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Modelling biological age based on plasma peptides in Han Chinese adults
Age-related disease burdens increased over time, and whether plasma peptides can be used to accurately predict age in order to explain the variation in biological indicators remains inadequately understood. Here we first developed a biological age model based on plasma peptides in 1890 Chinese Han a...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346055/ https://www.ncbi.nlm.nih.gov/pubmed/32501290 http://dx.doi.org/10.18632/aging.103286 |
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author | Cao, Weijie Zheng, Deqiang Wang, Guohua Zhang, Jie Ge, Siqi Singh, Manjot Wang, Hao Song, Manshu Li, Dong Wang, Wei Xu, Xizhu Wang, Youxin |
author_facet | Cao, Weijie Zheng, Deqiang Wang, Guohua Zhang, Jie Ge, Siqi Singh, Manjot Wang, Hao Song, Manshu Li, Dong Wang, Wei Xu, Xizhu Wang, Youxin |
author_sort | Cao, Weijie |
collection | PubMed |
description | Age-related disease burdens increased over time, and whether plasma peptides can be used to accurately predict age in order to explain the variation in biological indicators remains inadequately understood. Here we first developed a biological age model based on plasma peptides in 1890 Chinese Han adults. Based on mass spectrometry, 84 peptides were detected with masses in the range of 0.6-10.0 kDa, and 13 of these peptides were identified as known amino acid sequences. Five of these thirteen plasma peptides, including fragments of apolipoprotein A-I (m/z 2883.99), fibrinogen alpha chain (m/z 3060.13), complement C3 (m/z 2190.59), complement C4-A (m/z 1898.21), and breast cancer type 2 susceptibility protein (m/z 1607.84) were finally included in the final model by performing a multivariate linear regression with stepwise selection. This biological age model accounted for 72.3% of the variation in chronological age. Furthermore, the linear correlation between the actual age and biological age was 0.851 (95% confidence interval: 0.836-0.864) and 0.842 (95% confidence interval: 0.810-0.869) in the training and validation sets, respectively. The biological age based on plasma peptides has potential positive effects on primary prevention, and its biological meaning warrants further investigation. |
format | Online Article Text |
id | pubmed-7346055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-73460552020-07-15 Modelling biological age based on plasma peptides in Han Chinese adults Cao, Weijie Zheng, Deqiang Wang, Guohua Zhang, Jie Ge, Siqi Singh, Manjot Wang, Hao Song, Manshu Li, Dong Wang, Wei Xu, Xizhu Wang, Youxin Aging (Albany NY) Research Paper Age-related disease burdens increased over time, and whether plasma peptides can be used to accurately predict age in order to explain the variation in biological indicators remains inadequately understood. Here we first developed a biological age model based on plasma peptides in 1890 Chinese Han adults. Based on mass spectrometry, 84 peptides were detected with masses in the range of 0.6-10.0 kDa, and 13 of these peptides were identified as known amino acid sequences. Five of these thirteen plasma peptides, including fragments of apolipoprotein A-I (m/z 2883.99), fibrinogen alpha chain (m/z 3060.13), complement C3 (m/z 2190.59), complement C4-A (m/z 1898.21), and breast cancer type 2 susceptibility protein (m/z 1607.84) were finally included in the final model by performing a multivariate linear regression with stepwise selection. This biological age model accounted for 72.3% of the variation in chronological age. Furthermore, the linear correlation between the actual age and biological age was 0.851 (95% confidence interval: 0.836-0.864) and 0.842 (95% confidence interval: 0.810-0.869) in the training and validation sets, respectively. The biological age based on plasma peptides has potential positive effects on primary prevention, and its biological meaning warrants further investigation. Impact Journals 2020-06-05 /pmc/articles/PMC7346055/ /pubmed/32501290 http://dx.doi.org/10.18632/aging.103286 Text en Copyright © 2020 Cao et al. http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Cao, Weijie Zheng, Deqiang Wang, Guohua Zhang, Jie Ge, Siqi Singh, Manjot Wang, Hao Song, Manshu Li, Dong Wang, Wei Xu, Xizhu Wang, Youxin Modelling biological age based on plasma peptides in Han Chinese adults |
title | Modelling biological age based on plasma peptides in Han Chinese adults |
title_full | Modelling biological age based on plasma peptides in Han Chinese adults |
title_fullStr | Modelling biological age based on plasma peptides in Han Chinese adults |
title_full_unstemmed | Modelling biological age based on plasma peptides in Han Chinese adults |
title_short | Modelling biological age based on plasma peptides in Han Chinese adults |
title_sort | modelling biological age based on plasma peptides in han chinese adults |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7346055/ https://www.ncbi.nlm.nih.gov/pubmed/32501290 http://dx.doi.org/10.18632/aging.103286 |
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