Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk
- PMID: 39316822
- PMCID: PMC12142706
- DOI: 10.1097/EDE.0000000000001795
Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk
Abstract
Background: 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.
Methods: Using resources from CRC 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.
Results: 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 body mass index (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/nonsteroidal anti-inflammatory drugs 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.
Conclusions: 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.
Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.
Conflict of interest statement
S.G.: Brogent International LLC, co-founder, not related to submitted work. J.B.: co-founder and employee of BioRealm LLC. BioRealm LLC offers data analysis services, unrelated to this study. M.G.: Research funding from Servier and Janssen, unrelated to this study. Other authors report no conflicts of interest.
Similar articles
-
Chemoprevention of colorectal cancer: systematic review and economic evaluation.Health Technol Assess. 2010 Jun;14(32):1-206. doi: 10.3310/hta14320. Health Technol Assess. 2010. PMID: 20594533
-
Effects of a gluten-reduced or gluten-free diet for the primary prevention of cardiovascular disease.Cochrane Database Syst Rev. 2022 Feb 24;2(2):CD013556. doi: 10.1002/14651858.CD013556.pub2. Cochrane Database Syst Rev. 2022. PMID: 35199850 Free PMC article.
-
Nutritional interventions for survivors of childhood cancer.Cochrane Database Syst Rev. 2016 Aug 22;2016(8):CD009678. doi: 10.1002/14651858.CD009678.pub2. Cochrane Database Syst Rev. 2016. PMID: 27545902 Free PMC article.
-
Systemic pharmacological treatments for chronic plaque psoriasis: a network meta-analysis.Cochrane Database Syst Rev. 2021 Apr 19;4(4):CD011535. doi: 10.1002/14651858.CD011535.pub4. Cochrane Database Syst Rev. 2021. Update in: Cochrane Database Syst Rev. 2022 May 23;5:CD011535. doi: 10.1002/14651858.CD011535.pub5. PMID: 33871055 Free PMC article. Updated.
-
Dietary fibre for the prevention of recurrent colorectal adenomas and carcinomas.Cochrane Database Syst Rev. 2017 Jan 8;1(1):CD003430. doi: 10.1002/14651858.CD003430.pub2. Cochrane Database Syst Rev. 2017. PMID: 28064440 Free PMC article.
Cited by
-
Association between red and processed meat consumption and colorectal cancer risk: a comprehensive meta-analysis of prospective studies.Geroscience. 2025 Jun;47(3):5123-5140. doi: 10.1007/s11357-025-01646-1. Epub 2025 Apr 10. Geroscience. 2025. PMID: 40210826 Free PMC article.
-
Serum calcium-based interpretable machine learning model for predicting anastomotic leakage after rectal cancer resection: A multi-center study.World J Gastroenterol. 2025 May 21;31(19):105283. doi: 10.3748/wjg.v31.i19.105283. World J Gastroenterol. 2025. PMID: 40497096 Free PMC article.
References
-
- Sung H, Ferlay J, Siegel RL, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71(3):209–249. - PubMed
-
- Lichtenstein P, Holm NV, Verkasalo PK, et al. Environmental and Heritable Factors in the Causation of Cancer — Analyses of Cohorts of Twins from Sweden, Denmark, and Finland. N Engl J Med. 2000;343(2):78–85. - PubMed
MeSH terms
Grants and funding
- U01 HG004438/HG/NHGRI NIH HHS/United States
- U01 HG004446/HG/NHGRI NIH HHS/United States
- U10 CA037429/CA/NCI NIH HHS/United States
- K05 CA154337/CA/NCI NIH HHS/United States
- U01 CA167551/CA/NCI NIH HHS/United States
- R01 CA042182/CA/NCI NIH HHS/United States
- P01 CA196569/CA/NCI NIH HHS/United States
- R01 CA097325/CA/NCI NIH HHS/United States
- R01 CA059045/CA/NCI NIH HHS/United States
- R01 CA197350/CA/NCI NIH HHS/United States
- R35 CA197735/CA/NCI NIH HHS/United States
- R01 CA072520/CA/NCI NIH HHS/United States
- P01 CA087969/CA/NCI NIH HHS/United States
- U01 CA164974/CA/NCI NIH HHS/United States
- R01 CA248857/CA/NCI NIH HHS/United States
- P30 CA015704/CA/NCI NIH HHS/United States
- P30 CA006973/CA/NCI NIH HHS/United States
- Z01 CP010200/ImNIH/Intramural NIH HHS/United States
- R01 CA206279/CA/NCI NIH HHS/United States
- P01 CA055075/CA/NCI NIH HHS/United States
- R01 CA151993/CA/NCI NIH HHS/United States
- U01 CA152753/CA/NCI NIH HHS/United States
- S10 OD028685/OD/NIH HHS/United States
- R01 CA297681/CA/NCI NIH HHS/United States
- P30 DK034987/DK/NIDDK NIH HHS/United States
- R01 CA048998/CA/NCI NIH HHS/United States
- U01 CA137088/CA/NCI NIH HHS/United States
- R01 CA189184/CA/NCI NIH HHS/United States
- U01 CA167552/CA/NCI NIH HHS/United States
- U01 CA164930/CA/NCI NIH HHS/United States
- U01 CA261339/CA/NCI NIH HHS/United States
- R01 CA066635/CA/NCI NIH HHS/United States
- R21 CA191312/CA/NCI NIH HHS/United States
- U01 CA206110/CA/NCI NIH HHS/United States
- P20 CA252733/CA/NCI NIH HHS/United States
- R01 CA244588/CA/NCI NIH HHS/United States
- R01 CA242218/CA/NCI NIH HHS/United States
- R01 CA137178/CA/NCI NIH HHS/United States
- R01 CA189532/CA/NCI NIH HHS/United States
- R01 CA081488/CA/NCI NIH HHS/United States
- R01 CA143237/CA/NCI NIH HHS/United States
- T32 CA009168/CA/NCI NIH HHS/United States
- R01 CA201407/CA/NCI NIH HHS/United States
- R01 CA063464/CA/NCI NIH HHS/United States
- P01 CA033619/CA/NCI NIH HHS/United States
- U01 CA086308/CA/NCI NIH HHS/United States
- UM1 CA186107/CA/NCI NIH HHS/United States
- R01 CA207371/CA/NCI NIH HHS/United States
- R03 CA153323/CA/NCI NIH HHS/United States
- R01 CA060987/CA/NCI NIH HHS/United States
- R01 CA136726/CA/NCI NIH HHS/United States
- L70 CA284301/CA/NCI NIH HHS/United States
- UM1 CA167552/CA/NCI NIH HHS/United States
- K05 CA152715/CA/NCI NIH HHS/United States
- U01 CA122839/CA/NCI NIH HHS/United States
- U01 CA074783/CA/NCI NIH HHS/United States
- KL2 TR000421/TR/NCATS NIH HHS/United States
- UM1 CA182883/CA/NCI NIH HHS/United States
- 001/WHO_/World Health Organization/International
- R37 CA054281/CA/NCI NIH HHS/United States
- U19 CA148107/CA/NCI NIH HHS/United States
- T32 CA094880/CA/NCI NIH HHS/United States
- U01 AG018033/AG/NIA NIH HHS/United States
LinkOut - more resources
Full Text Sources
Medical