Evidence map›Paper›PMID 34152092›Full record

ArticlePhysiological reports2021

Physiological extremes of the human blood metabolome: A metabolomics analysis of highly glycolytic, oxidative, and anabolic athletes.

Daniela Schranner, Martin Schönfelder, Werner Römisch-Margl, Johannes Scherr, Jürgen Schlegel, Otto Zelger, Annett Riermeier, Stephanie Kaps, Cornelia Prehn, Jerzy Adamski and 6 more

Open access · goldAbstract read
In one paragraph

Article in Physiological reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.8field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
  2. Exercise and Fat: A Primer.Sports medicine - open · 2026
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  13. Taurine deficiency as a driver of aging.Science (New York, N.Y.) · 2023
    Article
  14. Review
  15. Article
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  19. Article
  20. Review
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

16 authors at 5 institutions in 3 countries.

Daniela SchrannerExercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.ORCID 0000-0003-2316-318X
Martin SchönfelderExercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Werner Römisch-MarglInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
Johannes ScherrUniversity Center for Prevention and Sports Medicine, University Hospital Balgrist, Universität Zürich, Zurich, Switzerland.
Jürgen SchlegelDepartment of Neuropathology, Institute of Pathology, Technische Universität München, Munich, Germany.
Otto ZelgerDepartment of Prevention and Sports Medicine, Technische Universität München, Munich, Germany.
Annett RiermeierExercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Stephanie KapsExercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Cornelia PrehnResearch Unit Molecular Endocrinology and Metabolism, Helmholtz Zentrum München, Neuherberg, Germany.
Jerzy AdamskiResearch Unit Molecular Endocrinology and Metabolism, Helmholtz Zentrum München, Neuherberg, Germany.
Quirin SöhnleinExercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Fabian StöckerTeaching and Educational Lab, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Florian KreuzpointnerPrevention Center, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Martin HalleDepartment of Prevention and Sports Medicine, Technische Universität München, Munich, Germany.
Gabi KastenmüllerInstitute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.ORCID 0000-0002-2368-7322
Henning WackerhageExercise Biology, Department of Sport and Health Sciences, Technische Universität München, Munich, Germany.
Technical University of Munich · DEHelmholtz Zentrum München · DEJoint Research Centre · DENational University of Singapore · SGUniversity of Zurich · CH

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

Human metabolism is highly variable. At one end of the spectrum, defects of enzymes, transporters, and metabolic regulation result in metabolic diseases such as diabetes mellitus or inborn errors of metabolism. At the other end of the spectrum, favorable genetics and years of training combine to result in physiologically extreme forms of metabolism in athletes. Here, we investigated how the highly glycolytic metabolism of sprinters, highly oxidative metabolism of endurance athletes, and highly anabolic metabolism of natural bodybuilders affect their serum metabolome at rest and after a bout of exercise to exhaustion. We used targeted mass spectrometry-based metabolomics to measure the serum concentrations of 151 metabolites and 43 metabolite ratios or sums in 15 competitive male athletes (6 endurance athletes, 5 sprinters, and 4 natural bodybuilders) and 4 untrained control subjects at fasted rest and 5 minutes after a maximum graded bicycle test to exhaustion. The analysis of all 194 metabolite concentrations, ratios and sums revealed that natural bodybuilders and endurance athletes had overall different metabolite profiles, whereas sprinters and untrained controls were more similar. Specifically, natural bodybuilders had 1.5 to 1.8-fold higher concentrations of specific phosphatidylcholines and lower levels of branched chain amino acids than all other subjects. Endurance athletes had 1.4-fold higher levels of a metabolite ratio showing the activity of carnitine-palmitoyl-transferase I and 1.4-fold lower levels of various alkyl-acyl-phosphatidylcholines. When we compared the effect of exercise between groups, endurance athletes showed 1.3-fold higher increases of hexose and of tetradecenoylcarnitine (C14:1). In summary, physiologically extreme metabolic capacities of endurance athletes and natural bodybuilders are associated with unique blood metabolite concentrations, ratios, and sums at rest and after exercise. Our results suggest that long-term specific training, along with genetics and other athlete-specific factors systematically change metabolite concentrations at rest and after exercise.

Indexed as

AthletesMetabolomeOxidation-ReductionAdultBlood ProteinsExercise TestGlycolysisHumansMalePhysical EnduranceYoung AdultBlood Proteinsathleteenergy metabolismexercise biomarkerexercise phenotype

Identifiers

PMID34152092
PMCPMC8215680
OpenAlexW3173834355

What OpenQuestion holds

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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.