Polygenic risk scores for prediction of breast cancer risk in Asian populations
Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups. The de...
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Veröffentlicht in: | Genetics in medicine 2022-03, Vol.24 (3), p.586-600 |
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creator | Ho, Weang-Kee Tai, Mei-Chee Dennis, Joe Shu, Xiang Li, Jingmei Ho, Peh Joo Millwood, Iona Y. Lin, Kuang Jee, Yon-Ho Lee, Su-Hyun Mavaddat, Nasim Bolla, Manjeet K. Wang, Qin Michailidou, Kyriaki Long, Jirong Wijaya, Eldarina Azfar Hassan, Tiara Rahmat, Kartini Tan, Veronique Kiak Mien Tan, Benita Kiat Tee Tan, Su Ming Tan, Ern Yu Lim, Swee Ho Gao, Yu-Tang Zheng, Ying Kang, Daehee Choi, Ji-Yeob Han, Wonshik Lee, Han-Byoel Kubo, Michiki Okada, Yukinori Namba, Shinichi Park, Sue K. Kim, Sung-Won Shen, Chen-Yang Wu, Pei-Ei Park, Boyoung Muir, Kenneth R. Lophatananon, Artitaya Wu, Anna H. Tseng, Chiu-Chen Matsuo, Keitaro Ito, Hidemi Kwong, Ava Chan, Tsun L. John, Esther M. Kurian, Allison W. Iwasaki, Motoki Yamaji, Taiki Kweon, Sun-Seog Aronson, Kristan J. Murphy, Rachel A. Koh, Woon-Puay Khor, Chiea-Chuen Yuan, Jian-Min Dorajoo, Rajkumar Walters, Robin G. Chen, Zhengming Li, Liming Lv, Jun Jung, Keum-Ji Kraft, Peter Pharoah, Paul D.B. Dunning, Alison M. Simard, Jacques Shu, Xiao-Ou Yip, Cheng-Har Taib, Nur Aishah Mohd Antoniou, Antonis C. Zheng, Wei Hartman, Mikael Easton, Douglas F. Teo, Soo-Hwang |
description | Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.
The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry. |
doi_str_mv | 10.1016/j.gim.2021.11.008 |
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The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.</description><identifier>ISSN: 1098-3600</identifier><identifier>ISSN: 1530-0366</identifier><identifier>EISSN: 1530-0366</identifier><identifier>DOI: 10.1016/j.gim.2021.11.008</identifier><identifier>PMID: 34906514</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Bayes Theorem ; Breast cancer ; Breast Neoplasms - epidemiology ; Breast Neoplasms - genetics ; Female ; Genetic ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Multifactorial Inheritance - genetics ; Polygenic risk score ; Polymorphism, Single Nucleotide - genetics ; Prospective Studies ; Risk Factors ; Risk prediction</subject><ispartof>Genetics in medicine, 2022-03, Vol.24 (3), p.586-600</ispartof><rights>2021 American College of Medical Genetics and Genomics</rights><rights>Copyright © 2021 American College of Medical Genetics and Genomics. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c517t-bd618d77e501270d56e47922e9cc53dc6bda5ce4a65b3034f020066bc433ace93</citedby><cites>FETCH-LOGICAL-c517t-bd618d77e501270d56e47922e9cc53dc6bda5ce4a65b3034f020066bc433ace93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,315,781,785,886,27929,27930</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34906514$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ho, Weang-Kee</creatorcontrib><creatorcontrib>Tai, Mei-Chee</creatorcontrib><creatorcontrib>Dennis, Joe</creatorcontrib><creatorcontrib>Shu, Xiang</creatorcontrib><creatorcontrib>Li, Jingmei</creatorcontrib><creatorcontrib>Ho, Peh Joo</creatorcontrib><creatorcontrib>Millwood, Iona Y.