and controls did not receive genetic testing. The validation cohort consisted of cases with genetic epilepsy confirmed by manual chart review and an independent set of controls who received negative genetic testing. The discovery and validation cohorts consisted of 503 and 344 individuals with genetic epilepsy and matched controls, respectively. The median age at the first encounter was 0.1 years and 7.9 years at the last encounter, and the mean duration of follow-up was 8.2 years. We extracted 188,295 Unified Medical Language System annotations for statistical analysis across 9659 encounters. Individuals with genetic epilepsy received an earlier epilepsy diagnosis and had more frequent and complex encounters with the healthcare system. Notably, the highest enrichment of encounters compared with the non-genetic groups was found during the transition from paediatric to adult care. Our computational approach could validate established comorbidities of genetic epilepsies, such as behavioural abnormality and intellectual disability. We also revealed novel associations for genitourinary abnormalities (odds ratio 1.91, 95% confidence interval: 1.66-2.20, P = 6.16 × 10-19) linked to a spectrum of underrecognized epilepsy-associated genetic disorders. This case-control study leveraged real-world data to identify novel features associated with the likelihood of a genetic aetiology and quantified the healthcare utilization of genetic epilepsies compared with matched controls. Our results strongly recommend early genetic testing to stratify individuals into specialized care paths, thus improving the clinical management of people with genetic epilepsies.

Genotype-phenotype associations in 1018 individuals with SCN1A-related epilepsies.

OBJECTIVE: SCN1A variants are associated with epilepsy syndromes ranging from mild genetic epilepsy with febrile seizures plus (GEFS+) to severe Dravet syndrome (DS). Many variants are de novo, making early phenotype prediction difficult, and genotype-phenotype associations remain poorly understood. METHODS: We assessed data from a retrospective cohort of 1018 individuals with SCN1A-related epilepsies. We explored relationships between variant characteristics (position, in silico prediction scores: Combined Annotation Dependent Depletion (CADD), Rare Exome Variant Ensemble Learner (REVEL), SCN1A genetic score), seizure characteristics, and epilepsy phenotype. RESULTS: DS had earlier seizure onset than other GEFS+ phenotypes (5.3 vs. 12.0 months, p < .001). In silico variant scores were higher in DS versus GEFS+ (p < .001). Patients with missense variants in functionally important regions (conserved N-terminus, S4-S6) exhibited earlier seizure onset (6.0 vs. 7.0 months, p = .003) and were more likely to have DS (280/340); those with missense variants in nonconserved regions had later onset (10.0 vs. 7.0 months, p = .036) and were more likely to have GEFS+ (15/29, χ2 = 19.16, p < .001). A minority of protein-truncating variants were associated with GEFS+ (10/393) and more likely to be located in the proximal first and last exon coding regions than elsewhere in the gene (9.7% vs. 1.0%, p < .001). Carriers of the same missense variant exhibited less variability in age at seizure onset compared with carriers of different missense variants for both DS (1.9 vs. 2.9 months, p = .001) and GEFS+ (8.0 vs. 11.0 months, p = .043). Status epilepticus as presenting seizure type is a highly specific (95.2%) but nonsensitive (32.7%) feature of DS. SIGNIFICANCE: Understanding genotype-phenotype associations in SCN1A-related epilepsies is critical for early diagnosis and management. We demonstrate an earlier disease onset in patients with missense variants in important functional regions, the occurrence of GEFS+ truncating variants, and the value of in silico prediction scores. Status epilepticus as initial seizure type is a highly specific, but not sensitive, early feature of DS.

Polygenic burden and its association with baseline cognitive function and postoperative cognitive outcome in temporal lobe epilepsy.

