Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry.
Stefanie H Mueller,
Alvina G Lai,
Maria Valkovskaya,
Kyriaki Michailidou,
Manjeet K Bolla,
Qin Wang,
Joe Dennis,
Michael Lush,
Zomoruda Abu-Ful,
Thomas U Ahearn,
Irene L Andrulis,
Hoda Anton-Culver,
Natalia N Antonenkova,
Volker Arndt,
Kristan J Aronson,
Annelie Augustinsson,
Thais Baert,
Laura E Beane Freeman,
Matthias W Beckmann,
Sabine Behrens,
Javier Benitez,
Marina Bermisheva,
Carl Blomqvist,
Natalia V Bogdanova,
Stig E Bojesen,
Bernardo Bonanni,
Hermann Brenner,
Sara Y Brucker,
Saundra S Buys,
Jose E Castelao,
Tsun L Chan,
Jenny Chang-Claude,
Stephen J Chanock,
Ji-Yeob Choi,
Wendy K Chung,
,
Sarah V Colonna,
,
Sten Cornelissen,
Fergus J Couch,
Kamila Czene,
Mary B Daly,
Peter Devilee,
Thilo Dörk,
Laure Dossus,
Miriam Dwek,
Diana M Eccles,
Arif B Ekici,
A Heather Eliassen,
Christoph Engel,
D Gareth Evans,
Peter A Fasching,
Olivia Fletcher,
Henrik Flyger,
Manuela Gago-Dominguez,
Yu-Tang Gao,
Montserrat García-Closas,
José A García-Sáenz,
Jeanine Genkinger,
Aleksandra Gentry-Maharaj,
Felix Grassmann,
Pascal Guénel,
Melanie Gündert,
Lothar Haeberle,
Eric Hahnen,
Christopher A Haiman,
Niclas Håkansson,
Per Hall,
Elaine F Harkness,
Patricia A Harrington,
Jaana M Hartikainen,
Mikael Hartman,
Alexander Hein,
Weang-Kee Ho,
Maartje J Hooning,
Reiner Hoppe,
John L Hopper,
Richard S Houlston,
Anthony Howell,
David J Hunter,
Dezheng Huo,
,
Hidemi Ito,
Motoki Iwasaki,
Anna Jakubowska,
Wolfgang Janni,
Esther M John,
Michael E Jones,
Audrey Jung,
Rudolf Kaaks,
Daehee Kang,
Elza K Khusnutdinova,
Sung-Won Kim,
Cari M Kitahara,
Stella Koutros,
Peter Kraft,
Vessela N Kristensen,
Katerina Kubelka-Sabit,
Allison W Kurian,
Ava Kwong,
James V Lacey,
Diether Lambrechts,
Loic Le Marchand,
Jingmei Li,
Martha Linet,
Wing-Yee Lo,
Jirong Long,
Artitaya Lophatananon,
Arto Mannermaa,
Mehdi Manoochehri,
Sara Margolin,
Keitaro Matsuo,
Dimitrios Mavroudis,
Usha Menon,
Kenneth Muir,
Rachel A Murphy,
Heli Nevanlinna,
William G Newman,
Dieter Niederacher,
Katie M O'Brien,
Nadia Obi,
Kenneth Offit,
Olufunmilayo I Olopade,
Andrew F Olshan,
Håkan Olsson,
Sue K Park,
Alpa V Patel,
Achal Patel,
Charles M Perou,
Julian Peto,
Paul D P Pharoah,
Dijana Plaseska-Karanfilska,
Nadege Presneau,
Brigitte Rack,
Paolo Radice,
Dhanya Ramachandran,
Muhammad U Rashid,
Gad Rennert,
Atocha Romero,
Kathryn J Ruddy,
Matthias Ruebner,
Emmanouil Saloustros,
Dale P Sandler,
Elinor J Sawyer,
Marjanka K Schmidt,
Rita K Schmutzler,
Michael O Schneider,
Christopher Scott,
Mitul Shah,
Priyanka Sharma,
Chen-Yang Shen,
Xiao-Ou Shu,
Jacques Simard,
Harald Surowy,
Rulla M Tamimi,
William J Tapper,
Jack A Taylor,
Soo Hwang Teo,
Lauren R Teras,
Amanda E Toland,
Rob A E M Tollenaar,
Diana Torres,
Gabriela Torres-Mejía,
Melissa A Troester,
Thérèse Truong,
Celine M Vachon,
Joseph Vijai,
Clarice R Weinberg,
Camilla Wendt,
Robert Winqvist,
Alicja Wolk,
Anna H Wu,
Taiki Yamaji,
Xiaohong R Yang,
Jyh-Cherng Yu,
Wei Zheng,
Argyrios Ziogas,
Elad Ziv,
Alison M Dunning,
Douglas F Easton,
Harry Hemingway,
Ute Hamann,
Karoline B Kuchenbaecker
Abstract
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.
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.
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.
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.