Cargando…

Modeling biological age using blood biomarkers and physical measurements in Chinese adults

BACKGROUND: This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stag...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Lu, Zhang, Yiqian, Yu, Canqing, Guo, Yu, Sun, Dianjianyi, Pang, Yuanjie, Pei, Pei, Yang, Ling, Millwood, Iona Y., Walters, Robin G., Chen, Yiping, Du, Huaidong, Liu, Yongmei, Burgess, Sushila, Stevens, Rebecca, Chen, Junshi, Chen, Zhengming, Li, Liming, Lv, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941058/
https://www.ncbi.nlm.nih.gov/pubmed/36758480
http://dx.doi.org/10.1016/j.ebiom.2023.104458
_version_ 1784891202562162688
author Chen, Lu
Zhang, Yiqian
Yu, Canqing
Guo, Yu
Sun, Dianjianyi
Pang, Yuanjie
Pei, Pei
Yang, Ling
Millwood, Iona Y.
Walters, Robin G.
Chen, Yiping
Du, Huaidong
Liu, Yongmei
Burgess, Sushila
Stevens, Rebecca
Chen, Junshi
Chen, Zhengming
Li, Liming
Lv, Jun
author_facet Chen, Lu
Zhang, Yiqian
Yu, Canqing
Guo, Yu
Sun, Dianjianyi
Pang, Yuanjie
Pei, Pei
Yang, Ling
Millwood, Iona Y.
Walters, Robin G.
Chen, Yiping
Du, Huaidong
Liu, Yongmei
Burgess, Sushila
Stevens, Rebecca
Chen, Junshi
Chen, Zhengming
Li, Liming
Lv, Jun
author_sort Chen, Lu
collection PubMed
description BACKGROUND: This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. METHODS: The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004–08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). FINDINGS: The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (−0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). INTERPRETATION: In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. FUNDING: This work was supported by 10.13039/501100001809National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the 10.13039/501100017647Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01).
format Online
Article
Text
id pubmed-9941058
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-99410582023-02-22 Modeling biological age using blood biomarkers and physical measurements in Chinese adults Chen, Lu Zhang, Yiqian Yu, Canqing Guo, Yu Sun, Dianjianyi Pang, Yuanjie Pei, Pei Yang, Ling Millwood, Iona Y. Walters, Robin G. Chen, Yiping Du, Huaidong Liu, Yongmei Burgess, Sushila Stevens, Rebecca Chen, Junshi Chen, Zhengming Li, Liming Lv, Jun eBioMedicine Articles BACKGROUND: This study aimed to: 1) assess the associations of biological age acceleration based on Klemera and Doubal's method (KDM-AA) with long-term risk of all-cause mortality; and 2) compare the association of KDM-AA with all-cause mortality among participants potentially at different stages of the cardiovascular disease (CVD) continuum. METHODS: The present study was based on a subpopulation of the China Kadoorie Biobank, with baseline survey during 2004–08. A total of 12,377 participants free of ischemic heart disease, stroke, or cancer at baseline were included, in which 8180 participants were identified to develop major coronary event (MCE), ischemic stroke (IS), intracerebral hemorrhage (ICH) or subarachnoid hemorrhage (SAH), and 4197 remained free of these cardiovascular diseases before 1 January 2014. These participants were followed up until 1 Jan 2018. KDM-AA was calculated by regressing biological age measurement, which was constructed based on baseline 16 physical and 9 biochemical markers using Klemera and Doubal's method, on chronological age. We estimated the associations of KDM-AA with the mortality risk using the hazard ratio (HR) and 95% confidence interval (CI) from Cox proportional hazard models. We assessed discrimination performance by Harrell's C-index and net reclassification index (NRI). FINDINGS: The participants who developed MCE (mean KDM-AA = 0.1 year, standard deviation [SD] = 1.6 years) or ICH/SAH (0.3 ± 1.5 years) during subsequent follow-up showed accelerated aging at baseline compared to those of IS (0.0 ± 1.2 years) and control (−0.3 ± 1.3 years) groups. The KDM-AA was positively associated with long-term risk of all-cause mortality (HR = 1.20; 95% CI: 1.17, 1.23), and the association was robust for participants potentially at different stages of the CVD continuum. Adding KDM-AA improved mortality prediction compared to the model only with sociodemographic and lifestyle factors in whole participants, with the Harrell's C-index increasing from 0.813 (0.807, 0.819) to 0.821 (0.815, 0.826) (NRI = 0.011; 95% CI: 0.003, 0.019). INTERPRETATION: In this middle-aged and elderly Chinese population, the KDM-AA is a promising measurement for biological age, and can capture the difference in cardiovascular health and predict the risk of all-cause mortality over a decade. FUNDING: This work was supported by 10.13039/501100001809National Natural Science Foundation of China (82192904, 82192901, 82192900, 81941018). The CKB baseline survey and the first re-survey were supported by a grant from the 10.13039/501100017647Kadoorie Charitable Foundation Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (212946/Z/18/Z, 202922/Z/16/Z, 104085/Z/14/Z, 088158/Z/09/Z), grants (2016YFC0900500) from the National Key R&D Program of China, National Natural Science Foundation of China (81390540, 91846303), and Chinese Ministry of Science and Technology (2011BAI09B01). Elsevier 2023-02-07 /pmc/articles/PMC9941058/ /pubmed/36758480 http://dx.doi.org/10.1016/j.ebiom.2023.104458 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Articles
Chen, Lu
Zhang, Yiqian
Yu, Canqing
Guo, Yu
Sun, Dianjianyi
Pang, Yuanjie
Pei, Pei
Yang, Ling
Millwood, Iona Y.
Walters, Robin G.
Chen, Yiping
Du, Huaidong
Liu, Yongmei
Burgess, Sushila
Stevens, Rebecca
Chen, Junshi
Chen, Zhengming
Li, Liming
Lv, Jun
Modeling biological age using blood biomarkers and physical measurements in Chinese adults
title Modeling biological age using blood biomarkers and physical measurements in Chinese adults
title_full Modeling biological age using blood biomarkers and physical measurements in Chinese adults
title_fullStr Modeling biological age using blood biomarkers and physical measurements in Chinese adults
title_full_unstemmed Modeling biological age using blood biomarkers and physical measurements in Chinese adults
title_short Modeling biological age using blood biomarkers and physical measurements in Chinese adults
title_sort modeling biological age using blood biomarkers and physical measurements in chinese adults
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941058/
https://www.ncbi.nlm.nih.gov/pubmed/36758480
http://dx.doi.org/10.1016/j.ebiom.2023.104458
work_keys_str_mv AT chenlu modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT zhangyiqian modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT yucanqing modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT guoyu modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT sundianjianyi modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT pangyuanjie modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT peipei modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT yangling modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT millwoodionay modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT waltersrobing modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT chenyiping modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT duhuaidong modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT liuyongmei modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT burgesssushila modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT stevensrebecca modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT chenjunshi modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT chenzhengming modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT liliming modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT lvjun modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults
AT modelingbiologicalageusingbloodbiomarkersandphysicalmeasurementsinchineseadults