</creatorcontrib><creatorcontrib>Lin, Kuang</creatorcontrib><creatorcontrib>Jee, Yon-Ho</creatorcontrib><creatorcontrib>Lee, Su-Hyun</creatorcontrib><creatorcontrib>Mavaddat, Nasim</creatorcontrib><creatorcontrib>Bolla, Manjeet K.</creatorcontrib><creatorcontrib>Wang, Qin</creatorcontrib><creatorcontrib>Michailidou, Kyriaki</creatorcontrib><creatorcontrib>Long, Jirong</creatorcontrib><creatorcontrib>Wijaya, Eldarina Azfar</creatorcontrib><creatorcontrib>Hassan, Tiara</creatorcontrib><creatorcontrib>Rahmat, Kartini</creatorcontrib><creatorcontrib>Tan, Veronique Kiak Mien</creatorcontrib><creatorcontrib>Tan, Benita Kiat Tee</creatorcontrib><creatorcontrib>Tan, Su Ming</creatorcontrib><creatorcontrib>Tan, Ern Yu</creatorcontrib><creatorcontrib>Lim, Swee Ho</creatorcontrib><creatorcontrib>Gao, Yu-Tang</creatorcontrib><creatorcontrib>Zheng, Ying</creatorcontrib><creatorcontrib>Kang, Daehee</creatorcontrib><creatorcontrib>Choi, Ji-Yeob</creatorcontrib><creatorcontrib>Han, Wonshik</creatorcontrib><creatorcontrib>Lee, Han-Byoel</creatorcontrib><creatorcontrib>Kubo, Michiki</creatorcontrib><creatorcontrib>Okada, Yukinori</creatorcontrib><creatorcontrib>Namba, Shinichi</creatorcontrib><creatorcontrib>Park, Sue K.</creatorcontrib><creatorcontrib>Kim, Sung-Won</creatorcontrib><creatorcontrib>Shen, Chen-Yang</creatorcontrib><creatorcontrib>Wu, Pei-Ei</creatorcontrib><creatorcontrib>Park, Boyoung</creatorcontrib><creatorcontrib>Muir, Kenneth R.</creatorcontrib><creatorcontrib>Lophatananon, Artitaya</creatorcontrib><creatorcontrib>Wu, Anna H.</creatorcontrib><creatorcontrib>Tseng, Chiu-Chen</creatorcontrib><creatorcontrib>Matsuo, Keitaro</creatorcontrib><creatorcontrib>Ito, Hidemi</creatorcontrib><creatorcontrib>Kwong, Ava</creatorcontrib><creatorcontrib>Chan, Tsun L.</creatorcontrib><creatorcontrib>John, Esther M.</creatorcontrib><creatorcontrib>Kurian, Allison W.</creatorcontrib><creatorcontrib>Iwasaki, Motoki</creatorcontrib><creatorcontrib>Yamaji, Taiki</creatorcontrib><creatorcontrib>Kweon, Sun-Seog</creatorcontrib><creatorcontrib>Aronson, Kristan J.</creatorcontrib><creatorcontrib>Murphy, Rachel A.</creatorcontrib><creatorcontrib>Koh, Woon-Puay</creatorcontrib><creatorcontrib>Khor, Chiea-Chuen</creatorcontrib><creatorcontrib>Yuan, Jian-Min</creatorcontrib><creatorcontrib>Dorajoo, Rajkumar</creatorcontrib><creatorcontrib>Walters, Robin G.</creatorcontrib><creatorcontrib>Chen, Zhengming</creatorcontrib><creatorcontrib>Li, Liming</creatorcontrib><creatorcontrib>Lv, Jun</creatorcontrib><creatorcontrib>Jung, Keum-Ji</creatorcontrib><creatorcontrib>Kraft, Peter</creatorcontrib><creatorcontrib>Pharoah, Paul D.B.</creatorcontrib><creatorcontrib>Dunning, Alison M.</creatorcontrib><creatorcontrib>Simard, Jacques</creatorcontrib><creatorcontrib>Shu, Xiao-Ou</creatorcontrib><creatorcontrib>Yip, Cheng-Har</creatorcontrib><creatorcontrib>Taib, Nur Aishah Mohd</creatorcontrib><creatorcontrib>Antoniou, Antonis C.</creatorcontrib><creatorcontrib>Zheng, Wei</creatorcontrib><creatorcontrib>Hartman, Mikael</creatorcontrib><creatorcontrib>Easton, Douglas F.</creatorcontrib><creatorcontrib>Teo, Soo-Hwang</creatorcontrib><creatorcontrib>The BioBank Japan Project</creatorcontrib><creatorcontrib>BioBank Japan Project</creatorcontrib><title>Polygenic risk scores for prediction of breast cancer risk in Asian populations</title><title>Genetics in medicine</title><addtitle>Genet Med</addtitle><description>Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.