OBJECTIVE: Demographic and disease factors are associated with cognitive deficits and postoperative cognitive declines in adults with pharmacoresistant temporal lobe epilepsy (TLE), but the role of genetic factors in cognition in TLE is not well understood. Polygenic scores (PGS) for neurological and neuropsychiatric disorders and IQ have been associated with cognition in patient and healthy populations. In this exploratory study, we examined the relationship between PGS for Alzheimer's disease (AD), depression, and IQ and cognitive outcomes in adults with TLE. METHODS: 202 adults with pharmacoresistant TLE had genotyping and completed neuropsychological evaluations as part of a presurgical work-up. A subset (n = 116) underwent temporal lobe resection and returned for postoperative cognitive testing. Logistic regression was used to determine if PGS for AD, depression, and IQ predicted baseline domain-specific cognitive function and cognitive phenotypes as well as postoperative language and memory decline. RESULTS: No significant findings survived correction for multiple comparisons. Prior to correction, higher PGS for AD and depression (i.e., increased genetic risk for the disorder), but lower PGS for IQ (i.e., decreased genetic likelihood of high IQ) appeared possibly associated with baseline cognitive impairment in TLE. In comparison, higher PGS for AD and IQ appeared as possible risk factors for cognitive decline following temporal lobectomy, while the possible relationship between PGS for depression and post-operative cognitive outcome was mixed. SIGNIFICANCE: We did not observe any relationships of large effect between PGS and cognitive function or postsurgical outcome; however, results highlight several promising trends in the data that warrant future investigation in larger samples better powered to detect small genetic effects.

Severe communication delays are independent of seizure burden and persist despite contemporary treatments in SCN1A+ Dravet syndrome: Insights from the ENVISION natural history study.

OBJECTIVE: Dravet syndrome (DS) is a developmental and epileptic encephalopathy characterized by high seizure burden, treatment-resistant epilepsy, and developmental stagnation. Family members rate communication deficits among the most impactful disease manifestations. We evaluated seizure burden and language/communication development in children with DS. METHODS: ENVISION was a prospective, observational study evaluating children with DS associated with SCN1A pathogenic variants (SCN1A+ DS) enrolled at age ≤5 years. Seizure burden and antiseizure medications were assessed every 3 months and communication and language every 6 months with the Bayley Scales of Infant and Toddler Development 3rd edition and the parent-reported Vineland Adaptive Behavior Scales 3rd edition. We report data from the first year of observation, including analyses stratified by age at Baseline: 0:6-2:0 years:months (Y:M; youngest), 2:1-3:6 Y:M (middle), and 3:7-5:0 Y:M (oldest). RESULTS: Between December 2020 and March 2023, 58 children with DS enrolled at 16 sites internationally. Median follow-up was 17.5 months (range = .0-24.0), with 54 of 58 (93.1%) followed for at least 6 months and 51 of 58 (87.9%) for 12 months. Monthly countable seizure frequency (MCSF) increased with age (median [minimum-maximum] = 1.0 in the youngest [1.0-70.0] and middle [1.0-242.0] age groups and 4.5 [.0-2647.0] in the oldest age group), and remained high, despite use of currently approved antiseizure medications. Language/communication delays were observed early, and developmental stagnation occurred after age 2 years with both instruments. In predictive modeling, chronologic age was the only significant covariate of seizure frequency (effect size = .52, p = .024). MCSF, number of antiseizure medications, age at first seizure, and convulsive status epilepticus were not predictors of language/communication raw scores. SIGNIFICANCE: In infants and young children with SCN1A+ DS, language/communication delay and stagnation were independent of seizure burden. Our findings emphasize that the optimal therapeutic window to prevent language/communication delay is before 3 years of age.

Deep histopathology genotype-phenotype analysis of focal cortical dysplasia type II differentiates between the GATOR1-altered autophagocytic subtype IIa and MTOR-altered migration deficient subtype IIb.

Focal cortical dysplasia type II (FCDII) is the most common cause of drug-resistant focal epilepsy in children. Herein, we performed a deep histopathology-based genotype-phenotype analysis to further elucidate the clinico-pathological and genetic presentation of FCDIIa compared to FCDIIb. Seventeen individuals with histopathologically confirmed diagnosis of FCD ILAE Type II and a pathogenic variant detected in brain derived DNA whole-exome sequencing or mTOR gene panel sequencing were included in this study. Clinical data were directly available from each contributing centre. Histopathological analyses were performed from formalin-fixed, paraffin-embedded tissue samples using haematoxylin-eosin and immunohistochemistry for NF-SMI32, NeuN, pS6, p62, and vimentin. Ten individuals carried loss-of-function variants in the GATOR1 complex encoding genes DEPDC5 (n = 7) and NPRL3 (n = 3), or gain-of-function variants in MTOR (n = 7). Whereas individuals with GATOR1 variants only presented with FCDIIa, i.e., lack of balloon cells, individuals with MTOR variants presented with both histopathology subtypes, FCDIIa and FCDIIb. Interestingly, 50% of GATOR1-positive cases showed a unique and predominantly vacuolizing phenotype with p62 immunofluorescent aggregates in autophagosomes. All cases with GATOR1 alterations had neurosurgery in the frontal lobe and the majority was confined to the cortical ribbon not affecting the white matter. This pattern was reflected by subtle or negative MRI findings in seven individuals with GATOR1 variants. Nonetheless, all individuals were seizure-free after surgery except four individuals carrying a DEPDC5 variant. We describe a yet underrecognized genotype-phenotype correlation of GATOR1 variants with FCDIIa in the frontal lobe. These lesions were histopathologically characterized by abnormally vacuolizing cells suggestive of an autophagy-altered phenotype. In contrast, individuals with FCDIIb and brain somatic MTOR variants showed larger lesions on MRI including the white matter, suggesting compromised neural cell migration.

SLC6A1 variant pathogenicity, molecular function and phenotype: a genetic and clinical analysis.

Genetic variants in the SLC6A1 gene can cause a broad phenotypic disease spectrum by altering the protein function. Thus, systematically curated clinically relevant genotype-phenotype associations are needed to understand the disease mechanism and improve therapeutic decision-making. We aggregated genetic and clinical data from 172 individuals with likely pathogenic/pathogenic (lp/p) SLC6A1 variants and functional data for 184 variants (14.1% lp/p). Clinical and functional data were available for a subset of 126 individuals. We explored the potential associations of variant positions on the GAT1 3D structure with variant pathogenicity, altered molecular function and phenotype severity using bioinformatic approaches. The GAT1 transmembrane domains 1, 6 and extracellular loop 4 (EL4) were enriched for patient over population variants. Across functionally tested missense variants (n = 156), the spatial proximity from the ligand was associated with loss-of-function in the GAT1 transporter activity. For variants with complete loss of in vitro GABA uptake, we found a 4.6-fold enrichment in patients having severe disease versus non-severe disease (P = 2.9 × 10-3, 95% confidence interval: 1.5-15.3). In summary, we delineated associations between the 3D structure and variant pathogenicity, variant function and phenotype in SLC6A1-related disorders. This knowledge supports biology-informed variant interpretation and research on GAT1 function. All our data can be interactively explored in the SLC6A1 portal (https://slc6a1-portal.broadinstitute.org/).

Prophecy or empiricism? Clinical value of predicting versus determining genetic variant functions.

The recent explosion of epilepsy genetic testing has created challenges for interpretation of gene variants. Assessments of the functional consequences of genetic variants either by predictive or experimental strategies can contribute to estimating pathogenicity, but there is no consensus on which approach is best. The Special Interest Group on Epilepsy Genetics hosted a session during the Annual American Epilepsy Society Meeting in December 2022 to discuss this topic. The session featured a debate of the relative advantages and limitations of predicting (prophecy) versus experimentally determining (empiricism) variant function using ion channel gene variants as examples. This commentary summarizes these discussions.

Genome-wide identification and phenotypic characterization of seizure-associated copy number variations in 741,075 individuals.

