Evidence map›Paper›PMID 35774538›Full record

ArticleFrontiers in nutrition2022

Plasma Metabolic Signatures of Healthy Overweight Subjects Challenged With an Oral Glucose Tolerance Test.

Jarlei Fiamoncini, Carlos M Donado-Pestana, Graziela Biude Silva Duarte, Milena Rundle, Elizabeth Louise Thomas, Yoana Kiselova-Kaneva, Thomas E Gundersen, Diana Bunzel, Jean-Pierre Trezzi, Sabine E Kulling and 10 more

Open access · goldAbstract 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. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.0field-weighted citation impact, top 25% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

20 authors at 11 institutions in 8 countries.

Jarlei FiamonciniDepartment Food and Nutrition, Technische Universität München, Freising, Germany.
Carlos M Donado-PestanaFood Research Center, Department of Food Science and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
Graziela Biude Silva DuarteFood Research Center, Department of Food Science and Experimental Nutrition, School of Pharmaceutical Sciences, University of São Paulo, São Paulo, Brazil.
Milena RundleDivision of Diabetes, Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom.
Elizabeth Louise ThomasResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom.
Yoana Kiselova-KanevaDepartment of Biochemistry, Molecular Medicine and Nutrigenomics, Medical University, Varna, Bulgaria.
Thomas E GundersenVitas Ltd., Oslo Science Park, Oslo, Norway.
Diana BunzelDepartment of Safety and Quality of Fruit and Vegetables, Federal Research Institute of Nutrition and Food, Max Rubner-Institut, Karlsruhe, Germany.
Jean-Pierre TrezziBraunschweig Integrated Centre of Systems Biology, University of Braunschweig, Braunschweig, Germany.
Sabine E KullingDepartment of Safety and Quality of Fruit and Vegetables, Federal Research Institute of Nutrition and Food, Max Rubner-Institut, Karlsruhe, Germany.
Karsten HillerBraunschweig Integrated Centre of Systems Biology, University of Braunschweig, Braunschweig, Germany.
Denise Sonntagbiocrates life sciences AG, Innsbruck, Austria.
Diana IvanovaDepartment of Biochemistry, Molecular Medicine and Nutrigenomics, Medical University, Varna, Bulgaria.
Lorraine BrennanUCD School of Agriculture and Food Science, Institute of Food and Health, Conway Institute, University College Dublin, Dublin, Ireland.
Suzan WopereisNetherlands Organisation for Applied Scientific Research, Netherlands Institute for Applied Scientific Research, Microbiology and Systems Biology, Zeist, Netherlands.
Ben van OmmenNetherlands Organisation for Applied Scientific Research, Netherlands Institute for Applied Scientific Research, Microbiology and Systems Biology, Zeist, Netherlands.
Gary FrostDivision of Diabetes, Endocrinology and Metabolism, Department of Medicine, Imperial College London, London, United Kingdom.
Jimmy BellResearch Centre for Optimal Health, School of Life Sciences, University of Westminster, London, United Kingdom.
Christian A DrevonVitas Ltd., Oslo Science Park, Oslo, Norway.
Hannelore DanielDepartment Food and Nutrition, Technische Universität München, Freising, Germany.
Imperial College London · GBLeibniz-Institute for Food Systems Biology at the Technical University of Munich · DEMax Rubner Institut · DEMedical University of Varna · BGNetherlands Organisation for Applied Scientific Research · NLTechnische Universität Braunschweig · DEUniversidade de São Paulo · BRUniversity of Westminster · GBVitas (Norway) · NOBiocrates Life Sciences (Austria) · ATUniversity College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Insulin secretion following ingestion of a carbohydrate load affects a multitude of metabolic pathways that simultaneously change direction and quantity of interorgan fluxes of sugars, lipids and amino acids. In the present study, we aimed at identifying markers associated with differential responses to an OGTT a population of healthy adults. By use of three metabolite profiling platforms, we assessed these postprandial responses of a total of 202 metabolites in plasma of 72 healthy volunteers undergoing comprehensive phenotyping and of which half enrolled into a weight-loss program over a three-month period. A standard oral glucose tolerance test (OGTT) served as dietary challenge test to identify changes in postprandial metabolite profiles. Despite classified as healthy according to WHO criteria, two discrete clusters (A and B) were identified based on the postprandial glucose profiles with a balanced distribution of volunteers based on gender and other measures. Cluster A individuals displayed 26% higher postprandial glucose levels, delayed glucose clearance and increased fasting plasma concentrations of more than 20 known biomarkers of insulin resistance and diabetes previously identified in large cohort studies. The volunteers identified by canonical postprandial responses that form cluster A may be called pre-pre-diabetics and defined as "at risk" for development of insulin resistance. Moreover, postprandial changes in selected fatty acids and complex lipids, bile acids, amino acids, acylcarnitines and sugars like mannose revealed marked differences in the responses seen in cluster A and cluster B individuals that sustained over the entire challenge test period of 240 min. Almost all metabolites, including glucose and insulin, returned to baseline values at the end of the test (at 240 min), except a variety of amino acids and here those that have been linked to diabetes development. Analysis of the corresponding metabolite profile in a fasting blood sample may therefore allow for early identification of these subjects at risk for insulin resistance without the need to undergo an OGTT.

Indexed as

dietary challenge testinsulin resistancemetabotypesOGTTpostprandial metabolism

Identifiers

PMID35774538
PMCPMC9237474
OpenAlexW4282843486

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.