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Dietary patterns, untargeted metabolite profiles and their association with colorectal cancer risk.
Bodén, Stina; Zheng, Rui; Ribbenstedt, Anton; Landberg, Rikard; Harlid, Sophia; Vidman, Linda; Gunter, Marc J; Winkvist, Anna; Johansson, Ingegerd; Van Guelpen, Bethany; Brunius, Carl.
Afiliación
  • Bodén S; Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden. stina.boden@umu.se.
  • Zheng R; Department of Clinical Sciences, Pediatrics, Umeå University, Umeå, Sweden. stina.boden@umu.se.
  • Ribbenstedt A; Department of Surgical Sciences, The EpiHub, Uppsala University, Uppsala, Sweden.
  • Landberg R; Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden.
  • Harlid S; Department of Life Sciences, Chalmers University of Technology, Gothenburg, Sweden.
  • Vidman L; Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden.
  • Gunter MJ; Department of Diagnostics and Intervention, Oncology, Umeå University, Umeå, Sweden.
  • Winkvist A; International Agency for Research On Cancer, Nutrition and Metabolism Section, 69372, Lyon Cedex 08, France.
  • Johansson I; Cancer Epidemiology and Prevention Research Unit, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
  • Van Guelpen B; Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Brunius C; Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden.
Sci Rep ; 14(1): 2244, 2024 01 26.
Article en En | MEDLINE | ID: mdl-38278865
ABSTRACT
We investigated data-driven and hypothesis-driven dietary patterns and their association to plasma metabolite profiles and subsequent colorectal cancer (CRC) risk in 680 CRC cases and individually matched controls. Dietary patterns were identified from combined exploratory/confirmatory factor analysis. We assessed association to LC-MS metabolic profiles by random forest regression and to CRC risk by multivariable conditional logistic regression. Principal component analysis was used on metabolite features selected to reflect dietary exposures. Component scores were associated to CRC risk and dietary exposures using partial Spearman correlation. We identified 12 data-driven dietary patterns, of which a breakfast food pattern showed an inverse association with CRC risk (OR per standard deviation increase 0.89, 95% CI 0.80-1.00, p = 0.04). This pattern was also inversely associated with risk of distal colon cancer (0.75, 0.61-0.96, p = 0.01) and was more pronounced in women (0.69, 0.49-0.96, p = 0.03). Associations between meat, fast-food, fruit soup/rice patterns and CRC risk were modified by tumor location in women. Alcohol as well as fruit and vegetables associated with metabolite profiles (Q2 0.22 and 0.26, respectively). One metabolite reflecting alcohol intake associated with increased CRC risk, whereas three metabolites reflecting fiber, wholegrain, and fruit and vegetables associated with decreased CRC risk.
Asunto(s)

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Dieta Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Suecia

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Dieta Tipo de estudio: Etiology_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Sci Rep Año: 2024 Tipo del documento: Article País de afiliación: Suecia