Copy number variants (CNV) are established risk factors for neurodevelopmental disorders with seizures or epilepsy. With the hypothesis that seizure disorders share genetic risk factors, we pooled CNV data from 10,590 individuals with seizure disorders, 16,109 individuals with clinically validated epilepsy, and 492,324 population controls and identified 25 genome-wide significant loci, 22 of which are novel for seizure disorders, such as deletions at 1p36.33, 1q44, 2p21-p16.3, 3q29, 8p23.3-p23.2, 9p24.3, 10q26.3, 15q11.2, 15q12-q13.1, 16p12.2, 17q21.31, duplications at 2q13, 9q34.3, 16p13.3, 17q12, 19p13.3, 20q13.33, and reciprocal CNVs at 16p11.2, and 22q11.21. Using genetic data from additional 248,751 individuals with 23 neuropsychiatric phenotypes, we explored the pleiotropy of these 25 loci. Finally, in a subset of individuals with epilepsy and detailed clinical data available, we performed phenome-wide association analyses between individual CNVs and clinical annotations categorized through the Human Phenotype Ontology (HPO). For six CNVs, we identified 19 significant associations with specific HPO terms and generated, for all CNVs, phenotype signatures across 17 clinical categories relevant for epileptologists. This is the most comprehensive investigation of CNVs in epilepsy and related seizure disorders, with potential implications for clinical practice.

Scanning mutagenesis of the voltage-gated sodium channel NaV1.2 using base editing.

It is challenging to apply traditional mutational scanning to voltage-gated sodium channels (NaVs) and functionally annotate the large number of coding variants in these genes. Using a cytosine base editor and a pooled viability assay, we screen a library of 368 guide RNAs (gRNAs) tiling NaV1.2 to identify more than 100 gRNAs that change NaV1.2 function. We sequence base edits made by a subset of these gRNAs to confirm specific variants that drive changes in channel function. Electrophysiological characterization of these channel variants validates the screen results and provides functional mechanisms of channel perturbation. Most of the changes caused by these gRNAs are classifiable as loss of function along with two missense mutations that lead to gain of function in NaV1.2 channels. This two-tiered strategy to functionally characterize ion channel protein variants at scale identifies a large set of loss-of-function mutations in NaV1.2.

Classification of missense variants in the N-methyl-d-aspartate receptor GRIN gene family as gain- or loss-of-function.

Advances in sequencing technology have generated a large amount of genetic data from patients with neurological conditions. These data have provided diagnosis of many rare diseases, including a number of pathogenic de novo missense variants in GRIN genes encoding N-methyl-d-aspartate receptors (NMDARs). To understand the ramifications for neurons and brain circuits affected by rare patient variants, functional analysis of the variant receptor is necessary in model systems. For NMDARs, this functional analysis needs to assess multiple properties in order to understand how variants could impact receptor function in neurons. One can then use these data to determine whether the overall actions will increase or decrease NMDAR-mediated charge transfer. Here, we describe an analytical and comprehensive framework by which to categorize GRIN variants as either gain-of-function (GoF) or loss-of-function (LoF) and apply this approach to GRIN2B variants identified in patients and the general population. This framework draws on results from six different assays that assess the impact of the variant on NMDAR sensitivity to agonists and endogenous modulators, trafficking to the plasma membrane, response time course and channel open probability. We propose to integrate data from multiple in vitro assays to arrive at a variant classification, and suggest threshold levels that guide confidence. The data supporting GoF and LoF determination are essential to assessing pathogenicity and patient stratification for clinical trials as personalized pharmacological and genetic agents that can enhance or reduce receptor function are advanced. This approach to functional variant classification can generalize to other disorders associated with missense variants.

Epilepsies of presumed genetic etiology show enrichment of rare variants that occur in the general population.

Previous studies suggested that severe epilepsies, e.g., developmental and epileptic encephalopathies (DEEs), are mainly caused by ultra-rare de novo genetic variants. For milder disease, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 control individuals. Here, we separately analyzed three different groups of epilepsies: severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in control individuals with an allele count ≥ 1 and a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD ≥ 20), and to have an odds ratio in individuals with epilepsy ≥ 2. We identified genes enriched with QRVs primarily in NAFE (n = 72), followed by GGE (n = 32) and DEE (n = 21). This suggests that rare variants may play a more important role for causality of NAFE than for DEE. Moreover, we found that genes harboring QRVs, e.g., HSGP2, FLNA, or TNC, encode proteins that are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE that occur also in the general population, while in DEE and GGE, the contribution of such variants appears more limited.

