Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as Supporting level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (Supporting, Moderate, Strong, Very Strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved Supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying Moderate and several reached Strong evidence levels. One tool reached Very Strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

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We describe a sibling pair displaying an early infantile-onset, progressive neurodegenerative phenotype, with symptoms of developmental delay and epileptic encephalopathy developing from 12 to 14 months of age. Using whole exome sequencing, compound heterozygous variants were identified in SLC5A6, which encodes the sodium-dependent multivitamin transporter (SMVT) protein. SMVT is an important transporter of the B-group vitamins biotin, pantothenate, and lipoate. The protein is ubiquitously expressed and has major roles in vitamin uptake in the digestive system, as well as transport of these vitamins across the blood–brain barrier. Pathogenicity of the identified variants was demonstrated by impaired biotin uptake of mutant SMVT. Identification of this vitamin transporter as the genetic basis of this disorder guided targeted therapeutic intervention, resulting clinically in improvement of the patient’s neurocognitive and neuromotor function. This is the second report of biallelic mutations in SLC5A6 leading to a neurodegenerative disorder due to impaired biotin, pantothenate and lipoate uptake. The genetic and phenotypic overlap of these cases confirms mutations in SLC5A6 as the genetic cause of this disease phenotype. Recognition of the genetic disorder caused by SLC5A6 mutations is essential for early diagnosis and to facilitate timely intervention by triple vitamin (biotin, pantothenate, and lipoate) replacement therapy.

Highlights d Mutations in CEP85L cause posterior-specific pachygyria d CEP85L is required for neuronal migration d Loss of CEP85L disrupts centrosome organization and function d CEP85L localizes and activates CDK5 at the centrosome

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME.

Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. Methods: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. Results: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. Conclusion:The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

BackgroundPseudodiastrophic dysplasia (PDD) is a severe skeletal dysplasia associated with prenatal manifestation and early lethality. Clinically, PDD is classified as a ‘dysplasia with multiple joint dislocations’; however, the molecular aetiology of the disorder is currently unknown.MethodsWhole exome sequencing (WES) was performed on three patients from two unrelated families, clinically diagnosed with PDD, in order to identify the underlying genetic cause. The functional effects of the identified variants were characterised using primary cells and human cell-based overexpression assays.ResultsWES resulted in the identification of biallelic variants in the established skeletal dysplasia genes, B3GAT3 (family 1) and CANT1 (family 2). Mutations in these genes have previously been reported to cause ‘multiple joint dislocations, short stature, and craniofacial dysmorphism with or without congenital heart defects’ (‘JDSCD’; B3GAT3) and Desbuquois dysplasia 1 (CANT1), disorders in the same nosological group as PDD. Follow-up of the B3GAT3 variants demonstrated significantly reduced B3GAT3/GlcAT-I expression. Downstream in vitro functional analysis revealed abolished biosynthesis of glycosaminoglycan side chains on proteoglycans. Functional evaluation of the CANT1 variant showed impaired nucleotidase activity, which results in inhibition of glycosaminoglycan synthesis through accumulation of uridine diphosphate.ConclusionFor the families described in this study, the PDD phenotype was caused by mutations in the known skeletal dysplasia genes B3GAT3 and CANT1, demonstrating the advantage of genomic analyses in delineating the molecular diagnosis of skeletal dysplasias. This finding expands the phenotypic spectrum of B3GAT3-related and CANT1-related skeletal dysplasias to include PDD and highlights the significant phenotypic overlap of conditions within the proteoglycan biosynthesis pathway.

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