Identification of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions

Research output: Contribution to journalJournal articleResearchpeer-review

  • Anja Schoeps
  • Anja Rudolph
  • Petra Seibold
  • Alison M Dunning
  • Roger L Milne
  • Anthony Swerdlow
  • Irene Andrulis
  • Hermann Brenner
  • Sabine Behrens
  • Nicholas Orr
  • Michael Jones
  • Alan Ashworth
  • Jingmei Li
  • Helen Cramp
  • Dan Connley
  • Kamila Czene
  • Hatef Darabi
  • Stephen J Chanock
  • Jolanta Lissowska
  • Jonine D Figueroa
  • Julia Knight
  • Gord Glendon
  • Anna M Mulligan
  • Martine Dumont
  • Gianluca Severi
  • Laura Baglietto
  • Janet Olson
  • Celine Vachon
  • Kristen Purrington
  • Matthieu Moisse
  • Patrick Neven
  • Hans Wildiers
  • Amanda Spurdle
  • Veli-Matti Kosma
  • Vesa Kataja
  • Jaana M Hartikainen
  • Ute Hamann
  • Yon-Dschun Ko
  • Aida K Dieffenbach
  • Volker Arndt
  • Christa Stegmaier
  • Núria Malats
  • José I Arias Perez
  • Javier Benítez
  • Henrik Flyger
  • Thérèse Truong
  • Emilie Cordina-Duverger
  • Florence Menegaux
  • Isabel dos Santos Silva
  • Olivia Fletcher
  • Nichola Johnson
  • Lothar Häberle
  • Matthias W Beckmann
  • Arif B Ekici
  • Linde Braaf
  • Femke Atsma
  • Alexandra J van den Broek
  • Enes Makalic
  • Daniel F Schmidt
  • Melissa C Southey
  • Angela Cox
  • Jacques Simard
  • Graham G Giles
  • Diether Lambrechts
  • Arto Mannermaa
  • Hiltrud Brauch
  • Pascal Guénel
  • Julian Peto
  • Peter A Fasching
  • John Hopper
  • Dieter Flesch-Janys
  • Fergus Couch
  • Georgia Chenevix-Trench
  • Paul D P Pharoah
  • Montserrat Garcia-Closas
  • Marjanka K Schmidt
  • Per Hall
  • Douglas F Easton
  • Jenny Chang-Claude

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10(-07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m(2) (OR = 1.26, 95% CI 1.15-1.38) but not in women with a BMI of 30 kg/m(2) or higher (OR = 0.89, 95% CI 0.72-1.11, P for interaction = 3.2 × 10(-05)). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci.

Original languageEnglish
JournalGenetic Epidemiology
Volume38
Issue number1
Pages (from-to)84-93
Number of pages10
ISSN0741-0395
DOIs
Publication statusPublished - Jan 2014

    Research areas

  • Adolescent, Body Height, Body Mass Index, Breast Neoplasms, Chromosomes, Human, Pair 21, Chromosomes, Human, Pair 6, European Continental Ancestry Group, Female, Gene-Environment Interaction, Genetic Loci, Genetic Predisposition to Disease, Humans, Linkage Disequilibrium, Menarche, Middle Aged, Parity, Polymorphism, Single Nucleotide, Postmenopause

ID: 138775681