Biology subjects

Cushman, B.

Publications and source records attributed to Cushman, B..

3 recordsLinked to original sources

bioRxiv2018

Assessing the Gene-Disease Association of 19 Genes with the RASopathies using the ClinGen Gene Curation Framework

The RASopathies are a complex group of diseases regarding phenotype and genetic etiology. The ClinGen RASopathy Expert Panel assessed published and other publicly available evidence supporting the association of 19 genes with RASopathy conditions. Using the semi-quantitative literature curation method developed by the ClinGen Gene Curation Working Group, evidence for each gene was curated and scored for Noonan syndrome, Costello syndrome, cardiofaciocutaneous (CFC) syndrome, Noonan syndrome with multiple lentigines (NSML), and Noonan-like syndrome with loose anagen hair (NS/LAH).\n\nThe curated evidence supporting each gene-disease relationship was then discussed and approved by the ClinGen RASopathy Expert Panel. Each associations strength was classified as Definitive, Strong, Moderate, Limited, Disputed, or No Evidence. Eleven genes were classified as definitively associated with at least one RASopathy condition. Two genes classified as strong for association with at least one RASopathy condition while one gene was moderate and three were limited. The RAS EP also refuted the association of two genes for a RASopathy condition. Overall, our results provide a greater understanding of the different gene-disease relationships within the RASopathies and can help guide and direct clinicians, patients and researchers who are identifying variants in individuals with a suspected RASopathy\n\nGRANT NUMBERSResearch reported in this publication was supported by the National Human Genome Research Institute (NHGRI) under award number U41HG006834. MZ received support from German Federal Ministry of Education and Research (BMBF): NSEuroNet (FKZ 01GM1602A), GeNeRARe (FKZ 01GM1519A).

genetics↗

bioRxiv2018

Expert Specification of the ACMG/AMP Variant Interpretation Guidelines for Genetic Hearing Loss

Due to the high genetic heterogeneity of hearing loss, current clinical testing includes sequencing large numbers of genes, which often yields a significant number of novel variants. Therefore, the standardization of variant interpretation is crucial to provide consistent and accurate diagnoses. The Hearing Loss Variant Curation Expert Panel was created within the Clinical Genome Resource to provide expert guidance for standardized genomic interpretation in the context of hearing loss. As one of its major tasks, our Expert Panel has adapted the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) standards and guidelines for the interpretation of sequence variants in hearing loss genes. Here, we provide a comprehensive illustration of the newly specified ACMG/AMP hearing loss rules. Three rules remained unchanged, four rules were removed, and the remaining twenty-one rules were specified. Of the specified rules, four had general recommendations, seven were gene/disease considerations, seven had strength-level specifications, and three rules had both gene/disease and strength-level specifications. These rules were further validated and refined using a pilot set of 51 variants assessed by curators. These hearing loss-specific ACMG/AMP rules will help standardize variant interpretation, ultimately leading to better care for individuals with hearing loss.\n\nGRANT NUMBERSResearch reported in this publication was supported by the National Human Genome Research Institute (NHGRI) under award number U41HG006834.

genetics↗

bioRxiv2018

Curating clinically relevant transcripts for the interpretation of sequence variants

Variant interpretation depends on accurate annotations using biologically relevant transcripts. We have developed a systematic strategy for designating primary transcripts, and applied it to 109 hearing loss-associated genes that were divided into 3 categories. Category 1 genes (n=38) had a single transcript, Category 2 genes (n=32) had multiple transcripts, but a single transcript was sufficient to represent all exons, and Category 3 genes (n=38) had multiple transcripts with unique exons. Transcripts were curated with respect to gene expression reported in the literature and the Genotype-Tissue Expression Project. In addition, high frequency loss of function variants in the Genome Aggregation Database, and disease-causing variants in ClinVar and the Human Gene Mutation Database across the 109 genes were queried. These data were used to classify exons as \"clinically relevant\", \"uncertain significance\", or \"clinically insignificant\". Interestingly, 7% of all exons, containing >124 \"clinically significant\" variants, were of \"uncertain significance\". Finally, we used exon-level next generation sequencing quality metrics generated at two clinical labs, and identified a total of 43 technically challenging exons in 20 different genes that had inadequate coverage and/or homology issues which might lead to false variant calls. We have demonstrated that transcript analysis plays a critical role in accurate clinical variant interpretation.

genomics↗