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J Med Genet. 2019 Sep;56(9):581-589. doi: 10.1136/jmedgenet-2019-106072. Epub 2019 Jun 11.

Addition of a 161-SNP polygenic risk score to family history-based risk prediction: impact on clinical management in non-BRCA1/2 breast cancer families.

Author information

1
Department of Human Genetics, Leids Universitair Medisch Centrum, Leiden, The Netherlands.
2
Breast International Group (BIG), Brussels, Belgium.
3
Department of Medical Statistics and Bioinformatics, Leids Universitair Medisch Centrum, Leiden, The Netherlands.
4
Public Health and Primary Care, Centre for Cancer Gentic Epidemiology, Cambridge University, Cambridge, UK.
5
Department of Medical Oncology, Erasmus MC Kanker Instituut, Rotterdam, The Netherlands.
6
Department of Clinical Genetics, VU medisch centrum, Amsterdam, The Netherlands.
7
Department of Genetics, Universitair Medisch Centrum Groningen, Groningen, The Netherlands.
8
Department of Human Genetics, Universitair Medisch Centrum Sint Radboud, Nijmegen, The Netherlands.
9
Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary.
10
Department of Gastroenterology and Hepatology, Leids Universitair Medisch Centrum, Leiden, The Netherlands.
11
Department of Clinical Genetics, Leids Universitair Medisch Centrum, Leiden, The Netherlands.
12
Department of Human Genetics, Leids Universitair Medisch Centrum, Leiden, The Netherlands p.devilee@lumc.nl.
13
Department of Pathology, Leids Universitair Medisch Centrum, Leiden, The Netherlands.
#
Contributed equally

Abstract

BACKGROUND:

The currently known breast cancer-associated single nucleotide polymorphisms (SNPs) are presently not used to guide clinical management. We explored whether a genetic test that incorporates a SNP-based polygenic risk score (PRS) is clinically meaningful in non-BRCA1/2 high-risk breast cancer families.

METHODS:

101 non-BRCA1/2 high-risk breast cancer families were included; 323 cases and 262 unaffected female relatives were genotyped. The 161-SNP PRS was calculated and standardised to 327 population controls (sPRS). Association analysis was performed using a Cox-type random effect regression model adjusted by family history. Updated individualised breast cancer lifetime risk scores were derived by combining the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm breast cancer lifetime risk with the effect of the sPRS.

RESULTS:

The mean sPRS for cases and their unaffected relatives was 0.70 (SD=0.9) and 0.53 (SD=0.9), respectively. A significant association was found between sPRS and breast cancer, HR=1.16, 95% CI 1.03 to 1.28, p=0.026. Addition of the sPRS to risk prediction based on family history alone changed screening recommendations in 11.5%, 14.7% and 19.8 % of the women according to breast screening guidelines from the USA (National Comprehensive Cancer Network), UK (National Institute for Health and Care Excellence and the Netherlands (Netherlands Comprehensive Cancer Organisation), respectively.

CONCLUSION:

Our results support the application of the PRS in risk prediction and clinical management of women from genetically unexplained breast cancer families.

KEYWORDS:

cancer: breast; clinical genetics; genetic epidemiology; genetic screening/counselling; polygenic risk score

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