Evidence map›Paper›PMID 38092834›Full record

ArticleScientific reports2023

Network dynamical stability analysis reveals key "mallostatic" natural variables that erode homeostasis and drive age-related decline of health.

Glen Pridham, Andrew D Rutenberg

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. How human and animal frailty index studies can inform each other: a brief narrative review.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Review
  2. High frailty index scores predict mortality and changes in blood-based biomarkers in aging female mice.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Article
  3. Article
  4. Dynamical Network Stability Analysis of Multiple Biological Ages Provides a Framework for Understanding the Aging Process.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Glen PridhamDepartment of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, B3H 4R2, Canada.
Andrew D RutenbergDepartment of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, B3H 4R2, Canada. adr@dal.ca.

Funding

Project-001R01AG017644 · NIA · UNIVERSITY OF LONDON INST OF NEUROLOGY · PI Andrew Steptoe · 2000 to 2026
$56.2M
NIA NIH HHS R01 AG017644
6 · The paper itself

Abstract

Using longitudinal study data, we dynamically model how aging affects homeostasis in both mice and humans. We operationalize homeostasis as a multivariate mean-reverting stochastic process. We hypothesize that biomarkers have stable equilibrium values, but that deviations from equilibrium of each biomarker affects other biomarkers through an interaction network-this precludes univariate analysis. We therefore looked for age-related changes to homeostasis using dynamic network stability analysis, which transforms observed biomarker data into independent "natural" variables and determines their associated recovery rates. Most natural variables remained near equilibrium and were essentially constant in time. A small number of natural variables were unable to equilibrate due to a gradual drift with age in their homeostatic equilibrium, i.e. allostasis. This drift caused them to accumulate over the lifespan course and makes them natural aging variables. Their rate of accumulation was correlated with risk of adverse outcomes: death or dementia onset. We call this tendency for aging organisms to drift towards an equilibrium position of ever-worsening health "mallostasis". We demonstrate that the effects of mallostasis on observed biomarkers are spread out through the interaction network. This could provide a redundancy mechanism to preserve functioning until multi-system dysfunction emerges at advanced ages.

Indexed as

AgingLongevityAnimalsBiomarkersHomeostasisHumansLongitudinal StudiesMiceBiomarkers

Identifiers

PMID38092834
PMCPMC10719307

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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.