Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/121464
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Type: Journal article
Title: Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: an ENIGMA resource to support clinical variant classification
Author: Parsons, M.T.
Tudini, E.
Li, H.
Hahnen, E.
Wappenschmidt, B.
Feliubadaló, L.
Aalfs, C.M.
Agata, S.
Aittomäki, K.
Alducci, E.
Alonso-Cerezo, M.C.
Arnold, N.
Auber, B.
Austin, R.
Azzollini, J.
Balmaña, J.
Barbieri, E.
Bartram, C.R.
Blanco, A.
Blümcke, B.
et al.
Citation: Human Mutation, 2019; 40(9):1557-1578
Publisher: Wiley
Issue Date: 2019
ISSN: 1059-7794
1098-1004
Statement of
Responsibility: 
Michael T. Parsons … Miriam Fine … Nicola K. Poplawski … et al.
Abstract: The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification.
Keywords: BRCA1
BRCA2
classification
clinical
multifactorial
quantitative
uncertain significance
variant
Rights: © 2019 The Authors Human Mutation Published by Wiley Periodicals, Inc.
DOI: 10.1002/humu.23818
Grant ID: http://purl.org/au-research/grants/nhmrc/1061779
http://purl.org/au-research/grants/nhmrc/1104808
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