6th International Workshop on Breast Densitometry and Breast ...

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6 th <strong>International</strong> <strong>Workshop</strong> on Breast Densitometry
and Breast Cancer Risk Assessment
META-ANALYSIS OF TWELVE GENOME-WIDE ASSOCIATION STUDIES (GWAS)
IDENTIFIES NOVEL GENETIC LOCI ASSOCIATED WITH MAMMOGRAPHIC
DENSITY PHENOTYPES
Sara Lindström 1,2 , Deborah Thompson 3 , Andrew D. Paterson 4 , Jingmei Li 5 , Gretchen L. Gierach 6 , Jennifer
Stone 7 , Julie A. Douglas 8 , Isabel dos Santos Silva 9 , Javier Benitez 10 , Christopher Scott 11 , Peter A. Fasching 12 ,
Laura Baglietto 13 , Melissa Southey 7 , Graham Giles 13 , Marina Pollan 10 , Jonine Figueroa 6 , Fergus Couch 11 , John
L. Hopper 7 , Per Hall 5 , Douglas F. Easton 3 , Norman F. Boyd 14 , Celine M. Vachon 11† , and Rulla M. Tamimi 1,2,15†
†
for the Markers of Density (MODE) consortium Co-Last Authors
1 Program in Molecular and Genetic Epidemiology; 2 Department of Epidemiology , Harvard School Of Public
Health, Boston, MA, USA; 3 Centre for Genetic Epidemiology, Department of Public Health and Primary Care,
University of Cambridge, Cambridge, UK; 4 Program in Genetics and Genome Biology, The Hospital for Sick
Children, Toronto, Ontario, Canada; 5 Department of Medical Epidemiology and Biostatistics, Karolinska
Institutet, Stockholm, Sweden; 6 Hormonal and Reproductive Epidemiology Branch, National Cancer Institute,
Rockville, MD ; 7 Centre for Molecular, Environmental, Genetic and Analytic Epidemiology, School of
Population Health, The University of Melbourne, Melbourne, Australia; 8 Department of Human Genetics,
University of Michigan Medical School, Ann Arbor, MI; 9 Faculty of Epidemiology and Population Health,
London School of Hygiene and Tropical Medicine, London, UK; 10 Centro Nacional de Investigaciones
Oncologicas, Madrid, Spain; 11 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA;
12 Erlangen University Perinatal Center, Department of Gynaecology and Obstetrics, Erlangen University
Hospital, Friedrich Alexander University of Erlangen-Nuremberg, Erlangen, Germany;
13 Cancer
Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia; 14 Campbell Family Institute for Breast
Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada; 15 Channing Division of Network
Medicine, Brigham and Women’s Hospital, Boston, MA
Mammographic density is one of the strongest risk factors for breast cancer and has been shown to have a
heritable component that remains poorly understood. In a previous meta-analysis of five genome-wide
association study (GWAS) of mammographic density in 4,887 women within the MODE consortium, we
identified common variants in the breast cancer susceptibility locus ZNF365 associated with percent
mammographic density. We have now extended our meta-analysis to include seven additional GWAS of
percent mammographic density as well as report results from the first GWAS of dense area and non-dense
area. We conducted a meta-analysis of 12 GWAS of percent mammographic density, dense area, and non-dense
area on a mammogram in almost 8,000 women of European descent. Ten of the studies used linear regression
treating the mammographic density phenotype as a quantitative trait adjusting for age, body mass index (BMI)
and menopausal status. Two studies selected women based on the extreme categories of mammographic
density (one using percent mammographic density and the other dense area) adjusted for age, BMI and
menopausal status. The differences in study design (extreme sampling vs. continuous trait) did not allow us to
perform meta-analysis based on the estimated effect size in each study as units of density measurement were
not comparable across studies. Therefore, we performed a combined test for each SNP by combining p-values
and the direction of association for each study, weighted by the square-root of the sample size and the study
specific inflation factor. We conducted replication of SNPs with P