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
Hauptverfasser: 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
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container_title Genetics in medicine
container_volume 24
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
format Article
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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><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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Xiao-Ou</creator><creator>Yip, Cheng-Har</creator><creator>Taib, Nur Aishah Mohd</creator><creator>Antoniou, Antonis C.</creator><creator>Zheng, Wei</creator><creator>Hartman, Mikael</creator><creator>Easton, Douglas F.</creator><creator>Teo, Soo-Hwang</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20220301</creationdate><title>Polygenic risk scores for prediction of breast cancer risk in Asian populations</title><author>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</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>
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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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