Expert Panel Curation of 31 Genes in Relation to Limb Girdle Muscular Dystrophy.

Introduction Limb girdle muscular dystrophies (LGMDs) are a group of genetically heterogeneous autosomal conditions with some degree of phenotypic homogeneity. LGMD is defined as having onset >2 years of age with progressive proximal weakness, elevated serum creatine kinase levels and dystrophic features on muscle biopsy. Advances in massively parallel sequencing have led to a surge in genes linked to LGMD. Methods The ClinGen Muscular Dystrophies and Myopathies gene curation expert panel (MDM GCEP, formerly Limb Girdle Muscular Dystrophy GCEP) convened to evaluate the strength of evidence supporting gene-disease relationships (GDR) using the ClinGen gene-disease clinical validity framework to evaluate 31 genes implicated in LGMD. Results The GDR was exclusively LGMD for 17 genes, whereas an additional 14 genes were related to a broader phenotype encompassing congenital weakness. Four genes (CAPN3, COL6A1, COL6A2, COL6A3) were split into two separate disease entities, based on each displaying both dominant and recessive inheritance patterns, resulting in curation of 35 GDRs. Of these, 30 (86%) were classified as Definitive, 4 (11%) as Moderate and 1 (3%) as Limited. Two genes, POMGNT1 and DAG1, though definitively related to myopathy, currently have insufficient evidence to support a relationship specifically with LGMD. Conclusions The expert-reviewed assertions on the clinical validity of genes implicated in LGMDs form an invaluable resource for clinicians and molecular geneticists. We encourage the global neuromuscular community to publish case-level data that help clarify disputed or novel LGMD associations.

Generating Clinical-Grade Gene-Disease Validity Classifications Through the ClinGen Data Platforms.

Clinical genetic laboratories must have access to clinically validated biomedical data for precision medicine. A lack of accessibility, normalized structure, and consistency in evaluation complicates interpretation of disease causality, resulting in confusion in assessing the clinical validity of genes and genetic variants for diagnosis. A key goal of the Clinical Genome Resource (ClinGen) is to fill the knowledge gap concerning the strength of evidence supporting the role of a gene in a monogenic disease, which is achieved through a process known as Gene-Disease Validity curation. Here we review the work of ClinGen in developing a curation infrastructure that supports the standardization, harmonization, and dissemination of Gene-Disease Validity data through the creation of frameworks and the utilization of common data standards. This infrastructure is based on several applications, including the ClinGen GeneTracker, Gene Curation Interface, Data Exchange, GeneGraph, and website.

Beyond gene-disease validity: capturing structured data on inheritance, allelic requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions.

BACKGROUND: As the availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including secondary findings. METHODS: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. RESULTS: For 36/65 gene-disease pairs, loss of function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using the CardiacG2P dataset as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. CONCLUSIONS: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is a pre-requisite for scalable genomic testing.

Variant Classification for Pompe disease; ACMG/AMP specifications from the ClinGen Lysosomal Diseases Variant Curation Expert Panel.

Accurate determination of the clinical significance of genetic variants is critical to the integration of genomics in medicine. To facilitate this process, the NIH-funded Clinical Genome Resource (ClinGen) has assembled Variant Curation Expert Panels (VCEPs), groups of experts and biocurators which provide gene- and disease- specifications to the American College of Medical Genetics & Genomics and Association for Molecular Pathology's (ACMG/AMP) variation classification guidelines. With the goal of classifying the clinical significance of GAA variants in Pompe disease (Glycogen storage disease, type II), the ClinGen Lysosomal Diseases (LD) VCEP has specified the ACMG/AMP criteria for GAA. Variant classification can play an important role in confirming the diagnosis of Pompe disease as well as in the identification of carriers. Furthermore, since the inclusion of Pompe disease on the Recommended Uniform Screening Panel (RUSP) for newborns in the USA in 2015, the addition of molecular genetic testing has become an important component in the interpretation of newborn screening results, particularly for asymptomatic individuals. To date, the LD VCEP has submitted classifications and supporting data on 243 GAA variants to public databases, specifically ClinVar and the ClinGen Evidence Repository. Here, we describe the ACMG/AMP criteria specification process for GAA, an update of the GAA-specific variant classification guidelines, and comparison of the ClinGen LD VCEP's GAA variant classifications with variant classifications submitted to ClinVar. The LD VCEP has added to the publicly available knowledge on the pathogenicity of variants in GAA by increasing the number of expert-curated GAA variants present in ClinVar, and aids in resolving conflicting classifications and variants of uncertain clinical significance.

