Nutrients (Aug 2022)
Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer
- Zoe S. Grenville,
- Urwah Noor,
- Mathilde His,
- Vivian Viallon,
- Sabina Rinaldi,
- Elom K. Aglago,
- Pilar Amiano,
- Louise Brunkwall,
- María Dolores Chirlaque,
- Isabel Drake,
- Fabian Eichelmann,
- Heinz Freisling,
- Sara Grioni,
- Alicia K. Heath,
- Rudolf Kaaks,
- Verena Katzke,
- Ana-Lucia Mayén-Chacon,
- Lorenzo Milani,
- Conchi Moreno-Iribas,
- Valeria Pala,
- Anja Olsen,
- Maria-Jose Sánchez,
- Matthias B. Schulze,
- Anne Tjønneland,
- Konstantinos K. Tsilidis,
- Elisabete Weiderpass,
- Anna Winkvist,
- Raul Zamora-Ros,
- Timothy J. Key,
- Karl Smith-Byrne,
- Ruth C. Travis,
- Julie A. Schmidt
Affiliations
- Zoe S. Grenville
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Urwah Noor
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Mathilde His
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
- Vivian Viallon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
- Sabina Rinaldi
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
- Elom K. Aglago
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
- Pilar Amiano
- Ministry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastian, Spain
- Louise Brunkwall
- Department of Clinical Sciences, Lund University, 221 84 Malmö, Sweden
- María Dolores Chirlaque
- CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
- Isabel Drake
- Department of Clinical Sciences, Lund University, 221 84 Malmö, Sweden
- Fabian Eichelmann
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558 Nuthetal, Germany
- Heinz Freisling
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
- Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
- Alicia K. Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
- Rudolf Kaaks
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Ana-Lucia Mayén-Chacon
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
- Lorenzo Milani
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, 10124 Turin, Italy
- Conchi Moreno-Iribas
- CIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, Spain
- Valeria Pala
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, Italy
- Anja Olsen
- Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark
- Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), 18011 Granada, Spain
- Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, 14558 Nuthetal, Germany
- Anne Tjønneland
- Danish Cancer Society Research Center, DK-2100 Copenhagen, Denmark
- Konstantinos K. Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
- Elisabete Weiderpass
- International Agency for Research on Cancer, World Health Organization, 69008 Lyon, France
- Anna Winkvist
- Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, 901 87 Umeå, Sweden
- Raul Zamora-Ros
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, 08908 Barcelona, Spain
- Timothy J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Karl Smith-Byrne
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- Julie A. Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UK
- DOI
- https://doi.org/10.3390/nu14163306
- Journal volume & issue
-
Vol. 14,
no. 16
p. 3306
Abstract
Three metabolite patterns have previously shown prospective inverse associations with the risk of aggressive prostate cancer within the European Prospective Investigation into Cancer and Nutrition (EPIC). Here, we investigated dietary and lifestyle correlates of these three prostate cancer-related metabolite patterns, which included: 64 phosphatidylcholines and three hydroxysphingomyelins (Pattern 1), acylcarnitines C18:1 and C18:2, glutamate, ornithine, and taurine (Pattern 2), and 8 lysophosphatidylcholines (Pattern 3). In a two-stage cross-sectional discovery (n = 2524) and validation (n = 518) design containing 3042 men free of cancer in EPIC, we estimated the associations of 24 dietary and lifestyle variables with each pattern and the contributing individual metabolites. Associations statistically significant after both correction for multiple testing (False Discovery Rate = 0.05) in the discovery set and at p < 0.05 in the validation set were considered robust. Intakes of alcohol, total fish products, and its subsets total fish and lean fish were positively associated with Pattern 1. Body mass index (BMI) was positively associated with Pattern 2, which appeared to be driven by a strong positive BMI-glutamate association. Finally, both BMI and fatty fish were inversely associated with Pattern 3. In conclusion, these results indicate associations of fish and its subtypes, alcohol, and BMI with metabolite patterns that are inversely associated with risk of aggressive prostate cancer.
Keywords