Evidence map›Paper›PMID 16138928›Full record

ArticleBMC biology2005

Modulation of extracellular matrix genes reflects the magnitude of physiological adaptation to aerobic exercise training in humans.

James A Timmons, Eva Jansson, Helene Fischer, Thomas Gustafsson, Paul L Greenhaff, John Ridden, Jonathan Rachman, Carl Johan Sundberg

Open access · goldAbstract read
In one paragraph

Article in BMC biology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 7% 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

53 citing papers in PubMed, 1 synthesis or guideline pooled it, 132 citations in OpenAlex.

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  15. Mitochondrial mutations alter endurance exercise response and determinants in mice.Proceedings of the National Academy of Sciences of the United States of America · 2022
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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

8 authors at 2 institutions in 2 countries.

James A TimmonsDepartment of Physiology and Pharmacology, Karolinska Institutet, Stockholm, SE171 77, Sweden. Jamie.Timmons@cgb.ki.se
Eva Jansson
Helene Fischer
Thomas Gustafsson
Paul L Greenhaff
John Ridden
Jonathan Rachman
Carl Johan Sundberg
Karolinska Institutet · SEOsys Technology · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRegular exercise reduces cardiovascular and metabolic disease partly through improved aerobic fitness. The determinants of exercise-induced gains in aerobic fitness in humans are not known. We have demonstrated that over 500 genes are activated in response to endurance-exercise training, including modulation of muscle extracellular matrix (ECM) genes. Real-time quantitative PCR, which is essential for the characterization of lower abundance genes, was used to examine 15 ECM genes potentially relevant for endurance-exercise adaptation. Twenty-four sedentary male subjects undertook six weeks of high-intensity aerobic cycle training with muscle biopsies being obtained both before and 24 h after training. Subjects were ranked based on improvement in aerobic fitness, and two cohorts were formed (n = 8 per group): the high-responder group (HRG; peak rate of oxygen consumption increased by +0.71 +/- 0.1 L min(-1); p < 0.0001) while the low-responder group (LRG; peak rate of oxygen consumption did not change, +0.17 +/- 0.1 L min(-1), ns). ECM genes profiled included the angiopoietin 1 and related genes (angiopoietin 2, tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1) and 2 (TIE2), vascular endothelial growth factor (VEGF) and related receptors (VEGF receptor 1, VEGF receptor 2 and neuropilin-1), thrombospondin-4, alpha2-macroglobulin and transforming growth factor beta2.

resultsneuropilin-1 (800%; p < 0.001) and VEGF receptor 2 (300%; p < 0.01) transcript abundance increased only in the HRG, whereas levels of VEGF receptor 1 mRNA actually declined in the LRG (p < 0.05). TIE1 and TIE2 mRNA levels were unaltered in the LRG, whereas transcription levels of both genes were increased by 2.5-fold in the HRG (p < 0.01). Levels of thrombospondin-4 (900%; p < 0.001) and alpha2-macroglobulin (300%, p < 0.05) mRNA increased substantially in the HRG. In contrast, the amount of transforming growth factor beta2 transcript increased only in the HRG (330%; p < 0.01), whereas it remained unchanged in the LRG (-80%).

conclusionWe demonstrate for the first time that aerobic training activates angiopoietin 1 and TIE2 genes in human muscle, but only when aerobic capacity adapts to exercise-training. The fourfold-greater increase in aerobic fitness and markedly differing gene expression profile in the HRG indicates that these ECM genes may be critical for physiological adaptation to exercise in humans. In addition, we show that, without careful demonstration of physiological adaptation, conclusions derived from gene expression profiling of human skeletal muscle following exercise may be of limited value. We propose that future studies should (a) investigate the mechanisms that underlie the apparent link between physiological adaptation and gene expression and (b) use the genes profiled in this paper as candidates for population genetic studies.

Indexed as

Physical FitnessAcclimatizationAerobiosisExerciseExtracellular MatrixExtracellular Matrix ProteinsGene Expression ProfilingGene Expression RegulationHumansOxygen ConsumptionReceptors, Vascular Endothelial Growth FactorVascular Endothelial Growth Factor AExtracellular Matrix ProteinsReceptors, Vascular Endothelial Growth FactorVascular Endothelial Growth Factor A

Identifiers

PMID16138928
PMCPMC1224855
OpenAlexW1527271891

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.