Beyond gene-disease validity: capturing structured data on inheritance, allelic-requirement, disease-relevant variant classes, and disease mechanism for inherited cardiac conditions.

Background: As availability of genomic testing grows, variant interpretation will increasingly be performed by genomic generalists, rather than domain-specific experts. Demand is rising for laboratories to accurately classify variants in inherited cardiac condition (ICC) genes, including as secondary findings. Methods: We analyse evidence for inheritance patterns, allelic requirement, disease mechanism and disease-relevant variant classes for 65 ClinGen-curated ICC gene-disease pairs. We present this information for the first time in a structured dataset, CardiacG2P, and assess application in genomic variant filtering. Results: For 36/65 gene-disease pairs, loss-of-function is not an established disease mechanism, and protein truncating variants are not known to be pathogenic. Using CardiacG2P as an initial variant filter allows for efficient variant prioritisation whilst maintaining a high sensitivity for retaining pathogenic variants compared with two other variant filtering approaches. Conclusions: Access to evidence-based structured data representing disease mechanism and allelic requirement aids variant filtering and analysis and is pre-requisite for scalable genomic testing.

Developing a disease-specific annotation protocol for VHL gene curation using Hypothes.is.

Von Hippel-Lindau (VHL) disease is a rare, autosomal dominant disorder that predisposes individuals to developing tumors in many organs. There is significant phenotypic variability and genetic variants encountered within this syndrome, posing a considerable challenge to patient care. The lack of VHL variant data sharing paired with the absence of aggregated genotype-phenotype information results in an arduous process, when characterizing genetic variants and predicting patient prognosis. To address these gaps in knowledge, the Clinical Genome Resource (ClinGen) VHL Variant Curation Expert Panel (VCEP) has been resolving a list of variants of uncertain significance within the VHL gene. Through community curation, we crowdsourced the laborious task of variant annotation by modifying the ClinGen Community Curation (C3)-developed Baseline Annotation protocol and annotating all published VHL cases with the reported genotype-phenotype information in Hypothes.is, an open-access web annotation tool. This process, incorporated into the ClinGen VCEP's workflow, will aid in their curation efforts. To facilitate the curation at all levels of genetics expertise, our team developed a 4-day biocuration training protocol and resource guide. To date, 91.3% of annotations have been completed by undergraduate and high-school students without formal academic genetics specialization. Here, we present our VHL-specific annotation protocol utilizing Hypothes.is, which offers a standardized method to present case-resolution data, and our biocuration training protocol, which can be adapted for other rare disease platforms. By facilitating training for community curation of VHL disease, we increased student engagement with clinical genetics while enhancing knowledge translation in the field of hereditary cancer. Database URL: https://hypothes.is/groups/dKymJJpZ/vhl-hypothesis-annotation.

Lumping versus splitting: How to approach defining a disease to enable accurate genomic curation.

The dilemma of how to categorize and classify diseases has been debated for centuries. The field of medical genetics has historically approached nosology based on clinical phenotypes observed in patients and families. Advances in genomic sequencing and understanding of genetic contributions to disease often provoke a need to reassess these classifications. The Clinical Genome Resource (ClinGen) has developed frameworks to classify the strength of evidence underlying monogenic gene-disease relationships, variant pathogenicity, and clinical actionability. It is therefore necessary to define the disease entity being evaluated, which can be challenging for genes associated with multiple conditions and/or a broad phenotypic spectrum. We therefore developed criteria to guide "lumping and splitting" decisions and improve consistency in defining monogenic gene-disease relationships. Here, we outline the precuration process, the lumping and splitting guidelines with examples, and describe the implications for clinical diagnosis, informatics, and care management.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels.

PURPOSE: Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not. METHODS: Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship. RESULTS: As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants. CONCLUSION: Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.

Utilizing ClinGen gene-disease validity and dosage sensitivity curations to inform variant classification.

Understanding whether there is enough evidence to implicate a gene's role in a given disease, as well as the mechanisms by which variants in this gene might cause this disease, is essential to determine clinical relevance. The National Institutes of Health-funded Clinical Genome Resource (ClinGen) has developed evaluation frameworks to assess both the strength of evidence supporting a relationship between a gene and disease (gene-disease validity), and whether loss (haploinsufficiency) or gain (triplosensitivity) of individual genes or genomic regions is a mechanism for disease (dosage sensitivity). ClinGen actively applies these frameworks across multiple disease domains, and makes this information publicly available via its website (https://www.clinicalgenome.org/) for use in multiple applications, including clinical variant classification. Here, we describe how the results of these curation processes can be utilized to inform the appropriate application of pathogenicity criteria for both sequence and copy number variants, as well as to guide test development and inform genomic filtering pipelines.

Evidence-Based Assessment of Genes in Dilated Cardiomyopathy.

BACKGROUND: Each of the cardiomyopathies, classically categorized as hypertrophic cardiomyopathy, dilated cardiomyopathy (DCM), and arrhythmogenic right ventricular cardiomyopathy, has a signature genetic theme. Hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy are largely understood as genetic diseases of sarcomere or desmosome proteins, respectively. In contrast, >250 genes spanning >10 gene ontologies have been implicated in DCM, representing a complex and diverse genetic architecture. To clarify this, a systematic curation of evidence to establish the relationship of genes with DCM was conducted. METHODS: An international panel with clinical and scientific expertise in DCM genetics evaluated evidence supporting monogenic relationships of genes with idiopathic DCM. The panel used the Clinical Genome Resource semiquantitative gene-disease clinical validity classification framework with modifications for DCM genetics to classify genes into categories on the basis of the strength of currently available evidence. Representation of DCM genes on clinically available genetic testing panels was evaluated. RESULTS: Fifty-one genes with human genetic evidence were curated. Twelve genes (23%) from 8 gene ontologies were classified as having definitive (BAG3, DES, FLNC, LMNA, MYH7, PLN, RBM20, SCN5A, TNNC1, TNNT2, TTN) or strong (DSP) evidence. Seven genes (14%; ACTC1, ACTN2, JPH2, NEXN, TNNI3, TPM1, VCL) including 2 additional ontologies were classified as moderate evidence; these genes are likely to emerge as strong or definitive with additional evidence. Of these 19 genes, 6 were similarly classified for hypertrophic cardiomyopathy and 3 for arrhythmogenic right ventricular cardiomyopathy. Of the remaining 32 genes (63%), 25 (49%) had limited evidence, 4 (8%) were disputed, 2 (4%) had no disease relationship, and 1 (2%) was supported by animal model data only. Of the 16 evaluated clinical genetic testing panels, most definitive genes were included, but panels also included numerous genes with minimal human evidence. CONCLUSIONS: In the curation of 51 genes, 19 had high evidence (12 definitive/strong, 7 moderate). It is notable that these 19 genes explain only a minority of cases, leaving the remainder of DCM genetic architecture incompletely addressed. Clinical genetic testing panels include most high-evidence genes; however, genes lacking robust evidence are also commonly included. We recommend that high-evidence DCM genes be used for clinical practice and that caution be exercised in the interpretation of variants in variable-evidence DCM genes.

International Evidence Based Reappraisal of Genes Associated With Arrhythmogenic Right Ventricular Cardiomyopathy Using the Clinical Genome Resource Framework.

