Evidence map›Paper›PMID 36211489›Full record

ArticleFrontiers in nutrition2022

Dynamic patterns of postprandial metabolic responses to three dietary challenges.

Patrick Weinisch, Jarlei Fiamoncini, Daniela Schranner, Johannes Raffler, Thomas Skurk, Manuela J Rist, Werner Römisch-Margl, Cornelia Prehn, Jerzy Adamski, Hans Hauner and 3 more

Registry-linked trialAbstract read
In one paragraph

Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06878781 (Standardized Meals With Different Macronutrient Ratios on the Postprandial Metabolome and Metabolic Flexibility), which is not on this map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT06878781 narecruitingnot on this mapstarted 2024, after this paper: background citation

Standardized Meals With Different Macronutrient Ratios on the Postprandial Metabolome and Metabolic Flexibility

TypeinterventionalSponsorInstituto Nacional de Medicina GenomicaRan2024 to 2026Enrolled300ConditionsFasting, Postprandial Hyperglycemia, Lipid Metabolism Disorders, Glucose Metabolism DisordersArmsHigh carbohydrate challenge, High lipid challenge, High proteinchallenge
3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Trial
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  8. Methods and protocols · 2025
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  9. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Patrick WeinischInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
Jarlei FiamonciniFood Research Center - FoRC, Department of Food Science and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
Daniela SchrannerInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
Johannes RafflerInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
Thomas SkurkCore Facility Human Studies, ZIEL Institute for Food and Health, Technical University of Munich, Freising, Germany.
Manuela J RistDepartment of Physiology and Biochemistry of Nutrition, Max Rubner-Institut, Karlsruhe, Germany.
Werner Römisch-MarglInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
Cornelia PrehnMetabolomics and Proteomics Core, Helmholtz Zentrum München, Neuherberg, Germany.
Jerzy AdamskiInstitute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany.
Hans HaunerElse Kröner Fresenius Center for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising, Germany.
Hannelore DanielDepartment of Food and Nutrition, Technical University of Munich, Freising, Germany.
Karsten SuhreDepartment of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha, Qatar.
Gabi KastenmüllerInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.

Funding

Project 4 - Mechanistic studies on the role of the gut microbiome in models for Alzheimer's diseaseU19AG063744 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Rima F Kaddurah-Daouk · 2019 to 2026
$54.1M
Metabolomic Signatures for Disease Sub-classification and Target Prioritization in AMP-ADU01AG061359 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, KASTENMULLER, GABI · 2018 to 2022
$10.0M
Metabolic Networks and Pathways Predictive of Sex Differences in AD Risk and Responsiveness to TreatmentRF1AG059093 · NIA · DUKE UNIVERSITY · PI BRINTON, ROBERTA EILEEN, CHANG, RUI · 2018 to 2018
$5.9M
Metabolic Network Analysis of Biochemical Trajectories in Alzheimer's DiseaseRF1AG057452 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, KASTENMULLER, GABI · 2017 to 2017
$3.5M
Gut Liver Brain Biochemical Axis in Alzheimer's DiseaseRF1AG058942 · NIA · DUKE UNIVERSITY · PI KADDURAH-DAOUK, RIMA F, VAN DUIJN, CORNELIA MARJA · 2018 to 2018
$3.4M
NIA NIH HHS RF1 AG057452NIA NIH HHS RF1 AG058942NIA NIH HHS RF1 AG059093NIA NIH HHS U01 AG061359NIA NIH HHS U19 AG063744
6 · The paper itself

Abstract

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 (

Indexed as

dietary challengelongitudinal metabolomicsmetabolic adaptationnutritional metabolomicspostprandial metabolismresponse patternstime-series data

Identifiers

PMID36211489
PMCPMC9540193

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.