<i>SCN8A</i> mutation in a child presenting with seizures and developmental delays

Malcolmson, Janet; Kleyner, Robert; Tegay, David; Adams, W. Y.; Ward, Kenneth; Coppinger, Justine; Nelson, Lesa; Meisler, Miriam H.; Wang, Kai; Robison, Reid; Lyon, Gholson J.

doi:10.1101/mcs.a001073

Cited by 12 publications

(5 citation statements)

References 43 publications

(58 reference statements)

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“…We recently reported this variant as a de novo mutation in a 4-year-old female who, at 5 months of age, exhibited symptoms of epilepsy that progressed to a severe condition with very little movement, including the inability to sit or walk on her own. 35 We illustrate the scoring logic for this variant. This variant is located in a protein domain called the ion transport domain.…”

Section: Summary Of the Interpretation Proceduresmentioning

confidence: 99%

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

Wang

2017

The American Journal of Human Genetics

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In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published updated standards and guidelines for the clinical interpretation of sequence variants with respect to human diseases on the basis of 28 criteria. However, variability between individual interpreters can be extensive because of reasons such as the different understandings of these guidelines and the lack of standard algorithms for implementing them, yet computational tools for semi-automated variant interpretation are not available. To address these problems, we propose a suite of methods for implementing these criteria and have developed a tool called InterVar to help human reviewers interpret the clinical significance of variants. InterVar can take a pre-annotated or VCF file as input and generate automated interpretation on 18 criteria. Furthermore, we have developed a companion web server, wInterVar, to enable user-friendly variant interpretation with an automated interpretation step and a manual adjustment step. These tools are especially useful for addressing severe congenital or very early-onset developmental disorders with high penetrance. Using results from a few published sequencing studies, we demonstrate the utility of InterVar in significantly reducing the time to interpret the clinical significance of sequence variants.

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Section: Summary Of the Interpretation Proceduresmentioning

confidence: 99%

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

Wang

2017

The American Journal of Human Genetics

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769

622

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“…The Comorbidities and Prognosis workgroup, building on the literature and with input from caregivers in the core panel, identified 19 initial possible comorbidities associated with SCN8A-related disorders 1,2,[5][6][7][8][9][10][11][12][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] (Table S2). In Round 1, the review panel was asked to identify how commonly these 19 comorbidities present across the phenotypes (>50% of the time, around 50% of the time, <50% of the time).…”

Section: Developing Questions: Comorbidities Resources Prognosismentioning

confidence: 99%

“…From the 19 pre-identified comorbidities queried, 17 had at least 40% agreement of occurrence >50% of the time among people with Severe DEE and were explored further. The 17 comorbidities included the addition of orthopedic issues, 1,16,17 sleep disturbances, and autonomic dysfunction 18 at the suggestion of respondents. Gastrointestinal (GI; encompassing constipation, reflux, vomiting) and feeding (the ability to eat and drink orally without aspiration or penetration) were divided into two separate comorbidities.…”

Section: Comorbiditiesmentioning

confidence: 99%

Global modified‐Delphi consensus on comorbidities and prognosis of SCN8A‐related epilepsy and/or neurodevelopmental disorders

Conecker,

Xia,

Hecker

et al. 2024

Epilepsia

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ObjectivesWe aimed to develop consensus on comorbidities (frequency, severity, and prognosis) and overall outcomes in epilepsy, development, and cognition for the five phenotypes of SCN8A‐related disorders.MethodsA core panel consisting of 13 clinicians, 1 researcher, and 6 caregivers was formed and split into three workgroups. One group focused on comorbidities and prognosis. All groups performed a literature review and developed questions for use in a modified‐Delphi process. Twenty‐eight clinicians, one researcher, and 13 caregivers from 16 countries participated in three rounds of the modified‐Delphi process. Consensus was defined as follows: strong consensus ≥80% fully agree; moderate consensus ≥80% fully or partially agree, <10% disagree; and modest consensus 67%–79% fully or partially agree, <10% disagree.ResultsConsensus was reached on the presence of 14 comorbidities in patients with Severe Developmental and Epileptic Encephalopathy (Severe DEE) spanning non‐seizure neurological disorders and other organ systems; impacts were mostly severe and unlikely to improve or resolve. Across Mild/Moderate Developmental and Epileptic Encephalopathy (Mild/Moderate DEE), Neurodevelopmental Delay with Generalized Epilepsy (NDDwGE), and NDD without Epilepsy (NDDwoE) phenotypes, cognitive and sleep‐related comorbidities as well as fine and gross motor delays may be present but are less severe and more likely to improve compared to Severe DEE. There was no consensus on comorbidities in the SeL(F)IE phenotype but strong conesensus that seizures would largely resolve. Seizure freedom is rare in patients with Severe DEE but may occur in some with Mild/Moderate DEE and NDDwGE.SignificanceSignificant comorbidities are present in most phenotypes of SCN8A‐related disorders but are most severe and pervasive in the Severe DEE phenotype. We hope that this work will improve recognition, early intervention, and long‐term management for patients with these comorbidities and provide the basis for future evidence‐based studies on optimal treatments of SCN8A‐related disorders. Identifying the prognosis of patients with SCN8A‐related disorders will also improve care and quality‐of‐life for patients and their caregivers.

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“…For example, OTG-snpcaller (Zhu et al, 2014) combined Ion Torrent’s Mapping Alignment Program (TMAP) and GATK for SNP calls. This had been used in WES analyses, leading to the identification of a missense mutation in sodium voltage-gated channel alpha subunit 8 (SCN8A) in a clinical presentation of early infantile epileptic encephalopathy type 13 (Malcolmson et al, 2016). ASEQ (Romanel et al, 2015) is designed to perform gene-level allele-specific expression analysis from genomic and transcriptomic NGS data to identify allele specific features, and had been used to analyze chemotherapy-resistant urothelial carcinoma for insight that can be used to develop new treatment modalities (Faltas et al, 2016).…”

Section: New Generation Of Big Data Analyticsmentioning

confidence: 99%

Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics

et al. 2019

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There is a growing attention toward personalized medicine. This is led by a fundamental shift from the ‘one size fits all’ paradigm for treatment of patients with conditions or predisposition to diseases, to one that embraces novel approaches, such as tailored target therapies, to achieve the best possible outcomes. Driven by these, several national and international genome projects have been initiated to reap the benefits of personalized medicine. Exome and targeted sequencing provide a balance between cost and benefit, in contrast to whole genome sequencing (WGS). Whole exome sequencing (WES) targets approximately 3% of the whole genome, which is the basis for protein-coding genes. Nonetheless, it has the characteristics of big data in large deployment. Herein, the application of WES and its relevance in advancing personalized medicine is reviewed. WES is mapped to Big Data “10 Vs” and the resulting challenges discussed. Application of existing biological databases and bioinformatics tools to address the bottleneck in data processing and analysis are presented, including the need for new generation big data analytics for the multi-omics challenges of personalized medicine. This includes the incorporation of artificial intelligence (AI) in the clinical utility landscape of genomic information, and future consideration to create a new frontier toward advancing the field of personalized medicine.

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SCN8A mutation in a child presenting with seizures and developmental delays

Cited by 12 publications

References 43 publications

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

InterVar: Clinical Interpretation of Genetic Variants by the 2015 ACMG-AMP Guidelines

Global modified‐Delphi consensus on comorbidities and prognosis of SCN8A‐related epilepsy and/or neurodevelopmental disorders

Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics

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