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

Michael T ParsonsEmma TudiniHongyan LiEric HahnenBarbara WappenschmidtLidia FeliubadalóCora M AalfsSimona AgataKristiina AittomäkiElisa AlducciMaría Concepción Alonso-CerezoNorbert ArnoldBernd AuberRachel AustinJacopo AzzolliniJudith BalmañaElena BarbieriClaus R BartramAna BlancoBritta BlümckeSandra BonacheBernardo BonanniÅke BorgBeatrice BortesiJoan BrunetCarla BruzzoneKarolin BuckschGiulia CagnoliTrinidad CaldésAlmuth CaliebeMaria A CaligoMariarosaria CalvelloGabriele L CaponeSandrine M CaputoIleana CarnevaliEstela CarrascoVirginie Caux-MoncoutierPietro CavalliGiulia CiniEdward M ClarkePaola ConcolinoElisa J CopsLaura CortesiFergus J CouchEsther DarderMiguel de la HoyaMichael DeanIrmgard DebatinJesús Del ValleCapucine DelnatteNicolas DeriveOrland DiezNina DitschSusan M DomchekVéronique DutrannoyDiana M EcclesHans EhrencronaUte EndersD Gareth EvansChantal FarraUlrike FaustUte FelborIrene FeroceMiriam FineWilliam D FoulkesHenrique C R GalvaoGaetana GambinoAndrea GehrigFrancesca GensiniAnne-Marie GerdesAldo GermaniJutta GieseckeViviana GismondiCarolina GómezEncarna B Gómez GarciaSara GonzálezElia GrauSabine GrillEva GrossAliana Guerrieri-GonzagaMarine Guillaud-BatailleSara Gutiérrez-EnríquezThomas HaafKarl HackmannThomas V O HansenMarion HarrisJan HaukeTilman HeinrichHeide HellebrandKaren N HeroldEllen HonischJudit HorvathClaude HoudayerVerena HübbelSilvia IglesiasAngel IzquierdoPaul A JamesLinda A M JanssenUdo JeschkeSilke KaulfußKatharina KeuppMarion KiechleAlexandra KölblSophie KriegerTorben A KruseAnders KvistFiona LallooMirjam LarsenVanessa L LattimoreCharlotte LautrupSusanne LedigElena LeinertAlexandra L LewisJoanna LimMarkus LoefflerAdrià López-FernándezEmanuela Lucci-CordiscoNicolai MaassSiranoush ManoukianMonica MarabelliLaura MatricardiAlfons MeindlRodrigo D MichelliSetareh MoghadasiAlejandro Moles-FernándezMarco MontagnaGemma MontalbanAlvaro N MonteiroEva MontesLuigi MoriLidia MoserleClemens R MüllerChristoph MundhenkeNadia NaldiKatherine L NathansonMatilde NavarroHeli NevanlinnaCassandra B NicholsDieter NiederacherHenriette R NielsenKai-Ren OngNicholas PachterEdenir I PalmeroLaura PapiInge Sokilde PedersenBernard PeisselPedro Perez-SeguraKatharina PfeiferMarta PinedaEsther Pohl-RescignoNicola K PoplawskiBerardino PorfirioAnne S QuanteJuliane RamserRui M ReisFrançoise RevillionKerstin RhiemBarbara RiboliJulia RitterDaniela RiveraPaula RofesAndreas RumpMonica SalinasAna María Sánchez de AbajoGunnar SchmidtUlrike SchoenwieseJochen SeggewißAres SolanesDoris SteinemannMathias StillerDominique Stoppa-LyonnetKelly J SullivanRachel SusmanChristian SutterSean V TavtigianSoo H TeoAlex TeuléMads ThomassenMaria Grazia TibilettiMarc TischkowitzSilvia TognazzoAmanda Ewart TolandEva TorneroTherese TörngrenSara Torres-EsquiusAngela TossAlison H TrainerKatherine M TuckerChristi J van AsperenMarion T van MackelenberghLiliana VarescoGardenia Vargas-ParraRaymonda VaronAna VegaÁngela VelascoAnne-Sophie VesperAlessandra VielMaaike P G VreeswijkSebastian A WagnerAnke WahaLogan C WalkerRhiannon J WaltersShan Wang-GohrkeBernhard H F WeberWilko WeichertKerstin WielandLisa WiesmüllerIsabell WitzelAchim WöckelEmma Roisin WoodwardSilke ZachariaeValentina ZampigaChristine Zeder-Gößnull nullConxi LázaroArcangela De NicoloPaolo RadiceChristoph EngelRita K SchmutzlerDavid E GoldgarAmanda B Spurdle

Published in: Human mutation (2020)

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.