Search

Although the rates of disease gene discovery have steadily increased with the expanding use of genome and exome sequencing by clinical and research laboratories, only ~16% of genes in the genome have confirmed disease associations. Here we describe our clinical laboratory's experience utilizing GeneMatcher, an online portal designed to promote disease gene discovery and data sharing. Since 2016, we submitted 246 candidates from 243 unique genes to GeneMatcher, of which 111 (45%) are now clinically characterized. Submissions meeting our candidate gene‐reporting criteria based on a scoring system using patient and molecular‐weighted evidence were significantly more likely to be characterized as of October 2021 versus genes that did not meet our clinical‐reporting criteria (p = 0.025). We reported relevant findings related to these newly characterized gene–disease associations in 477 probands. In 218 (46%) instances, we issued reclassifications after an initial negative or candidate gene (uncertain) report. We coauthored 104 publications delineating gene–disease relationships, including descriptions of new associations (60%), additional supportive evidence (13%), subsequent descriptive cohorts (23%), and phenotypic expansions (4%). Clinical laboratories are pivotal for disease gene discovery efforts and can screen phenotypes based on genotype matches, contact clinicians of relevant cases, and issue proactive reclassification reports. [ABSTRACT FROM AUTHOR]

Clinical guidelines consider expanded carrier screening (ECS) to be an acceptable method of carrier screening. However, broader guideline support and payer adoption require evidence for associations between the genes on ECS panels and the conditions for which they aim to identify carriers. We applied a standardized framework for evaluation of gene‐disease association to assess the clinical validity of conditions screened by ECS panels. The Clinical Genome Resource (ClinGen) gene curation framework was used to assess genetic and experimental evidence of associations between 208 genes and conditions screened on two commercial ECS panels. Twenty‐one conditions were previously classified by ClinGen, and the remaining 187 were evaluated by curation teams at two laboratories. To ensure consistent application of the framework across the laboratories, concordance was evaluated on a subset of conditions. All 208 evaluated conditions met the evidence threshold for supporting a gene‐disease association. Furthermore, 203 of 208 (98%) achieved the strongest ("Definitive") level of gene‐disease association. All conditions evaluated by both commercial laboratories were similarly classified. Assessment using the ClinGen standardized framework revealed strong evidence of gene‐disease association for conditions on two ECS panels. This result establishes the disease‐level clinical validity of the panels considered herein. [ABSTRACT FROM AUTHOR]

The field of epilepsy genetics is advancing rapidly and epilepsy is emerging as a frequent indication for diagnostic genetic testing. Within the larger ClinGen framework, the ClinGen Epilepsy Gene Curation Expert Panel is tasked with connecting two increasingly separate fields: the domain of traditional clinical epileptology, with its own established language and classification criteria, and the rapidly evolving area of diagnostic genetic testing that adheres to formal criteria for gene and variant curation. We identify critical components unique to the epilepsy gene curation effort, including: (a) precise phenotype definitions within existing disease and phenotype ontologies; (b) consideration of when epilepsy should be curated as a distinct disease entity; (c) strategies for gene selection; and (d) emerging rules for evaluating functional models for seizure disorders. Given that de novo variants play a prominent role in many of the epilepsies, sufficient genetic evidence is often awarded early in the curation process. Therefore, the emphasis of gene curation is frequently shifted toward an iterative precuration process to better capture phenotypic associations. We demonstrate that within the spectrum of neurodevelopmental disorders, gene curation for epilepsy‐associated genes is feasible and suggest epilepsy‐specific conventions, laying the groundwork for a curation process of all major epilepsy‐associated genes. Epilepsy is emerging as a frequent indication for diagnostic genetic testing. The ClinGen Epilepsy Gene Curation Expert Panel is tasked with connecting the domain of traditional clinical epileptology and the rapidly evolving area of diagnostic genetic testing. We identify precise phenotype definitions and phenotypic boundaries, gene selection strategies, and rules functional models for seizure disorders as critical components of the gene curation process. We demonstrate that curation for epilepsy‐associated genes is feasible and suggest epilepsy‐specific conventions. [ABSTRACT FROM AUTHOR]

In order for ClinGen to maintain up‐to‐date gene‐disease clinical validity classifications for use by clinicians and clinical laboratories, an appropriate timeline for reevaluating curated gene‐disease associations will need to be determined. To provide guidance on how often a gene‐disease association should be recurated, a retrospective analysis of 30 gene curations was performed. Curations were simulated at one‐year intervals starting with the year of the first publication to assert disease‐causing variants in the gene to observe trends in the classification over time, as well as factors that influenced changes in classification. On average, gene‐disease associations spent the least amount of time in the "Moderate" classification before progressing to "Strong" or "Definitive." In contrast, gene‐disease associations that spent five or more years in the "Limited" classification were most likely to remain "Limited" or become "Disputed/Refuted." Large population datasets contributed to the reclassification of several gene‐disease associations from "Limited" to "Disputed/Refuted." Finally, recent advancements in sequencing technology correlated with an increase in the quantity of case‐level evidence that was curated per paper. This study provided a number of key points to consider when determining how often to recurate a gene‐disease association. Maintaining the most current ClinGen gene‐disease clinical validity classifications requires an appropriate timeline for re‐evaluating curated gene‐disease associations. In order to provide guidance on how often a gene‐disease association should be re‐evaluated, a retrospective analysis of 30 gene curations was performed at one‐year intervals to identify trends in the classification over time and factors that influenced changes in classification. This study provides key consideration points for determining the most effective timeline for re‐evaluating gene‐disease associations. [ABSTRACT FROM AUTHOR]

ABSTRACT Ascertaining a diagnosis through exome sequencing can provide potential benefits to patients, insurance companies, and the healthcare system. Yet, as diagnostic sequencing is increasingly employed, vast amounts of human genetic data are produced that need careful curation. We discuss methods for accurately assessing the clinical validity of gene-disease relationships to interpret new research findings in a clinical context and increase the diagnostic rate. The specifics of a gene-disease scoring system adapted for use in a clinical laboratory are described. In turn, clinical validity scoring of gene-disease relationships can inform exome reporting for the identification of new or the upgrade of previous, clinically relevant gene findings. Our retrospective analysis of all reclassification reports from the first 4 years of diagnostic exome sequencing showed that 78% were due to new gene-disease discoveries published in the literature. Among all exome positive/likely positive findings in characterized genes, 32% were in genetic etiologies that were discovered after 2010. Our data underscore the importance and benefits of active and up-to-date curation of a gene-disease database combined with critical clinical validity scoring and proactive reanalysis in the clinical genomics era. [ABSTRACT FROM AUTHOR]