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1.
Genet Med ; 23(11): 2208-2212, 2021 11.
Article En | MEDLINE | ID: mdl-34230634

PURPOSE: The ClinGen Variant Curation Expert Panels (VCEPs) provide disease-specific rules for accurate variant interpretation. Using the hearing loss-specific American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines, the Hearing Loss VCEP (HL VCEP) illustrates the utility of expert specifications in variant interpretation. METHODS: A total of 157 variants across nine HL genes, previously submitted to ClinVar, were curated by the HL VCEP. The curation process involved collecting published and unpublished data for each variant by biocurators, followed by bimonthly meetings of an expert curation subgroup that reviewed all evidence and applied the HL-specific ACMG/AMP guidelines to reach a final classification. RESULTS: Before expert curation, 75% (117/157) of variants had single or multiple variants of uncertain significance (VUS) submissions (17/157) or had conflicting interpretations in ClinVar (100/157). After applying the HL-specific ACMG/AMP guidelines, 24% (4/17) of VUS and 69% (69/100) of discordant variants were resolved into benign (B), likely benign (LB), likely pathogenic (LP), or pathogenic (P). Overall, 70% (109/157) variants had unambiguous classifications (B, LB, LP, P). We quantify the contribution of the HL-specified ACMG/AMP codes to variant classification. CONCLUSION: Expert specification and application of the HL-specific ACMG/AMP guidelines effectively resolved discordant interpretations in ClinVar. This study highlights the utility of ClinGen VCEPs in supporting more consistent clinical variant interpretation.


Genome, Human , Hearing Loss , Humans , Genetic Testing , Genetic Variation/genetics , Hearing Loss/diagnosis , Hearing Loss/genetics
2.
Genet Med ; 21(11): 2442-2452, 2019 11.
Article En | MEDLINE | ID: mdl-31160754

PURPOSE: Pathogenic variants in GJB2 are the most common cause of autosomal recessive sensorineural hearing loss. The classification of c.101T>C/p.Met34Thr and c.109G>A/p.Val37Ile in GJB2 are controversial. Therefore, an expert consensus is required for the interpretation of these two variants. METHODS: The ClinGen Hearing Loss Expert Panel collected published data and shared unpublished information from contributing laboratories and clinics regarding the two variants. Functional, computational, allelic, and segregation data were also obtained. Case-control statistical analyses were performed. RESULTS: The panel reviewed the synthesized information, and classified the p.Met34Thr and p.Val37Ile variants utilizing professional variant interpretation guidelines and professional judgment. We found that p.Met34Thr and p.Val37Ile are significantly overrepresented in hearing loss patients, compared with population controls. Individuals homozygous or compound heterozygous for p.Met34Thr or p.Val37Ile typically manifest mild to moderate hearing loss. Several other types of evidence also support pathogenic roles for these two variants. CONCLUSION: Resolving controversies in variant classification requires coordinated effort among a panel of international multi-institutional experts to share data, standardize classification guidelines, review evidence, and reach a consensus. We concluded that p.Met34Thr and p.Val37Ile variants in GJB2 are pathogenic for autosomal recessive nonsyndromic hearing loss with variable expressivity and incomplete penetrance.


Connexins/genetics , Hearing Loss/genetics , Alleles , Case-Control Studies , Connexin 26/genetics , Connexins/metabolism , Deafness/genetics , Female , Hearing Loss, Sensorineural/genetics , Humans , Male , Mutation , Polymorphism, Single Nucleotide/genetics
4.
Genet Med ; 21(10): 2239-2247, 2019 10.
Article En | MEDLINE | ID: mdl-30894701

PURPOSE: Proper 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 semiquantitative framework to assign clinical validity to gene-disease relationships. METHODS: The 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. RESULTS: The 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 ). CONCLUSION: This 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.


Deafness/genetics , Genetic Testing/methods , Hearing Loss/genetics , Data Curation/methods , Databases, Genetic , Genetic Testing/standards , Genetic Variation , Genome, Human , Genomics/methods , Humans , Mutation , Reproducibility of Results
6.
Hum Mutat ; 39(11): 1494-1504, 2018 11.
Article En | MEDLINE | ID: mdl-30311372

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.


