Cargando…
Dynamic patterns of postprandial metabolic responses to three dietary challenges
Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabo...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540193/ https://www.ncbi.nlm.nih.gov/pubmed/36211489 http://dx.doi.org/10.3389/fnut.2022.933526 |
_version_ | 1784803657023225856 |
---|---|
author | Weinisch, Patrick Fiamoncini, Jarlei Schranner, Daniela Raffler, Johannes Skurk, Thomas Rist, Manuela J. Römisch-Margl, Werner Prehn, Cornelia Adamski, Jerzy Hauner, Hans Daniel, Hannelore Suhre, Karsten Kastenmüller, Gabi |
author_facet | Weinisch, Patrick Fiamoncini, Jarlei Schranner, Daniela Raffler, Johannes Skurk, Thomas Rist, Manuela J. Römisch-Margl, Werner Prehn, Cornelia Adamski, Jerzy Hauner, Hans Daniel, Hannelore Suhre, Karsten Kastenmüller, Gabi |
author_sort | Weinisch, Patrick |
collection | PubMed |
description | Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake. |
format | Online Article Text |
id | pubmed-9540193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95401932022-10-08 Dynamic patterns of postprandial metabolic responses to three dietary challenges Weinisch, Patrick Fiamoncini, Jarlei Schranner, Daniela Raffler, Johannes Skurk, Thomas Rist, Manuela J. Römisch-Margl, Werner Prehn, Cornelia Adamski, Jerzy Hauner, Hans Daniel, Hannelore Suhre, Karsten Kastenmüller, Gabi Front Nutr Nutrition Food intake triggers extensive changes in the blood metabolome. The kinetics of these changes depend on meal composition and on intrinsic, health-related characteristics of each individual, making the assessment of changes in the postprandial metabolome an opportunity to assess someone's metabolic status. To enable the usage of dietary challenges as diagnostic tools, profound knowledge about changes that occur in the postprandial period in healthy individuals is needed. In this study, we characterize the time-resolved changes in plasma levels of 634 metabolites in response to an oral glucose tolerance test (OGTT), an oral lipid tolerance test (OLTT), and a mixed meal (SLD) in healthy young males (n = 15). Metabolite levels for samples taken at different time points (20 per individual) during the challenges were available from targeted (132 metabolites) and non-targeted (502 metabolites) metabolomics. Almost half of the profiled metabolites (n = 308) showed a significant change in at least one challenge, thereof 111 metabolites responded exclusively to one particular challenge. Examples include azelate, which is linked to ω-oxidation and increased only in OLTT, and a fibrinogen cleavage peptide that has been linked to a higher risk of cardiovascular events in diabetes patients and increased only in OGTT, making its postprandial dynamics a potential target for risk management. A pool of 89 metabolites changed their plasma levels during all three challenges and represents the core postprandial response to food intake regardless of macronutrient composition. We used fuzzy c-means clustering to group these metabolites into eight clusters based on commonalities of their dynamic response patterns, with each cluster following one of four primary response patterns: (i) “decrease-increase” (valley-like) with fatty acids and acylcarnitines indicating the suppression of lipolysis, (ii) “increase-decrease” (mountain-like) including a cluster of conjugated bile acids and the glucose/insulin cluster, (iii) “steady decrease” with metabolites reflecting a carryover from meals prior to the study, and (iv) “mixed” decreasing after the glucose challenge and increasing otherwise. Despite the small number of subjects, the diversity of the challenges and the wealth of metabolomic data make this study an important step toward the characterization of postprandial responses and the identification of markers of metabolic processes regulated by food intake. Frontiers Media S.A. 2022-09-22 /pmc/articles/PMC9540193/ /pubmed/36211489 http://dx.doi.org/10.3389/fnut.2022.933526 Text en Copyright © 2022 Weinisch, Fiamoncini, Schranner, Raffler, Skurk, Rist, Römisch-Margl, Prehn, Adamski, Hauner, Daniel, Suhre and Kastenmüller. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Nutrition Weinisch, Patrick Fiamoncini, Jarlei Schranner, Daniela Raffler, Johannes Skurk, Thomas Rist, Manuela J. Römisch-Margl, Werner Prehn, Cornelia Adamski, Jerzy Hauner, Hans Daniel, Hannelore Suhre, Karsten Kastenmüller, Gabi Dynamic patterns of postprandial metabolic responses to three dietary challenges |
title | Dynamic patterns of postprandial metabolic responses to three dietary challenges |
title_full | Dynamic patterns of postprandial metabolic responses to three dietary challenges |
title_fullStr | Dynamic patterns of postprandial metabolic responses to three dietary challenges |
title_full_unstemmed | Dynamic patterns of postprandial metabolic responses to three dietary challenges |
title_short | Dynamic patterns of postprandial metabolic responses to three dietary challenges |
title_sort | dynamic patterns of postprandial metabolic responses to three dietary challenges |
topic | Nutrition |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9540193/ https://www.ncbi.nlm.nih.gov/pubmed/36211489 http://dx.doi.org/10.3389/fnut.2022.933526 |
work_keys_str_mv | AT weinischpatrick dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT fiamoncinijarlei dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT schrannerdaniela dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT rafflerjohannes dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT skurkthomas dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT ristmanuelaj dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT romischmarglwerner dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT prehncornelia dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT adamskijerzy dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT haunerhans dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT danielhannelore dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT suhrekarsten dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges AT kastenmullergabi dynamicpatternsofpostprandialmetabolicresponsestothreedietarychallenges |