Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.

Elisha Hughes; Susanne Wagner; Dmitry Pruss; Ryan Bernhisel; Braden Probst; Victor Abkevich; Timothy Simmons; Brooke Hullinger; Thaddeus Judkins; Eric Rosenthal; Benjamin Roa; Susan M Domchek; Charis Eng; Judy Garber; Monique Gary; Jennifer Klemp; Semanti Mukherjee; Kenneth Offit; Olufunmilayo I Olopade; Joseph Vijai; Jeffrey N Weitzel; Pat Whitworth; Lamis Yehia; Ora K Gordon; Holly Pederson; Allison Kurian; Thomas P Slavin; Alexander Gutin; Jerry S Lanchbury

Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.

Elisha Hughes, Susanne Wagner, Dmitry Pruss, Ryan Bernhisel, Braden Probst, Victor Abkevich, Timothy Simmons, Brooke Hullinger, Thaddeus Judkins, Eric Rosenthal, Benjamin Roa, Susan M Domchek, Charis Eng, Judy Garber, Monique Gary, Jennifer Klemp, Semanti Mukherjee, Kenneth Offit, Olufunmilayo I Olopade, Joseph VijaiJeffrey N Weitzel, Pat Whitworth, Lamis Yehia, Ora K Gordon, Holly Pederson, Allison Kurian, Thomas P Slavin, Alexander Gutin, Jerry S Lanchbury

Research output: Contribution to journal › Article

Abstract

PURPOSE: Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases.

MATERIALS AND METHODS: Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution.

RESULTS: In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46;

CONCLUSION: The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.

Original language	Undefined/Unknown
Journal	Articles, Abstracts, and Reports
State	Published - Nov 1 2022

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http://digitalcommons.providence.org/publications/6830

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Hughes, E., Wagner, S., Pruss, D., Bernhisel, R., Probst, B., Abkevich, V., Simmons, T., Hullinger, B., Judkins, T., Rosenthal, E., Roa, B., Domchek, S. M., Eng, C., Garber, J., Gary, M., Klemp, J., Mukherjee, S., Offit, K., Olopade, O. I., ... Lanchbury, J. S. (2022). Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition. Articles, Abstracts, and Reports. http://digitalcommons.providence.org/publications/6830

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title = "Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.",

abstract = "PURPOSE: Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS: Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS: In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; CONCLUSION: The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.",

author = "Elisha Hughes and Susanne Wagner and Dmitry Pruss and Ryan Bernhisel and Braden Probst and Victor Abkevich and Timothy Simmons and Brooke Hullinger and Thaddeus Judkins and Eric Rosenthal and Benjamin Roa and Domchek, {Susan M} and Charis Eng and Judy Garber and Monique Gary and Jennifer Klemp and Semanti Mukherjee and Kenneth Offit and Olopade, {Olufunmilayo I} and Joseph Vijai and Weitzel, {Jeffrey N} and Pat Whitworth and Lamis Yehia and Gordon, {Ora K} and Holly Pederson and Allison Kurian and Slavin, {Thomas P} and Alexander Gutin and Lanchbury, {Jerry S}",

year = "2022",

month = nov,

day = "1",

language = "Undefined/Unknown",

journal = "Articles, Abstracts, and Reports",

}

Hughes, E, Wagner, S, Pruss, D, Bernhisel, R, Probst, B, Abkevich, V, Simmons, T, Hullinger, B, Judkins, T, Rosenthal, E, Roa, B, Domchek, SM, Eng, C, Garber, J, Gary, M, Klemp, J, Mukherjee, S, Offit, K, Olopade, OI, Vijai, J, Weitzel, JN, Whitworth, P, Yehia, L, Gordon, OK, Pederson, H, Kurian, A, Slavin, TP, Gutin, A & Lanchbury, JS 2022, 'Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.', Articles, Abstracts, and Reports. <http://digitalcommons.providence.org/publications/6830>

TY - JOUR

T1 - Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition.

AU - Hughes, Elisha

AU - Wagner, Susanne

AU - Pruss, Dmitry

AU - Bernhisel, Ryan

AU - Probst, Braden

AU - Abkevich, Victor

AU - Simmons, Timothy

AU - Hullinger, Brooke

AU - Judkins, Thaddeus

AU - Rosenthal, Eric

AU - Roa, Benjamin

AU - Domchek, Susan M

AU - Eng, Charis

AU - Garber, Judy

AU - Gary, Monique

AU - Klemp, Jennifer

AU - Mukherjee, Semanti

AU - Offit, Kenneth

AU - Olopade, Olufunmilayo I

AU - Vijai, Joseph

AU - Weitzel, Jeffrey N

AU - Whitworth, Pat

AU - Yehia, Lamis

AU - Gordon, Ora K

AU - Pederson, Holly

AU - Kurian, Allison

AU - Slavin, Thomas P

AU - Gutin, Alexander

AU - Lanchbury, Jerry S

PY - 2022/11/1

Y1 - 2022/11/1

N2 - PURPOSE: Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS: Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS: In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; CONCLUSION: The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.

AB - PURPOSE: Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS: Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS: In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; CONCLUSION: The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.

M3 - Article

JO - Articles, Abstracts, and Reports

JF - Articles, Abstracts, and Reports

ER -