Evidence map›Paper›PMID 28212624›Full record

ArticleBMC genomics2017

Understanding the response to endurance exercise using a systems biology approach: combining blood metabolomics, transcriptomics and miRNomics in horses.

Núria Mach, Yuliaxis Ramayo-Caldas, Allison Clark, Marco Moroldo, Céline Robert, Eric Barrey, Jesús Maria López, Laurence Le Moyec

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

25 citing papers in PubMed, 48 citations in OpenAlex.

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  6. Immunology of Physical Exercise: IsInternational journal of molecular sciences · 2024
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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 4 institutions in 2 countries.

Núria MachAnimal Genetics and Integrative Biology unit (GABI), INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France. nuria.mach@inra.fr.ORCID 0000-0002-8001-6314
Yuliaxis Ramayo-CaldasAnimal Genetics and Integrative Biology unit (GABI), INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
Allison ClarkHealth Science Department, Open University of Catalonia (UOC), Barcelona, Spain.
Marco MoroldoAnimal Genetics and Integrative Biology unit (GABI), INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
Céline RobertAnimal Genetics and Integrative Biology unit (GABI), INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
Eric BarreyAnimal Genetics and Integrative Biology unit (GABI), INRA, AgroParisTech, Université Paris-Saclay, 78350, Jouy-en-Josas, France.
Jesús Maria LópezHealth Science Department, Open University of Catalonia (UOC), Barcelona, Spain.
Laurence Le MoyecIntegrative Biology of Exercise Adaptations unit, UBIAE, EA7362, Evry Val d'Essone University, Evry, France.
AgroParisTech · FRUniversitat Oberta de Catalunya · ESÉcole Nationale Vétérinaire d'Alfort · FRUniversité d'Évry Val-d'Essonne · FR

Funding

The Metabolomics Data Center and Workbench (MDCW)U01DK097430 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SUBRAMANIAM, SHANKAR · 2012 to 2017
$7.4M
NIDDK NIH HHS U01 DK097430
6 · The paper itself

Abstract

backgroundEndurance exercise in horses requires adaptive processes involving physiological, biochemical, and cognitive-behavioral responses in an attempt to regain homeostasis. We hypothesized that the identification of the relationships between blood metabolome, transcriptome, and miRNome during endurance exercise in horses could provide significant insights into the molecular response to endurance exercise. For this reason, the serum metabolome and whole-blood transcriptome and miRNome data were obtained from ten horses before and after a 160 km endurance competition.

resultsWe obtained a global regulatory network based on 11 unique metabolites, 263 metabolic genes and 5 miRNAs whose expression was significantly altered at T1 (post- endurance competition) relative to T0 (baseline, pre-endurance competition). This network provided new insights into the cross talk between the distinct molecular pathways (e.g. energy and oxygen sensing, oxidative stress, and inflammation) that were not detectable when analyzing single metabolites or transcripts alone. Single metabolites and transcripts were carrying out multiple roles and thus sharing several biochemical pathways. Using a regulatory impact factor metric analysis, this regulatory network was further confirmed at the transcription factor and miRNA levels. In an extended cohort of 31 independent animals, multiple factor analysis confirmed the strong associations between lactate, methylene derivatives, miR-21-5p, miR-16-5p, let-7 family and genes that coded proteins involved in metabolic reactions primarily related to energy, ubiquitin proteasome and lipopolysaccharide immune responses after the endurance competition. Multiple factor analysis also identified potential biomarkers at T0 for an increased likelihood for failure to finish an endurance competition.

conclusionsTo the best of our knowledge, the present study is the first to provide a comprehensive and integrated overview of the metabolome, transcriptome, and miRNome co-regulatory networks that may have a key role in regulating the metabolic and immune response to endurance exercise in horses.

Indexed as

Gene Expression ProfilingMetabolomicsSystems BiologyAdaptation, PhysiologicalAnimalsBiomarkersGene Regulatory NetworksHorsesMicroRNAsPhysical Conditioning, AnimalPhysical EnduranceTranscription FactorsBiomarkersMicroRNAsTranscription FactorsEndurance exerciseHorseMetabolomemiRNomeMultiple factor analysisRegulomeSystems biologyTranscriptome

Identifiers

PMID28212624
PMCPMC5316211
OpenAlexW2588527247

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.