Roland Wedekind1, Pekka Keski-Rahkonen1, Nivonirina Robinot1, Vivian Viallon1, Joseph A Rothwell2,3, Marie-Christine Boutron-Ruault2,3, Krasimira Aleksandrova4,5, Clemens Wittenbecher6,7,8, Matthias B Schulze5,6, Jytte Halkjaer9, Agnetha Linn Rostgaard-Hansen9, Rudolf Kaaks10, Verena Katzke10, Giovanna Masala11, Rosario Tumino12, Maria Santucci de Magistris13, Vittorio Krogh14, Carlotta Sacerdote15, Paula Jakszyn16,17, Elisabete Weiderpass18, Marc J Gunter1, Inge Huybrechts1, Augustin Scalbert1. 1. Nutrition and Metabolism Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, Lyon, France. 2. CESP, Faculté de Medicine, Université Paris-Saclay, Inserm, Villejuif, France. 3. Institut Gustave Roussy, Villejuif, France. 4. Department of Nutrition and Gerontology, Nutrition, Immunity and Metabolism Senior Scientist Group, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany. 5. Institute of Nutritional Science, University of Potsdam, Potsdam, Germany. 6. Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany. 7. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 8. German Center of Diabetes Research (DZD), Neuherberg, Germany. 9. Danish Cancer Society Research Centre, Diet, Genes and Environment, Copenhagen, Denmark. 10. Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany. 11. Cancer Risk Factors and Life-Style Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network - ISPRO, Florence, Italy. 12. Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7), Ragusa, Italy. 13. AOU FEDERICO II, Naples, Italy. 14. Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milano, Italy. 15. Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital, Turin, Italy. 16. Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology, Barcelona, Spain. 17. Blanquerna School of Health Sciences, Ramon Llull University, Barcelona, Spain. 18. International Agency for Research on Cancer, 150 cours Albert Thomas, Lyon, France.
Abstract
SCOPE: Processed meat intake has been associated with adverse health outcomes. However, little is known about the type of processed meat more particularly responsible for these effects. This study aims to identify novel biomarkers for processed meat intake. METHODS AND RESULTS: In a controlled randomized cross-over dietary intervention study, 12 healthy volunteers consume different processed and non-processed meats for 3 consecutive days each. Metabolomics analyses are applied on post-intervention fasting blood and urine samples to identify discriminating molecular features of processed meat intake. Nine and five pepper alkaloid metabolites, including piperine, are identified as major discriminants of salami intake in urine and plasma, respectively. The associations with processed meat intake are tested for replication in a cross-sectional study (n = 418) embedded within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Three of the serum metabolites including piperine are associated with habitual intake of sausages and to a lesser extent of total processed meat. CONCLUSION:Pepper alkaloids are major discriminants of intake for sausages that contain high levels of pepper used as ingredient. Further work is needed to assess if pepper alkaloids in combination with other metabolites may serve as biomarkers of processed meat intake.
RCT Entities:
SCOPE: Processed meat intake has been associated with adverse health outcomes. However, little is known about the type of processed meat more particularly responsible for these effects. This study aims to identify novel biomarkers for processed meat intake. METHODS AND RESULTS: In a controlled randomized cross-over dietary intervention study, 12 healthy volunteers consume different processed and non-processed meats for 3 consecutive days each. Metabolomics analyses are applied on post-intervention fasting blood and urine samples to identify discriminating molecular features of processed meat intake. Nine and five pepper alkaloid metabolites, including piperine, are identified as major discriminants of salami intake in urine and plasma, respectively. The associations with processed meat intake are tested for replication in a cross-sectional study (n = 418) embedded within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Three of the serum metabolites including piperine are associated with habitual intake of sausages and to a lesser extent of total processed meat. CONCLUSION:Pepper alkaloids are major discriminants of intake for sausages that contain high levels of pepper used as ingredient. Further work is needed to assess if pepper alkaloids in combination with other metabolites may serve as biomarkers of processed meat intake.
Authors: Roland Wedekind; Joseph A Rothwell; Vivian Viallon; Pekka Keski-Rahkonen; Julie A Schmidt; Veronique Chajes; Vna Katzke; Theron Johnson; Maria Santucci de Magistris; Vittorio Krogh; Pilar Amiano; Carlotta Sacerdote; Daniel Redondo-Sánchez; José María Huerta; Anne Tjønneland; Pratik Pokharel; Paula Jakszyn; Rosario Tumino; Eva Ardanaz; Torkjel M Sandanger; Anna Winkvist; Johan Hultdin; Matthias B Schulze; Elisabete Weiderpass; Marc J Gunter; Inge Huybrechts; Augustin Scalbert Journal: Clin Nutr Date: 2022-06-08 Impact factor: 7.643