TY - JOUR
T1 - Addition of a 161-SNP polygenic risk score to family history-based risk prediction
T2 - impact on clinical management in non-BRCA1/2 breast cancer families
AU - Lakeman, Inge M M
AU - Hilbers, Florentine S
AU - Rodríguez-Girondo, Mar
AU - Lee, Andrew
AU - Vreeswijk, Maaike P G
AU - Hollestelle, Antoinette
AU - Seynaeve, Caroline
AU - Meijers-Heijboer, Hanne
AU - Oosterwijk, Jan C
AU - Hoogerbrugge, Nicoline
AU - Olah, Edith
AU - Vasen, Hans F A
AU - van Asperen, Christi J
AU - Devilee, Peter
N1 - © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.
PY - 2019/9
Y1 - 2019/9
N2 - 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.
AB - 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.
U2 - 10.1136/jmedgenet-2019-106072
DO - 10.1136/jmedgenet-2019-106072
M3 - Article
C2 - 31186341
SN - 0022-2593
VL - 56
SP - 581
EP - 589
JO - Journal of Medical Genetics
JF - Journal of Medical Genetics
IS - 9
ER -