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Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study

BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic...

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Autores principales: Eriksen, Rebeca, Perez, Isabel Garcia, Posma, Joram M., Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, Louise E., Koivula, Robert W., Bizzotto, Roberto, Mari, Andrea, Giordano, Giuseppe N., Pavo, Imre, Schwenk, Jochen M., De Masi, Federico, Tsirigos, Konstantinos D., Brunak, Søren, Viñuela, Ana, Mahajan, Anubha, McDonald, Timothy J., Kokkola, Tarja, Rutter, Femke, Teare, Harriet, Hansen, Tue H., Fernandez, Juan, Jones, Angus, Jennison, Chris, Walker, Mark, McCarthy, Mark I., Pedersen, Oluf, Ruetten, Hartmut, Forgie, Ian, Bell, Jimmy D., Pearson, Ewan R., Franks, Paul W., Adamski, Jerzy, Holmes, Elaine, Frost, Gary
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406914/
https://www.ncbi.nlm.nih.gov/pubmed/32763829
http://dx.doi.org/10.1016/j.ebiom.2020.102932
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author Eriksen, Rebeca
Perez, Isabel Garcia
Posma, Joram M.
Haid, Mark
Sharma, Sapna
Prehn, Cornelia
Thomas, Louise E.
Koivula, Robert W.
Bizzotto, Roberto
Prehn, Cornelia
Mari, Andrea
Giordano, Giuseppe N.
Pavo, Imre
Schwenk, Jochen M.
De Masi, Federico
Tsirigos, Konstantinos D.
Brunak, Søren
Viñuela, Ana
Mahajan, Anubha
McDonald, Timothy J.
Kokkola, Tarja
Rutter, Femke
Teare, Harriet
Hansen, Tue H.
Fernandez, Juan
Jones, Angus
Jennison, Chris
Walker, Mark
McCarthy, Mark I.
Pedersen, Oluf
Ruetten, Hartmut
Forgie, Ian
Bell, Jimmy D.
Pearson, Ewan R.
Franks, Paul W.
Adamski, Jerzy
Holmes, Elaine
Frost, Gary
author_facet Eriksen, Rebeca
Perez, Isabel Garcia
Posma, Joram M.
Haid, Mark
Sharma, Sapna
Prehn, Cornelia
Thomas, Louise E.
Koivula, Robert W.
Bizzotto, Roberto
Prehn, Cornelia
Mari, Andrea
Giordano, Giuseppe N.
Pavo, Imre
Schwenk, Jochen M.
De Masi, Federico
Tsirigos, Konstantinos D.
Brunak, Søren
Viñuela, Ana
Mahajan, Anubha
McDonald, Timothy J.
Kokkola, Tarja
Rutter, Femke
Teare, Harriet
Hansen, Tue H.
Fernandez, Juan
Jones, Angus
Jennison, Chris
Walker, Mark
McCarthy, Mark I.
Pedersen, Oluf
Ruetten, Hartmut
Forgie, Ian
Bell, Jimmy D.
Pearson, Ewan R.
Franks, Paul W.
Adamski, Jerzy
Holmes, Elaine
Frost, Gary
author_sort Eriksen, Rebeca
collection PubMed
description BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. METHODS: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (T(pred)) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous T(pred) score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. FINDINGS: A higher T(pred) score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=–0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher T(pred) score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the T(pred) score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher T(pred) score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. INTERPRETATION: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. FUNDING: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies.
