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Co-observation of germline pathogenic variants in breast cancer predisposition genes: Results from analysis of the BRIDGES sequencing dataset

  • Aimee L. Davidson
  • , Kyriaki Michailidou
  • , Michael T. Parsons
  • , The NBCS Collaborators
  • , kConFab Investigators
  • , Cristina Fortuno
  • , Manjeet K. Bolla
  • , Qin Wang
  • , Joe Dennis
  • , Marc Naven
  • , Mustapha Abubakar
  • , Thomas U. Ahearn
  • , M. Rosario Alonso
  • , Irene L. Andrulis
  • , Antonis C. Antoniou
  • , Päivi Auvinen
  • , Sabine Behrens
  • , Marina A. Bermisheva
  • , Natalia V. Bogdanova
  • , Stig E. Bojesen
  • Thomas Brüning, Helen J. Byers, Nicola J. Camp, Archie Campbell, Jose E. Castelao, Melissa H. Cessna, Jenny Chang-Claude, Anne Lise Børresen-Dale
  • Queensland Institute of Medical Research
  • Cyprus Institute of Neurology and Genetics
  • University of Cambridge
  • National Cancer Institute (Bethesda, Md)
  • Centro de Investigación Biomédica en Red de Cáncer (CIBERONC)
  • University of Toronto
  • University of Eastern Finland
  • German Cancer Research Center
  • Institute of Biochemistry and Genetics, Ufa Scientific Center RAS
  • Hannover Medical School
  • N.N. Alexandrov Research Institute of Oncology and Medical Radiology
  • Copenhagen University Hospital (Nordvest)
  • University of Copenhagen
  • Institute for Prevention and Occupational Medicine of the German Social Accident Insurance (IPA)
  • University of Manchester
  • University of Utah School of Medicine
  • University of Edinburgh
  • Complejo Hospitalario Universitario de Santiago
  • Primary Children's Medical Center
  • University Medical Center Hamburg-Eppendorf
  • Karolinska Institutet
  • University Hospital of South Manchester
  • Friedrich-Alexander University Erlangen-Nürnberg
  • Instituto de Investigación Sanitaria de Santiago de Compostela
  • Institute of Cancer Research (ICR), London
  • Health and Medical University

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)
47 Downloads (Pure)

Abstract

Co-observation of a gene variant with a pathogenic variant in another gene that explains the disease presentation has been designated as evidence against pathogenicity for commonly used variant classification guidelines. Multiple variant curation expert panels have specified, from consensus opinion, that this evidence type is not applicable for the classification of breast cancer predisposition gene variants. Statistical analysis of sequence data for 55,815 individuals diagnosed with breast cancer from the BRIDGES sequencing project was undertaken to formally assess the utility of co-observation data for germline variant classification. Our analysis included expected loss-of-function variants in 11 breast cancer predisposition genes and pathogenic missense variants in BRCA1, BRCA2, and TP53. We assessed whether co-observation of pathogenic variants in two different genes occurred more or less often than expected under the assumption of independence. Co-observation of pathogenic variants in each of BRCA1, BRCA2, and PALB2 with the remaining genes was less frequent than expected. This evidence for depletion remained after adjustment for age at diagnosis, study design (familial versus population-based), and country. Co-observation of a variant of uncertain significance in BRCA1, BRCA2, or PALB2 with a pathogenic variant in another breast cancer gene equated to supporting evidence against pathogenicity following criterion strength assignment based on the likelihood ratio and showed utility in reclassification of missense BRCA1 and BRCA2 variants identified in BRIDGES. Our approach has applicability for assessing the value of co-observation as a predictor of variant pathogenicity in other clinical contexts, including for gene-specific guidelines developed by ClinGen Variant Curation Expert Panels.

Original languageEnglish
Pages (from-to)2059-2069
Number of pages11
JournalAmerican Journal of Human Genetics
Volume111
Issue number9
DOIs
Publication statusPublished - 5 Sept 2024

Bibliographical note

Publisher Copyright:
© 2024 American Society of Human Genetics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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