Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk

Claire E. Thomas; Yi Lin; Michelle Kim; Eric S. Kawaguchi; Conghui Qu; Caroline Y. Um; Brigid M. Lynch; Bethany Van Guelpen; Kostas Tsilidis; Robert Carreras-Torres; Franzel J.B. Van Duijnhoven; Lori C. Sakoda; Peter T. Campbell; Yu Tian; Jenny Chang-Claude; Stéphane Bézieau; Arif Budiarto; Julie R. Palmer; Polly A. Newcomb; Graham Casey; Loic Le Marchandz; Marios Giannakis; Christopher I. Li; Andrea Gsur; Christina Newton; Mireia Obón-Santacana; Victor Moreno; Pavel Vodicka; Hermann Brenner; Michael Hoffmeister; Andrew J. Pellatt; Robert E. Schoen; Niki Dimou; Neil Murphy; Marc J. Gunter; Sergi Castellví-Bel; Jane C. Figueiredo; Andrew T. Chan; Mingyang Song; Li Li; D. Timothy Bishop; Stephen B. Gruber; James W. Baurley; Stephanie A. Bien; David V. Conti; Jeroen R. Huyghe; Anshul Kundaje; Yu-Ru Su; Jun Wang; Temitope O. Keku; Michael O. Woods; Sonja I. Berndt; Stephen J. Chanock; Catherine M. Tangen; Alicja Wolk; Andrea Burnett-Hartman; Anna H. Wu; Emily White; Matthew A. Devall; Virginia Díez-Obrero; David A Drew; Edward Giovannucci; Akihisa Hidaka; Andre E. Kim; Juan Pablo Lewinger; John Morrison; Jennifer Ose; Nikos Papadimitriou; Bens Pardamean; Anita R. Peoples; Edward A. Ruiz-Narvaez; Anna Shcherbina; Mariana C. Stern; Xuechen Chen; Duncan C. Thomas; Elizabeth A. Platz; W. James Gauderman; Ulrike Peters; Li Hsu

doi:10.1097/EDE.0000000000001795

Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk

Claire E. Thomas
, Yi Lin
, Michelle Kim
, Eric S. Kawaguchi
, Conghui Qu
, Caroline Y. Um
, Brigid M. Lynch
, Bethany Van Guelpen
, Kostas Tsilidis
, Robert Carreras-Torres
, Franzel J.B. Van Duijnhoven
, Lori C. Sakoda
, Peter T. Campbell
, Yu Tian
, Jenny Chang-Claude
, Stéphane Bézieau
, Arif Budiarto
, Julie R. Palmer
, Polly A. Newcomb
, Graham Casey

Loic Le Marchandz, Marios Giannakis, Christopher I. Li, Andrea Gsur, Christina Newton, Mireia Obón-Santacana, Victor Moreno, Pavel Vodicka, Hermann Brenner, Michael Hoffmeister, Andrew J. Pellatt, Robert E. Schoen, Niki Dimou, Neil Murphy, Marc J. Gunter, Sergi Castellví-Bel, Jane C. Figueiredo, Andrew T. Chan, Mingyang Song, Li Li, D. Timothy Bishop, Stephen B. Gruber, James W. Baurley, Stephanie A. Bien, David V. Conti, Jeroen R. Huyghe, Anshul Kundaje, Yu-Ru Su, Jun Wang, Temitope O. Keku, Michael O. Woods, Sonja I. Berndt, Stephen J. Chanock, Catherine M. Tangen, Alicja Wolk, Andrea Burnett-Hartman, Anna H. Wu, Emily White, Matthew A. Devall, Virginia Díez-Obrero, David A Drew, Edward Giovannucci, Akihisa Hidaka, Andre E. Kim, Juan Pablo Lewinger, John Morrison, Jennifer Ose, Nikos Papadimitriou, Bens Pardamean, Anita R. Peoples, Edward A. Ruiz-Narvaez, Anna Shcherbina, Mariana C. Stern, Xuechen Chen, Duncan C. Thomas, Elizabeth A. Platz, W. James Gauderman, Ulrike Peters, Li Hsu

Research output: Contribution to Journal › Article › Academic › peer-review

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.