BACKGROUND: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited disease characterized by ventricular arrhythmias and progressive ventricular dysfunction. Genetic testing is recommended, and a pathogenic variant in an ARVC-associated gene is a major criterion for diagnosis according to the 2010 Task Force Criteria. As incorrect attribution of a gene to ARVC can contribute to misdiagnosis, we assembled an international multidisciplinary ARVC Clinical Genome Resource Gene Curation Expert Panel to reappraise all reported ARVC genes. METHODS: Following a comprehensive literature search, six 2-member teams conducted blinded independent curation of reported ARVC genes using the semiquantitative Clinical Genome Resource framework. RESULTS: Of 26 reported ARVC genes, only 6 (PKP2, DSP, DSG2, DSC2, JUP, and TMEM43) had strong evidence and were classified as definitive for ARVC causation. There was moderate evidence for 2 genes, DES and PLN. The remaining 18 genes had limited or no evidence. RYR2 was refuted as an ARVC gene since clinical data and model systems exhibited a catecholaminergic polymorphic ventricular tachycardia phenotype. In ClinVar, only 5 pathogenic/likely pathogenic variants (1.1%) in limited evidence genes had been reported in ARVC cases in contrast to 450 desmosome gene variants (97.4%). CONCLUSIONS: Using the Clinical Genome Resource approach to gene-disease curation, only 8 genes (PKP2, DSP, DSG2, DSC2, JUP, TMEM43, PLN, and DES) had definitive or moderate evidence for ARVC, and these genes accounted for nearly all pathogenic/likely pathogenic ARVC variants in ClinVar. Therefore, only pathogenic/likely pathogenic variants in these 8 genes should yield a major criterion for ARVC diagnosis. Pathogenic/likely pathogenic variants identified in other genes in a patient should prompt further phenotyping as variants in many of these genes are associated with other cardiovascular conditions.

Interpretable Clinical Genomics with a Likelihood Ratio Paradigm.

Human Phenotype Ontology (HPO)-based analysis has become standard for genomic diagnostics of rare diseases. Current algorithms use a variety of semantic and statistical approaches to prioritize the typically long lists of genes with candidate pathogenic variants. These algorithms do not provide robust estimates of the strength of the predictions beyond the placement in a ranked list, nor do they provide measures of how much any individual phenotypic observation has contributed to the prioritization result. However, given that the overall success rate of genomic diagnostics is only around 25%-50% or less in many cohorts, a good ranking cannot be taken to imply that the gene or disease at rank one is necessarily a good candidate. Here, we present an approach to genomic diagnostics that exploits the likelihood ratio (LR) framework to provide an estimate of (1) the posttest probability of candidate diagnoses, (2) the LR for each observed HPO phenotype, and (3) the predicted pathogenicity of observed genotypes. LIkelihood Ratio Interpretation of Clinical AbnormaLities (LIRICAL) placed the correct diagnosis within the first three ranks in 92.9% of 384 case reports comprising 262 Mendelian diseases, and the correct diagnosis had a mean posttest probability of 67.3%. Simulations show that LIRICAL is robust to many typically encountered forms of genomic and phenomic noise. In summary, LIRICAL provides accurate, clinically interpretable results for phenotype-driven genomic diagnostics.

A myelin-related transcriptomic profile is shared by Pitt-Hopkins syndrome models and human autism spectrum disorder.

Autism spectrum disorder (ASD) is genetically heterogeneous with convergent symptomatology, suggesting common dysregulated pathways. In this study, we analyzed brain transcriptional changes in five mouse models of Pitt-Hopkins syndrome (PTHS), a syndromic form of ASD caused by mutations in the TCF4 gene, but not the TCF7L2 gene. Analyses of differentially expressed genes (DEGs) highlighted oligodendrocyte (OL) dysregulation, which we confirmed in two additional mouse models of syndromic ASD (Ptenm3m4/m3m4 and Mecp2tm1.1Bird). The PTHS mouse models showed cell-autonomous reductions in OL numbers and myelination, functionally confirming OL transcriptional signatures. We also integrated PTHS mouse model DEGs with human idiopathic ASD postmortem brain RNA-sequencing data and found significant enrichment of overlapping DEGs and common myelination-associated pathways. Notably, DEGs from syndromic ASD mouse models and reduced deconvoluted OL numbers distinguished human idiopathic ASD cases from controls across three postmortem brain data sets. These results implicate disruptions in OL biology as a cellular mechanism in ASD pathology.

Evaluating the Clinical Validity of Hypertrophic Cardiomyopathy Genes.