The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.</description><subject>Bayes Theorem</subject><subject>Breast cancer</subject><subject>Breast Neoplasms - epidemiology</subject><subject>Breast Neoplasms - genetics</subject><subject>Female</subject><subject>Genetic</subject><subject>Genetic Predisposition to Disease</subject><subject>Genome-Wide Association Study</subject><subject>Humans</subject><subject>Multifactorial Inheritance - genetics</subject><subject>Polygenic risk score</subject><subject>Polymorphism, Single Nucleotide - genetics</subject><subject>Prospective Studies</subject><subject>Risk Factors</subject><subject>Risk 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Y.</creator><creator>Lin, Kuang</creator><creator>Jee, Yon-Ho</creator><creator>Lee, Su-Hyun</creator><creator>Mavaddat, Nasim</creator><creator>Bolla, Manjeet K.</creator><creator>Wang, Qin</creator><creator>Michailidou, Kyriaki</creator><creator>Long, Jirong</creator><creator>Wijaya, Eldarina Azfar</creator><creator>Hassan, Tiara</creator><creator>Rahmat, Kartini</creator><creator>Tan, Veronique Kiak Mien</creator><creator>Tan, Benita Kiat Tee</creator><creator>Tan, Su Ming</creator><creator>Tan, Ern Yu</creator><creator>Lim, Swee Ho</creator><creator>Gao, Yu-Tang</creator><creator>Zheng, Ying</creator><creator>Kang, Daehee</creator><creator>Choi, Ji-Yeob</creator><creator>Han, Wonshik</creator><creator>Lee, Han-Byoel</creator><creator>Kubo, Michiki</creator><creator>Okada, Yukinori</creator><creator>Namba, Shinichi</creator><creator>Park, Sue K.</creator><creator>Kim, Sung-Won</creator><creator>Shen, Chen-Yang</creator><creator>Wu, Pei-Ei</creator><creator>Park, 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Ern Yu ; Lim, Swee Ho ; Gao, Yu-Tang ; Zheng, Ying ; Kang, Daehee ; Choi, Ji-Yeob ; Han, Wonshik ; Lee, Han-Byoel ; Kubo, Michiki ; Okada, Yukinori ; Namba, Shinichi ; Park, Sue K. ; Kim, Sung-Won ; Shen, Chen-Yang ; Wu, Pei-Ei ; Park, Boyoung ; Muir, Kenneth R. ; Lophatananon, Artitaya ; Wu, Anna H. ; Tseng, Chiu-Chen ; Matsuo, Keitaro ; Ito, Hidemi ; Kwong, Ava ; Chan, Tsun L. ; John, Esther M. ; Kurian, Allison W. ; Iwasaki, Motoki ; Yamaji, Taiki ; Kweon, Sun-Seog ; Aronson, Kristan J. ; Murphy, Rachel A. ; Koh, Woon-Puay ; Khor, Chiea-Chuen ; Yuan, Jian-Min ; Dorajoo, Rajkumar ; Walters, Robin G. ; Chen, Zhengming ; Li, Liming ; Lv, Jun ; Jung, Keum-Ji ; Kraft, Peter ; Pharoah, Paul D.B. ; Dunning, Alison M. ; Simard, Jacques ; Shu, Xiao-Ou ; Yip, Cheng-Har ; Taib, Nur Aishah Mohd ; Antoniou, Antonis C. ; Zheng, Wei ; Hartman, Mikael ; Easton, Douglas F. ; Teo, Soo-Hwang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c517t-bd618d77e501270d56e47922e9cc53dc6bda5ce4a65b3034f020066bc433ace93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Bayes Theorem</topic><topic>Breast cancer</topic><topic>Breast Neoplasms - epidemiology</topic><topic>Breast Neoplasms - genetics</topic><topic>Female</topic><topic>Genetic</topic><topic>Genetic Predisposition to Disease</topic><topic>Genome-Wide Association Study</topic><topic>Humans</topic><topic>Multifactorial Inheritance - genetics</topic><topic>Polygenic risk score</topic><topic>Polymorphism, Single Nucleotide - genetics</topic><topic>Prospective Studies</topic><topic>Risk Factors</topic><topic>Risk prediction</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ho, Weang-Kee</creatorcontrib><creatorcontrib>Tai, Mei-Chee</creatorcontrib><creatorcontrib>Dennis, Joe</creatorcontrib><creatorcontrib>Shu, Xiang</creatorcontrib><creatorcontrib>Li, Jingmei</creatorcontrib><creatorcontrib>Ho, Peh Joo</creatorcontrib><creatorcontrib>Millwood, Iona Y.</creatorcontrib><creatorcontrib>Lin, Kuang</creatorcontrib><creatorcontrib>Jee, Yon-Ho</creatorcontrib><creatorcontrib>Lee, Su-Hyun</creatorcontrib><creatorcontrib>Mavaddat, Nasim</creatorcontrib><creatorcontrib>Bolla, Manjeet K.</creatorcontrib><creatorcontrib>Wang, Qin</creatorcontrib><creatorcontrib>Michailidou, Kyriaki</creatorcontrib><creatorcontrib>Long, Jirong</creatorcontrib><creatorcontrib>Wijaya, Eldarina Azfar</creatorcontrib><creatorcontrib>Hassan, Tiara</creatorcontrib><creatorcontrib>Rahmat, Kartini</creatorcontrib><creatorcontrib>Tan, Veronique Kiak Mien</creatorcontrib><creatorcontrib>Tan, Benita Kiat Tee</creatorcontrib><creatorcontrib>Tan, Su Ming</creatorcontrib><creatorcontrib>Tan, Ern Yu</creatorcontrib><creatorcontrib>Lim, Swee Ho</creatorcontrib><creatorcontrib>Gao, Yu-Tang</creatorcontrib><creatorcontrib>Zheng, Ying</creatorcontrib><creatorcontrib>Kang, Daehee</creatorcontrib><creatorcontrib>Choi, Ji-Yeob</creatorcontrib><creatorcontrib>Han, Wonshik</creatorcontrib><creatorcontrib>Lee, Han-Byoel</creatorcontrib><creatorcontrib>Kubo, Michiki</creatorcontrib><creatorcontrib>Okada, Yukinori</creatorcontrib><creatorcontrib>Namba, Shinichi</creatorcontrib><creatorcontrib>Park, Sue K.</creatorcontrib><creatorcontrib>Kim, Sung-Won</creatorcontrib><creatorcontrib>Shen, Chen-Yang</creatorcontrib><creatorcontrib>Wu, Pei-Ei</creatorcontrib><creatorcontrib>Park, Boyoung</creatorcontrib><creatorcontrib>Muir, Kenneth R.</creatorcontrib><creatorcontrib>Lophatananon, Artitaya</creatorcontrib><creatorcontrib>Wu, Anna H.</creatorcontrib><creatorcontrib>Tseng, Chiu-Chen</creatorcontrib><creatorcontrib>Matsuo, Keitaro</creatorcontrib><creatorcontrib>Ito, Hidemi</creatorcontrib><creatorcontrib>Kwong, Ava</creatorcontrib><creatorcontrib>Chan, Tsun L.</creatorcontrib><creatorcontrib>John, Esther M.</creatorcontrib><creatorcontrib>Kurian, Allison W.</creatorcontrib><creatorcontrib>Iwasaki, Motoki</creatorcontrib><creatorcontrib>Yamaji, Taiki</creatorcontrib><creatorcontrib>Kweon, Sun-Seog</creatorcontrib><creatorcontrib>Aronson, Kristan J.</creatorcontrib><creatorcontrib>Murphy, Rachel A.