Genome, Human/genetics , Genomics/methods , Disease Progression , Humans , Retrospective Studies
7.
Hum Mutat ; 39(11): 1593-1613, 2018 11.
Article En | MEDLINE | ID: mdl-30311386

Due to the high genetic heterogeneity of hearing loss (HL), 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 HL. 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) guidelines for the interpretation of sequence variants in HL genes. Here, we provide a comprehensive illustration of the newly specified ACMG/AMP HL rules. Three rules remained unchanged, four rules were removed, and the remaining 21 rules were specified. These rules were further validated and refined using a pilot set of 51 variants assessed by curators and disease experts. Of the 51 variants evaluated in the pilot, 37% (19/51) changed category based upon application of the expert panel specified rules and/or aggregation of evidence across laboratories. These HL-specific ACMG/AMP rules will help standardize variant interpretation, ultimately leading to better care for individuals with HL.


Genetic Testing/methods , Genome, Human/genetics , Hearing Loss/genetics , Gene Frequency/genetics , Genetic Variation/genetics , Genomics/methods , Humans , Mutation/genetics , Sequence Analysis, DNA , Societies, Medical , United States
8.
J Mol Diagn ; 20(6): 789-801, 2018 11.
Article En | MEDLINE | ID: mdl-30096381

Variant interpretation depends on accurate annotations using biologically relevant transcripts. We have developed a systematic strategy for designating primary transcripts and have applied it to 109 hearing loss-associated genes that were divided into three categories. Category 1 genes (n = 38) had a single transcript; category 2 genes (n = 33) 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 significant, insignificant, or of uncertain significance. Interestingly, 6% of all exons, containing 124 reportedly disease-causing variants, were of uncertain significance. Finally, we used exon-level next-generation sequencing quality metrics generated at two clinical laboratories and identified a total of 43 technically challenging exons in 20 different genes that had inadequate coverage and/or homology issues that might lead to false-variant calls. We have demonstrated that transcript analysis plays a critical role in accurate clinical variant interpretation.


Genetic Variation , Exons/genetics , Humans , RNA, Messenger/genetics , RNA, Messenger/metabolism
9.
Article En | MEDLINE | ID: mdl-29945942

The ClinVar database is a useful tool for patients and physicians to view variant interpretations submitted by clinical and nonclinical labs. However, variants of uncertain significance (VUS) in ClinVar can pose a significant burden on patients. If possible, it is important to resolve discrepancies and uncertainties surrounding interpreted variants. Here we highlight a case of a family who received a report of a variant (c.622A>G, p.Ile208Val) in BRAF following prenatal RASopathy testing. The variant had been previously classified by our laboratory as a VUS, so the mother contacted our laboratory via ClinVar for further information, which prompted reevaluation of the variant. Multiple sources of case-level data as well as the presence of the variant in the general population yielded sufficient evidence to reclassify the variant as likely benign. This reclassification alleviated significant concern for the family, and the child was born healthy with no clinical manifestations of Noonan syndrome or a RASopathy.


Data Curation/methods , Information Dissemination/methods , Proto-Oncogene Proteins B-raf/genetics , Databases, Genetic/trends , Genetic Predisposition to Disease/genetics , Genetic Testing/trends , Genetic Variation/genetics , Genome, Human/genetics , Humans , Reproducibility of Results , Uncertainty
10.
Hum Mutat ; 39(8): 1051-1060, 2018 08.
Article En | MEDLINE | ID: mdl-29790234

ClinVar Miner is a Web-based suite that utilizes the data held in the National Center for Biotechnology Information's ClinVar archive. The goal is to render the data more accessible to processes pertaining to conflict resolution of variant interpretation as well as tracking details of data submission and data management for detailed variant curation. Here, we establish the use of these tools to address three separate use cases and to perform analyses across submissions. We demonstrate that the ClinVar Miner tools are an effective means to browse and consolidate data for variant submitters, curation groups, and general oversight. These tools are also relevant to the variant interpretation community in general.


Databases, Genetic , Genetic Variation/genetics , Genome, Human/genetics , Genomics , Humans , Software
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