A clinical variant in SCN1A inherited from a mosaic father cosegregates with a novel variant to cause Dravet syndrome in a consanguineous family

Case Report: Novel Homozygous Likely Pathogenic SCN1A Variant With Autosomal Recessive Inheritance and Review of the Literature

Dominant pathogenic variations in the SCN1A gene are associated with several neuro developmental disorders with or without epilepsy, including Dravet syndrome (DS). Conversely, there are few published cases with homozygous or compound heterozygous variations in the SCN1A gene. Here, we describe two siblings from a consanguineous pedigree with epilepsy phenotype compatible with genetic epilepsy with febrile seizures plus (GEFS+) associated with the homozygous likely pathogenic variant (NM_001165963.1): c.4513A > C (p.Lys1505Gln). Clinical and genetic data were compared to those of other 10 previously published patients with epilepsy and variants in compound heterozygosity or homozygosity in the SCN1A gene. Most patients (11/12) had missense variants. Patients in whom the variants were located at the cytoplasmic or the extracellular domains frequently presented a less severe phenotype than those in whom they are located at the pore-forming domains. Five of the patients (41.7%) meet clinical criteria for Dravet syndrome (DS), one of them associated acute encephalopathy. Other five patients (41.7%) had a phenotype of epilepsy with febrile seizures plus familial origin, while the two remaining (17%) presented focal epileptic seizures. SCN1A-related epilepsies present in most cases an autosomal dominant inheritance; however, there is growing evidence that some genetic variants only manifest clinical symptoms when they are present in both alleles, following an autosomal recessive inheritance.

Age-related evolution of EEG in Dravet syndrome: Meta-analysis of 155 patients

PURPOSE

Dravet syndrome is an early-onset developmental and epileptic encephalopathy caused by pathogenic SCN1A variants in 80-90% of patients. EEG is initially normal, but abnormalities, both generalized and focal, may develop later. There is a limited understanding of typical EEG evolution in Dravet syndrome.

METHODS

We searched Pubmed in July 2020 for studies including: ≥ 1 patient with Dravet syndrome clinical diagnosis and SCN1A pathogenic variant, and for each such patient, a description of ≥ 1 EEG and age at the time of the EEG. For each study, we evaluated for bias in patient selection. We also reviewed our research database for Dravet patients with available EEG reports. We extracted demographic data and EEG abnormalities reported (generalized/focal epileptiform abnormalities, focal/diffuse slowing). We determined the earliest ages at which different abnormalities were seen, as well as the percentage of reported abnormalities for different age ranges.

RESULTS

We included 247 EEGs from 155 patients (from 31 studies and our research database). The earliest reported ages of generalized epileptiform discharges, focal epileptiform discharges, diffuse background slowing, and focal slowing, were six months, four months, four months, and four months, respectively. In patients 0-12 months, EEG was abnormal in 43%, but this rose to 90% for the 1-2 year-old group, and remained at approximately the same level for the remainder of the age groups.

CONCLUSION

Our results help clarify the relationship between age and EEG in Dravet syndrome; however, findings should be interpreted with caution given the inherent potential biases in the study design.

Analysis of pooled genome sequences from Djallonke and Sahelian sheep of Ghana reveals co-localisation of regions of reduced heterozygosity with candidate genes for disease resistance and adaptation to a tropical environment

BACKGROUND

The Djallonke sheep is well adapted to harsh environmental conditions, and is relatively resistant to Haemonchosis and resilient to animal trypanosomiasis. The larger Sahelian sheep, which cohabit the same region, is less well adapted to these disease challenges. Haemonchosis and Trypanosomiasis collectively cost the worldwide animal industry billions of dollars in production losses annually.

RESULTS

Here, we separately sequenced and then pooled according to breed the genomes from five unrelated individuals from each of the Djallonke and Sahelian sheep breeds (sourced from Ghana), at greater than 22-fold combined coverage for each breed. A total of approximately 404 million (97%) and 343 million (97%) sequence reads from the Djallonke and Sahelian breeds respectively, were successfully mapped to the sheep reference genome Oar v3.1. We identified approximately 11.1 million and 10.9 million single nucleotide polymorphisms (SNPs) in the Djallonke and Sahelian breeds, with approximately 15 and 16% respectively of these not previously reported in sheep. Multiple regions of reduced heterozygosity were also found; 70 co-localised within genomic regions harbouring genes that mediate disease resistance, immune response and adaptation in sheep or cattle. Thirty- three of the regions of reduced heterozygosity co-localised with previously reported genes for resistance to haemonchosis and trypanosomiasis.

CONCLUSIONS

Our analyses suggest that these regions of reduced heterozygosity may be signatures of selection for these economically important diseases.

