Predicting biological age using an accumulated neurotoxicity biomarker for amyloid Beta oligomers

This study proposes using accumulated neurotoxicity, defined as the time integral of Aβ oligomer concentration, as a biomarker for neuronal aging. A relationship between biological age and accumulated neurotoxicity is proposed. Numerical analysis guided the development of a new analytical solution linking the biological and calendar ages of neurons. The effects of Aβ monomer and oligomer half-lives-key indicators of proteolytic efficiency-on biological age are examined. Both constant and age-dependent (exponentially increasing) half-life scenarios are considered. The findings indicate that increasing the half-life of Aβ monomers and oligomers with age accelerates biological aging. Reducing Aβ monomer production is shown to slow biological aging, with a linear relationship established between these two quantities. Additionally, biological age is found to depend linearly on the half-deposition time of Aβ oligomers into senile plaques. The model demonstrates that biological age is irreversible, providing a theoretical explanation for why plaque-clearing therapies cannot reverse established cognitive impairment. The model also demonstrates that biological age is path-dependent rather than state-dependent.

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Publication Details

Journal
Mathematical Medicine and Biology A Journal of the IMA
Published
2026-07-16
DOI
https://doi.org/10.1093/imammb/dqag005
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
8.68
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article

Predicting biological age using an accumulated neurotoxicity biomarker for amyloid Beta oligomers

A. V. Kuznetsov
2 citations
Mathematical Medicine and Biology A Journal of the IMA
Computational Drug Discovery Methods
8.68
article

Predicting biological age using an accumulated neurotoxicity biomarker for amyloid Beta oligomers

A. V. Kuznetsov
article en
2 citations

Abstract

This study proposes using accumulated neurotoxicity, defined as the time integral of Aβ oligomer concentration, as a biomarker for neuronal aging. A relationship between biological age and accumulated neurotoxicity is proposed. Numerical analysis guided the development of a new analytical solution linking the biological and calendar ages of neurons. The effects of Aβ monomer and oligomer half-lives-key indicators of proteolytic efficiency-on biological age are examined. Both constant and age-dependent (exponentially increasing) half-life scenarios are considered. The findings indicate that increasing the half-life of Aβ monomers and oligomers with age accelerates biological aging. Reducing Aβ monomer production is shown to slow biological aging, with a linear relationship established between these two quantities. Additionally, biological age is found to depend linearly on the half-deposition time of Aβ oligomers into senile plaques. The model demonstrates that biological age is irreversible, providing a theoretical explanation for why plaque-clearing therapies cannot reverse established cognitive impairment. The model also demonstrates that biological age is path-dependent rather than state-dependent.

Mathematical Medicine and Biology A Journal of the IMA
North Carolina State University (US)
Openalex Percentile: Top 6%
Computational Drug Discovery Methods
8.68
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