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Information and clonal concepts in ageing

J A Morris1

  • 1Lancaster Moor Hospital, UK.

Medical Hypotheses
|February 1, 1994
PubMed
Summary
This summary is machine-generated.

This study combines information theory and somatic mutation models to explain aging. It suggests that errors in biological information processing and expanding mutant stem cells contribute to aging, disease, and mortality.

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Area of Science:

  • Biogerontology
  • Information Theory
  • Somatic Mutation

Background:

  • Biological systems rely on information processing for integrity.
  • Decision-making processes are fallible, leading to errors, disease, and death.
  • Component decay increases error rates with age, influenced by system redundancy.

Purpose of the Study:

  • To develop a composite theory of aging by integrating information theory and somatic mutation models.
  • To provide a mathematical framework for understanding age-related incidence of mortality and disease.
  • To explore the role of mutant stem cells in the aging process.

Main Methods:

  • Combined a model based on information theory with a model of somatic mutation in expanding cell populations.
  • Developed a mathematical formula derived from information theory to fit age-incidence data.

Related Experiment Videos

  • Applied a somatic mutation model to data on cancer and dominant mutations.

    • Main Results:

    • A mathematical formula closely fits the age incidence of mortality and disease in middle and old age.
    • Identified a rising error rate with age due to component decay and system redundancy.
    • Proposed that expanding mutant stem cells with proliferative advantages contribute to aging.

    Conclusions:

    • The composite theory explains aging as a result of information processing errors and stem cell mutations.
    • Aging is less influenced by the external environment than previously thought, with a significant role for the intrauterine environment.
    • This model provides a comprehensive view of aging mechanisms, integrating internal biological processes.