Evidence map›Paper›PMID 40911433›Full record

ReviewThe Journal of physiology2026

The cardiac pacemakers: A paradigm of robustness in evolutionary biology.

Denis Noble

Abstract readReview
In one paragraph

Review in The Journal of physiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. The principles of systems biology.Experimental physiology · 2026
    Review
  5. 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

1 author.

Denis NobleDepartment of Physiology, Anatomy & Genetics, University of Oxford and Daegu-Gyeongbuk Institute of Science and Technology, South Korea.ORCID https://orcid.org/0000-0002-3013-3694

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cardiac pacemaker activity is formed from multiple interlocking physiological networks, any one of which can generate rhythm. The interlocking is reciprocal so that they automatically replace each other. In such interlocking control systems, the association scores for individual components are necessarily low, even though causation, measured by the electric current carried by the relevant ion channels, is large. This kind of reciprocally based robustness is widespread in living organisms, which explains why most association scores in genome-wide association studies are low, or even zero. It also explains why the polygenic scores do not reliably predict disease states. Genomics alone is therefore a poor method for the discovery of treatments for polygenic diseases. Reliance on genomics has led to a gene-centric impasse in healthcare, which requires a shift in favour of physiological studies that can reveal genuine causation rather than just association. The case for such a shift includes understanding that DNA is not a good self-replicator in very large genomes. Self-replication of DNA and RNA in purely chemical environments confirms that fact. The error rate would amount to hundreds of thousands in a genome of three billion base pairs. Living cells can orchestrate the enzymes necessary for nearly perfect replication before cell division by correcting those errors. These cellular proof-reading processes also open the way to control processes that are used to generate new DNA sequences when the immune and other systems need to do so.

Indexed as

Biological ClocksBiological EvolutionHeartAnimalsGenome-Wide Association StudyHumanscardiac pacemakerscausation in physiological networkscentral dogmadifference between association and causationDNA self‐replicationgenome‐wide association studies

Identifiers

PMID40911433
PMCPMC13327764

What OpenQuestion holds

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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.