Original language	English
Pages (from-to)	126-138
Journal	Epidemiology
Volume	36
Issue number	1
DOIs	https://doi.org/10.1097/EDE.0000000000001795
Publication status	Published - 1 Jan 2025
Externally published	Yes

Funding

EPICOLON: This work was supported by grants from Fondo de Investigación Sanitaria/FEDER (PI08/0024, PI08/1276, PS09/02368, P111/00219, PI11/00681, PI14/00173, PI14/00230, PI17/00509, 17/00878, PI20/00113, PI20/00226, Acción Transversal de Cáncer), Xunta de Galicia (PGIDIT07PXIB9101209PR), Ministerio de Economia y Competitividad (SAF07-64873, SAF 2010-19273, SAF2014-54453R), Fundación Científica de la Asociación Española contra el Cáncer (GCB13131592CAST), Beca Grupo de Trabajo “Oncología” AEG (Asociación Española de Gastroenterología), Fundación Privada Olga Torres, FP7 CHIBCHA Consortium, Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya, 2014SGR135, 2014SGR255, 2017SGR21, 2017SGR653), Catalan Tumour Bank Network (Pla Director d’Oncologia, Generalitat de Catalunya), PERIS (SLT002/16/00398, Generalitat de Catalunya), CERCA Programme (Generalitat de Catalunya) and COST Action BM1206 and CA17118. CIBERehd is funded by the Instituto de Salud Carlos III. ASTERISK: a Hospital Clinical Research Program (PHRC-BRD09/C) from the University Hospital Center of Nantes (CHU de Nantes) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC). LCCS: The Leeds Colorectal Cancer Study was funded by the Food Standards Agency and Cancer Research UK Programme Award (C588/A19167). ESTHER/VERDI. This work was supported by grants from the Baden-Württemberg Ministry of Science, Research and Arts and the German Cancer Aid. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 509348, 209057, 251553 and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. BMLynch was supported by MCRF18005 from the Victorian Cancer Agency. M Giannakis: Research funding from Servier and Janssen, unrelated to this study. NFCCR: This work was supported by an Interdisciplinary Health Research Team award from the Canadian Institutes of Health Research (CRT 43821); the National Institutes of Health, U.S. Department of Health and Human Serivces (U01 CA074783); and National Cancer Institute of Canada grants (18223 and 18226). The authors wish to acknowledge the contribution of Alexandre Belisle and the genotyping team of the McGill University and Génome Québec Innovation Centre, Montréal, Canada, for genotyping the Sequenom panel in the NFCCR samples. Funding was provided to Michael O. Woods by the Canadian Cancer Society Research Institute. The Colon Cancer Family Registry (CCFR, www.coloncfr.org) is supported in part by funding from the National Cancer Institute (NCI), National Institutes of Health (NIH) (award U01 CA167551). Support for case ascertainment was provided in part from the Surveillance, Epidemiology, and End Results (SEER) Program and the following U.S. state cancer registries: AZ, CO, MN, NC, NH; and by the Victoria Cancer Registry (Australia) and Ontario Cancer Registry (Canada). The CCFR Set-1 (Illumina 1M/1M-Duo) was supported by NIH awards U01 CA122839 and R01 CA143237 (to GC). The CCFR Set-3 (Affymetrix Axiom CORECT Set array) was supported by NIH award U19 CA148107 and R01 CA81488 (to SBG). The CCFR Set-4 (Illumina OncoArray 600K SNP array) was supported by NIH award U19 CA148107 (to SBG) and by the Center for Inherited Disease Research (CIDR), which is funded by the NIH to the Johns Hopkins University, contract number HHSN268201200008I. The content of this manuscript does not necessarily reflect the views or policies of the NCI, NIH or any of the collaborating centers in the Colon Cancer Family Registry (CCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government, any cancer registry, or the CCFR. Swedish Mammography Cohort and Cohort of Swedish Men: This work is supported by the Swedish Research Council /Infrastructure grant, the Swedish Cancer Foundation, and the Karolinska Institute´s Distinguished Professor Award to Alicja Wolk. PLCO: This work was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Funding was provided by National Institutes of Health (NIH), Genes, Environment and Health Initiative (GEI) Z01 CP 010200, NIH U01 HG004446, and NIH GEI U01 HG 004438. WHI: The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. This work was supported by the National Cancer Institute (grant P01 CA074184 to J.D.P. and P.A.N., grants R01 CA097325, R03 CA153323, and K05 CA152715 to P.A.N., and the National Center for Advancing Translational Sciences at the National Institutes of Health (grant KL2 TR000421 to A.N.B.-H.). CLUE II funding was from the National Cancer Institute (U01 CA086308, Early Detection Research Network; P30 CA006973), National Institute on Aging (U01 AG018033), and the American Institute for Cancer Research. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. Harvard cohorts: HPFS is supported by the National Institutes of Health (P01 CA055075, UM1 CA167552, U01 CA167552, R01 CA137178, R01 CA151993, and R35 CA197735), NHS by the National Institutes of Health (P01 CA087969, UM1 CA186107, R01 CA137178, R01 CA151993, and R35 CA197735), and PHS by the National Institutes of Health (R01 CA042182). REACH & SMS: This work was supported by the National Cancer Institute (grant P01 CA074184 to J.D.P. and P.A.N., grants R01 CA097325, R03 CA153323, and K05 CA152715 to P.A.N., and the National Center for Advancing Translational Sciences at the National Institutes of Health (grant KL2 TR000421 to A.N.B.-H.) MECC: This work was supported by the National Institutes of Health, U.S. Department of Health and Human Services (R01 CA081488, R01 CA197350, U19 CA148107, R01 CA242218, and a generous gift from Daniel and Maryann Fong. NCCCS I & II: We acknowledge funding support for this project from the National Institutes of Health, R01 CA066635 and P30 DK034987. Kentucky: This work was supported by the following grant support: Clinical Investigator Award from Damon Runyon Cancer Research Foundation (CI-8); NCI R01CA136726. Funding: Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO): National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services (U01 CA137088, R01 CA059045, U01 CA164930, R21 CA191312, R01 CA244588, R01 206279, R01 201407, R01 CA488857, P20 CA252733). Genotyping/Sequencing services were provided by the Center for Inherited Disease Research (CIDR) contract number HHSN268201700006I and HHSN268201200008I . This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA015704. Scientific Computing Infrastructure at Fred Hutch funded by ORIP grant S10OD028685. C.E. Thomas is supported by L70 CA284301, T32 CA094880, and T32 CA009168. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Cancer Institutes or the National Institutes of Health. SELECT: Research reported in this publication was supported in part by the National Cancer Institute of the National Institutes of Health under Award Numbers U10 CA037429 (CD Blanke), and UM1 CA182883 (CM Tangen/IM Thompson). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Funders	Funder number
Agència de Gestió d'Ajuts Universitaris i de Recerca
Groupement des Entreprises Françaises dans la lutte contre le Cancer
Programme Award
Conseil Régional des Pays de la Loire
Ministerium für Wissenschaft, Forschung und Kunst Baden-Württemberg
Cancer Council Victoria
Instituto de Salud Carlos III
Fundación Privada Olga Torres
Johnson & Johnson Innovative Medicine
Interdisciplinary Health Research Team award
Victoria Cancer Registry
FP7 CHIBCHA Consortium
Food Standards Agency
Swedish Cancer Foundation
Division of Cancer Prevention, National Cancer Institute
Victorian Cancer Agency
Karolinska Institutet
Fondo de Investigación Sanitaria
National Heart, Lung, and Blood Institute
Division of Cancer Epidemiology and Genetics
VicHealth
Centre Hospitalier Universitaire de Nantes
Deutsche Krebshilfe
Association Anne de Bretagne Genetique
National Center for Advancing Translational Sciences
Servier
Ligue Régionale Contre le Cancer
Vetenskapsrådet
American Institute for Cancer Research
National Institutes of Health	Z01 CP 010200, R35 CA197735, U01 HG004446, U01 CA167552, R01 CA137178, P01 CA087969, U01 CA167551, KL2 TR000421, R01 CA042182, R01 CA066635, P30 DK034987, R01 CA151993, P01 CA055075, U10 CA037429, GEI U01 HG 004438, UM1 CA182883, UM1 CA186107
European Cooperation in Science and Technology	BM1206, CA17118
National Institute on Aging	U01 AG018033
U.S. Department of Health and Human Services	HHSN268201100004C, HHSN268201100003C, U19 CA148107, U01 CA074783, R01 CA197350, HHSN271201100004C, R01 CA081488, R01 CA242218, HHSN268201100002C, HHSN268201100046C, HHSN268201100001C
Canadian Institutes of Health Research	CRT 43821
Damon Runyon Cancer Research Foundation	CI-8
Office of Research Infrastructure Programs	S10OD028685, T32 CA094880, L70 CA284301, T32 CA009168
National Cancer Institute	P30 CA006973, P01 CA074184, R01CA136726, U01 CA086308, R03 CA153323, P30 CA015704, K05 CA152715, R01 CA097325
Johns Hopkins University	HHSN268201200008I
Generalitat de Catalunya	2017SGR653, 2017SGR21, 2014SGR135, 2014SGR255
National Cancer Institute of Canada	18223, 18226
National Health and Medical Research Council	251553, 504711, 209057, 509348, MCRF18005
Xunta de Galicia	PGIDIT07PXIB9101209PR
Xarxa de Bancs de Tumors de Catalunya	SLT002/16/00398
Ontario Cancer Registry	U01 CA122839, R01 CA143237, R01 CA81488
Cancer Research UK	C588/A19167
Fundación Científica de la Asociación Española	GCB13131592CAST
European Regional Development Fund	PI20/00113, PI20/00226, PI17/00509, PI14/00173, PI11/00681, P111/00219, PS09/02368, PI08/1276, PI14/00230, 17/00878, PI08/0024
Ministerio de Economía y Competitividad	SAF 2010-19273, SAF07-64873, SAF2014-54453R