</creatorcontrib><creatorcontrib>Koh, Woon-Puay</creatorcontrib><creatorcontrib>Khor, Chiea-Chuen</creatorcontrib><creatorcontrib>Yuan, Jian-Min</creatorcontrib><creatorcontrib>Dorajoo, Rajkumar</creatorcontrib><creatorcontrib>Walters, Robin G.</creatorcontrib><creatorcontrib>Chen, Zhengming</creatorcontrib><creatorcontrib>Li, Liming</creatorcontrib><creatorcontrib>Lv, Jun</creatorcontrib><creatorcontrib>Jung, Keum-Ji</creatorcontrib><creatorcontrib>Kraft, Peter</creatorcontrib><creatorcontrib>Pharoah, Paul D.B.</creatorcontrib><creatorcontrib>Dunning, Alison M.</creatorcontrib><creatorcontrib>Simard, Jacques</creatorcontrib><creatorcontrib>Shu, Xiao-Ou</creatorcontrib><creatorcontrib>Yip, Cheng-Har</creatorcontrib><creatorcontrib>Taib, Nur Aishah Mohd</creatorcontrib><creatorcontrib>Antoniou, Antonis C.</creatorcontrib><creatorcontrib>Zheng, Wei</creatorcontrib><creatorcontrib>Hartman, Mikael</creatorcontrib><creatorcontrib>Easton, Douglas F.</creatorcontrib><creatorcontrib>Teo, Soo-Hwang</creatorcontrib><creatorcontrib>The BioBank Japan Project</creatorcontrib><creatorcontrib>BioBank Japan Project</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Genetics in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ho, Weang-Kee</au><au>Tai, Mei-Chee</au><au>Dennis, Joe</au><au>Shu, Xiang</au><au>Li, Jingmei</au><au>Ho, Peh Joo</au><au>Millwood, Iona Y.</au><au>Lin, Kuang</au><au>Jee, Yon-Ho</au><au>Lee, Su-Hyun</au><au>Mavaddat, Nasim</au><au>Bolla, Manjeet K.</au><au>Wang, Qin</au><au>Michailidou, Kyriaki</au><au>Long, Jirong</au><au>Wijaya, Eldarina Azfar</au><au>Hassan, Tiara</au><au>Rahmat, Kartini</au><au>Tan, Veronique Kiak Mien</au><au>Tan, Benita Kiat Tee</au><au>Tan, Su Ming</au><au>Tan, Ern Yu</au><au>Lim, Swee Ho</au><au>Gao, Yu-Tang</au><au>Zheng, Ying</au><au>Kang, Daehee</au><au>Choi, Ji-Yeob</au><au>Han, Wonshik</au><au>Lee, Han-Byoel</au><au>Kubo, Michiki</au><au>Okada, Yukinori</au><au>Namba, Shinichi</au><au>Park, Sue K.</au><au>Kim, Sung-Won</au><au>Shen, Chen-Yang</au><au>Wu, Pei-Ei</au><au>Park, Boyoung</au><au>Muir, Kenneth R.</au><au>Lophatananon, Artitaya</au><au>Wu, Anna H.</au><au>Tseng, Chiu-Chen</au><au>Matsuo, Keitaro</au><au>Ito, Hidemi</au><au>Kwong, Ava</au><au>Chan, Tsun L.</au><au>John, Esther M.</au><au>Kurian, Allison W.</au><au>Iwasaki, Motoki</au><au>Yamaji, Taiki</au><au>Kweon, Sun-Seog</au><au>Aronson, Kristan J.</au><au>Murphy, Rachel A.</au><au>Koh, Woon-Puay</au><au>Khor, Chiea-Chuen</au><au>Yuan, Jian-Min</au><au>Dorajoo, Rajkumar</au><au>Walters, Robin G.</au><au>Chen, Zhengming</au><au>Li, Liming</au><au>Lv, Jun</au><au>Jung, Keum-Ji</au><au>Kraft, Peter</au><au>Pharoah, Paul D.B.</au><au>Dunning, Alison M.</au><au>Simard, Jacques</au><au>Shu, Xiao-Ou</au><au>Yip, Cheng-Har</au><au>Taib, Nur Aishah Mohd</au><au>Antoniou, Antonis C.