BACKGROUND: Genetic testing for families with hypertrophic cardiomyopathy (HCM) provides a significant opportunity to improve care. Recent trends to increase gene panel sizes often mean variants in genes with questionable association are reported to patients. Classification of HCM genes and variants is critical, as misclassification can lead to genetic misdiagnosis. We show the validity of previously reported HCM genes using an established method for evaluating gene-disease associations. METHODS: A systematic approach was used to assess the validity of reported gene-disease associations, including associations with isolated HCM and syndromes including left ventricular hypertrophy. Genes were categorized as having definitive, strong, moderate, limited, or no evidence of disease causation. We also reviewed current variant classifications for HCM in ClinVar, a publicly available variant resource. RESULTS: Fifty-seven genes were selected for curation based on their frequent inclusion in HCM testing and prior association reports. Of 33 HCM genes, only 8 (24%) were categorized as definitive ( MYBPC3, MYH7, TNNT2, TNNI3, TPM1, ACTC1, MYL2, and MYL3); 3 had moderate evidence ( CSRP3, TNNC1, and JPH2; 33%); and 22 (66%) had limited (n=16) or no evidence (n=6). There were 12 of 24 syndromic genes definitively associated with isolated left ventricular hypertrophy. Of 4191 HCM variants in ClinVar, 31% were in genes with limited or no evidence of disease association. CONCLUSIONS: The majority of genes previously reported as causative of HCM and commonly included in diagnostic tests have limited or no evidence of disease association. Systematically curated HCM genes are essential to guide appropriate reporting of variants and ensure the best possible outcomes for HCM families.

The progression of the ClinGen gene clinical validity classification over time.

In order for ClinGen to maintain up-to-date gene-disease clinical validity classifications for use by clinicians and clinical laboratories, an appropriate timeline for reevaluating curated gene-disease associations will need to be determined. To provide guidance on how often a gene-disease association should be recurated, a retrospective analysis of 30 gene curations was performed. Curations were simulated at one-year intervals starting with the year of the first publication to assert disease-causing variants in the gene to observe trends in the classification over time, as well as factors that influenced changes in classification. On average, gene-disease associations spent the least amount of time in the "Moderate" classification before progressing to "Strong" or "Definitive." In contrast, gene-disease associations that spent five or more years in the "Limited" classification were most likely to remain "Limited" or become "Disputed/Refuted." Large population datasets contributed to the reclassification of several gene-disease associations from "Limited" to "Disputed/Refuted." Finally, recent advancements in sequencing technology correlated with an increase in the quantity of case-level evidence that was curated per paper. This study provided a number of key points to consider when determining how often to recurate a gene-disease association.

The ClinGen Epilepsy Gene Curation Expert Panel-Bridging the divide between clinical domain knowledge and formal gene curation criteria.

The field of epilepsy genetics is advancing rapidly and epilepsy is emerging as a frequent indication for diagnostic genetic testing. Within the larger ClinGen framework, the ClinGen Epilepsy Gene Curation Expert Panel is tasked with connecting two increasingly separate fields: the domain of traditional clinical epileptology, with its own established language and classification criteria, and the rapidly evolving area of diagnostic genetic testing that adheres to formal criteria for gene and variant curation. We identify critical components unique to the epilepsy gene curation effort, including: (a) precise phenotype definitions within existing disease and phenotype ontologies; (b) consideration of when epilepsy should be curated as a distinct disease entity; (c) strategies for gene selection; and (d) emerging rules for evaluating functional models for seizure disorders. Given that de novo variants play a prominent role in many of the epilepsies, sufficient genetic evidence is often awarded early in the curation process. Therefore, the emphasis of gene curation is frequently shifted toward an iterative precuration process to better capture phenotypic associations. We demonstrate that within the spectrum of neurodevelopmental disorders, gene curation for epilepsy-associated genes is feasible and suggest epilepsy-specific conventions, laying the groundwork for a curation process of all major epilepsy-associated genes.

Common Pathophysiology in Multiple Mouse Models of Pitt-Hopkins Syndrome.

