Biology subjects

Abou Tayoun, A. N.

Publications and source records attributed to Abou Tayoun, A. N..

4 recordsLinked to original sources

bioRxiv2019

Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework

BackgroundThe American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) clinical variant interpretation guidelines established criteria (PS3/BS3) for functional assays that specified a \"strong\" level of evidence. However, they did not provide detailed guidance on how functional evidence should be evaluated, and differences in the application of the PS3/BS3 codes is a contributor to variant interpretation discordance between laboratories. This recommendation seeks to provide a more structured approach to the assessment of functional assays for variant interpretation and guidance on the use of various levels of strength based on assay validation.\n\nMethodsThe Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Group used curated functional evidence from ClinGen Variant Curation Expert Panel-developed rule specifications and expert opinions to refine the PS3/BS3 criteria over multiple in-person and virtual meetings. We estimated odds of pathogenicity for assays using various numbers of variant controls to determine the minimum controls required to reach moderate level evidence. Feedback from the ClinGen Steering Committee and outside experts were incorporated into the recommendations at multiple stages of development.\n\nResultsThe SVI Working Group developed recommendations for evaluators regarding the assessment of the clinical validity of functional data and a four-step provisional framework to determine the appropriate strength of evidence that can be applied in clinical variant interpretation. These steps are: 1. Define the disease mechanism; 2. Evaluate applicability of general classes of assays used in the field; 3. Evaluate validity of specific instances of assays; 4. Apply evidence to individual variant interpretation. We found that a minimum of eleven total pathogenic and benign variant controls are required to reach moderate-level evidence in the absence of rigorous statistical analysis.\n\nConclusionsThe recommendations and approach to functional evidence evaluation described here should help clarify the clinical variant interpretation process for functional assays. Further, we hope that these recommendations will help develop productive partnerships with basic scientists who have developed functional assays that are useful for interrogating the function of a variety of genes.

genetics↗

bioRxiv2019

ClinGen Expert Clinical Validity Curation of 164 Hearing Loss Gene-Disease Pairs

PurposeProper interpretation of genomic variants is critical to successful medical decision making based on genetic testing results. A fundamental prerequisite to accurate variant interpretation is the clear understanding of the clinical validity of gene-disease relationships. The Clinical Genome Resource (ClinGen) has developed a semi-quantitative framework to assign clinical validity to gene-disease relationships. MethodsThe ClinGen Hearing Loss Gene Curation Expert Panel (HL GCEP) uses this framework to perform evidence-based curations of genes present on testing panels from 17 clinical laboratories in the Genetic Testing Registry. The HL GCEP curated and reviewed 142 genes and 164 gene-disease pairs, including 105 nonsyndromic and 59 syndromic forms of hearing loss. ResultsThe final outcome included 82 Definitive (50%), 12 Strong (7%), 25 Moderate (15%), 32 Limited (20%), 10 Disputed (6%), and 3 Refuted (2%) classifications. The summary of each curation is date stamped with the HL GCEP approval, is live, and will be kept up-to-date on the ClinGen website (https://search.clinicalgenome.org/kb/gene-validity). ConclusionThis gene curation approach serves to optimize the clinical sensitivity of genetic testing while reducing the rate of uncertain or ambiguous test results caused by the interrogation of genes with insufficient evidence of a disease link.

genomics↗

bioRxiv2018

Rapid interpretation of clinical exomes using Phenoxome: a computational phenotype-driven approach

Clinical exome sequencing (CES) has become the preferred diagnostic platform for complex pediatric disorders with suspected monogenic etiologies, solving up to 20%-50% of cases depending on indication. Despite rapid advancements in CES analysis, the major challenge still resides in identifying the casual variants among the thousands of variants detected during CES testing, and thus establishing a molecular diagnosis. To improve the clinical exome diagnostic efficiency, we developed Phenoxome, a robust phenotype-driven model that adopts a network-based approach to facilitate automated variant prioritization and subsequent classification. Phenoxome dissects the phenotypic manifestation of a patient in conjunction with their genomic profile to filter and then prioritize putative pathogenic variants. To validate our method, we have compiled a clinical cohort of 105 positive patient samples (i.e. at least one reported pathogenic variant) that represent a wide range of genetic heterogeneity from The Childrens Hospital of Philadelphia. Our approach identifies the causative variants within the top 5, 10, or 25 candidates in more than 50%, 71%, or 88% of these patient samples respectively. Furthermore, we show that our method is optimized for clinical testing by yielding superior ranking of the pathogenic variants compared to current state-of-art methods. The web application of Phenoxome is available to the public at http://phenoxome.chop.edu/.

bioinformatics↗

bioRxiv2018

ExomeSlicer: a resource for the development and validation of exome-based clinical panels

Exome-based panels (exome slices) are becoming the preferred diagnostic strategy in clinical laboratories, especially for genetically heterogeneous disorders. The advantages of this approach include enabling frequent updates to gene content without the need for re-designing, reflexing to exome analysis bioinformatically without requiring additional sequencing, and streamlining laboratory operation by using established exome kits and protocols. Despite their increasing use, there are currently no guidelines or appropriate resources to support their clinical implementation. Here, we highlight principles and important considerations for the clinical development and validation of exome-based panels, guided by clinical data from a diagnostic epilepsy panel using this approach. We also present a novel, publically accessible web-based resource, ExomeSlicer, and demonstrate its clinical utility in predicting gene-specific and exome-wide technically challenging regions that are not amenable to Next Generation Sequencing (NGS), and that might significantly lead to increased post hoc Sanger fill in burden. Using this tool, we also characterize > 2000 low complexity, GC-rich and/or high homology, regions across the exome that can be a source of false positive or false negative variant calls thus potentially leading to misdiagnoses in tested patients.

genomics↗