Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

Jie Ping; Guochong Jia; Qiuyin Cai; Xingyi Guo; Ran Tao; Christine Ambrosone; Dezheng Huo; Stefan Ambs; Mollie E. Barnard; Yu Chen; Montserrat Garcia-Closas; Jian Gu; Jennifer J. Hu; Esther M. John; Christopher I. Li; Katherine Nathanson; Barbara Nemesure; Olufunmilayo I. Olopade; Tuya Pal; Michael F. Press; Maureen Sanderson; Dale P. Sandler; Toshio Yoshimatsu; Prisca O. Adejumo; Thomas Ahearn; Abenaa M. Brewster; Anselm J.M. Hennis; Timothy Makumbi; Paul Ndom; Katie M. O’Brien; Andrew F. Olshan; Mojisola M. Oluwasanu; Sonya Reid; Song Yao; Ebonee N. Butler; Maosheng Huang; Atara Ntekim; Bingshan Li; Melissa A. Troester; Julie R. Palmer; Christopher A. Haiman; Jirong Long; Wei Zheng

doi:10.1038/s41467-024-47650-5

Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

Jie Ping, Guochong Jia, Qiuyin Cai, Xingyi Guo, Ran Tao, Christine Ambrosone, Dezheng Huo, Stefan Ambs, Mollie E. Barnard, Yu Chen, Montserrat Garcia-Closas, Jian Gu, Jennifer J. Hu, Esther M. John, Christopher I. Li, Katherine Nathanson, Barbara Nemesure, Olufunmilayo I. Olopade, Tuya Pal, Michael F. PressMaureen Sanderson, Dale P. Sandler, Toshio Yoshimatsu, Prisca O. Adejumo, Thomas Ahearn, Abenaa M. Brewster, Anselm J.M. Hennis, Timothy Makumbi, Paul Ndom, Katie M. O’Brien, Andrew F. Olshan, Mojisola M. Oluwasanu, Sonya Reid, Song Yao, Ebonee N. Butler, Maosheng Huang, Atara Ntekim, Bingshan Li, Melissa A. Troester, Julie R. Palmer, Christopher A. Haiman, Jirong Long, Wei Zheng

Urban Initiative

Research output: Contribution to journal › Article › peer-review

Abstract

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

Original language	English (US)
Article number	3718
Journal	Nature communications
Volume	15
Issue number	1
DOIs	https://doi.org/10.1038/s41467-024-47650-5
State	Published - Dec 2024

ASJC Scopus subject areas

General Chemistry
General Biochemistry, Genetics and Molecular Biology
General Physics and Astronomy

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10.1038/s41467-024-47650-5

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Ping, J., Jia, G., Cai, Q., Guo, X., Tao, R., Ambrosone, C., Huo, D., Ambs, S., Barnard, M. E., Chen, Y., Garcia-Closas, M., Gu, J., Hu, J. J., John, E. M., Li, C. I., Nathanson, K., Nemesure, B., Olopade, O. I., Pal, T., ... Zheng, W. (2024). Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes. Nature communications, 15(1), Article 3718. https://doi.org/10.1038/s41467-024-47650-5

Ping, J, Jia, G, Cai, Q, Guo, X, Tao, R, Ambrosone, C, Huo, D, Ambs, S, Barnard, ME, Chen, Y, Garcia-Closas, M, Gu, J, Hu, JJ, John, EM, Li, CI, Nathanson, K, Nemesure, B, Olopade, OI, Pal, T, Press, MF, Sanderson, M, Sandler, DP, Yoshimatsu, T, Adejumo, PO, Ahearn, T, Brewster, AM, Hennis, AJM, Makumbi, T, Ndom, P, O’Brien, KM, Olshan, AF, Oluwasanu, MM, Reid, S, Yao, S, Butler, EN, Huang, M, Ntekim, A, Li, B, Troester, MA, Palmer, JR, Haiman, CA, Long, J & Zheng, W 2024, 'Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes', Nature communications, vol. 15, no. 1, 3718. https://doi.org/10.1038/s41467-024-47650-5

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title = "Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes",

abstract = "African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.",

author = "Jie Ping and Guochong Jia and Qiuyin Cai and Xingyi Guo and Ran Tao and Christine Ambrosone and Dezheng Huo and Stefan Ambs and Barnard, {Mollie E.} and Yu Chen and Montserrat Garcia-Closas and Jian Gu and Hu, {Jennifer J.} and John, {Esther M.} and Li, {Christopher I.} and Katherine Nathanson and Barbara Nemesure and Olopade, {Olufunmilayo I.} and Tuya Pal and Press, {Michael F.} and Maureen Sanderson and Sandler, {Dale P.} and Toshio Yoshimatsu and Adejumo, {Prisca O.} and Thomas Ahearn and Brewster, {Abenaa M.} and Hennis, {Anselm J.M.} and Timothy Makumbi and Paul Ndom and O{\textquoteright}Brien, {Katie M.} and Olshan, {Andrew F.} and Oluwasanu, {Mojisola M.} and Sonya Reid and Song Yao and Butler, {Ebonee N.} and Maosheng Huang and Atara Ntekim and Bingshan Li and Troester, {Melissa A.} and Palmer, {Julie R.} and Haiman, {Christopher A.} and Jirong Long and Wei Zheng",

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doi = "10.1038/s41467-024-47650-5",

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T1 - Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

AU - Ping, Jie

AU - Jia, Guochong

AU - Cai, Qiuyin

AU - Guo, Xingyi

AU - Tao, Ran

AU - Ambrosone, Christine

AU - Huo, Dezheng

AU - Ambs, Stefan

AU - Barnard, Mollie E.

AU - Chen, Yu

AU - Garcia-Closas, Montserrat

AU - Gu, Jian

AU - Hu, Jennifer J.

AU - John, Esther M.

AU - Li, Christopher I.

AU - Nathanson, Katherine

AU - Nemesure, Barbara

AU - Olopade, Olufunmilayo I.

AU - Pal, Tuya

AU - Press, Michael F.

AU - Sanderson, Maureen

AU - Sandler, Dale P.

AU - Yoshimatsu, Toshio

AU - Adejumo, Prisca O.

AU - Ahearn, Thomas

AU - Brewster, Abenaa M.

AU - Hennis, Anselm J.M.

AU - Makumbi, Timothy

AU - Ndom, Paul

AU - O’Brien, Katie M.

AU - Olshan, Andrew F.

AU - Oluwasanu, Mojisola M.

AU - Reid, Sonya

AU - Yao, Song

AU - Butler, Ebonee N.

AU - Huang, Maosheng

AU - Ntekim, Atara

AU - Li, Bingshan

AU - Troester, Melissa A.

AU - Palmer, Julie R.

AU - Haiman, Christopher A.

AU - Long, Jirong

AU - Zheng, Wei

PY - 2024/12

Y1 - 2024/12

N2 - African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

AB - African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

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JO - Nature communications

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Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

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