Evidence map›Paper›PMID 38216698›Full record

ArticleScientific reports2024

The Gompertz Law emerges naturally from the inter-dependencies between sub-components in complex organisms.

Pernille Yde Nielsen, Majken K Jensen, Namiko Mitarai, Samir Bhatt

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2024. 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
3.4field-weighted citation impact, top 8% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Embracing non-linearity in human ageing.Nature reviews. Genetics · 2026
    Review
  2. Article
  3. The rhythm of aging: Stability and drift in the individual rate of senescence.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Article
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 at 3 institutions in 2 countries.

Pernille Yde NielsenDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, 2800, Kongens Lyngby, Denmark. pydni@dtu.dk.
Majken K JensenDepartment of Public Health, University of Copenhagen, Copenhagen, Denmark.
Namiko MitaraiNiels Bohr Institute, University of Copenhagen, Copenhagen, Denmark.
Samir BhattDepartment of Public Health, University of Copenhagen, Copenhagen, Denmark.
University of Copenhagen · DKLondon Centre for Neglected Tropical Disease Research · GBTechnical University of Denmark · DK

Funding

Novo Nordisk Challenge Programme NNF17OC0027812
6 · The paper itself

Abstract

Understanding and facilitating healthy aging has become a major goal in medical research and it is becoming increasingly acknowledged that there is a need for understanding the aging phenotype as a whole rather than focusing on individual factors. Here, we provide a universal explanation for the emergence of Gompertzian mortality patterns using a systems approach to describe aging in complex organisms that consist of many inter-dependent subsystems. Our model relates to the Sufficient-Component Cause Model, widely used within the field of epidemiology, and we show that including inter-dependencies between subsystems and modeling the temporal evolution of subsystem failure results in Gompertizan mortality on the population level. Our model also provides temporal trajectories of mortality-risk for the individual. These results may give insight into understanding how biological age evolves stochastically within the individual, and how this in turn leads to a natural heterogeneity of biological age in a population.

Indexed as

Biomedical ResearchHealthy AgingAgingHumansModels, BiologicalMortalityPhenotype

Identifiers

PMID38216698
PMCPMC10786855
OpenAlexW4390827023

What Socratic holds

Textmetadata
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 Socratic graph.