Clinical and molecular analysis of epilepsy-related genes in patients with Dravet syndrome

Dravet syndrome is considered to be one of the most severe types of genetic epilepsy. Mutations in SCN1A gene have been found to be responsible for at least 80% of patients with Dravet syndrome, and 90% of these mutations arise de novo. The variable clinical phenotype is commonly observed among these patients with SCN1A mutations, suggesting that genetic modifiers may influence the phenotypic expression of Dravet syndrome. In the present study, we described the clinical, pathological, and molecular characteristics of 13 Han Chinese pedigrees clinically diagnosed with Dravet syndrome. By targeted-exome sequencing, bioinformatics analysis and Sanger sequencing verification, 11 variants were identified in SCN1A gene among 11 pedigrees including 7 missense mutations, 2 splice site mutations, and 2 frameshift mutations (9 novel variants and 2 reported mutations). Particularly, 2 of these Dravet syndrome patients with SCN1A variants also harbored SCN9A, KCNQ2, or SLC6A8 variants. In addition, 2 subjects were failed to detect any pathogenic mutations in SCN1A and other epilepsy-related genes. These data suggested that SCN1A variants account for about 84.6% of Dravet syndrome in our cohort. This study expanded the mutational spectrum for the SCN1A gene, and also provided clinical and genetic evidence for the hypothesis that genetic modifiers may contribute to the variable manifestation of Dravet syndrome patients with SCN1A mutations. Thus, targeted-exome sequencing will make it possible to detect the interactions of epilepsy-related genes and reveal their modification on the severity of SCN1A mutation-related Dravet syndrome.

A novel homozygous GALC variant has been associated with Krabbe disease in a consanguineous family

Krabbe disease (KD) or globoid cell leukodystrophy is an autosomal recessive lysosomal storage disorder involving the white matter of the peripheral and the central nervous systems. It is caused by a deficiency of galactocerebrosidase enzyme activity. The most common manifestation is the classical early onset KD that leads to patient's loss before the age of 2. Herein, we report the evaluation of a consanguineous family with three affected children manifesting severe neurological findings that ended with death before the age of 2, in an attempt to provide genetic diagnosis to the family. One of the children underwent detailed physical and neurological examinations, including brain magnetic resonance imaging (MRI) and scalp electroencephalography (EEG) evaluations. GALC genetic testing on this child enabled identification of a novel homozygous variant (NM_000153.3: c.1394C>T; p.(Thr465Ile)), which confirmed diagnosis as KD. Familial segregation of this variant was performed by PCR amplification and Sanger sequencing that revealed the parents as heterozygous carriers. We believe this novel GALC variant will not only help in genetic counseling to this family but will also aid in identification of future KD cases.

SYNE1 related cerebellar ataxia presents with variable phenotypes in a consanguineous family from Turkey

SYNE1 related autosomal recessive cerebellar ataxia type 1 (ARCA1) is a late-onset cerebellar ataxia with slow progression originally demonstrated in French-Canadian populations of Quebec, Canada. Nevertheless, recent studies on SYNE1 ataxia have conveyed the condition from a geographically limited pure cerebellar recessive ataxia to a complex multisystem phenotype that is relatively common on the global scale. To determine the underlying genetic cause of the ataxia phenotype in a consanguineous family from Turkey presenting with very slow progressive cerebellar symptoms including dysarthria, dysmetria, and gait ataxia, we performed SNP-based linkage analysis in the family along with whole exome sequencing (WES) in two affected siblings. We identified a homozygous variant in SYNE1 (NM_033071.3: c.13086delC; p.His4362GlnfsX2) in all four affected siblings. This variant presented herein has originally been associated with only pure ataxia in a single case. We thus present segregation and phenotypic manifestations of this variant in four affected family members and further extend the pure ataxia phenotype with upper motor neuron involvement and peripheral neuropathy. Our findings in turn established a precise molecular diagnosis in this family, demonstrating the use of WES combined with linkage analysis in families as a powerful tool for establishing a quick and precise genetic diagnosis of complex neurological phenotypes.

Clinical Interpretation of Genomic Variations

Novel high-throughput sequencing technologies generate large-scale genomic data and are used extensively for disease mapping of monogenic and/or complex disorders, personalized treatment, and pharmacogenomics. Next-generation sequencing is rapidly becoming routine tool for diagnosis and molecular monitoring of patients to evaluate therapeutic efficiency. The next-generation sequencing platforms generate huge amounts of genetic variation data and it remains a challenge to interpret the variations that are identified. Such data interpretation needs close collaboration among bioinformaticians, clinicians, and geneticists. There are several problems that must be addressed, such as the generation of new algorithms for mapping and annotation, harmonization of the terminology, correct use of nomenclature, reference genomes for different populations, rare disease variant databases, and clinical reports.

FMFilter: A fast model based variant filtering tool

The availability of whole exome and genome sequencing has completely changed the structure of genetic disease studies. It is now possible to solve the disease causing mechanisms within shorter time and budgets. For this reason, mining out the valuable information from the huge amount of data produced by next generation techniques becomes a challenging task. Current tools analyze sequencing data in various methods. However, there is still need for fast, easy to use and efficacious tools. Considering genetic disease studies, there is a lack of publicly available tools which support compound heterozygous and de novo models. Also, existing tools either require advanced IT expertise or are inefficient for handling large variant files. In this work, we provide FMFilter, an efficient sieving tool for next generation sequencing data produced by genetic disease studies. We develop a software which allows to choose the inheritance model (recessive, dominant, compound heterozygous and de novo), the affected and control individuals. The program provides a user friendly Graphical User Interface which eliminates the requirement of advanced computer techniques. It has various filtering options which enable to eliminate the majority of the false alarms. FMFilter requires negligible memory, therefore it can easily handle very large variant files like multiple whole genomes with ordinary computers. We demonstrate the variant reduction capability and effectiveness of the proposed tool with public and in-house data for different inheritance models. We also compare FMFilter with the existing filtering software. We conclude that FMFilter provides an effective and easy to use environment for analyzing next generation sequencing data from Mendelian diseases.