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

Inge M. M. Lakeman, Florentine S. Hilbers, Mar Rodríguez-Girondo, Andrew Lee, Maaike P. G. Vreeswijk, Antoinette Hollestelle, Caroline Seynaeve, Hanne Meijers-Heijboer, Jan C. Oosterwijk, Nicoline Hoogerbrugge, Edith Olah, Hans F. A. Vasen, Christi J. van Asperen, Peter Devilee

Research output: Contribution to journalArticleAcademicpeer-review

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.
Original languageEnglish
JournalJournal of Medical Genetics
DOIs
Publication statusPublished - 2019

Cite this

Lakeman, Inge M. M. ; Hilbers, Florentine S. ; Rodríguez-Girondo, Mar ; Lee, Andrew ; Vreeswijk, Maaike P. G. ; Hollestelle, Antoinette ; Seynaeve, Caroline ; Meijers-Heijboer, Hanne ; Oosterwijk, Jan C. ; Hoogerbrugge, Nicoline ; Olah, Edith ; Vasen, Hans F. A. ; van Asperen, Christi J. ; Devilee, Peter. / 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. In: Journal of Medical Genetics. 2019.
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title = "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",
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.",
author = "Lakeman, {Inge M. M.} and Hilbers, {Florentine S.} and Mar Rodr{\'i}guez-Girondo and Andrew Lee and Vreeswijk, {Maaike P. G.} and Antoinette Hollestelle and Caroline Seynaeve and Hanne Meijers-Heijboer and Oosterwijk, {Jan C.} and Nicoline Hoogerbrugge and Edith Olah and Vasen, {Hans F. A.} and {van Asperen}, {Christi J.} and Peter Devilee",
year = "2019",
doi = "10.1136/jmedgenet-2019-106072",
language = "English",
journal = "Journal of Medical Genetics",
issn = "0022-2593",
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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. / Lakeman, Inge M. M.; Hilbers, Florentine S.; Rodríguez-Girondo, Mar; Lee, Andrew; Vreeswijk, Maaike P. G.; Hollestelle, Antoinette; Seynaeve, Caroline; Meijers-Heijboer, Hanne; Oosterwijk, Jan C.; Hoogerbrugge, Nicoline; Olah, Edith; Vasen, Hans F. A.; van Asperen, Christi J.; Devilee, Peter.

In: Journal of Medical Genetics, 2019.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - 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

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

PY - 2019

Y1 - 2019

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.

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U2 - 10.1136/jmedgenet-2019-106072

DO - 10.1136/jmedgenet-2019-106072

M3 - Article

JO - Journal of Medical Genetics

JF - Journal of Medical Genetics

SN - 0022-2593

ER -