Modeling biological age using blood biomarkers and physical measurements in Chinese adults
<p><strong>Background</strong> 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 parti...
| Main Authors: | , , , , , , , , , , |
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| Other Authors: | |
| Format: | Journal article |
| Language: | English |
| Published: |
Elsevier
2023
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| _version_ | 1797109678608482304 |
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| author | Chen, L Zhang, Y Yu, C Yang, L Millwood, IY Walters, RG Chen, Y Du, H Burgess, S Stevens, R Chen, Z |
| author2 | China Kadoorie Biobank Collaborative Group |
| author_facet | China Kadoorie Biobank Collaborative Group Chen, L Zhang, Y Yu, C Yang, L Millwood, IY Walters, RG Chen, Y Du, H Burgess, S Stevens, R Chen, Z |
| author_sort | Chen, L |
| collection | OXFORD |
| description | <p><strong>Background</strong> 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.</p>
<p><strong>Methods</strong> 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).</p>
<p><strong>Findings</strong> 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).</p>
<p><strong>Interpretation</strong> 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.</p>
<p><strong>Funding</strong> This work was supported by National 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 Kadoorie 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).</p> |
| first_indexed | 2024-03-07T07:44:53Z |
| format | Journal article |
| id | oxford-uuid:0d111a9d-f048-4315-be49-1112ef199d83 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:44:53Z |
| publishDate | 2023 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oxford-uuid:0d111a9d-f048-4315-be49-1112ef199d832023-05-31T11:03:08ZModeling biological age using blood biomarkers and physical measurements in Chinese adultsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:0d111a9d-f048-4315-be49-1112ef199d83EnglishSymplectic ElementsElsevier2023Chen, LZhang, YYu, CYang, LMillwood, IYWalters, RGChen, YDu, HBurgess, SStevens, RChen, ZChina Kadoorie Biobank Collaborative Group<p><strong>Background</strong> 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.</p> <p><strong>Methods</strong> 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).</p> <p><strong>Findings</strong> 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).</p> <p><strong>Interpretation</strong> 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.</p> <p><strong>Funding</strong> This work was supported by National 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 Kadoorie 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).</p> |
| spellingShingle | Chen, L Zhang, Y Yu, C Yang, L Millwood, IY Walters, RG Chen, Y Du, H Burgess, S Stevens, R Chen, Z 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 |
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