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The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence. [Display omitted] The ClinGen SVI Splicing Subgroup provides recommendations for the application of existing splicing-related ACMG/AMP codes and re-purposing of other codes to capture splicing-related evidence. This study outlines a process for developing a gene-specific PVS1 decision tree and provides methodology to calibrate bioinformatic splice prediction tools. [ABSTRACT FROM AUTHOR]

To understand the impact of genome sequence variation (the genotype) responsible for biological diversity and human health (the phenotype) including cystic fibrosis and Alzheimer's disease, we developed a Gaussian-process-based machine learning (ML) approach, variation spatial profiling (VSP). VSP uses a sparse collection of known variants found in the population that perturb the protein fold to define unknown variant function based on the emergent general principle of spatial covariance (SCV). SCV quantitatively captures the role of proximity in genotype-to-phenotype spatial-temporal relationships. Phenotype landscapes generated through SCV provide a platform that can be used to describe the functional properties that drive sequence-to-function-to-structure design of the polypeptide fold at atomic resolution. We provide proof of principle that SCV can enable the use of population-based genomic platforms to define the origins and mechanism of action of genotype-to-phenotype transformations contributing to the health and disease of an individual., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

We investigated early phenotypes caused by familial Alzheimer's disease (fAD) mutations in isogenic human iPSC-derived neurons. Analysis of neurons carrying fAD PS1 or APP mutations introduced using genome editing technology at the endogenous loci revealed that fAD mutant neurons had previously unreported defects in the recycling state of endocytosis and soma-to-axon transcytosis of APP and lipoproteins. The endocytosis reduction could be rescued through treatment with a β-secretase inhibitor. Our data suggest that accumulation of β-CTFs of APP, but not Aβ, slow vesicle formation from an endocytic recycling compartment marked by the transcytotic GTPase Rab11. We confirm previous results that endocytosis is affected in AD and extend these to uncover a neuron-specific defect. Decreased lipoprotein endocytosis and transcytosis to the axon suggest that a neuron-specific impairment in endocytic axonal delivery of lipoproteins and other key materials might compromise synaptic maintenance in fAD., (Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.)