Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures

Author:

Ye Zhoufeng1ORCID,Dite Gillian S.12ORCID,Nguyen Tuong L.1ORCID,MacInnis Robert J.13ORCID,Schmidt Daniel F.4ORCID,Makalic Enes1ORCID,Al-Qershi Osamah M.1ORCID,Nguyen-Dumont Tu35ORCID,Goudey Benjamin67ORCID,Stone Jennifer8ORCID,Dowty James G.1ORCID,Giles Graham G.135ORCID,Southey Melissa C.359ORCID,Hopper John L.1ORCID,Li Shuai151011ORCID

Affiliation:

1. 1Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Victoria, Australia.

2. 2Genetic Technologies Limited, Fitzroy, Victoria, Australia.

3. 3Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.

4. 4Department of Data Science and AI, Faculty of IT, Monash University, Melbourne, Victoria, Australia.

5. 5Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Victoria, Australia.

6. 6ARC Training Centre in Cognitive Computing for Medical Technologies, University of Melbourne, Carlton, Victoria, Australia.

7. 7The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia.

8. 8Genetic Epidemiology Group, School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia.

9. 9Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia.

10. 10Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia.

11. 11Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom.

Abstract

Abstract Background: Cirrus is an automated risk predictor for breast cancer that comprises texture-based mammographic features and is mostly independent of mammographic density. We investigated genetic and environmental variance of variation in Cirrus. Methods: We measured Cirrus for 3,195 breast cancer–free participants, including 527 pairs of monozygotic (MZ) twins, 271 pairs of dizygotic (DZ) twins, and 1,599 siblings of twins. Multivariate normal models were used to estimate the variance and familial correlations of age-adjusted Cirrus as a function of age. The classic twin model was expanded to allow the shared environment effects to differ by zygosity. The SNP-based heritability was estimated for a subset of 2,356 participants. Results: There was no evidence that the variance or familial correlations depended on age. The familial correlations were 0.52 (SE, 0.03) for MZ pairs and 0.16(SE, 0.03) for DZ and non-twin sister pairs combined. Shared environmental factors specific to MZ pairs accounted for 20% of the variance. Additive genetic factors accounted for 32% (SE = 5%) of the variance, consistent with the SNP-based heritability of 36% (SE = 16%). Conclusion: Cirrus is substantially familial due to genetic factors and an influence of shared environmental factors that was evident for MZ twin pairs only. The latter could be due to nongenetic factors operating in utero or in early life that are shared by MZ twins. Impact: Early-life factors, shared more by MZ pairs than DZ/non-twin sister pairs, could play a role in the variation in Cirrus, consistent with early life being recognized as a critical window of vulnerability to breast carcinogens.

Publisher

American Association for Cancer Research (AACR)

Subject

Oncology,Epidemiology

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