Breast Cancer Research (Apr 2022)
Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci
- Hongjie Chen,
- Shaoqi Fan,
- Jennifer Stone,
- Deborah J. Thompson,
- Julie Douglas,
- Shuai Li,
- Christopher Scott,
- Manjeet K. Bolla,
- Qin Wang,
- Joe Dennis,
- Kyriaki Michailidou,
- Christopher Li,
- Ulrike Peters,
- John L. Hopper,
- Melissa C. Southey,
- Tu Nguyen-Dumont,
- Tuong L. Nguyen,
- Peter A. Fasching,
- Annika Behrens,
- Gemma Cadby,
- Rachel A. Murphy,
- Kristan Aronson,
- Anthony Howell,
- Susan Astley,
- Fergus Couch,
- Janet Olson,
- Roger L. Milne,
- Graham G. Giles,
- Christopher A. Haiman,
- Gertraud Maskarinec,
- Stacey Winham,
- Esther M. John,
- Allison Kurian,
- Heather Eliassen,
- Irene Andrulis,
- D. Gareth Evans,
- William G. Newman,
- Per Hall,
- Kamila Czene,
- Anthony Swerdlow,
- Michael Jones,
- Marina Pollan,
- Pablo Fernandez-Navarro,
- Daniel S. McConnell,
- Vessela N. Kristensen,
- NBCS Investigators,
- Joseph H. Rothstein,
- Pei Wang,
- Laurel A. Habel,
- Weiva Sieh,
- Alison M. Dunning,
- Paul D. P. Pharoah,
- Douglas F. Easton,
- Gretchen L. Gierach,
- Rulla M. Tamimi,
- Celine M. Vachon,
- Sara Lindström
Affiliations
- Hongjie Chen
- Department of Epidemiology, School of Public Health, University of Washington
- Shaoqi Fan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute
- Jennifer Stone
- School of Population and Global Health, University of Western Australia
- Deborah J. Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Julie Douglas
- Department of Human Genetics, University of Michigan Medical School
- Shuai Li
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Christopher Scott
- Department of Health Sciences Research, Mayo Clinic
- Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics
- Christopher Li
- Department of Epidemiology, School of Public Health, University of Washington
- Ulrike Peters
- Department of Epidemiology, School of Public Health, University of Washington
- John L. Hopper
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne
- Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University
- Tu Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University
- Tuong L. Nguyen
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne
- Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg
- Annika Behrens
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center ER-EMN, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg
- Gemma Cadby
- School of Population and Global Health, University of Western Australia
- Rachel A. Murphy
- Cancer Control Research, BC Cancer and School of Population and Public Health, University of British Columbia
- Kristan Aronson
- Public Health Sciences, Queen’s University
- Anthony Howell
- Division of Cancer Sciences, University of Manchester
- Susan Astley
- Division of Informatics, Imaging and Data Sciences, University of Manchester
- Fergus Couch
- Department of Health Sciences Research, Mayo Clinic
- Janet Olson
- Department of Health Sciences Research, Mayo Clinic
- Roger L. Milne
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne
- Graham G. Giles
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne
- Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Preventive Medicine, Keck School of Medicine, University of Southern California
- Gertraud Maskarinec
- Epidemiology Program, University of Hawaii Cancer Center
- Stacey Winham
- Department of Health Sciences Research, Mayo Clinic
- Esther M. John
- Department of Epidemiology and Population Health, Stanford University School of Medicine
- Allison Kurian
- Department of Epidemiology and Population Health, Stanford University School of Medicine
- Heather Eliassen
- Department of Epidemiology, Harvard T.H. Chan School of Public Health
- Irene Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital
- D. Gareth Evans
- Division of Evolution and Genomic Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester
- William G. Newman
- Division of Evolution and Genomic Medicine, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester
- Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet
- Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet
- Anthony Swerdlow
- Division of Genetics and Epidemiology, The Institute of Cancer Research
- Michael Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research
- Marina Pollan
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health
- Pablo Fernandez-Navarro
- Cancer and Environmental Epidemiology Unit, National Center for Epidemiology, Carlos III Institute of Health
- Daniel S. McConnell
- Department of Epidemiology, School of Public Health, University of Michigan
- Vessela N. Kristensen
- Department of Medical Genetics, Oslo University Hospital and University of Oslo
- NBCS Investigators
- Joseph H. Rothstein
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai
- Pei Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai
- Laurel A. Habel
- Division of Research, Kaiser Permanente Northern California
- Weiva Sieh
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai
- Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Paul D. P. Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge
- Gretchen L. Gierach
- Division of Cancer Epidemiology and Genetics, National Cancer Institute
- Rulla M. Tamimi
- Division of Epidemiology, Population Health Science, Weill Cornell Medicine
- Celine M. Vachon
- Department of Health Sciences Research, Mayo Clinic
- Sara Lindström
- Department of Epidemiology, School of Public Health, University of Washington
- DOI
- https://doi.org/10.1186/s13058-022-01524-0
- Journal volume & issue
-
Vol. 24,
no. 1
pp. 1 – 15
Abstract
Abstract Background Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. Methods We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. Results We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. Conclusions Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.
Keywords
- Mammographic density
- Breast cancer
- Genome-wide association study (GWAS)
- Transcriptome-wide association study (TWAS)
