1D NMR Spectroscopy - Explore the Science & Experts | ideXlab


Scan Science and Technology

Contact Leading Edge Experts & Companies

1D NMR Spectroscopy

The Experts below are selected from a list of 48798 Experts worldwide ranked by ideXlab platform

1D NMR Spectroscopy – Access All Experts and Articles

Serge Hercberg – One of the best experts on this subject based on the ideXlab platform.

  • Abstract P1-02-01: NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
    Poster Session Abstracts, 2018
    Co-Authors: Lucie Lécuyer, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, A. Victor Bala, Serge Hercberg

    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 non-targeted 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 etiology of this complex disease. Methods: A prospective nested case-control study was set up in the SU.VI.MAX cohort, including 206 breast cancer cases diagnosed during a 13y follow-up, and 396 matched controls. Non-targeted 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 (OR T3vsT1 =0.37[0.23-0.61] for glycerol-derived compounds) to 0.04 (OR T3vsT1 =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 favorable 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. Citation Format: Lecuyer L, Victor Bala A, Deschasaux M, Bouchemal N, Nawfal Triba M, Vasson M-P, Rossary A, Demidem A, Galan P, Hercberg S, Partula V, Le Moyec L, Srour B, Fiolet T, Latino-Martel P, Kesse-Guyot E, Zelek L, Savarin P, Touvier M. NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-02-01.

  • NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer.
    International journal of epidemiology, 2018
    Co-Authors: Lucie Lécuyer, Agnès Victor Bala, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, Serge Hercberg

    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 Supplementation en Vitamines et Mineraux 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.

  • NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
    International Journal of Epidemiology, 2018
    Co-Authors: Lucie Lécuyer, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, Agnès Victor Bala, Serge Hercberg

    Abstract:

    Background: Combination of metabolomics and epidemiological approaches opens new perspectives for groundbreaking discoveries. The aim of the present study was to investigate for the first time whether plasma non-targeted 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 SU.VI.MAX cohort, including 206 breast cancer cases diagnosed during a 13y follow-up, and 396 matched controls. Non-targeted 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 (ORT3vsT1=0.37[0.23-0.61] for glycerol-derived compounds) to 0.04 (ORT3vsT1=1.61[1.02-2.55] for glutamine). Conclusion: This prospective study showed that baseline NMR plasma metabolomic signatures reveal predictive metabolites associated with 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

Lucie Lécuyer – One of the best experts on this subject based on the ideXlab platform.

  • Abstract P1-02-01: NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
    Poster Session Abstracts, 2018
    Co-Authors: Lucie Lécuyer, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, A. Victor Bala, Serge Hercberg

    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 non-targeted 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 etiology of this complex disease. Methods: A prospective nested case-control study was set up in the SU.VI.MAX cohort, including 206 breast cancer cases diagnosed during a 13y follow-up, and 396 matched controls. Non-targeted 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 (OR T3vsT1 =0.37[0.23-0.61] for glycerol-derived compounds) to 0.04 (OR T3vsT1 =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 favorable 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. Citation Format: Lecuyer L, Victor Bala A, Deschasaux M, Bouchemal N, Nawfal Triba M, Vasson M-P, Rossary A, Demidem A, Galan P, Hercberg S, Partula V, Le Moyec L, Srour B, Fiolet T, Latino-Martel P, Kesse-Guyot E, Zelek L, Savarin P, Touvier M. NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-02-01.

  • NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer.
    International journal of epidemiology, 2018
    Co-Authors: Lucie Lécuyer, Agnès Victor Bala, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, Serge Hercberg

    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 Supplementation en Vitamines et Mineraux 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.

  • NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
    International Journal of Epidemiology, 2018
    Co-Authors: Lucie Lécuyer, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, Agnès Victor Bala, Serge Hercberg

    Abstract:

    Background: Combination of metabolomics and epidemiological approaches opens new perspectives for groundbreaking discoveries. The aim of the present study was to investigate for the first time whether plasma non-targeted 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 SU.VI.MAX cohort, including 206 breast cancer cases diagnosed during a 13y follow-up, and 396 matched controls. Non-targeted 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 (ORT3vsT1=0.37[0.23-0.61] for glycerol-derived compounds) to 0.04 (ORT3vsT1=1.61[1.02-2.55] for glutamine). Conclusion: This prospective study showed that baseline NMR plasma metabolomic signatures reveal predictive metabolites associated with 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

Mélanie Deschasaux – One of the best experts on this subject based on the ideXlab platform.

  • Abstract P1-02-01: NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
    Poster Session Abstracts, 2018
    Co-Authors: Lucie Lécuyer, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, A. Victor Bala, Serge Hercberg

    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 non-targeted 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 etiology of this complex disease. Methods: A prospective nested case-control study was set up in the SU.VI.MAX cohort, including 206 breast cancer cases diagnosed during a 13y follow-up, and 396 matched controls. Non-targeted 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 (OR T3vsT1 =0.37[0.23-0.61] for glycerol-derived compounds) to 0.04 (OR T3vsT1 =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 favorable 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. Citation Format: Lecuyer L, Victor Bala A, Deschasaux M, Bouchemal N, Nawfal Triba M, Vasson M-P, Rossary A, Demidem A, Galan P, Hercberg S, Partula V, Le Moyec L, Srour B, Fiolet T, Latino-Martel P, Kesse-Guyot E, Zelek L, Savarin P, Touvier M. NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P1-02-01.

  • NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer.
    International journal of epidemiology, 2018
    Co-Authors: Lucie Lécuyer, Agnès Victor Bala, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, Serge Hercberg

    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 Supplementation en Vitamines et Mineraux 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.

  • NMR metabolomic signatures reveal predictive plasma metabolites associated with long-term risk of developing breast cancer
    International Journal of Epidemiology, 2018
    Co-Authors: Lucie Lécuyer, Mélanie Deschasaux, Nadia Bouchemal, Mohamed N. Triba, Marie-paule Vasson, Adrien Rossary, Aicha Demidem, Pilar Galan, Agnès Victor Bala, Serge Hercberg

    Abstract:

    Background: Combination of metabolomics and epidemiological approaches opens new perspectives for groundbreaking discoveries. The aim of the present study was to investigate for the first time whether plasma non-targeted 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 SU.VI.MAX cohort, including 206 breast cancer cases diagnosed during a 13y follow-up, and 396 matched controls. Non-targeted 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 (ORT3vsT1=0.37[0.23-0.61] for glycerol-derived compounds) to 0.04 (ORT3vsT1=1.61[1.02-2.55] for glutamine). Conclusion: This prospective study showed that baseline NMR plasma metabolomic signatures reveal predictive metabolites associated with 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