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| 005 | 20241127150022.0 | ||
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| 100 | 1 | _ | |a Thomas, Claire E |b 0 |
| 245 | _ | _ | |a Characterization of additive gene-environment interactions for colorectal cancer risk. |
| 260 | _ | _ | |a Baltimore, Md. |c 2025 |b Wolters Kluwer Health, Lippincott Williams & Wilkins |
| 336 | 7 | _ | |a article |2 DRIVER |
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| 500 | _ | _ | |a 2025 Jan 1;36(1):126-138 |
| 520 | _ | _ | |a Colorectal cancer (CRC) is a common, fatal cancer. Identifying subgroups who may benefit more from intervention is of critical public health importance. Previous studies have assessed multiplicative interaction between genetic risk scores and environmental factors, but few have assessed additive interaction, the relevant public health measure.Using resources from colorectal cancer consortia including 45,247 CRC cases and 52,671 controls, we assessed multiplicative and additive interaction (relative excess risk due to interaction, RERI) using logistic regression between 13 harmonized environmental factors and genetic risk score including 141 variants associated with CRC risk.There was no evidence of multiplicative interaction between environmental factors and genetic risk score. There was additive interaction where, for individuals with high genetic susceptibility, either heavy drinking [RERI = 0.24, 95% confidence interval, CI, (0.13, 0.36)], ever smoking [0.11 (0.05, 0.16)], high BMI [female 0.09 (0.05, 0.13), male 0.10 (0.05, 0.14)], or high red meat intake [highest versus lowest quartile 0.18 (0.09, 0.27)] was associated with excess CRC risk greater than that for individuals with average genetic susceptibility. Conversely, we estimate those with high genetic susceptibility may benefit more from reducing CRC risk with aspirin/NSAID use [-0.16 (-0.20, -0.11)] or higher intake of fruit, fiber, or calcium [highest quartile versus lowest quartile -0.12 (-0.18, -0.050); -0.16 (-0.23, -0.09); -0.11 (-0.18, -0.05), respectively] than those with average genetic susceptibility.Additive interaction is important to assess for identifying subgroups who may benefit from intervention. The subgroups identified in this study may help inform precision CRC prevention. |
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| 700 | 1 | _ | |a Kim, Michelle |b 2 |
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| 700 | 1 | _ | |a Qu, Conghui |b 4 |
| 700 | 1 | _ | |a Um, Caroline Y |b 5 |
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