TY - JOUR

T1 - Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants

T2 - An ENIGMA resource to support clinical variant classification

AU - Parsons, Michael T

AU - Tudini, Emma

AU - Li, Hongyan

AU - Hahnen, Eric

AU - Wappenschmidt, Barbara

AU - Feliubadaló, Lidia

AU - Aalfs, Cora M

AU - Agata, Simona

AU - Aittomäki, Kristiina

AU - Alducci, Elisa

AU - Alonso-Cerezo, María Concepción

AU - Arnold, Norbert

AU - Auber, Bernd

AU - Austin, Rachel

AU - Azzollini, Jacopo

AU - Balmaña, Judith

AU - Barbieri, Elena

AU - Bartram, Claus R

AU - Blanco, Ana

AU - Blümcke, Britta

AU - Bonache, Sandra

AU - Bonanni, Bernardo

AU - Borg, Åke

AU - Bortesi, Beatrice

AU - Brunet, Joan

AU - Bruzzone, Carla

AU - Bucksch, Karolin

AU - Cagnoli, Giulia

AU - Caldés, Trinidad

AU - Caliebe, Almuth

AU - Caligo, Maria A

AU - Calvello, Mariarosaria

AU - Capone, Gabriele L

AU - Caputo, Sandrine M

AU - Carnevali, Ileana

AU - Carrasco, Estela

AU - Caux-Moncoutier, Virginie

AU - Cavalli, Pietro

AU - Cini, Giulia

AU - Clarke, Edward M

AU - Concolino, Paola

AU - Cops, Elisa J

AU - Cortesi, Laura

AU - Couch, Fergus J

AU - Darder, Esther

AU - de la Hoya, Miguel

AU - Dean, Michael

AU - Gerdes, Anne-Marie

AU - Hansen, Thomas V. O.

AU - Wagner, Sebastian A

AU - kConFab Investigators

N1 - Special Issue: The Fifth Critical Assessment of Genome Interpretation (CAGI5)

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Alternative Splicing

KW - BRCA1 Protein/genetics

KW - BRCA2 Protein/genetics

KW - Computational Biology/methods

KW - Early Detection of Cancer

KW - Female

KW - Genetic Predisposition to Disease

KW - Humans

KW - Likelihood Functions

KW - Male

KW - Multifactorial Inheritance

KW - Mutation, Missense

KW - Neoplasms/diagnosis

U2 - 10.1002/humu.23818

DO - 10.1002/humu.23818

M3 - Journal article

C2 - 31131967

VL - 40

SP - 1557

EP - 1578

JO - Human Mutation

JF - Human Mutation

SN - 1059-7794

IS - 9

ER -