TY - JOUR
T1 - Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry
AU - Mueller, Stefanie H.
AU - Lai, Alvina G.
AU - NBCS Collaborators
AU - CTS Consortium
AU - ABCTB Investigators
AU - Valkovskaya, Maria
AU - Michailidou, Kyriaki
AU - Bolla, Manjeet K.
AU - Wang, Qin
AU - Dennis, Joe
AU - Lush, Michael
AU - Abu-Ful, Zomoruda
AU - Ahearn, Thomas U.
AU - Andrulis, Irene L.
AU - Anton-Culver, Hoda
AU - Antonenkova, Natalia N.
AU - Arndt, Volker
AU - Aronson, Kristan J.
AU - Augustinsson, Annelie
AU - Baert, Thais
AU - Freeman, Laura E.Beane
AU - Beckmann, Matthias W.
AU - Behrens, Sabine
AU - Benitez, Javier
AU - Bermisheva, Marina
AU - Blomqvist, Carl
AU - Bogdanova, Natalia V.
AU - Bojesen, Stig E.
AU - Bonanni, Bernardo
AU - Brenner, Hermann
AU - Brucker, Sara Y.
AU - Buys, Saundra S.
AU - Castelao, Jose E.
AU - Chan, Tsun L.
AU - Chang-Claude, Jenny
AU - Chanock, Stephen J.
AU - Choi, Ji Yeob
AU - Chung, Wendy K.
AU - Sahlberg, Kristine K.
AU - Børresen-Dale, Anne Lise
AU - Ottestad, Lars
AU - Kåresen, Rolf
AU - Schlichting, Ellen
AU - Holmen, Marit Muri
AU - Sauer, Toril
AU - Haakensen, Vilde
AU - Engebråten, Olav
AU - Naume, Bjørn
AU - Fosså, Alexander
AU - Kiserud, Cecile E.
AU - Engel, Christoph
AU - Hooning, Maartje J.
AU - Kraft, Peter
N1 - Funding Information:
This result is part of a project that has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 948561).
Funding Information:
BCAC is funded by the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633,784 for BRIDGES and B-CAST respectively), and the PERSPECTIVE I&I project, funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie et de l'Innovation du Québec through Genome Québec, the Quebec Breast Cancer Foundation. The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Additional funding for BCAC is provided via the Confluence project which is funded with intramural funds from the National Cancer Institute Intramural Research Program, National Institutes of Health.
Publisher Copyright: © 2023, The Author(s).
PY - 2023/1/26
Y1 - 2023/1/26
N2 - Background: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. Methods: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes’ coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10−6) and AC058822.1 (P = 1.47 × 10−4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10−5), demonstrating the importance of diversifying study cohorts.
AB - Background: Low-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes. Methods: We evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes’ coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry. Results: In European ancestry samples, 14 genes were significantly associated (q < 0.05) with BC. Of those, two genes, FMNL3 (P = 6.11 × 10−6) and AC058822.1 (P = 1.47 × 10−4), represent new associations. High FMNL3 expression has previously been linked to poor prognosis in several other cancers. Meta-analysis of samples with diverse ancestry discovered further associations including established candidate genes ESR1 and CBLB. Furthermore, literature review and database query found further support for a biologically plausible link with cancer for genes CBLB, FMNL3, FGFR2, LSP1, MAP3K1, and SRGAP2C. Conclusions: Using extended gene-based aggregation tests including coding and regulatory variation, we report identification of plausible target genes for previously identified single-marker associations with BC as well as the discovery of novel genes implicated in BC development. Including multi ancestral cohorts in this study enabled the identification of otherwise missed disease associations as ESR1 (P = 1.31 × 10−5), demonstrating the importance of diversifying study cohorts.
UR - http://www.scopus.com/inward/record.url?scp=85146966233&partnerID=8YFLogxK
U2 - 10.1186/s13073-022-01152-5
DO - 10.1186/s13073-022-01152-5
M3 - Article
C2 - 36703164
AN - SCOPUS:85146966233
SN - 1756-994X
VL - 15
JO - Genome Medicine
JF - Genome Medicine
IS - 1
M1 - 7
ER -
