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Testing for Gene-Environment Interactions Using a Prospective Family Cohort Design: Body Mass Index in Early and Later Adulthood and Risk of Breast Cancer.
- Source :
- American Journal of Epidemiology; 3/15/2017, Vol. 185 Issue 6, p487-500, 14p
- Publication Year :
- 2017
-
Abstract
- Initially submitted February 1, 2016; accepted for publication August 4, 2016. The ability to classify people according to their underlying genetic susceptibility to a disease is increasing with new knowledge, better family data, and more sophisticated risk prediction models, allowing for more effective prevention and screening. To do so, however, we need to know whether risk associations are the same for people with different genetic susceptibilities. To illustrate one way to estimate such gene-environment interactions, we used prospective data from 3 Australian family cancer cohort studies, 2 enriched for familial risk of breast cancer. There were 288 incident breast cancers in 9,126 participants from 3,222 families. We used Cox proportional hazards models to investigate whether associations of breast cancer with body mass index (BMI; weight (kg)/height (m)2) at age 18-21 years, BMI at baseline, and change in BMI differed according to genetic risk based on lifetime breast cancer risk from birth, as estimated by BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) software, adjusted for age at baseline data collection. Although no interactions were statistically significant, we have demonstrated the power with which gene-environment interactions can be investigated using a cohort enriched for persons with increased genetic risk and a continuous measure of genetic risk based on family history. [ABSTRACT FROM AUTHOR]
- Subjects :
- BREAST tumors
BREAST tumor risk factors
AGE distribution
BODY weight
CONFIDENCE intervals
DISEASE susceptibility
ECOLOGY
INTERVIEWING
LONGITUDINAL method
OBESITY
PROBABILITY theory
QUESTIONNAIRES
RISK assessment
BODY mass index
PROPORTIONAL hazards models
FAMILY history (Medicine)
DATA analysis software
DESCRIPTIVE statistics
GENETICS
Subjects
Details
- Language :
- English
- ISSN :
- 00029262
- Volume :
- 185
- Issue :
- 6
- Database :
- Complementary Index
- Journal :
- American Journal of Epidemiology
- Publication Type :
- Academic Journal
- Accession number :
- 121858172
- Full Text :
- https://doi.org/10.1093/aje/kww241