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10.1097/EDE.0000000000001795

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Cite this

Thomas, C. E., Lin, Y., Kim, M., Kawaguchi, E. S., Qu, C., Um, C. Y., Lynch, B. M., Van Guelpen, B., Tsilidis, K., Carreras-Torres, R., Van Duijnhoven, F. J. B., Sakoda, L. C., Campbell, P. T., Tian, Y., Chang-Claude, J., Bézieau, S., Budiarto, A., Palmer, J. R., Newcomb, P. A., ... Hsu, L. (2025). Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk. Epidemiology, 36(1), 126-138. https://doi.org/10.1097/EDE.0000000000001795

@article{9c2aa334fc8540b8b98b347b444467e0,

title = "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.",

author = "Thomas, \{Claire E.\} and Yi Lin and Michelle Kim and Kawaguchi, \{Eric S.\} and Conghui Qu and Um, \{Caroline Y.\} and Lynch, \{Brigid M.\} and \{Van Guelpen\}, Bethany and Kostas Tsilidis and Robert Carreras-Torres and \{Van Duijnhoven\}, \{Franzel J.B.\} and Sakoda, \{Lori C.\} and Campbell, \{Peter T.\} and Yu Tian and Jenny Chang-Claude and St{\'e}phane B{\'e}zieau and Arif Budiarto and Palmer, \{Julie R.\} and Newcomb, \{Polly A.\} and Graham Casey and \{Le Marchandz\}, Loic and Marios Giannakis and Li, \{Christopher I.\} and Andrea Gsur and Christina Newton and Mireia Ob{\'o}n-Santacana and Victor Moreno and Pavel Vodicka and Hermann Brenner and Michael Hoffmeister and Pellatt, \{Andrew J.\} and Schoen, \{Robert E.\} and Niki Dimou and Neil Murphy and Gunter, \{Marc J.\} and Sergi Castellv{\'i}-Bel and Figueiredo, \{Jane C.\} and Chan, \{Andrew T.\} and Mingyang Song and Li Li and Bishop, \{D. Timothy\} and Gruber, \{Stephen B.\} and Baurley, \{James W.\} and Bien, \{Stephanie A.\} and Conti, \{David V.\} and Huyghe, \{Jeroen R.\} and Anshul Kundaje and Yu-Ru Su and Jun Wang and Keku, \{Temitope O.\} and Woods, \{Michael O.\} and Berndt, \{Sonja I.\} and Chanock, \{Stephen J.\} and Tangen, \{Catherine M.\} and Alicja Wolk and Andrea Burnett-Hartman and Wu, \{Anna H.\} and Emily White and Devall, \{Matthew A.\} and Virginia D{\'i}ez-Obrero and Drew, \{David A\} and Edward Giovannucci and Akihisa Hidaka and Kim, \{Andre E.\} and Lewinger, \{Juan Pablo\} and John Morrison and Jennifer Ose and Nikos Papadimitriou and Bens Pardamean and Peoples, \{Anita R.\} and Ruiz-Narvaez, \{Edward A.\} and Anna Shcherbina and Stern, \{Mariana C.\} and Xuechen Chen and Thomas, \{Duncan C.\} and Platz, \{Elizabeth A.\} and Gauderman, \{W. James\} and Ulrike Peters and Li Hsu",

