Estimating the proportion of pathogenic variants from breast cancer case–control data: Application to calibration of ACMG/AMP variant classification criteria

James, Paul; Fortuño, Cristina; Li, Na; Lim, Belle W.X.; Spurdle, Amanda B.

doi:10.1002/humu.24357

Cited by 8 publications

(4 citation statements)

References 8 publications

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“…The Hereditary Breast Ovarian and Pancreatic Cancer VCEP has designated BP7 application for variants at or beyond positions +7/-40 in the ATM gene. The ENIGMA BRCA1 and BRCA2 VCEP specifications justify the application of BP7 for variants outside splice motifs based on maximum likelihood estimation analysis of breast cancer case-control data 57 with results indicating that location of an intronic variant at or beyond positions +7/-21 provides moderate evidence against pathogenicity - even without applying a bioinformatic prediction filter.…”

Section: Resultsmentioning

confidence: 99%

Application of the Acmg/Amp Framework to Capture Evidence Relevant to Predicted and Observed Impact on Splicing: Recommendations From the Clingen Svi Splicing Subgroup

Walker

Hoya

Wiggins

et al. 2023

Preprint

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The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence

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Section: Resultsmentioning

confidence: 99%

Application of the Acmg/Amp Framework to Capture Evidence Relevant to Predicted and Observed Impact on Splicing: Recommendations From the Clingen Svi Splicing Subgroup

Walker

Hoya

Wiggins

et al. 2023

Preprint

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“…BP1 was used to capture strong evidence against pathogenicity for a variant outside of a known clinically important functional domain predicted to encode a silent or missense/in-frame substitution only (without known or predicted impact on splicing), with strength assigned from probability based studies 17 , and VCEP consideration of large-scale case-control findings for missense variants. 20 ; 21 PP4 and BP5 were repurposed to capture combined LR estimates towards pathogenicity (PP4) or against pathogenicity (BP5), as derived from calibrated multifactorial likelihood ratio analysis (but excluding any direct statistical measurement of bioinformatic prediction scores, to avoid overlap with other computational codes).…”

Section: Resultsmentioning

confidence: 99%

Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel

Parsons,

de la Hoya,

Richardson

et al. 2024

Preprint

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The ENIGMA research consortium (https://enigmaconsortium.org/) develops and applies methods to determine clinical significance of variants in Hereditary Breast and Ovarian Cancer genes. An ENIGMA BRCA1/2 classification sub-group, originally formed in 2016 as a ClinGen external expert panel, evolved into a ClinGen internal Variant Curation Expert Panel (VCEP) to align with Federal Drug Administration recognized processes for ClinVar contributions. The VCEP reviewed American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) classification criteria for relevance to interpreting BRCA1 and BRCA2 variants. Statistical methods were used to calibrate evidence strength for different data types. Pilot specifications were tested on 40 variants, and documentation revised for clarity and ease-of-use. The original criterion descriptions for 13 evidence codes were considered non-applicable or overlapping with other criteria. Scenario of use was extended or re-purposed for eight codes. Extensive analysis and/or data review informed specification descriptions and weights for all codes. Specifications were applied to pilot variants with pre-existing ClinVar classification as follows: 13 Uncertain Significance or Conflicting, 14 Pathogenic and/or Likely Pathogenic, and 13 Benign and/or Likely Benign. Review resolved classification for 11/13 Uncertain Significance or Conflicting variants, and retained or improved confidence in classification for the remaining variants. Alignment of pre-existing ENIGMA research classification processes with ACMG/AMP classification guidelines highlighted several gaps in both the research processes and the baseline ACMG/AMP criteria. Calibration of evidence types was key to justify utility and strength of different evidence types for gene-specific application. The gene-specific criteria demonstrated value for improving ACMG/AMP-aligned classification of BRCA1 and BRCA2 variants.

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“…Large part of variations, in many genes the majority, are benign and without phenotype. Experimental studies [ 252 ] and predictions [ 209 , 210 , 253 ] have indicated that genes display a wide range of vulnerabilities for genetic alterations. Even in Cancer Gene Census -classified cancer-related genes [ 254 ] with substitutions, just 40% of amino acid substitutions were predicted to be harmful [ 255 ].…”

Section: Genetic Heterogeneity and Diseasesmentioning

confidence: 99%

Individual Genetic Heterogeneity

Vihinen

2022

Genes

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Genetic variation has been widely covered in literature, however, not from the perspective of an individual in any species. Here, a synthesis of genetic concepts and variations relevant for individual genetic constitution is provided. All the different levels of genetic information and variation are covered, ranging from whether an organism is unmixed or hybrid, has variations in genome, chromosomes, and more locally in DNA regions, to epigenetic variants or alterations in selfish genetic elements. Genetic constitution and heterogeneity of microbiota are highly relevant for health and wellbeing of an individual. Mutation rates vary widely for variation types, e.g., due to the sequence context. Genetic information guides numerous aspects in organisms. Types of inheritance, whether Mendelian or non-Mendelian, zygosity, sexual reproduction, and sex determination are covered. Functions of DNA and functional effects of variations are introduced, along with mechanism that reduce and modulate functional effects, including TARAR countermeasures and intraindividual genetic conflict. TARAR countermeasures for tolerance, avoidance, repair, attenuation, and resistance are essential for life, integrity of genetic information, and gene expression. The genetic composition, effects of variations, and their expression are considered also in diseases and personalized medicine. The text synthesizes knowledge and insight on individual genetic heterogeneity and organizes and systematizes the central concepts.

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Estimating the proportion of pathogenic variants from breast cancer case–control data: Application to calibration of ACMG/AMP variant classification criteria

Cited by 8 publications

References 8 publications

Application of the Acmg/Amp Framework to Capture Evidence Relevant to Predicted and Observed Impact on Splicing: Recommendations From the Clingen Svi Splicing Subgroup

Application of the Acmg/Amp Framework to Capture Evidence Relevant to Predicted and Observed Impact on Splicing: Recommendations From the Clingen Svi Splicing Subgroup

Evidence-based recommendations for gene-specific ACMG/AMP variant classification from the ClinGen ENIGMA BRCA1 and BRCA2 Variant Curation Expert Panel

Individual Genetic Heterogeneity

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