Mutations or deletions of the transcription factor TCF4 are linked to Pitt-Hopkins syndrome (PTHS) and schizophrenia, suggesting that the precise pathogenic mutations dictate cellular, synaptic, and behavioral consequences. Here, we generated two novel mouse models of PTHS, one that mimics the most common pathogenic TCF4 point mutation (human R580W, mouse R579W) and one that deletes three pathogenic arginines, and explored phenotypes of these lines alongside models of pan-cellular or CNS-specific heterozygous Tcf4 disruption. We used mice of both sexes to show that impaired Tcf4 function results in consistent microcephaly, hyperactivity, reduced anxiety, and deficient spatial learning. All four PTHS mouse models demonstrated exaggerated hippocampal long-term potentiation (LTP), consistent with deficits in hippocampus-mediated behaviors. We further examined R579W mutant mice and mice with pan-cellular Tcf4 heterozygosity and found that they exhibited hippocampal NMDA receptor hyperfunction, which likely drives the enhanced LTP. Together, our data pinpoint convergent neurobiological features in PTHS mouse models and provide a foundation for preclinical studies and a rationale for testing whether NMDAR antagonists might be used to treat PTHS.SIGNIFICANCE STATEMENT Pitt-Hopkins syndrome (PTHS) is a rare neurodevelopmental disorder associated with TCF4 mutations/deletions. Despite this genetic insight, there is a need to identify the function of TCF4 in the brain. Toward this goal, we developed two mouse lines, including one harboring the most prevalent pathogenic point mutation, and compared them with two existing models that conditionally delete Tcf4 Our data identify a set of overlapping phenotypes that may serve as outcome measures for preclinical studies of PTHS treatments. We also discovered penetrant enhanced synaptic plasticity across mouse models that may be linked to increased NMDA receptor function. These data reveal convergent neurobiological characteristics of PTHS mouse models and support the further investigation of NMDA receptor antagonists as a possible PTHS treatment.

Decreased Axon Caliber Underlies Loss of Fiber Tract Integrity, Disproportional Reductions in White Matter Volume, and Microcephaly in Angelman Syndrome Model Mice.

Angelman syndrome (AS) is a debilitating neurodevelopmental disorder caused by loss of function of the maternally inherited UBE3A allele. It is currently unclear how the consequences of this genetic insult unfold to impair neurodevelopment. We reasoned that by elucidating the basis of microcephaly in AS, a highly penetrant syndromic feature with early postnatal onset, we would gain new insights into the mechanisms by which maternal UBE3A loss derails neurotypical brain growth and function. Detailed anatomical analysis of both male and female maternal Ube3a-null mice reveals that microcephaly in the AS mouse model is primarily driven by deficits in the growth of white matter tracts, which by adulthood are characterized by densely packed axons of disproportionately small caliber. Our results implicate impaired axon growth in the pathogenesis of AS and identify noninvasive structural neuroimaging as a potentially valuable tool for gauging therapeutic efficacy in the disorder.SIGNIFICANCE STATEMENT People who maternally inherit a deletion or nonfunctional copy of the UBE3A gene develop Angelman syndrome (AS), a severe neurodevelopmental disorder. To better understand how loss of maternal UBE3A function derails brain development, we analyzed brain structure in a maternal Ube3a knock-out mouse model of AS. We report that the volume of white matter (WM) is disproportionately reduced in AS mice, indicating that deficits in WM development are a major factor underlying impaired brain growth and microcephaly in the disorder. Notably, we find that axons within the WM pathways of AS model mice are abnormally small in caliber. This defect is associated with slowed nerve conduction, which could contribute to behavioral deficits in AS, including motor dysfunction.

Organization and maintenance of molecular domains in myelinated axons.

Over a century ago, Ramon y Cajal first proposed the idea of a directionality involved in nerve conduction and neuronal communication. Decades later, it was discovered that myelin, produced by glial cells, insulated axons with periodic breaks where nodes of Ranvier (nodes) form to allow for saltatory conduction. In the peripheral nervous system (PNS), Schwann cells are the glia that can either individually myelinate the axon from one neuron or ensheath axons of many neurons. In the central nervous system (CNS), oligodendrocytes are the glia that myelinate axons from different neurons. Review of more recent studies revealed that this myelination created polarized domains adjacent to the nodes. However, the molecular mechanisms responsible for the organization of axonal domains are only now beginning to be elucidated. The molecular domains in myelinated axons include the axon initial segment (AIS), where various ion channels are clustered and action potentials are initiated; the node, where sodium channels are clustered and action potentials are propagated; the paranode, where myelin loops contact with the axolemma; the juxtaparanode (JXP), where delayed-rectifier potassium channels are clustered; and the internode, where myelin is compactly wrapped. Each domain contains a unique subset of proteins critical for the domain's function. However, the roles of these proteins in axonal domain organization are not fully understood. In this review, we highlight recent advances on the molecular nature and functions of some of the components of each axonal domain and their roles in axonal domain organization and maintenance for proper neuronal communication.