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Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk
CE. Thomas, Y. Lin, M. Kim, ES. Kawaguchi, C. Qu, CY. Um, BM. Lynch, B. Van Guelpen, K. Tsilidis, R. Carreras-Torres, FJB. van Duijnhoven, LC. Sakoda, PT. Campbell, Y. Tian, J. Chang-Claude, S. Bézieau, A. Budiarto, JR. Palmer, PA. Newcomb, G....
Language English Country United States
Document type Journal Article
Grant support
001
World Health Organization - International
- MeSH
- Diet MeSH
- Adult MeSH
- Genetic Predisposition to Disease * MeSH
- Body Mass Index MeSH
- Gene-Environment Interaction * MeSH
- Polymorphism, Single Nucleotide MeSH
- Colorectal Neoplasms * genetics epidemiology MeSH
- Smoking adverse effects MeSH
- Middle Aged MeSH
- Humans MeSH
- Logistic Models MeSH
- Alcohol Drinking MeSH
- Risk Factors MeSH
- Aged MeSH
- Case-Control Studies MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
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.
Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia
Broad Institute of Harvard and MIT Cambridge MA
Broad Institute of MIT and Harvard Cambridge MA
Cancer Epidemiology Division Cancer Council Victoria Melbourne Victoria Australia
Center for Cancer Research Medical University of Vienna Vienna Austria
Center for Gastrointestinal Biology and Disease University of North Carolina Chapel Hill NC
Center for Public Health Genomics University of Virginia Charlottesville VA
Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia
Consortium for Biomedical Research in Epidemiology and Public Health Madrid Spain
Department of Biostatistics University of Washington Seattle WA
Department of Cancer Medicine The University of Texas MD Anderson Cancer Center Houston TX
Department of Computer Science Stanford University Stanford CA
Department of Epidemiology and Population Health Albert Einstein College of Medicine Bronx NY
Department of Epidemiology Harvard T H Chan School of Public Health Harvard University Boston MA
Department of Epidemiology Johns Hopkins Bloomberg School of Public Health Baltimore MD
Department of Epidemiology University of Washington School of Public Health Seattle WA
Department of Epidemiology University of Washington Seattle WA
Department of Family Medicine University of Virginia Charlottesville VA
Department of Genetics Stanford University Stanford CA
Department of Hygiene and Epidemiology University of Ioannina School of Medicine Ioannina Greece
Department of Medical Oncology Dana Farber Cancer Institute Boston MA
Department of Medicine Brigham and Women's Hospital Harvard Medical School Boston MA
Department of Nutrition Harvard T H Chan School of Public Health Harvard University Boston MA
Department of Nutritional Sciences University of Michigan School of Public Health Ann Arbor MI
Department of Population Health Sciences University of Utah Salt Lake City UT
Department of Population Science American Cancer Society Atlanta GA
Department of Radiation Sciences Oncology Unit Umeå University Umeå Sweden
Departments of Epidemiology and Nutrition Harvard TH Chan School of Public Health Boston MA
Departments of Medicine and Epidemiology University of Pittsburgh Medical Center Pittsburgh PA
Digestive Diseases and Microbiota Group Girona Biomedical Research Institute Salt Girona Spain
Division of Cancer Epidemiology German Cancer Research Center Heidelberg Germany
Division of Gastroenterology Massachusetts General Hospital and Harvard Medical School Boston MA
Division of Human Nutrition and Health Wageningen University and Research Wageningen The Netherlands
Division of Preventive Oncology German Cancer Research Center Heidelberg Germany
Division of Research Kaiser Permanente Northern California Oakland CA
Faculty of Medicine and Biomedical Center in Pilsen Charles University Pilsen Czech Republic
From the Public Health Sciences Division Fred Hutchinson Cancer Center Seattle WA
German Cancer Consortium Heidelberg Germany
Harvard TH Chan School of Public Health
Huntsman Cancer Institute Salt Lake City UT
Institute for Health Research Kaiser Permanente Colorado Aurora CO
Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden
Leeds Institute of Medical Research University of Leeds Leeds UK
Memorial University of Newfoundland Discipline of Genetics St John's Canada
Norris Comprehensive Cancer Center University of Southern California Los Angeles CA
Nutrition and Metabolism Branch International Agency for Research on Cancer Lyon France
ONCOBELL Program Bellvitge Biomedical Research Institute L'Hospitalet de Llobregat Barcelona Spain
School of Public Health Capital Medical University Beijing China
Service de Génétique Médicale Centre Hospitalier Universitaire Nantes Nantes France
Slone Epidemiology Center at Boston University Boston MA
SWOG Statistical Center Fred Hutchinson Cancer Center Seattle WA
Unit of Biomarkers and Suceptibility L'Hospitalet del Llobregat Barcelona Spain
University Medical Centre Hamburg Eppendorf University Cancer Centre Hamburg Hamburg Germany
University of Hawaii Cancer Center Honolulu HI
University of Southern California Department of Population and Public Health Sciences Los Angeles CA
Wallenberg Centre for Molecular Medicine Umeå University Umeå Sweden
References provided by Crossref.org
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- $a Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk / $c CE. Thomas, Y. Lin, M. Kim, ES. Kawaguchi, C. Qu, CY. Um, BM. Lynch, B. Van Guelpen, K. Tsilidis, R. Carreras-Torres, FJB. van Duijnhoven, LC. Sakoda, PT. Campbell, Y. Tian, J. Chang-Claude, S. Bézieau, A. Budiarto, JR. Palmer, PA. Newcomb, G. Casey, L. Le Marchandz, M. Giannakis, CI. Li, A. Gsur, C. Newton, M. Obón-Santacana, V. Moreno, P. Vodicka, H. Brenner, M. Hoffmeister, AJ. Pellatt, RE. Schoen, N. Dimou, N. Murphy, MJ. Gunter, S. Castellví-Bel, JC. Figueiredo, AT. Chan, M. Song, L. Li, DT. Bishop, SB. Gruber, JW. Baurley, SA. Bien, DV. Conti, JR. Huyghe, A. Kundaje, YR. Su, J. Wang, TO. Keku, MO. Woods, SI. Berndt, SJ. Chanock, CM. Tangen, A. Wolk, A. Burnett-Hartman, AH. Wu, E. White, MA. Devall, V. Díez-Obrero, DA. Drew, E. Giovannucci, A. Hidaka, AE. Kim, JP. Lewinger, J. Morrison, J. Ose, N. Papadimitriou, B. Pardamean, AR. Peoples, EA. Ruiz-Narvaez, A. Shcherbina, MC. Stern, X. Chen, DC. Thomas, EA. Platz, WJ. Gauderman, U. Peters, L. Hsu
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- $a 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.
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