year = "2025",

month = jan,

day = "1",

doi = "10.1097/EDE.0000000000001795",

language = "English",

volume = "36",

pages = "126--138",

journal = "Epidemiology",

issn = "1044-3983",

publisher = "Lippincott Williams and Wilkins",

number = "1",

}

Thomas, CE, Lin, Y, Kim, M, Kawaguchi, ES, Qu, C, Um, CY, Lynch, BM, Van Guelpen, B, Tsilidis, K, Carreras-Torres, R, Van Duijnhoven, FJB, Sakoda, LC, Campbell, PT, Tian, Y, Chang-Claude, J, Bézieau, S, Budiarto, A, Palmer, JR, Newcomb, PA, Casey, G, Le Marchandz, L, Giannakis, M, Li, CI, Gsur, A, Newton, C, Obón-Santacana, M, Moreno, V, Vodicka, P, Brenner, H, Hoffmeister, M, Pellatt, AJ, Schoen, RE, Dimou, N, Murphy, N, Gunter, MJ, Castellví-Bel, S, Figueiredo, JC, Chan, AT, Song, M, Li, L, Bishop, DT, Gruber, SB, Baurley, JW, Bien, SA, Conti, DV, Huyghe, JR, Kundaje, A, Su, Y-R, Wang, J, Keku, TO, Woods, MO, Berndt, SI, Chanock, SJ, Tangen, CM, Wolk, A, Burnett-Hartman, A, Wu, AH, White, E, Devall, MA, Díez-Obrero, V, Drew, DA, Giovannucci, E, Hidaka, A, Kim, AE, Lewinger, JP, Morrison, J, Ose, J, Papadimitriou, N, Pardamean, B, Peoples, AR, Ruiz-Narvaez, EA, Shcherbina, A, Stern, MC, Chen, X, Thomas, DC, Platz, EA, Gauderman, WJ, Peters, U & Hsu, L 2025, 'Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk', Epidemiology, vol. 36, no. 1, pp. 126-138. https://doi.org/10.1097/EDE.0000000000001795

TY - JOUR

T1 - Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk

AU - Thomas, Claire E.

AU - Lin, Yi

AU - Kim, Michelle

AU - Kawaguchi, Eric S.

AU - Qu, Conghui

AU - Um, Caroline Y.

AU - Lynch, Brigid M.

AU - Van Guelpen, Bethany

AU - Tsilidis, Kostas

AU - Carreras-Torres, Robert

AU - Van Duijnhoven, Franzel J.B.

AU - Sakoda, Lori C.

AU - Campbell, Peter T.

AU - Tian, Yu

AU - Chang-Claude, Jenny

AU - Bézieau, Stéphane

AU - Budiarto, Arif

AU - Palmer, Julie R.

AU - Newcomb, Polly A.

AU - Casey, Graham

AU - Le Marchandz, Loic

AU - Giannakis, Marios

AU - Li, Christopher I.

AU - Gsur, Andrea

AU - Newton, Christina

AU - Obón-Santacana, Mireia

AU - Moreno, Victor

AU - Vodicka, Pavel

AU - Brenner, Hermann

AU - Hoffmeister, Michael

AU - Pellatt, Andrew J.

AU - Schoen, Robert E.

AU - Dimou, Niki

AU - Murphy, Neil

AU - Gunter, Marc J.

AU - Castellví-Bel, Sergi

AU - Figueiredo, Jane C.

AU - Chan, Andrew T.

AU - Song, Mingyang

AU - Li, Li

AU - Bishop, D. Timothy

AU - Gruber, Stephen B.

AU - Baurley, James W.

AU - Bien, Stephanie A.

AU - Conti, David V.

AU - Huyghe, Jeroen R.

AU - Kundaje, Anshul

AU - Su, Yu-Ru

AU - Wang, Jun

AU - Keku, Temitope O.

AU - Woods, Michael O.

AU - Berndt, Sonja I.

AU - Chanock, Stephen J.

AU - Tangen, Catherine M.

AU - Wolk, Alicja

AU - Burnett-Hartman, Andrea

AU - Wu, Anna H.

AU - White, Emily

AU - Devall, Matthew A.

AU - Díez-Obrero, Virginia

AU - Drew, David A

AU - Giovannucci, Edward

AU - Hidaka, Akihisa

AU - Kim, Andre E.

AU - Lewinger, Juan Pablo

AU - Morrison, John

AU - Ose, Jennifer

AU - Papadimitriou, Nikos

AU - Pardamean, Bens

AU - Peoples, Anita R.

AU - Ruiz-Narvaez, Edward A.

AU - Shcherbina, Anna

AU - Stern, Mariana C.

AU - Chen, Xuechen

AU - Thomas, Duncan C.

AU - Platz, Elizabeth A.

AU - Gauderman, W. James

AU - Peters, Ulrike

AU - Hsu, Li

PY - 2025/1/1

Y1 - 2025/1/1

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85205921385

U2 - 10.1097/EDE.0000000000001795

DO - 10.1097/EDE.0000000000001795

M3 - Article

SN - 1044-3983

VL - 36

SP - 126

EP - 138

JO - Epidemiology

JF - Epidemiology

IS - 1

ER -

Characterization of Additive Gene-environment Interactions For Colorectal Cancer Risk

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