Clinical applicability of the Polygenic Risk Score for breast cancer risk prediction in familial cases

Inge M M Lakeman; Mar D M Rodríguez-Girondo; Andrew Lee; Nandi Celosse; Merel E Braspenning; Klaartje van Engelen; Irma van de Beek; Annemiek H van der Hout; Encarna B Gómez García; Arjen R Mensenkamp; Margreet G E M Ausems; Maartje J Hooning; Muriel A Adank; Antoinette Hollestelle; Marjanka K Schmidt; Christi J van Asperen; Peter Devilee

doi:10.1136/jmg-2022-108502

Clinical applicability of the Polygenic Risk Score for breast cancer risk prediction in familial cases

J Med Genet. 2023 Apr;60(4):327-336. doi: 10.1136/jmg-2022-108502. Epub 2022 Sep 22.

Authors

Inge M M Lakeman^{1

2}, Mar D M Rodríguez-Girondo³, Andrew Lee⁴, Nandi Celosse¹, Merel E Braspenning¹, Klaartje van Engelen⁵, Irma van de Beek⁵, Annemiek H van der Hout⁶, Encarna B Gómez García⁷, Arjen R Mensenkamp⁸, Margreet G E M Ausems⁹, Maartje J Hooning¹⁰, Muriel A Adank¹¹, Antoinette Hollestelle¹⁰, Marjanka K Schmidt^{2

12}, Christi J van Asperen², Peter Devilee^{13

14}

Affiliations

¹ Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands.
² Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands.
³ Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.
⁴ Public Health and Primary Care, University of Cambridge Centre for Cancer Genetic Epidemiology, Cambridge, UK.
⁵ Department of Human Genetics, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands.
⁶ Department of Clinical Genetics, University Medical Centre Groningen, Groningen, The Netherlands.
⁷ Department of Clinical Genetics, Maastricht University Medical Centre+, Maastricht, The Netherlands.
⁸ Department of Human Genetics, University Medical Center Nijmegen, Nijmegen, The Netherlands.
⁹ Department of Medical Genetics, University Medical Centre Utrecht, Utrecht, The Netherlands.
¹⁰ Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus Medical Center, Rotterdam, The Netherlands.
¹¹ Family Cancer Clinic, Antoni van Leeuwenhoek Netherlands Cancer Institute, Amsterdam, The Netherlands.
¹² Division of Psychosocial Research and Epidemiology, Antoni van Leeuwenhoek Netherlands Cancer Institute, Amsterdam, The Netherlands.
¹³ Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands p.devilee@lumc.nl.
¹⁴ Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands.

PMID: 36137616
DOI: 10.1136/jmg-2022-108502

Abstract

Background: Common low-risk variants are presently not used to guide clinical management of familial breast cancer (BC). We explored the additive impact of a 313-variant-based Polygenic Risk Score (PRS₃₁₃) relative to standard gene testing in non-BRCA1/2 Dutch BC families.

Methods: We included 3918 BC cases from 3492 Dutch non-BRCA1/2 BC families and 3474 Dutch population controls. The association of the standardised PRS₃₁₃ with BC was estimated using a logistic regression model, adjusted for pedigree-based family history. Family history of the controls was imputed for this analysis. SEs were corrected to account for relatedness of individuals. Using the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.5 model, lifetime risks were retrospectively calculated with and without individual PRS₃₁₃. For 2586 cases and 2584 controls, the carrier status of pathogenic variants (PVs) in ATM, CHEK2 and PALB2 was known.

Results: The family history-adjusted PRS₃₁₃ was significantly associated with BC (per SD OR=1.97, 95% CI 1.84 to 2.11). Including the PRS₃₁₃ in BOADICEA family-based risk prediction would have changed screening recommendations in up to 27%, 36% and 34% of cases according to BC screening guidelines from the USA, UK and the Netherlands (National Comprehensive Cancer Network, National Institute for Health and Care Excellence, and Netherlands Comprehensive Cancer Organisation), respectively. For the population controls, without information on family history, this was up to 39%, 44% and 58%, respectively. Among carriers of PVs in known moderate BC susceptibility genes, the PRS₃₁₃ had the largest impact for CHEK2 and ATM.

Conclusions: Our results support the application of the PRS₃₁₃ in risk prediction for genetically uninformative BC families and families with a PV in moderate BC risk genes.

Keywords: Genetic Predisposition to Disease; Medical Oncology; Polymorphism, Genetic.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Breast Neoplasms* / diagnosis
Breast Neoplasms* / epidemiology
Breast Neoplasms* / genetics
Female
Genetic Predisposition to Disease
Humans
Retrospective Studies
Risk Assessment / methods
Risk Factors