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 - 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 - Riis, Margit

AU - Flyger, Henrik

AU - Gao, Yu Tang

AU - Scott, Christopher

AU - NBCS Collaborators

AU - CTS Consortium

AU - ABCTB Investigators

N1 - Publisher Copyright: © 2023, The Author(s).

PY - 2023

Y1 - 2023

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.

KW - Breast cancer susceptibility

KW - Diverse ancestry

KW - Gene regulation

KW - Genome-wide association study

KW - Rare variants

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 - Journal article

C2 - 36703164

AN - SCOPUS:85146966233

VL - 15

JO - Genome Medicine

JF - Genome Medicine

SN - 1756-994X

IS - 1

M1 - 7

ER -