Unique aspects of sequence variant interpretation for inborn errors of metabolism (IEM): The ClinGen IEM Working Group and the Phenylalanine Hydroxylase Gene

Zastrow, Diane B.; Baudet, Heather; Shen, Wei; Thomas, Amanda L.; Si, Yue; Weaver, Meredith; Lager, Angela M.; Liu, Jixia; Mangels, Rachel; Dwight, Selina S.; Wright, Mathew W.; Dobrowolski, Steven F.; Eilbeck, Karen; Enns, Gregory M.; Feigenbaum, Annette; Lichter‐Konecki, Uta; Lyon, Elaine; Pasquali, Marzia; Watson, Michael S.; Blau, Nenad; Steiner, Robert D.; Craigen, William J.; Mao, Rong

doi:10.1002/humu.23649

Cited by 56 publications

(50 citation statements)

References 28 publications

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“…The accurate interpretation of these variants has a significant impact in clinical and research settings. For example, their pathogenicity affects the gene-specific allele frequency thresholds used as evidence for pathogenic or benign variant interpretation 4 . Recently, ClinGen experts curated 103 variants with an allele frequency exceeding 5% and concluded that only four of them were pathogenic 5 .…”

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confidence: 99%

Reinterpretation of common pathogenic variants in ClinVar revealed a high proportion of downgrades

Xiang

Chen

et al. 2020

Sci Rep

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High-frequency disease-causing alleles exist, but their number is rather small. This study aimed to interpret and reclassify common pathogenic (P) and likely pathogenic (LP) variants in ClinVar and to identify indicators linked with reclassification. We analyzed P/LP variants without conflicting interpretations in ClinVar. Only variants with an allele frequency exceeding 0.5% in at least one ancestry in gnomAD were included. Variants were manually interpreted according to the guidelines of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Of 326 variants retrieved, 217 variants in 173 genes were selected for curation. Overall, 87 (40%) variants were downgraded to benign, likely benign or variant of uncertain significance. Five variants (2%) were found to be more likely to be risk factors. Most of the reclassifications were of variants with a low rank, an older classification, a higher allele frequency, or which were collected through methods other than clinical testing. ClinVar provides a universal platform for users who intend to share the classification variants, resulting in the improved concordance of variant interpretation. P/LP variants with a high allele frequency should be used with caution. Ongoing improvements would further improve the practicability of ClinVar database.

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confidence: 99%

Reinterpretation of common pathogenic variants in ClinVar revealed a high proportion of downgrades

Xiang

Chen

et al. 2020

Sci Rep

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“…In response to calls to further standardize variant interpretation [3,4], the Clinical Genome Resource (ClinGen) established the Sequence Variant Interpretation Working Group (SVI) [5] and condition-specific Variant Curation Expert Panels (VCEPs) to refine ACMG/AMP guidelines for each evidence criterion [6]. To date, six VCEPs have published recommendations, including their assay validation requirements and which assays were ultimately approved for PS3/BS3 evidence application [7][8][9][10][11][12]. VCEP-approved assays varied greatly and included splicing assays, animal and cellular models, and different in vitro systems [Kanavy et al, submitted].…”

Section: Introductionmentioning

confidence: 99%

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

Brnich

Tayoun

Couch³

et al. 2019

Preprint

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193

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Background:The 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. Methods: The Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI)Working Group used curated functional evidence from ClinGen Variant Curation Expert Paneldeveloped rule specifications and expert opinions to refine the PS3/BS3 criteria over multiple inperson 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. Results:The 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 4 pathogenic and benign variant controls are required to reach moderate-level evidence in the absence of rigorous statistical analysis. Conclusions:The 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.

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“…The ACMG/AMP guidelines have suggested another way to evaluate variants such that the same variant observed in multiple unrelated affected individuals with consistent phenotypes, and its absence in population databases, could be used as PS4 evidence at a moderate level of evidence 1 . Recently, the Clinical Genome Resource (ClinGen) published reports regarding variant interpretation according to ACMG guidelines, focusing on unique features of particular genes or genomic regions [3][4][5][6][7][8] . These reports describe the number of observations in unrelated affected individuals and any of modified strengths of each rule, according to disease-gene specifications [3][4][5][6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

“…Recently, the Clinical Genome Resource (ClinGen) published reports regarding variant interpretation according to ACMG guidelines, focusing on unique features of particular genes or genomic regions [3][4][5][6][7][8] . These reports describe the number of observations in unrelated affected individuals and any of modified strengths of each rule, according to disease-gene specifications [3][4][5][6][7][8] . These observations can be acquired through internal lab data, publicly available data, and through scientific literature.…”

Section: Introductionmentioning

confidence: 99%

A novel PS4 criterion approach based on symptoms of rare diseases and in-house frequency data in a Bayesian framework

Cho¹,

Won²,

Keum³

et al. 2020

Preprint

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The American College of Medical Genetics (ACMG) and Genomics/Association for Molecular Pathology (AMP) previously reported standardized guidance for the assessment of genetic variants. One of the criteria regarding the prevalence in a case-control study, PS4, is important due to its evidence of pathogenicity. Despite recent studies approaching gene- and disease-specific probands, interpretation of a variant to PS4 still has certain limitations for rare variants. Here, we suggest a generalized method, Bayesian odds ratio (BayesianOR), applicable to PS4 via decomposing a disease to its symptoms and applying a Bayesian framework. Using this approach, we demonstrate reproducibility of the calculation of the original odds ratio from well-studied epilepsy data and verify the applicability to in-house frequencies for various rare diseases. In addition, BayesianOR showed a significant difference in tendency with different ClinVar pathogenicity, using in-house data. Thus, the novel method described here should provide an improved interpretation of sequence variants. Furthermore, we anticipate that it will enhance the diagnosis of patients with rare diseases.

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Unique aspects of sequence variant interpretation for inborn errors of metabolism (IEM): The ClinGen IEM Working Group and the Phenylalanine Hydroxylase Gene

Cited by 56 publications

References 28 publications

Reinterpretation of common pathogenic variants in ClinVar revealed a high proportion of downgrades

Reinterpretation of common pathogenic variants in ClinVar revealed a high proportion of downgrades

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

A novel PS4 criterion approach based on symptoms of rare diseases and in-house frequency data in a Bayesian framework

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