</au><au>Zheng, Wei</au><au>Hartman, Mikael</au><au>Easton, Douglas F.</au><au>Teo, Soo-Hwang</au><aucorp>The BioBank Japan Project</aucorp><aucorp>BioBank Japan Project</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Polygenic risk scores for prediction of breast cancer risk in Asian populations</atitle><jtitle>Genetics in medicine</jtitle><addtitle>Genet Med</addtitle><date>2022-03-01</date><risdate>2022</risdate><volume>24</volume><issue>3</issue><spage>586</spage><epage>600</epage><pages>586-600</pages><issn>1098-3600</issn><issn>1530-0366</issn><eissn>1530-0366</eissn><abstract>Non-European populations are under-represented in genetics studies, hindering clinical implementation of breast cancer polygenic risk scores (PRSs). We aimed to develop PRSs using the largest available studies of Asian ancestry and to assess the transferability of PRS across ethnic subgroups.
The development data set comprised 138,309 women from 17 case-control studies. PRSs were generated using a clumping and thresholding method, lasso penalized regression, an Empirical Bayes approach, a Bayesian polygenic prediction approach, or linear combinations of multiple PRSs. These PRSs were evaluated in 89,898 women from 3 prospective studies (1592 incident cases).
The best performing PRS (genome-wide set of single-nucleotide variations [formerly single-nucleotide polymorphism]) had a hazard ratio per unit SD of 1.62 (95% CI = 1.46-1.80) and an area under the receiver operating curve of 0.635 (95% CI = 0.622-0.649). Combined Asian and European PRSs (333 single-nucleotide variations) had a hazard ratio per SD of 1.53 (95% CI = 1.37-1.71) and an area under the receiver operating curve of 0.621 (95% CI = 0.608-0.635). The distribution of the latter PRS was different across ethnic subgroups, confirming the importance of population-specific calibration for valid estimation of breast cancer risk.
PRSs developed in this study, from association data from multiple ancestries, can enhance risk stratification for women of Asian ancestry.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>34906514</pmid><doi>10.1016/j.gim.2021.11.008</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1098-3600 |
ispartof | Genetics in medicine, 2022-03, Vol.24 (3), p.586-600 |
issn | 1098-3600 1530-0366 1530-0366 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7612481 |
source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
subjects | Bayes Theorem Breast cancer Breast Neoplasms - epidemiology Breast Neoplasms - genetics Female Genetic Genetic Predisposition to Disease Genome-Wide Association Study Humans Multifactorial Inheritance - genetics Polygenic risk score Polymorphism, Single Nucleotide - genetics Prospective Studies Risk Factors Risk prediction |
title | Polygenic risk scores for prediction of breast cancer risk in Asian populations |
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