NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing prostate cancer

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Victor Bala, Agnès | Lecuyer, Lucie | Bouchemal, Nadia | Triba, Mohamed Nawfal | Rossary, Adrien | Demidem, Aïcha | Galan, Pilar | Hercberg, Serge | Partula, Valentin | Le Moyec, Laurence | Srour, Bernard | Latino Martel, Paule | Kesse-Guyot, Emmanuelle | Deschasaux, Mélanie | Vasson, Marie-Paule | Savarin, Philippe | Touvier, Mathilde

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International audience. Background: Combination of metabolomics and epidemiological approaches opens new perspectives for ground-breaking discoveries. The aim of the present study was to investigate whether plasma untargeted metabolomic profiles, established from a simple blood draw from healthy men, could contribute to predict the risk of developing prostate cancer within the following decade and to better understand the etiology of this complex disease.Methods: A prospective nested case-control study was set up in the SU.VI.MAX cohort, including 162 prostate cancer cases diagnosed during a 13y follow-up, and 162 matched controls. Untargeted NMR metabolomic profiles were established from baseline pre-diagnosis plasma samples using NOESY 1D and CPMG NMR sequences from 500 MHz NMR spectrometer Bruker Avance III. Multivariable conditional logistic regression models were computed for each individual NMR variable. Results: Men characterized by higher fasting plasma levels of valine, glutamine, creatine/albumin lysyl, tyrosine, phenylalanine, histidine, albumin, 3-methylhistidine and lower plasma levels of urea, CH2 lipoproteins, methionine and citrate had a higher risk of developing prostate cancer. The metabolite the most associated with prostate cancer risk was histidine (OR=1.46 [1.12-1.88], p=0.004).Conclusion: This study highlighted associations between baseline NMR plasma metabolomic signatures and long-term prostate cancer risk. These results provide interesting insights to better understand complex mechanisms involved in prostate carcinogenesis. If replicated in independent cohort studies, they may contribute to develop screening strategies for the identification of at-risk men for prostate cancer well before symptoms appear.

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