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spelling pubmed-74069142020-08-12 Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study Eriksen, Rebeca Perez, Isabel Garcia Posma, Joram M. Haid, Mark Sharma, Sapna Prehn, Cornelia Thomas, Louise E. Koivula, Robert W. Bizzotto, Roberto Prehn, Cornelia Mari, Andrea Giordano, Giuseppe N. Pavo, Imre Schwenk, Jochen M. De Masi, Federico Tsirigos, Konstantinos D. Brunak, Søren Viñuela, Ana Mahajan, Anubha McDonald, Timothy J. Kokkola, Tarja Rutter, Femke Teare, Harriet Hansen, Tue H. Fernandez, Juan Jones, Angus Jennison, Chris Walker, Mark McCarthy, Mark I. Pedersen, Oluf Ruetten, Hartmut Forgie, Ian Bell, Jimmy D. Pearson, Ewan R. Franks, Paul W. Adamski, Jerzy Holmes, Elaine Frost, Gary EBioMedicine Research paper BACKGROUND: Dietary advice remains the cornerstone of prevention and management of type 2 diabetes (T2D). However, understanding the efficacy of dietary interventions is confounded by the challenges inherent in assessing free living diet. Here we profiled dietary metabolites to investigate glycaemic deterioration and cardiometabolic risk in people at risk of or living with T2D. METHODS: We analysed data from plasma collected at baseline and 18-month follow-up in individuals from the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohort 1 n = 403 individuals with normal or impaired glucose regulation (prediabetic) and cohort 2 n = 458 individuals with new onset of T2D. A dietary metabolite profile model (T(pred)) was constructed using multivariable regression of 113 plasma metabolites obtained from targeted metabolomics assays. The continuous T(pred) score was used to explore the relationships between diet, glycaemic deterioration and cardio-metabolic risk via multiple linear regression models. FINDINGS: A higher T(pred) score was associated with healthier diets high in wholegrain (β=3.36 g, 95% CI 0.31, 6.40 and β=2.82 g, 95% CI 0.06, 5.57) and lower energy intake (β=-75.53 kcal, 95% CI -144.71, -2.35 and β=-122.51 kcal, 95% CI -186.56, -38.46), and saturated fat (β=-0.92 g, 95% CI -1.56, -0.28 and β=–0.98 g, 95% CI -1.53, -0.42 g), respectively for cohort 1 and 2. In both cohorts a higher T(pred) score was also associated with lower total body adiposity and favourable lipid profiles HDL-cholesterol (β=0.07 mmol/L, 95% CI 0.03, 0.1), (β=0.08 mmol/L, 95% CI 0.04, 0.1), and triglycerides (β=-0.1 mmol/L, 95% CI -0.2, -0.03), (β=-0.2 mmol/L, 95% CI -0.3, -0.09), respectively for cohort 1 and 2. In cohort 2, the T(pred) score was negatively associated with liver fat (β=-0.74%, 95% CI -0.67, -0.81), and lower fasting concentrations of HbA1c (β=-0.9 mmol/mol, 95% CI -1.5, -0.1), glucose (β=-0.2 mmol/L, 95% CI -0.4, -0.05) and insulin (β=-11.0 pmol/mol, 95% CI -19.5, -2.6). Longitudinal analysis showed at 18-month follow up a higher T(pred) score was also associated lower total body adiposity in both cohorts and lower fasting glucose (β=-0.2 mmol/L, 95% CI -0.3, -0.01) and insulin (β=-9.2 pmol/mol, 95% CI -17.9, -0.4) concentrations in cohort 2. INTERPRETATION: Plasma dietary metabolite profiling provides objective measures of diet intake, showing a relationship to glycaemic deterioration and cardiometabolic health. FUNDING: This work was supported by the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115,317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007–2013) and EFPIA companies. Elsevier 2020-08-04 /pmc/articles/PMC7406914/ /pubmed/32763829 http://dx.doi.org/10.1016/j.ebiom.2020.102932 Text en Crown Copyright © 2020 Published by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research paper
Eriksen, Rebeca
Perez, Isabel Garcia
Posma, Joram M.
Haid, Mark
Sharma, Sapna
Prehn, Cornelia
Thomas, Louise E.
Koivula, Robert W.
Bizzotto, Roberto
Prehn, Cornelia
Mari, Andrea
Giordano, Giuseppe N.
Pavo, Imre
Schwenk, Jochen M.
De Masi, Federico
Tsirigos, Konstantinos D.
Brunak, Søren
Viñuela, Ana
Mahajan, Anubha
McDonald, Timothy J.
Kokkola, Tarja
Rutter, Femke
Teare, Harriet
Hansen, Tue H.
Fernandez, Juan
Jones, Angus
Jennison, Chris
Walker, Mark
McCarthy, Mark I.
Pedersen, Oluf
Ruetten, Hartmut
Forgie, Ian
Bell, Jimmy D.
Pearson, Ewan R.
Franks, Paul W.
Adamski, Jerzy
Holmes, Elaine
Frost, Gary
Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
title Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
title_full Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
title_fullStr Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
title_full_unstemmed Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
title_short Dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: An IMI DIRECT study
title_sort dietary metabolite profiling brings new insight into the relationship between nutrition and metabolic risk: an imi direct study
topic Research paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7406914/
https://www.ncbi.nlm.nih.gov/pubmed/32763829
http://dx.doi.org/10.1016/j.ebiom.2020.102932
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