Breast and bowel cancers diagnosed in people ‘too young to have cancer’: A blueprint for research using family and twin studies

Author:

Hopper John L.1,Li Shuai1234ORCID,MacInnis Robert J.15,Dowty James G.1,Nguyen Tuong L.1ORCID,Bui Minh1,Dite Gillian S.16,Esser Vivienne F. C.1,Ye Zhoufeng1ORCID,Makalic Enes1,Schmidt Daniel F.7,Goudey Benjamin89ORCID,Alpen Karen1,Kapuscinski Miroslaw1,Win Aung Ko11011,Dugué Pierre‐Antoine145,Milne Roger L.145,Jayasekara Harindra15,Brooks Jennifer D.12ORCID,Malta Sue1,Calais‐Ferreira Lucas1ORCID,Campbell Alexander C.13,Young Jesse T.112131415,Nguyen‐Dumont Tu4,Sung Joohon161718,Giles Graham G.145,Buchanan Daniel19,Winship Ingrid20,Terry Mary Beth21,Southey Melissa C.4519,Jenkins Mark A.110

Affiliation:

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

2. Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care University of Cambridge Cambridge UK

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

4. Precision Medicine, School of Clinical Sciences at Monash Health Monash University Clayton Victoria Australia

5. Cancer Epidemiology Division Cancer Council Victoria Melbourne Victoria Australia

6. Genetic Technologies Ltd. Fitzroy Victoria Australia

7. Department of Data Science and AI, Faculty of Information Technology Monash University Melbourne Victoria Australia

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

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

10. University of Melbourne Centre for Cancer Research Victorian Comprehensive Cancer Centre Melbourne Victoria Australia

11. Genetic Medicine Royal Melbourne Hospital Parkville Victoria Australia

12. Dalla Lana School of Public Health University of Toronto Toronto Ontario Canada

13. Institute for Mental Health Policy Research Centre for Addiction and Mental Health Toronto Ontario Canada

14. Centre for Adolescent Health Murdoch Children's Research Institute Parkville Victoria Australia

15. School of Population and Global Health The University of Western Australia Perth Western Australia Australia

16. Department of Public Health Sciences, Division of Genome and Health Big Data, Graduate School of Public Health Seoul National University Seoul South Korea

17. Genome Medicine Institute Seoul National University Seoul South Korea

18. Institute of Health and Environment Seoul National University Seoul South Korea

19. Department of Clinical Pathology The University of Melbourne Parkville Victoria Australia

20. Department of Medicine, Royal Melbourne Hospital The University of Melbourne Parkville Victoria Australia

21. Department of Epidemiology, Mailman School of Public Health Columbia University New York New York USA

Abstract

AbstractYoung breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age‐specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age‐specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome‐wide association study data, and the within‐pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.

Funder

National Health and Medical Research Council

Publisher

Wiley

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