Testing for Gene-Environment Interactions Using a Prospective Family Cohort Design: Body Mass Index in Early and Later Adulthood and Risk of Breast Cancer

Abstract

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.

Keywords: BOADICEA; body mass index; breast cancer; cohort studies; familial risk; family studies; gene-environment interaction.

Figure 1.

Logarithms of adjusted hazard ratios (HRs) for the risk of breast cancer according to body mass index (BMI; weight (kg)/height (m)²) at baseline (per 5-unit increment) and BMI at ages 18–21 years (per 5-unit increment) in quartiles of the residuals of age-adjusted BOADICEA lifetime risk score (from left to right, median values from quartile 1 to quartile 4), Australia, 1992–2010. Bars, 95% confidence intervals. BOADICEA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm.

Figure 2.

Logarithms of adjusted hazard ratios (HRs) for the risk of breast cancer according to change in body mass index (BMI; weight (kg)/height (m)²) since baseline (per 5-unit increment) and BMI at ages 18–21 years (per 5-unit increment) in quartiles of the residuals of age-adjusted BOADICEA lifetime risk score (from left to right, median values from quartile 1 to quartile 4), Australia, 1992–2010. Bars, 95% confidence intervals. BOADICEA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm.