Biological age in healthy elderly predicts aging-related diseases including dementia
Abstract Application of biological age as a measure of an individual´s health status offers new perspectives into extension of both lifespan and healthspan. While algorithms predicting mortality and most aging-related morbidities have been reported, the major shortcoming has been an inability to pre...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2021-08-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-021-95425-5 |
| _version_ | 1818421079741300736 |
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| author | Julia W. Wu Amber Yaqub Yuan Ma Wouter Koudstaal Albert Hofman M. Arfan Ikram Mohsen Ghanbari Jaap Goudsmit |
| author_facet | Julia W. Wu Amber Yaqub Yuan Ma Wouter Koudstaal Albert Hofman M. Arfan Ikram Mohsen Ghanbari Jaap Goudsmit |
| author_sort | Julia W. Wu |
| collection | DOAJ |
| description | Abstract Application of biological age as a measure of an individual´s health status offers new perspectives into extension of both lifespan and healthspan. While algorithms predicting mortality and most aging-related morbidities have been reported, the major shortcoming has been an inability to predict dementia. We present a community-based cohort study of 1930 participants with a mean age of 72 years and a follow-up period of over 7 years, using two variants of a phenotypic blood-based algorithm that either excludes (BioAge1) or includes (BioAge2) neurofilament light chain (NfL) as a neurodegenerative marker. BioAge1 and BioAge2 predict dementia equally well, as well as lifespan and healthspan. Each one-year increase in BioAge1/2 was associated with 11% elevated risk (HR 1.11; 95%CI 1.08–1.14) of mortality and 7% elevated risk (HR 1.07; 95%CI 1.05–1.09) of first morbidities. We additionally tested the association of microRNAs with age and identified 263 microRNAs significantly associated with biological and chronological age alike. Top differentially expressed microRNAs based on biological age had a higher significance level than those based on chronological age, suggesting that biological age captures aspects of aging signals at the epigenetic level. We conclude that accelerated biological age for a given age is a predictor of major age-related morbidity, including dementia, among healthy elderly. |
| first_indexed | 2024-12-14T13:04:40Z |
| format | Article |
| id | doaj.art-8a4784fa5b184545b3e5fc85ad14cfce |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-12-14T13:04:40Z |
| publishDate | 2021-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-8a4784fa5b184545b3e5fc85ad14cfce2022-12-21T23:00:21ZengNature PortfolioScientific Reports2045-23222021-08-0111111010.1038/s41598-021-95425-5Biological age in healthy elderly predicts aging-related diseases including dementiaJulia W. Wu0Amber Yaqub1Yuan Ma2Wouter Koudstaal3Albert Hofman4M. Arfan Ikram5Mohsen Ghanbari6Jaap Goudsmit7Department of Epidemiology, Harvard T.H. Chan School of Public HealthDepartment of Epidemiology, Erasmus MC University Medical CenterDepartment of Epidemiology, Harvard T.H. Chan School of Public HealthHuman Vaccines ProjectDepartment of Epidemiology, Harvard T.H. Chan School of Public HealthDepartment of Epidemiology, Erasmus MC University Medical CenterDepartment of Epidemiology, Erasmus MC University Medical CenterDepartment of Epidemiology, Harvard T.H. Chan School of Public HealthAbstract Application of biological age as a measure of an individual´s health status offers new perspectives into extension of both lifespan and healthspan. While algorithms predicting mortality and most aging-related morbidities have been reported, the major shortcoming has been an inability to predict dementia. We present a community-based cohort study of 1930 participants with a mean age of 72 years and a follow-up period of over 7 years, using two variants of a phenotypic blood-based algorithm that either excludes (BioAge1) or includes (BioAge2) neurofilament light chain (NfL) as a neurodegenerative marker. BioAge1 and BioAge2 predict dementia equally well, as well as lifespan and healthspan. Each one-year increase in BioAge1/2 was associated with 11% elevated risk (HR 1.11; 95%CI 1.08–1.14) of mortality and 7% elevated risk (HR 1.07; 95%CI 1.05–1.09) of first morbidities. We additionally tested the association of microRNAs with age and identified 263 microRNAs significantly associated with biological and chronological age alike. Top differentially expressed microRNAs based on biological age had a higher significance level than those based on chronological age, suggesting that biological age captures aspects of aging signals at the epigenetic level. We conclude that accelerated biological age for a given age is a predictor of major age-related morbidity, including dementia, among healthy elderly.https://doi.org/10.1038/s41598-021-95425-5 |
| spellingShingle | Julia W. Wu Amber Yaqub Yuan Ma Wouter Koudstaal Albert Hofman M. Arfan Ikram Mohsen Ghanbari Jaap Goudsmit Biological age in healthy elderly predicts aging-related diseases including dementia Scientific Reports |
| title | Biological age in healthy elderly predicts aging-related diseases including dementia |
| title_full | Biological age in healthy elderly predicts aging-related diseases including dementia |
| title_fullStr | Biological age in healthy elderly predicts aging-related diseases including dementia |
| title_full_unstemmed | Biological age in healthy elderly predicts aging-related diseases including dementia |
| title_short | Biological age in healthy elderly predicts aging-related diseases including dementia |
| title_sort | biological age in healthy elderly predicts aging related diseases including dementia |
| url | https://doi.org/10.1038/s41598-021-95425-5 |
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