Lucie Lécuyer1, Agnès Victor Bala2, Mélanie Deschasaux1, Nadia Bouchemal2, Mohamed Nawfal Triba2, Marie-Paule Vasson3,4, Adrien Rossary3, Aicha Demidem3, Pilar Galan1, Serge Hercberg1,5, Valentin Partula1, Laurence Le Moyec6, Bernard Srour1, Thibault Fiolet1, Paule Latino-Martel1, Emmanuelle Kesse-Guyot1, Philippe Savarin2, Mathilde Touvier1. 1. Sorbonne Paris Cité Epidemiology and Statistics Research Center (CRESS), French National Institute of Health and Medical Research (Inserm) U1153, French National Institute for Agricultural Research (Inra) U1125, French National Conservatory of Arts and Crafts (Cnam), Paris 13 University, Nutritional Epidemiology Research Team (EREN), 93017 Bobigny Cedex, France. 2. Chemistry Structures Properties of Biomaterials and Therapeutic Agents (CSPBAT), The National Center for Scientific Research (CNRS) 7244, Paris 13 University, Spectroscopy Biomolecules and Biological Environment (SBMB), 93017 Bobigny Cedex, France. 3. Clermont Auvergne University, INRA, Human Nutrition Unit (UNH), CRNH Auvergne, 63009 Clermont-Ferrand Cedex, France. 4. Anticancer Center Jean-Perrin, CHU Clermont-Ferrand, 63011 Clermont-Ferrand Cedex, France. 5. Public Health Department, Avicenne Hospital, 93000 Bobigny, France. 6. UBIAE, INSERM, Evry University, Paris-Saclay University, 91025 Evry, France.
Abstract
Background: Combination of metabolomics and epidemiological approaches opens new perspectives for ground-breaking discoveries. The aim of the present study was to investigate for the first time whether plasma untargeted metabolomic profiles, established from a simple blood draw from healthy women, could contribute to predict the risk of developing breast cancer within the following decade and to better understand the aetiology of this complex disease. Methods: A prospective nested case-control study was set up in the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, including 206 breast cancer cases diagnosed during a 13-year follow-up and 396 matched controls. Untargeted nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples. Multivariable conditional logistic regression models were computed for each individual NMR variable and for combinations of variables derived by principal component analysis. Results: Several metabolomic variables from 1D NMR spectroscopy were associated with breast cancer risk. Women characterized by higher fasting plasma levels of valine, lysine, arginine, glutamine, creatine, creatinine and glucose, and lower plasma levels of lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds and unsaturated lipids had a higher risk of developing breast cancer. P-values ranged from 0.00007 [odds ratio (OR)T3vsT1=0.37 (0.23-0.61) for glycerol-derived compounds] to 0.04 [ORT3vsT1=1.61 (1.02-2.55) for glutamine]. Conclusion: This study highlighted associations between baseline NMR plasma metabolomic signatures and long-term breast cancer risk. These results provide interesting insights to better understand complex mechanisms involved in breast carcinogenesis and evoke plasma metabolic disorders favourable for carcinogenesis initiation. This study may contribute to develop screening strategies for the identification of at-risk women for breast cancer well before symptoms appear.
Background: Combination of metabolomics and epidemiological approaches opens new perspectives for ground-breaking discoveries. The aim of the present study was to investigate for the first time whether plasma untargeted metabolomic profiles, established from a simple blood draw from healthy women, could contribute to predict the risk of developing breast cancer within the following decade and to better understand the aetiology of this complex disease. Methods: A prospective nested case-control study was set up in the Supplémentation en Vitamines et Minéraux Antioxydants (SU.VI.MAX) cohort, including 206 breast cancer cases diagnosed during a 13-year follow-up and 396 matched controls. Untargeted nuclear magnetic resonance (NMR) metabolomic profiles were established from baseline plasma samples. Multivariable conditional logistic regression models were computed for each individual NMR variable and for combinations of variables derived by principal component analysis. Results: Several metabolomic variables from 1D NMR spectroscopy were associated with breast cancer risk. Women characterized by higher fasting plasma levels of valine, lysine, arginine, glutamine, creatine, creatinine and glucose, and lower plasma levels of lipoproteins, lipids, glycoproteins, acetone, glycerol-derived compounds and unsaturated lipids had a higher risk of developing breast cancer. P-values ranged from 0.00007 [odds ratio (OR)T3vsT1=0.37 (0.23-0.61) for glycerol-derived compounds] to 0.04 [ORT3vsT1=1.61 (1.02-2.55) for glutamine]. Conclusion: This study highlighted associations between baseline NMR plasma metabolomic signatures and long-term breast cancer risk. These results provide interesting insights to better understand complex mechanisms involved in breast carcinogenesis and evoke plasma metabolic disorders favourable for carcinogenesis initiation. This study may contribute to develop screening strategies for the identification of at-risk women for breast cancer well before symptoms appear.
Authors: Thore Buergel; Jakob Steinfeldt; Greg Ruyoga; Maik Pietzner; Daniele Bizzarri; Dina Vojinovic; Julius Upmeier Zu Belzen; Lukas Loock; Paul Kittner; Lara Christmann; Noah Hollmann; Henrik Strangalies; Jana M Braunger; Benjamin Wild; Scott T Chiesa; Joachim Spranger; Fabian Klostermann; Erik B van den Akker; Stella Trompet; Simon P Mooijaart; Naveed Sattar; J Wouter Jukema; Birgit Lavrijssen; Maryam Kavousi; Mohsen Ghanbari; Mohammad A Ikram; Eline Slagboom; Mika Kivimaki; Claudia Langenberg; John Deanfield; Roland Eils; Ulf Landmesser Journal: Nat Med Date: 2022-09-22 Impact factor: 87.241
Authors: Kristen D Brantley; Oana A Zeleznik; Bernard Rosner; Rulla M Tamimi; Julian Avila-Pacheco; Clary B Clish; A Heather Eliassen Journal: Cancer Epidemiol Biomarkers Prev Date: 2022-04-01 Impact factor: 4.090
Authors: Mathilde His; Vivian Viallon; Laure Dossus; Audrey Gicquiau; David Achaintre; Augustin Scalbert; Pietro Ferrari; Isabelle Romieu; N Charlotte Onland-Moret; Elisabete Weiderpass; Christina C Dahm; Kim Overvad; Anja Olsen; Anne Tjønneland; Agnès Fournier; Joseph A Rothwell; Gianluca Severi; Tilman Kühn; Renée T Fortner; Heiner Boeing; Antonia Trichopoulou; Anna Karakatsani; Georgia Martimianaki; Giovanna Masala; Sabina Sieri; Rosario Tumino; Paolo Vineis; Salvatore Panico; Carla H van Gils; Therese H Nøst; Torkjel M Sandanger; Guri Skeie; J Ramón Quirós; Antonio Agudo; Maria-Jose Sánchez; Pilar Amiano; José María Huerta; Eva Ardanaz; Julie A Schmidt; Ruth C Travis; Elio Riboli; Konstantinos K Tsilidis; Sofia Christakoudi; Marc J Gunter; Sabina Rinaldi Journal: BMC Med Date: 2019-09-24 Impact factor: 8.775