Evidence map›Paper›PMID 24825544›Full record

ArticleNature communications2014

Exercise training reduces resting heart rate via downregulation of the funny channel HCN4.

Alicia D'Souza, Annalisa Bucchi, Anne Berit Johnsen, Sunil Jit R J Logantha, Oliver Monfredi, Joseph Yanni, Sukhpal Prehar, George Hart, Elizabeth Cartwright, Ulrik Wisloff and 4 more

Open access · hybridAbstract read
In one paragraph

Article in Nature communications, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 108 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
108citing papers in PubMed, 3 pooled it
12.0field-weighted citation impact, top 1% 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

108 citing papers in PubMed, 3 syntheses or guidelines pooled it, 266 citations in OpenAlex.

  1. Pooled it
  2. The effects of exercise training on hypertensive older adults: an umbrella meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2021
    Pooled it
  3. Guideline
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  19. Aging and sinus node dysfunction: mechanisms and future directions.Clinical science (London, England : 1979) · 2025
    Review
  20. Mapping HRV in sports science: from monitoring to machine learning.Frontiers in sports and active living · 2025
    Review

48 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 3 institutions in 3 countries.

Alicia D'Souza1] Institute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK [2].
Annalisa Bucchi1] Department of Biosciences, University of Milano, Milano 20133, Italy [2].
Anne Berit Johnsen1] Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim 7491, Norway [2].
Sunil Jit R J Logantha1] Institute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK [2].
Oliver MonfrediInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
Joseph YanniInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
Sukhpal PreharInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
George HartInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
Elizabeth CartwrightInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
Ulrik WisloffDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim 7491, Norway.
Halina DobryznskiInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
Dario DiFrancescoDepartment of Biosciences, University of Milano, Milano 20133, Italy.
Gwilym M MorrisInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
Mark R BoyettInstitute of Cardiovascular Sciences, University of Manchester, Manchester M13 9NT, UK.
University of Manchester · GBNorwegian University of Science and Technology · NOUniversity of Milan · IT

Funding

British Heart Foundation PG/10/031/28331British Heart Foundation RG/11/18/29257
6 · The paper itself

Abstract

Endurance athletes exhibit sinus bradycardia, that is a slow resting heart rate, associated with a higher incidence of sinus node (pacemaker) disease and electronic pacemaker implantation. Here we show that training-induced bradycardia is not a consequence of changes in the activity of the autonomic nervous system but is caused by intrinsic electrophysiological changes in the sinus node. We demonstrate that training-induced bradycardia persists after blockade of the autonomous nervous system in vivo in mice and in vitro in the denervated sinus node. We also show that a widespread remodelling of pacemaker ion channels, notably a downregulation of HCN4 and the corresponding ionic current, If. Block of If abolishes the difference in heart rate between trained and sedentary animals in vivo and in vitro. We further observe training-induced downregulation of Tbx3 and upregulation of NRSF and miR-1 (transcriptional regulators) that explains the downregulation of HCN4. Our findings provide a molecular explanation for the potentially pathological heart rate adaptation to exercise training.

Indexed as

Physical Conditioning, AnimalAdaptation, PhysiologicalAnimalsBradycardiaDown-RegulationHeart RateHyperpolarization-Activated Cyclic Nucleotide-Gated ChannelsIn Vitro TechniquesMiceMicroRNAsRatsRE1-Silencing Transcription FactorRepressor ProteinsRNA, MessengerSinoatrial NodeT-Box Domain ProteinsHyperpolarization-Activated Cyclic Nucleotide-Gated ChannelsMicroRNAsMirn1 microRNA, mouseMIRN1 microRNA, ratRE1-Silencing Transcription FactorRepressor ProteinsRNA, MessengerT-Box Domain ProteinsTbx3 protein, mouse

Identifiers

PMID24825544
PMCPMC4024745
OpenAlexW2051730836

What OpenQuestion holds

Textmetadata
LicenceTDM
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.