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Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Françoise Revillion Michael T. Parsons 1 Emma Tudini Hongyan Li 2 Eric Hahnen Barbara Wappenschmidt 3 Lídia Feliubadaló 4 Cora M. Aalfs 5 Simona Agata Kristiina Aittomäki 6 Elisa Alducci María Concepción Alonso‐cerezo Norbert Arnold 7 Bernd Auber Rachel Austin Jacopo Azzollini 8 Judith Balmaña 9 Elena Barbieri Claus R. Bartram 10 Ana Blanco 11 Britta Blümcke Sandra Bonache Bernardo Bonanni 12 Åke Borg 13 Beatrice Bortesi Joan Brunet 14 Carla Bruzzone Karolin Bucksch Giulia Cagnoli Trinidad Caldes 15 Almuth Caliebe Maria A. Caligo Mariarosaria Calvello Gabriele L. Capone Sandrine M. Caputo 16 Ileana Carnevali Estela Carrasco Virginie Caux‐moncoutier Pietro Cavalli Giulia Cini Edward M. Clarke Paola Concolino Elisa J. Cops Laura Cortesi Fergus J. Couch Esther Darder 17 Miguel de La Hoya 18 Michael Dean Irmgard Debatin Jesús Del Valle Capucine Delnatte 19 Nicolas Derive 20 Orland Diez 21 Nina Ditsch 22 Susan M. Domchek Véronique Dutrannoy 23 Diana M. Eccles 24 Hans Ehrencrona 25 Ute Enders D. Gareth Evans 26 Ulrike Faust Ute Felbor Irene Feroce Miriam Fine Henrique C.R. Galvao Gaetana Gambino Andrea Gehrig 27 Francesca Gensini Anne‐marie Gerdes Aldo Germani Jutta Giesecke Viviana Gismondi Carolina Gomez Encarna B. Gómez Garcia Sara Gonzalez 28 Elia Grau Sabine Grill Eva Gross 29 Aliana Guerrieri‐gonzaga Marine Guillaud‐bataille Sara Gutiérrez‐enríquez Thomas Haaf 30 Karl Hackmann Thomas V.O. Hansen Marion Harris Jan Hauke Tilman Heinrich Heide Hellebrand 29 Karen N. Herold Ellen Honisch 31 Judit Horvath 32 Claude Houdayer 33 Verena Hübbel Silvia Iglesias Angel Izquierdo Paul A. James Linda A.M. Janssen Udo Jeschke 34 Silke Kaulfuß Katharina Keupp Marion Kiechle 29 Alexandra Kölbl Sophie Krieger 35, 36 Torben A. Kruse 37 Anders Kvist 38 Fiona Lalloo 39 Mirjam Larsen Vanessa L. Lattimore Charlotte Lautrup Susanne Ledig Elena Leinert Alexandra L. Lewis Joanna Lim Markus Loeffler 40 Adrià López‐fernández Emanuela Lucci‐cordisco Nicolai Maass 41 Siranoush Manoukian 42 Monica Marabelli Laura Matricardi Alfons Meindl 43 Rodrigo D. Michelli Setareh Moghadasi Alejandro Moles‐fernández Marco Montagna 44 Gemma Montalban Alvaro N. Monteiro Eva Montes Luigi Mori Lidia Moserle Clemens R. Müller Christoph Mundhenke 45 Nadia Naldi Katherine L. Nathanson Matilde Navarro Heli Nevanlinna 46 Cassandra B. Nichols Dieter Niederacher 47 Henriette R. Nielsen Kai‐ren Ong Nicholas Pachter Edenir I. Palmero Laura Papi 48 Inge Søkilde Pedersen 49 Bernard Peissel 42 Pedro Pérez‐segura Katharina Pfeifer Marta Pineda Esther Pohl‐rescigno Nicola K. Poplawski Berardino Porfirio Anne S. Quante Juliane Ramser Rui M. Reis Françoise Révillion 50 Kerstin Rhiem 51 Barbara Riboli Julia Ritter Daniela Rivera Paula Rofes Andreas Rump Monica Salinas Ana María Sánchez De Abajo Gunnar Schmidt Ulrike Schoenwiese Jochen Seggewiß Ares Solanes Doris Steinemann 52 Mathias Stiller 53 Dominique Stoppa‐lyonnet Kelly J. Sullivan Rachel Susman Christian Sutter 54 Sean V. Tavtigian 55 Soo H. Teo Alex Teulé 56 Mads Thomassen 57 Maria Grazia Tibiletti Silvia Tognazzo 58 Amanda E. Toland Eva Tornero 59 Therese Törngren Sara Torres‐esquius Angela Toss Alison H. Trainer Christi J. Van Asperen Marion T. Van Mackelenbergh Liliana Varesco 60 Gardenia Vargas‐parra Raymonda Varon 61 Ana Vega 62 Ángela Velasco Anne‐sophie Vesper Alessandra Viel 63 Maaike P.G. Vreeswijk Sebastian A. Wagner Anke Waha Logan C. Walker 64 Rhiannon J. Walters Shan Wang‐gohrke Bernhard H.F. Weber Wilko Weichert 65 Kerstin Wieland Lisa Wiesmüller Isabell Witzel 66 Achim Wöckel Emma R. Woodward Silke Zachariae Valentina Zampiga Christine Zeder‐göß Kconfab Investigators 67 Conxi Lazaro 68 Arcangela De Nicolo Paolo Radice 69 Christoph Engel 70 Rita K. Schmutzler 71 David E. Goldgar Amanda B. Spurdle 1
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 1395 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; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to 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 non‐pathogenic 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.
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02194510
Contributor : Université Normandie <>
Submitted on : Thursday, July 25, 2019 - 3:49:31 PM
Last modification on : Wednesday, October 14, 2020 - 4:15:06 AM

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Françoise Revillion, Michael T. Parsons, Emma Tudini, Hongyan Li, Eric Hahnen, et al.. Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification. Human Mutation, Wiley, 2019, 40 (9), pp.1557-1578. ⟨10.1002/humu.23818⟩. ⟨hal-02194510⟩

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