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LipidClock: A Lipid-Based Predictor of Biological Age

Complexity is a fundamental feature of biological systems. Omics techniques like lipidomics can simultaneously quantify many thousands of molecules, thereby directly capturing the underlying biological complexity. However, this approach transfers the original biological complexity to the resulting d...

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Autores principales: Unfried, Maximilian, Ng, Li Fang, Cazenave-Gassiot, Amaury, Batchu, Krishna Chaithanya, Kennedy, Brian K., Wenk, Markus R., Tolwinski, Nicholas, Gruber, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9261347/
https://www.ncbi.nlm.nih.gov/pubmed/35821819
http://dx.doi.org/10.3389/fragi.2022.828239
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author Unfried, Maximilian
Ng, Li Fang
Cazenave-Gassiot, Amaury
Batchu, Krishna Chaithanya
Kennedy, Brian K.
Wenk, Markus R.
Tolwinski, Nicholas
Gruber, Jan
author_facet Unfried, Maximilian
Ng, Li Fang
Cazenave-Gassiot, Amaury
Batchu, Krishna Chaithanya
Kennedy, Brian K.
Wenk, Markus R.
Tolwinski, Nicholas
Gruber, Jan
author_sort Unfried, Maximilian
collection PubMed
description Complexity is a fundamental feature of biological systems. Omics techniques like lipidomics can simultaneously quantify many thousands of molecules, thereby directly capturing the underlying biological complexity. However, this approach transfers the original biological complexity to the resulting datasets, posing challenges in data reduction and analysis. Aging is a prime example of a process that exhibits complex behaviour across multiple scales of biological organisation. The aging process is characterised by slow, cumulative and detrimental changes that are driven by intrinsic biological stochasticity and mediated through non-linear interactions and feedback within and between these levels of organization (ranging from metabolites, macromolecules, organelles and cells to tissue and organs). Only collectively and over long timeframes do these changes manifest as the exponential increases in morbidity and mortality that define biological aging, making aging a problem more difficult to study than the aetiologies of specific diseases. But aging’s time dependence can also be exploited to extract key insights into its underlying biology. Here we explore this idea by using data on changes in lipid composition across the lifespan of an organism to construct and test a LipidClock to predict biological age in the nematode Caenorhabdits elegans. The LipidClock consist of a feature transformation via Principal Component Analysis followed by Elastic Net regression and yields and Mean Absolute Error of 1.45 days for wild type animals and 4.13 days when applied to mutant strains with lifespans that are substantially different from that of wild type. Gompertz aging rates predicted by the LipidClock can be used to simulate survival curves that are in agreement with those from lifespan experiments.
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spelling pubmed-92613472022-07-11 LipidClock: A Lipid-Based Predictor of Biological Age Unfried, Maximilian Ng, Li Fang Cazenave-Gassiot, Amaury Batchu, Krishna Chaithanya Kennedy, Brian K. Wenk, Markus R. Tolwinski, Nicholas Gruber, Jan Front Aging Aging Complexity is a fundamental feature of biological systems. Omics techniques like lipidomics can simultaneously quantify many thousands of molecules, thereby directly capturing the underlying biological complexity. However, this approach transfers the original biological complexity to the resulting datasets, posing challenges in data reduction and analysis. Aging is a prime example of a process that exhibits complex behaviour across multiple scales of biological organisation. The aging process is characterised by slow, cumulative and detrimental changes that are driven by intrinsic biological stochasticity and mediated through non-linear interactions and feedback within and between these levels of organization (ranging from metabolites, macromolecules, organelles and cells to tissue and organs). Only collectively and over long timeframes do these changes manifest as the exponential increases in morbidity and mortality that define biological aging, making aging a problem more difficult to study than the aetiologies of specific diseases. But aging’s time dependence can also be exploited to extract key insights into its underlying biology. Here we explore this idea by using data on changes in lipid composition across the lifespan of an organism to construct and test a LipidClock to predict biological age in the nematode Caenorhabdits elegans. The LipidClock consist of a feature transformation via Principal Component Analysis followed by Elastic Net regression and yields and Mean Absolute Error of 1.45 days for wild type animals and 4.13 days when applied to mutant strains with lifespans that are substantially different from that of wild type. Gompertz aging rates predicted by the LipidClock can be used to simulate survival curves that are in agreement with those from lifespan experiments. Frontiers Media S.A. 2022-05-27 /pmc/articles/PMC9261347/ /pubmed/35821819 http://dx.doi.org/10.3389/fragi.2022.828239 Text en Copyright © 2022 Unfried, Ng, Cazenave-Gassiot, Batchu, Kennedy, Wenk, Tolwinski and Gruber. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Aging
Unfried, Maximilian
Ng, Li Fang
Cazenave-Gassiot, Amaury
Batchu, Krishna Chaithanya
Kennedy, Brian K.
Wenk, Markus R.
Tolwinski, Nicholas
Gruber, Jan
LipidClock: A Lipid-Based Predictor of Biological Age
title LipidClock: A Lipid-Based Predictor of Biological Age
title_full LipidClock: A Lipid-Based Predictor of Biological Age
title_fullStr LipidClock: A Lipid-Based Predictor of Biological Age
title_full_unstemmed LipidClock: A Lipid-Based Predictor of Biological Age
title_short LipidClock: A Lipid-Based Predictor of Biological Age
title_sort lipidclock: a lipid-based predictor of biological age
topic Aging
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9261347/
https://www.ncbi.nlm.nih.gov/pubmed/35821819
http://dx.doi.org/10.3389/fragi.2022.828239
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