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Biological age estimation using circulating blood biomarkers
Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603148/ https://www.ncbi.nlm.nih.gov/pubmed/37884697 http://dx.doi.org/10.1038/s42003-023-05456-z |
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author | Bortz, Jordan Guariglia, Andrea Klaric, Lucija Tang, David Ward, Peter Geer, Michael Chadeau-Hyam, Marc Vuckovic, Dragana Joshi, Peter K. |
author_facet | Bortz, Jordan Guariglia, Andrea Klaric, Lucija Tang, David Ward, Peter Geer, Michael Chadeau-Hyam, Marc Vuckovic, Dragana Joshi, Peter K. |
author_sort | Bortz, Jordan |
collection | PubMed |
description | Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI [0.767–0.788]), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI [0.739–0.761]), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual’s mortality risk. Values ranged between 20-years younger and 20-years older than individuals’ chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population. |
format | Online Article Text |
id | pubmed-10603148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106031482023-10-28 Biological age estimation using circulating blood biomarkers Bortz, Jordan Guariglia, Andrea Klaric, Lucija Tang, David Ward, Peter Geer, Michael Chadeau-Hyam, Marc Vuckovic, Dragana Joshi, Peter K. Commun Biol Article Biological age captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for biological age estimation. This study aims to improve biological age estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (n = 306,116). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk (C-Index = 0.778; 95% CI [0.767–0.788]), which outperforms the well-known blood-biomarker based PhenoAge model (C-Index = 0.750; 95% CI [0.739–0.761]), providing a C-Index lift of 0.028 representing an 11% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. Biological age is estimated as the equivalent age within the same-sex population which corresponds to an individual’s mortality risk. Values ranged between 20-years younger and 20-years older than individuals’ chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of Biological Age, available to the general population. Nature Publishing Group UK 2023-10-26 /pmc/articles/PMC10603148/ /pubmed/37884697 http://dx.doi.org/10.1038/s42003-023-05456-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Bortz, Jordan Guariglia, Andrea Klaric, Lucija Tang, David Ward, Peter Geer, Michael Chadeau-Hyam, Marc Vuckovic, Dragana Joshi, Peter K. Biological age estimation using circulating blood biomarkers |
title | Biological age estimation using circulating blood biomarkers |
title_full | Biological age estimation using circulating blood biomarkers |
title_fullStr | Biological age estimation using circulating blood biomarkers |
title_full_unstemmed | Biological age estimation using circulating blood biomarkers |
title_short | Biological age estimation using circulating blood biomarkers |
title_sort | biological age estimation using circulating blood biomarkers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10603148/ https://www.ncbi.nlm.nih.gov/pubmed/37884697 http://dx.doi.org/10.1038/s42003-023-05456-z |
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