Technological and computational approaches to detect somatic mosaicism in epilepsy.

Lesional epilepsy is a common and severe disease commonly associated with malformations of cortical development, including focal cortical dysplasia and hemimegalencephaly. Recent advances in sequencing and variant calling technologies have identified several genetic causes, including both short/single nucleotide and structural somatic variation. In this review, we aim to provide a comprehensive overview of the methodological advancements in this field while highlighting the unresolved technological and computational challenges that persist, including ultra-low variant allele fractions in bulk tissue, low availability of paired control samples, spatial variability of mutational burden within the lesion, and the issue of false-positive calls and validation procedures. Information from genetic testing in focal epilepsy may be integrated into clinical care to inform histopathological diagnosis, postoperative prognosis, and candidate precision therapies.

CNV-ClinViewer: enhancing the clinical interpretation of large copy-number variants online.

MOTIVATION: Pathogenic copy-number variants (CNVs) can cause a heterogeneous spectrum of rare and severe disorders. However, most CNVs are benign and are part of natural variation in human genomes. CNV pathogenicity classification, genotype-phenotype analyses, and therapeutic target identification are challenging and time-consuming tasks that require the integration and analysis of information from multiple scattered sources by experts. RESULTS: Here, we introduce the CNV-ClinViewer, an open-source web application for clinical evaluation and visual exploration of CNVs. The application enables real-time interactive exploration of large CNV datasets in a user-friendly designed interface and facilitates semi-automated clinical CNV interpretation following the ACMG guidelines by integrating the ClassifCNV tool. In combination with clinical judgment, the application enables clinicians and researchers to formulate novel hypotheses and guide their decision-making process. Subsequently, the CNV-ClinViewer enhances for clinical investigators' patient care and for basic scientists' translational genomic research. AVAILABILITY AND IMPLEMENTATION: The web application is freely available at https://cnv-ClinViewer.broadinstitute.org and the open-source code can be found at https://github.com/LalResearchGroup/CNV-clinviewer.

Ganglioglioma with adverse clinical outcome and atypical histopathological features were defined by alterations in PTPN11/KRAS/NF1 and other RAS-/MAP-Kinase pathway genes.

Exome-wide sequencing studies recently described PTPN11 as a novel brain somatic epilepsy gene. In contrast, germline mutations of PTPN11 are known to cause Noonan syndrome, a multisystem disorder characterized by abnormal facial features, developmental delay, and sporadically, also brain tumors. Herein, we performed a deep phenotype-genotype analysis of a comprehensive series of ganglioglioma (GG) with brain somatic alterations of the PTPN11/KRAS/NF1 genes compared to GG with common MAP-Kinase signaling pathway alterations, i.e., BRAFV600E. Seventy-two GG were submitted to whole exome sequencing and genotyping and 84 low grade epilepsy associated tumors (LEAT) to DNA-methylation analysis. In 28 tumours, both analyses were available from the same sample. Clinical data were retrieved from hospital files including disease onset, age at surgery, brain localization, and seizure outcome. A comprehensive histopathology staining panel was available in all cases. We identified eight GG with PTPN11 alterations, copy number variant (CNV) gains of chromosome 12, and the commonality of additional CNV gains in NF1, KRAS, FGFR4 and RHEB, as well as BRAFV600E alterations. Histopathology revealed an atypical glio-neuronal phenotype with subarachnoidal tumor spread and large, pleomorphic, and multinuclear cellular features. Only three out of eight patients with GG and PTPN11/KRAS/NF1 alterations were free of disabling-seizures 2 years after surgery (38% had Engel I). This was remarkably different from our series of GG with only BRAFV600E mutations (85% had Engel I). Unsupervised cluster analysis of DNA methylation arrays separated these tumours from well-established LEAT categories. Our data point to a subgroup of GG with cellular atypia in glial and neuronal cell components, adverse postsurgical outcome, and genetically characterized by complex alterations in PTPN11 and other RAS-/MAP-Kinase and/or mTOR signaling pathways. These findings need prospective validation in clinical practice as they argue for an adaptation of the WHO grading system in developmental, glio-neuronal tumors associated with early onset focal epilepsy.

