Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing

Melissa C. Southey, James G. Dowty, Moeen Riaz, Jason A. Steen, Anne Laure Renault, Katherine Tucker, Judy Kirk, Paul James, Ingrid Winship, Nicholas Pachter, Nicola Poplawski, Scott Grist, Daniel J. Park, Bernard J. Pope, Khalid Mahmood, Fleur Hammet, Maryam Mahmoodi, Helen Tsimiklis, Derrick Theys, Amanda RewseAmanda Willis, April Morrow, Catherine Speechly, Rebecca Harris, Robert Sebra, Eric Schadt, Paul Lacaze, John J. McNeil, Graham G. Giles, Roger L. Milne, John L. Hopper, Tú Nguyen-Dumont

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing are urgently required. Most prior research has been based on women selected for high-risk features and more data is needed to make inference about breast cancer risk for women unselected for family history, an important consideration of population screening. We tested 1464 women diagnosed with breast cancer and 862 age-matched controls participating in the Australian Breast Cancer Family Study (ABCFS), and 6549 healthy, older Australian women enroled in the ASPirin in Reducing Events in the Elderly (ASPREE) study for rare germline variants using a 24-gene-panel. Odds ratios (ORs) were estimated using unconditional logistic regression adjusted for age and other potential confounders. We identified pathogenic variants in 11.1% of the ABCFS cases, 3.7% of the ABCFS controls and 2.2% of the ASPREE (control) participants. The estimated breast cancer OR [95% confidence interval] was 5.3 [2.1–16.2] for BRCA1, 4.0 [1.9–9.1] for BRCA2, 3.4 [1.4–8.4] for ATM and 4.3 [1.0–17.0] for PALB2. Our findings provide a population-based perspective to gene-panel testing for breast cancer predisposition and opportunities to improve predictors for identifying women who carry pathogenic variants in breast cancer predisposition genes.

Original languageEnglish
Article number153
Number of pages7
Journalnpj Breast Cancer
Volume7
Issue number1
DOIs
Publication statusPublished - Dec 2021
Externally publishedYes

Keywords

  • Population-based modelling
  • breast cancer risk
  • gene-panel testing
  • pathogenic variants
  • genetic predisposition to disease

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