Attenzione: i dati modificati non sono ancora stati salvati. Per confermare inserimenti o cancellazioni di voci è necessario confermare con il tasto SALVA/INSERISCI in fondo alla pagina
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.
Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification
Parsons, Michael T.;Tudini, Emma;Li, Hongyan;Hahnen, Eric;Wappenschmidt, Barbara;Feliubadaló, Lidia;Aalfs, Cora M.;Agata, Simona;Aittomäki, Kristiina;Alducci, Elisa;Alonso-Cerezo, María Concepción;Arnold, Norbert;Auber, Bernd;Austin, Rachel;Azzollini, Jacopo;Balmaña, Judith;Barbieri, Elena;Bartram, Claus R.;Blanco, Ana;Blümcke, Britta;Bonache, Sandra;Bonanni, Bernardo;Borg, Åke;Bortesi, Beatrice;Brunet, Joan;Bruzzone, Carla;Bucksch, Karolin;Cagnoli, Giulia;Caldés, Trinidad;Caliebe, Almuth;Caligo, Maria A.;Calvello, Mariarosaria;Capone, Gabriele L.;Caputo, Sandrine M.;Carnevali, Ileana;Carrasco, Estela;Caux-Moncoutier, Virginie;Cavalli, Pietro;Cini, Giulia;Clarke, Edward M.;Concolino, Paola;Cops, Elisa J.;Cortesi, Laura;Couch, Fergus J.;Darder, Esther;de la Hoya, Miguel;Dean, Michael;Debatin, Irmgard;del Valle, Jesús;Delnatte, Capucine;Derive, Nicolas;Diez, Orland;Ditsch, Nina;Domchek, Susan M.;Dutrannoy, Véronique;Eccles, Diana M.;Ehrencrona, Hans;Enders, Ute;Evans, D. Gareth;Faust, Ulrike;Felbor, Ute;Feroce, Irene;Fine, Miriam;Galvao, Henrique C. R.;Gambino, Gaetana;Gehrig, Andrea;Gensini, Francesca;Gerdes, Anne-Marie;Germani, Aldo;Giesecke, Jutta;Gismondi, Viviana;Gómez, Carolina;Gómez Garcia, Encarna B.;González, Sara;Grau, Elia;Grill, Sabine;Gross, Eva;Guerrieri-Gonzaga, Aliana;Guillaud-Bataille, Marine;Gutiérrez-Enríquez, Sara;Haaf, Thomas;Hackmann, Karl;Hansen, Thomas V. O.;Harris, Marion;Hauke, Jan;Heinrich, Tilman;Hellebrand, Heide;Herold, Karen N.;Honisch, Ellen;Horvath, Judit;Houdayer, Claude;Hübbel, Verena;Iglesias, Silvia;Izquierdo, Angel;James, Paul A.;Janssen, Linda A. M.;Jeschke, Udo;Kaulfuß, Silke;Keupp, Katharina;Kiechle, Marion;Kölbl, Alexandra;Krieger, Sophie;Kruse, Torben A.;Kvist, Anders;Lalloo, Fiona;Larsen, Mirjam;Lattimore, Vanessa L.;Lautrup, Charlotte;Ledig, Susanne;Leinert, Elena;Lewis, Alexandra L.;Lim, Joanna;Loeffler, Markus;López-Fernández, Adrià;Lucci-Cordisco, Emanuela;Maass, Nicolai;Manoukian, Siranoush;Marabelli, Monica;Matricardi, Laura;Meindl, Alfons;Michelli, Rodrigo D.;Moghadasi, Setareh;Moles-Fernández, Alejandro;Montagna, Marco;Montalban, Gemma;Monteiro, Alvaro N.;Montes, Eva;Mori, Luigi;Moserle, Lidia;Müller, Clemens R.;Mundhenke, Christoph;Naldi, Nadia;Nathanson, Katherine L.;Navarro, Matilde;Nevanlinna, Heli;Nichols, Cassandra B.;Niederacher, Dieter;Nielsen, Henriette R.;Ong, Kai-ren;Pachter, Nicholas;Palmero, Edenir I.;Papi, Laura;Pedersen, Inge Sokilde;Peissel, Bernard;Pérez-Segura, Pedro;Pfeifer, Katharina;Pineda, Marta;Pohl-Rescigno, Esther;Poplawski, Nicola K.;Porfirio, Berardino;Quante, Anne S.;Ramser, Juliane;Reis, Rui M.;Revillion, Françoise;Rhiem, Kerstin;Riboli, Barbara;Ritter, Julia;Rivera, Daniela;Rofes, Paula;Rump, Andreas;Salinas, Monica;Sánchez de Abajo, Ana María;Schmidt, Gunnar;Schoenwiese, Ulrike;Seggewiß, Jochen;Solanes, Ares;Steinemann, Doris;Stiller, Mathias;Stoppa-Lyonnet, Dominique;Sullivan, Kelly J.;Susman, Rachel;Sutter, Christian;Tavtigian, Sean V.;Teo, Soo H.;Teulé, Alex;Thomassen, Mads;Tibiletti, Maria Grazia;Tognazzo, Silvia;Toland, Amanda E.;Tornero, Eva;Törngren, Therese;Torres-Esquius, Sara;Toss, Angela;Trainer, Alison H.;van Asperen, Christi J.;van Mackelenbergh, Marion T.;Varesco, Liliana;Vargas-Parra, Gardenia;Varon, Raymonda;Vega, Ana;Velasco, Ángela;Vesper, Anne-Sophie;Viel, Alessandra;Vreeswijk, Maaike P. G.;Wagner, Sebastian A.;Waha, Anke;Walker, Logan C.;Walters, Rhiannon J.;Wang-Gohrke, Shan;Weber, Bernhard H. F.;Weichert, Wilko;Wieland, Kerstin;Wiesmüller, Lisa;Witzel, Isabell;Wöckel, Achim;Woodward, Emma R.;Zachariae, Silke;Zampiga, Valentina;Zeder-Göß, Christine;Lázaro, Conxi;De Nicolo, Arcangela;Radice, Paolo;Engel, Christoph;Schmutzler, Rita K.;Goldgar, David E.;Spurdle, Amanda B.
2019
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.
Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1179823
Citazioni
50
90
82
social impact
Conferma cancellazione
Sei sicuro che questo prodotto debba essere cancellato?
simulazione ASN
La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. L’Università di Modena e Reggio Emilia non si assume alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione.