Precision medicine for developmental and epileptic encephalopathies in Africa-strategies for a resource-limited setting.

PURPOSE: Sub-Saharan Africa bears the highest burden of epilepsy worldwide. A presumed proportion is genetic, but this etiology is buried under the burden of infections and perinatal insults in a setting of limited awareness and few options for testing. Children with developmental and epileptic encephalopathies (DEEs) are most severely affected by this diagnostic gap in Africa, because the rate of actionable findings is highest in DEE-associated genes. METHODS: We tested 234 genetically naive South African children diagnosed with/possible DEE using gene panels, exome sequencing, and chromosomal microarray. Statistical comparison of electroclinical features in children with and children without candidate variants was performed to identify characteristics most likely predictive of a positive genetic finding. RESULTS: Of the 41 (of 234) children with likely/pathogenic variants, 26 had variants supporting precision therapy. Multivariate regression modeling highlighted neonatal or infantile-onset seizures and movement abnormalities as predictive of a positive genetic finding. We used this, coupled with an emphasis on precision medicine outcomes, to propose the pragmatic "Think-Genetics" strategy for early recognition of a possible genetic etiology. CONCLUSION: Our findings emphasize the importance of an early genetic diagnosis in DEE. We designed the Think-Genetics strategy for early recognition, appropriate interim management, and genetic testing for DEE in resource-constrained settings.

mTORC1 functional assay reveals SZT2 loss-of-function variants and a founder in-frame deletion.

Biallelic pathogenic variants in SZT2 result in a neurodevelopmental disorder with shared features, including early-onset epilepsy, developmental delay, macrocephaly, and corpus callosum abnormalities. SZT2 is as a critical scaffolding protein in the amino acid sensing arm of the mTORC1 signalling pathway. Due to its large size (3432 amino acids), lack of crystal structure, and absence of functional domains, it is difficult to determine the pathogenicity of SZT2 missense and in-frame deletions, but these variants are increasingly detected and reported by clinical genetic testing in individuals with epilepsy. To exemplify this latter point, here we describe a cohort of 12 individuals with biallelic SZT2 variants and phenotypic overlap with SZT2-related neurodevelopmental disorders. However, the majority of individuals carried one or more SZT2 variants of uncertain significance (VUS), highlighting the need for functional characterization to determine, which, if any, of these VUS were pathogenic. Thus, we developed a novel individualized platform to identify SZT2 loss-of-function variants in the context of mTORC1 signalling and reclassify VUS. Using this platform, we identified a recurrent in-frame deletion (SZT2 p.Val1984del) which was determined to be a loss-of-function variant and therefore likely pathogenic. Haplotype analysis revealed that this single in-frame deletion is a founder variant in those of Ashkenazi Jewish ancestry. Moreover, this approach allowed us to tentatively reclassify all of the VUS in our cohort of 12 individuals, identifying five individuals with biallelic pathogenic or likely pathogenic variants. Clinical features of these five individuals consisted of early-onset seizures (median 24 months), focal seizures, developmental delay and macrocephaly similar to previous reports. However, we also show a widening of the phenotypic spectrum, as none of the five individuals had corpus callosum abnormalities, in contrast to previous reports. Overall, we present a rapid assay to resolve VUS in SZT2, identify a founder variant in individuals of Ashkenazi Jewish ancestry, and demonstrate that corpus callosum abnormalities is not a hallmark feature of this condition. Our approach is widely applicable to other mTORopathies including the most common causes of the focal genetic epilepsies, DEPDC5, TSC1/2, MTOR and NPRL2/3.

Recommendations for Uniform Variant Calling of SARS-CoV-2 Genome Sequence across Bioinformatic Workflows.

Genomic sequencing of clinical samples to identify emerging variants of SARS-CoV-2 has been a key public health tool for curbing the spread of the virus. As a result, an unprecedented number of SARS-CoV-2 genomes were sequenced during the COVID-19 pandemic, which allowed for rapid identification of genetic variants, enabling the timely design and testing of therapies and deployment of new vaccine formulations to combat the new variants. However, despite the technological advances of deep sequencing, the analysis of the raw sequence data generated globally is neither standardized nor consistent, leading to vastly disparate sequences that may impact identification of variants. Here, we show that for both Illumina and Oxford Nanopore sequencing platforms, downstream bioinformatic protocols used by industry, government, and academic groups resulted in different virus sequences from same sample. These bioinformatic workflows produced consensus genomes with differences in single nucleotide polymorphisms, inclusion and exclusion of insertions, and/or deletions, despite using the same raw sequence as input datasets. Here, we compared and characterized such discrepancies and propose a specific suite of parameters and protocols that should be adopted across the field. Consistent results from bioinformatic workflows are fundamental to SARS-CoV-2 and future pathogen surveillance efforts, including pandemic preparation, to allow for a data-driven and timely public health response.

Towards increased accuracy and reproducibility in SARS-CoV-2 next generation sequence analysis for public health surveillance.

During the COVID-19 pandemic, SARS-CoV-2 surveillance efforts integrated genome sequencing of clinical samples to identify emergent viral variants and to support rapid experimental examination of genome-informed vaccine and therapeutic designs. Given the broad range of methods applied to generate new viral genomes, it is critical that consensus and variant calling tools yield consistent results across disparate pipelines. Here we examine the impact of sequencing technologies (Illumina and Oxford Nanopore) and 7 different downstream bioinformatic protocols on SARS-CoV-2 variant calling as part of the NIH Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Tracking Resistance and Coronavirus Evolution (TRACE) initiative, a public-private partnership established to address the COVID-19 outbreak. Our results indicate that bioinformatic workflows can yield consensus genomes with different single nucleotide polymorphisms, insertions, and/or deletions even when using the same raw sequence input datasets. We introduce the use of a specific suite of parameters and protocols that greatly improves the agreement among pipelines developed by diverse organizations. Such consistency among bioinformatic pipelines is fundamental to SARS-CoV-2 and future pathogen surveillance efforts. The application of analysis standards is necessary to more accurately document phylogenomic trends and support data-driven public health responses.