The role of rare genetic variants enrichment in epilepsies of presumed genetic etiology.

Previous studies suggested that severe epilepsies e.g., developmental and epileptic encephalopathies (DEE) are mainly caused by ultra-rare de novo genetic variants. For milder phenotypes, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 controls. Here, we separately analyzed three different groups of epilepsies : severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in controls at a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD≥20), and to have an odds ratio in epilepsy cases ≥2. We identified genes enriched with QRVs in DEE (n=21), NAFE (n=72), and GGE (n=32) - the number of enriched genes are found greatest in NAFE and least in DEE. This suggests that rare variants may play a more important role for causality of NAFE than in DEE. Moreover, we found that QRV-carrying genes e.g., HSGP2, FLNA or TNC are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE, while in DEE and GGE, the contribution of such variants appears more limited.

The phenotypic spectrum associated with loss-of-function variants in monogenic epilepsy genes in the general population.

Variants in monogenic epilepsy genes can cause phenotypes of varying severity. For example, pathogenic variants in the SCN1A gene can cause the severe, sporadic, and drug-resistant Dravet syndrome or the milder familiar GEFS + syndrome. We hypothesized that coding variants in epilepsy-associated genes could lead to other disease-related phenotypes in the general population. We selected 127 established monogenic epilepsy genes and explored rare loss-of-function (LoF) variant associations with 3700 phenotypes across 281,850 individuals from the UK Biobank with whole-exome sequencing data. For 5.5% of epilepsy genes, we found significant associations of LoF variants with non-epilepsy phenotypes, mostly related to mental health. These findings suggest that LoF variants in epilepsy genes are associated with neurological or psychiatric phenotypes in the general population. The evidence provided may warrant further research and genetic screening of patients with atypical presentation and inform clinical care of comorbid disorders in individuals with monogenic epilepsy forms.

Delineation of functionally essential protein regions for 242 neurodevelopmental genes.

Neurodevelopmental disorders (NDDs), including severe paediatric epilepsy, autism and intellectual disabilities are heterogeneous conditions in which clinical genetic testing can often identify a pathogenic variant. For many of them, genetic therapies will be tested in this or the coming years in clinical trials. In contrast to first-generation symptomatic treatments, the new disease-modifying precision medicines require a genetic test-informed diagnosis before a patient can be enrolled in a clinical trial. However, even in 2022, most identified genetic variants in NDD genes are 'variants of uncertain significance'. To safely enrol patients in precision medicine clinical trials, it is important to increase our knowledge about which regions in NDD-associated proteins can 'tolerate' missense variants and which ones are 'essential' and will cause a NDD when mutated. In addition, knowledge about functionally indispensable regions in the 3D structure context of proteins can also provide insights into the molecular mechanisms of disease variants. We developed a novel consensus approach that overlays evolutionary, and population based genomic scores to identify 3D essential sites (Essential3D) on protein structures. After extensive benchmarking of AlphaFold predicted and experimentally solved protein structures, we generated the currently largest expert curated protein structure set for 242 NDDs and identified 14 377 Essential3D sites across 189 gene disorders associated proteins. We demonstrate that the consensus annotation of Essential3D sites improves prioritization of disease mutations over single annotations. The identified Essential3D sites were enriched for functional features such as intermembrane regions or active sites and discovered key inter-molecule interactions in protein complexes that were otherwise not annotated. Using the currently largest autism, developmental disorders, and epilepsies exome sequencing studies including >360 000 NDD patients and population controls, we found that missense variants at Essential3D sites are 8-fold enriched in patients. In summary, we developed a comprehensive protein structure set for 242 NDDs and identified 14 377 Essential3D sites in these. All data are available at https://es-ndd.broadinstitute.org for interactive visual inspection to enhance variant interpretation and development of mechanistic hypotheses for 242 NDDs genes. The provided resources will enhance clinical variant interpretation and in silico drug target development for NDD-associated genes and encoded proteins.