Evidence map›Paper›PMID 36442091›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Stochastic survival of the densest and mitochondrial DNA clonal expansion in aging.

Ferdinando Insalata, Hanne Hoitzing, Juvid Aryaman, Nick S Jones

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

4 authors.

Ferdinando InsalataDepartment of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom.ORCID 0000-0003-4881-8138
Hanne HoitzingDepartment of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom.
Juvid AryamanDepartment of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom.ORCID 0000-0002-2605-052X
Nick S JonesDepartment of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom.ORCID 0000-0002-4083-972X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The expansion of mitochondrial DNA molecules with deletions has been associated with aging, particularly in skeletal muscle fibers; its mechanism has remained unclear for three decades. Previous accounts have assigned a replicative advantage (RA) to mitochondrial DNA containing deletion mutations, but there is also evidence that cells can selectively remove defective mitochondrial DNA. Here we present a spatial model that, without an RA, but instead through a combination of enhanced density for mutants and noise, produces a wave of expanding mutations with speeds consistent with experimental data. A standard model based on RA yields waves that are too fast. We provide a formula that predicts that wave speed drops with copy number, consonant with experimental data. Crucially, our model yields traveling waves of mutants even if mutants are preferentially eliminated. Additionally, we predict that mutant loads observed in single-cell experiments can be produced by de novo mutation rates that are drastically lower than previously thought for neutral models. Given this exemplar of how spatial structure (multiple linked mtDNA populations), noise, and density affect muscle cell aging, we introduce the mechanism of stochastic survival of the densest (SSD), an alternative to RA, that may underpin other evolutionary phenomena.

Indexed as

DNA, MitochondrialMitochondriaCellular SenescenceMuscle Fibers, SkeletalDNA, Mitochondrialagingbiomathematicsevolutionmitochondriastochastic

Identifiers

PMID36442091
PMCPMC9894218

What OpenQuestion holds

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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.