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Using gene-environment interactions to explore pathways for colorectal cancer risk

  • Emmanouil Bouras
  • , Ren Yu
  • , Andre E. Kim
  • , Georgios Markozannes
  • , Neil Murphy
  • , Demetrius Albanes
  • , Laura N. Anderson
  • , Elizabeth L. Barry
  • , Sonja I. Berndt
  • , D. Timothy Bishop
  • , Hermann Brenner
  • , Andrea Burnett-Hartman
  • , Peter T. Campbell
  • , Robert Carreras-Torres
  • , Andrew T. Chan
  • , Iona Cheng
  • , Matthew A. Devall
  • , Virginia Diez-Obrero
  • , Niki Dimou
  • , David A. Drew
  • Stephen B. Gruber, Andrea Gsur, Michael Hoffmeister, Li Hsu, Jeroen R. Huyghe, Eric Kawaguchi, Temitope O. Keku, Anshul Kundaje, Sébastien Küry, Loïc Le Marchand, Juan Pablo Lewinger, Li Li, Brigid M. Lynch, Victor Moreno, John L. Morrison, Christina C. Newton, Mireia Obón-Santacana, Julie R. Palmer, Nikos Papadimitriou, Andrew J. Pellatt, Anita R. Peoples, Paul D.P. Pharoah, Elizabeth A. Platz, Conghui Qu, Edward Ruiz-Narvaez, Joel Sanchez Mendez, Robert E. Schoen, Mariana C. Stern, Claire E. Thomas, Yu Tian, Caroline Y. Um, Kala Visvanathan, Pavel Vodicka, Veronika Vymetalkova, Emily White, Alicja Wolk, Michael O. Woods, Anna H. Wu, Marc J. Gunter, W. James Gauderman, Ulrike Peters, Marina Evangelou, Konstantinos K. Tsilidis

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Colorectal cancer (CRC) is a significant public health concern, highlighting the critical need for identifying novel intervention targets for its prevention. Methods: We conducted genome-wide interaction analyses for 15 exposures with established or putative CRC risk [body mass index (BMI), height, physical activity, smoking, type 2 diabetes, use of menopausal hormone therapy, non-steroidal anti-inflammatory drugs, and intake of alcohol, calcium, fibre, folate, fruits, processed meat, red meat, and vegetables], and used interaction estimates to explore pathways and genes underlying CRC risk. The adaptive combination of Bayes Factors (ADABF), and over-representation analysis (ORA) were used for pathway analyses, and findings were further investigated using publicly available resources [hallmarks of cancer, Open Targets Platform (OTP)]. Findings: A total of 1973 pathways using ADABF, and 840 pathways using ORA, out of the 2950 analysed, were enriched (P < 0.05) for at least one exposure, as well as 1227 genes within the enriched pathways. Data were available for 811/1227 coding genes in the OTP, 241 of which were supported by strong relative abundance of prior evidence (overall OTP score > 0.05). Fifty percent of the genes (617/1227) mapped to at least one hallmark of cancer, most of which (388/617) pertained to the Sustaining Proliferative Signalling hallmark. Our findings reflect previously established pathways for CRC risk and highlight the emerging importance of several less studied genes. Common pathways were found for several combinations of exposures, potentially suggesting common underlying mechanisms. Interpretation: The results of the present analysis provide a basis for further functional research. If confirmed, they may help elucidate the etiological associations between risk factors and CRC risk and ultimately inform personalized prevention strategies. Funding: This study was funded by Cancer Research UK (CRUK; grant number: PPRCPJT∖100005) and World Cancer Research Fund International (WCRF; IIG_FULL_2020_022). Funding for grant IIG_FULL_2020_022 was obtained froma Wereld Kanker Onderzoek Fondsy (WKOF) as part of the World Cancer Research Fund International grant programme. Full funding details for the individual consortia are provided in the acknowledgements.

Original languageEnglish (US)
Article number105964
JournalEBioMedicine
Volume121
DOIs
StatePublished - Nov 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Colorectal cancer
  • Gene-environment interactions
  • Mechanisms
  • Molecular pathways
  • Pathway analysis

ASJC Scopus subject areas

  • General Medicine
  • General Biochemistry, Genetics and Molecular Biology

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