Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer
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 m...
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MDPI AG
2022-08-01
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| author | 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 |
| author_facet | 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 |
| author_sort | Zoe S. Grenville |
| collection | DOAJ |
| description | 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 (<i>n</i> = 2524) and validation (<i>n</i> = 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 <i>p</i> < 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. |
| first_indexed | 2024-03-09T04:00:24Z |
| format | Article |
| id | doaj.art-62763c18493642f99355c742982d3884 |
| institution | Directory Open Access Journal |
| issn | 2072-6643 |
| language | English |
| last_indexed | 2024-03-09T04:00:24Z |
| publishDate | 2022-08-01 |
| publisher | MDPI AG |
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| series | Nutrients |
| spelling | doaj.art-62763c18493642f99355c742982d38842023-12-03T14:14:08ZengMDPI AGNutrients2072-66432022-08-011416330610.3390/nu14163306Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate CancerZoe S. Grenville0Urwah Noor1Mathilde His2Vivian Viallon3Sabina Rinaldi4Elom K. Aglago5Pilar Amiano6Louise Brunkwall7María Dolores Chirlaque8Isabel Drake9Fabian Eichelmann10Heinz Freisling11Sara Grioni12Alicia K. Heath13Rudolf Kaaks14Verena Katzke15Ana-Lucia Mayén-Chacon16Lorenzo Milani17Conchi Moreno-Iribas18Valeria Pala19Anja Olsen20Maria-Jose Sánchez21Matthias B. Schulze22Anne Tjønneland23Konstantinos K. Tsilidis24Elisabete Weiderpass25Anna Winkvist26Raul Zamora-Ros27Timothy J. Key28Karl Smith-Byrne29Ruth C. Travis30Julie A. Schmidt31Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UKCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UKNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, FranceNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, FranceNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, FranceDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UKMinistry of Health of the Basque Government, Sub Directorate for Public Health and Addictions of Gipuzkoa, 20013 San Sebastian, SpainDepartment of Clinical Sciences, Lund University, 221 84 Malmö, SwedenCIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, SpainDepartment of Clinical Sciences, Lund University, 221 84 Malmö, SwedenDepartment of Molecular Epidemiology, German Institute of Human Nutrition, 14558 Nuthetal, GermanyNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, FranceEpidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, ItalyDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UKDepartment of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyDepartment of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, GermanyNutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, 69008 Lyon, FranceCancer Epidemiology Unit, Department of Medical Sciences, University of Turin, 10124 Turin, ItalyCIBER of Epidemiology and Public Health (CIBERESP), 28029 Madrid, SpainEpidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20133 Milan, ItalyDanish Cancer Society Research Center, DK-2100 Copenhagen, DenmarkEscuela Andaluza de Salud Pública (EASP), 18011 Granada, SpainDepartment of Molecular Epidemiology, German Institute of Human Nutrition, 14558 Nuthetal, GermanyDanish Cancer Society Research Center, DK-2100 Copenhagen, DenmarkDepartment of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UKInternational Agency for Research on Cancer, World Health Organization, 69008 Lyon, FranceSustainable Health, Department of Public Health and Clinical Medicine, Umeå University, 901 87 Umeå, SwedenUnit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, 08908 Barcelona, SpainCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UKCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UKCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UKCancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford OX3 7LF, UKThree 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 (<i>n</i> = 2524) and validation (<i>n</i> = 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 <i>p</i> < 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.https://www.mdpi.com/2072-6643/14/16/3306metabolitesdietprostate cancercross-sectional |
| spellingShingle | 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 Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer Nutrients metabolites diet prostate cancer cross-sectional |
| title | Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer |
| title_full | Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer |
| title_fullStr | Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer |
| title_full_unstemmed | Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer |
| title_short | Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer |
| title_sort | diet and bmi correlate with metabolite patterns associated with aggressive prostate cancer |
| topic | metabolites diet prostate cancer cross-sectional |
| url | https://www.mdpi.com/2072-6643/14/16/3306 |
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