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Cohen syndrome (CS) is a rare multisystem autosomal recessive disorder associated with mutations in VPS13B (vacuolar protein sorting homolog 13B). The NAPB-related neurodevelopmental disorder is characterized mainly by early-onset epileptic encephalopathy (EOEE) and is associated with mutations in NAPB that encodes for SNAP-beta (soluble NSF attachment protein beta). Here we describe male triplets, clinically presenting with the phenotype of subtle but distinctive facial features, intellectual disability, increased body weight, neonatal EOEE, and prominently variable abnormal behaviors of autism and sexual arousal. The EEG showed multifocal epilepsy, while the brain MRI showed no abnormalities. Diagnostic exome sequencing (ES), the applied next-generation sequencing approach, revealed the interesting finding of two novel homozygous variants in two genes: VPS13B missense variant (c.8516G > A) and NAPB splice-site loss (c.354 + 2 T > G). Sanger sequencing verified the segregation of the two recessive gene variants with the phenotype in family members. The prediction algorithms support the pathogenicity of these variants. Homozygosity mapping of ES data of this consanguineous family revealed multiple chromosomal regions of homozygosity stretches with the residing of VPS13B (chr8: 100830758G > A) and NAPB (Chr20: 23,375,774 A > C) variants within the largest homozygous blocks further supporting the disease-genes causal role. Interestingly, the functions of the two proteins; VPS13B, a transmembrane protein involved in intracellular protein transport, and SNAP-beta involved in neurotransmitters release at the neuronal synaptic complexes, have been associated with Golgi-mediated vesicular trafficking. Our ES findings provide new insights into the pathologic mechanism underlying the expansion of the neurodevelopmental spectrum in CS and further highlight the importance of Golgi and Golgi-membrane-related proteins in the development of neurodevelopmental syndromes associated with early-onset non-channelopathy epilepsy. To our knowledge, this is the first report documenting multifocal EOEE in CS patients with the association of a pathogenic NAPB variant.

Purpose Next-generation sequencing has implicated some risk variants for human spina bifida (SB), but the genome-wide contribution of structural variation to this complex genetic disorder remains largely unknown. We examined copy-number variant (CNV) participation in the genetic architecture underlying SB risk. Methods A high-confidence ensemble approach to genome sequences (GS) was benchmarked and employed for systematic detection of common and rare CNVs in two separate ancestry-matched SB case–control cohorts. Results SB cases were enriched with exon disruptive rare CNVs, 44% of which were under 10 kb, in both ancestral populations (P = 6.75 × 10−7; P = 7.59 × 10−4). Genes containing these disruptive CNVs fall into molecular pathways, supporting a role for these genes in SB. Our results expand the catalog of variants and genes with potential contribution to genetic and gene–environment interactions that interfere with neurulation, useful for further functional characterization. Conclusion This study underscores the need for genome-wide investigation and extends our previous threshold model of exonic, single-nucleotide variation toward human SB risk to include structural variation. Since GS data afford detection of CNVs with greater resolution than microarray methods, our results have important implications toward a more comprehensive understanding of the genetic risk and mechanisms underlying neural tube defect pathogenesis.

Significance Genetic investigations of most structural birth defects, including spina bifida (SB), congenital heart disease, and craniofacial anomalies, have been underpowered for genome-wide association studies because of their rarity, genetic heterogeneity, incomplete penetrance, and environmental influences. Our systems biology strategy to investigate SB predisposition controls for population stratification and avoids much of the bias inherent in candidate gene searches that are pervasive in the field. We examine both protein coding and noncoding regions of whole genomes to analyze sequence variants, collapsed by gene or regulatory region, and apply machine learning, gene enrichment, and pathway analyses to elucidate molecular pathways and genes contributing to human SB., Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance, and environmental influences that hamper genome-wide association studies approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases versus controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation, and essential transcriptional regulation consistent with their having impact on the pathogenesis of human SB. Additionally, an interrogation of conserved noncoding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to the interrogation of coding and noncoding sequence variant contributions to rare complex genetic disorders.

Introduction: Mutations in genes-encoding collagen VI-a chain are known to cause congenital muscular dystrophies, (CMDs). Aim: Screening for COL6A mutations in CMDs’ patients. Methods: WGS, Sanger sequencing, plasmids-construction, Western-blot and RT-PCR. Results: Missense and novel nonsense mutations in COL6A1 and COL6A2 were detected. The analysis revealed a decreased stability of the COL6A mutants as compared to wild-type. Conclusion: Collagen related muscular dystrophies may demonstrate the early presentation as of joints and bone involvement rather than of muscular weakness hence, likely may be misdiagnosed. Collagen VI muscular dystrophy was not identified in Qatari patients with muscular dystrophies, in our cohort.