Progress in biological age research
Biological age (BA) is a common model to evaluate the function of aging individuals as it may provide a more accurate measure of the extent of human aging than chronological age (CA). Biological age is influenced by the used biomarkers and standards in selected aging biomarkers and the statistical m...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-04-01
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| Series: | Frontiers in Public Health |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1074274/full |
| _version_ | 1797848046079311872 |
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| author | Zhe Li Zhe Li Weiguang Zhang Yuting Duan Yuting Duan Yue Niu Yizhi Chen Yizhi Chen Xiaomin Liu Zheyi Dong Ying Zheng Xizhao Chen Zhe Feng Yong Wang Delong Zhao Xuefeng Sun Guangyan Cai Hongwei Jiang Xiangmei Chen |
| author_facet | Zhe Li Zhe Li Weiguang Zhang Yuting Duan Yuting Duan Yue Niu Yizhi Chen Yizhi Chen Xiaomin Liu Zheyi Dong Ying Zheng Xizhao Chen Zhe Feng Yong Wang Delong Zhao Xuefeng Sun Guangyan Cai Hongwei Jiang Xiangmei Chen |
| author_sort | Zhe Li |
| collection | DOAJ |
| description | Biological age (BA) is a common model to evaluate the function of aging individuals as it may provide a more accurate measure of the extent of human aging than chronological age (CA). Biological age is influenced by the used biomarkers and standards in selected aging biomarkers and the statistical method to construct BA. Traditional used BA estimation approaches include multiple linear regression (MLR), principal component analysis (PCA), Klemera and Doubal’s method (KDM), and, in recent years, deep learning methods. This review summarizes the markers for each organ/system used to construct biological age and published literature using methods in BA research. Future research needs to explore the new aging markers and the standard in select markers and new methods in building BA models. |
| first_indexed | 2024-04-09T18:22:13Z |
| format | Article |
| id | doaj.art-7b559b5bc9ad46ca80e566b9132d5076 |
| institution | Directory Open Access Journal |
| issn | 2296-2565 |
| language | English |
| last_indexed | 2024-04-09T18:22:13Z |
| publishDate | 2023-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj.art-7b559b5bc9ad46ca80e566b9132d50762023-04-12T05:54:55ZengFrontiers Media S.A.Frontiers in Public Health2296-25652023-04-011110.3389/fpubh.2023.10742741074274Progress in biological age researchZhe Li0Zhe Li1Weiguang Zhang2Yuting Duan3Yuting Duan4Yue Niu5Yizhi Chen6Yizhi Chen7Xiaomin Liu8Zheyi Dong9Ying Zheng10Xizhao Chen11Zhe Feng12Yong Wang13Delong Zhao14Xuefeng Sun15Guangyan Cai16Hongwei Jiang17Xiangmei Chen18The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, Hainan Hospital of Chinese PLA General Hospital, Hainan Academician Team Innovation Center, Sanya, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaThe First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, ChinaDepartment of Nephrology, First Medical Center of Chinese PLA General Hospital, Nephrology Institute of the Chinese People's Liberation Army, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Disease Research, Beijing, ChinaBiological age (BA) is a common model to evaluate the function of aging individuals as it may provide a more accurate measure of the extent of human aging than chronological age (CA). Biological age is influenced by the used biomarkers and standards in selected aging biomarkers and the statistical method to construct BA. Traditional used BA estimation approaches include multiple linear regression (MLR), principal component analysis (PCA), Klemera and Doubal’s method (KDM), and, in recent years, deep learning methods. This review summarizes the markers for each organ/system used to construct biological age and published literature using methods in BA research. Future research needs to explore the new aging markers and the standard in select markers and new methods in building BA models.https://www.frontiersin.org/articles/10.3389/fpubh.2023.1074274/fullagingbiological ageaging biomarkerschronological agedeep learningage |
| spellingShingle | Zhe Li Zhe Li Weiguang Zhang Yuting Duan Yuting Duan Yue Niu Yizhi Chen Yizhi Chen Xiaomin Liu Zheyi Dong Ying Zheng Xizhao Chen Zhe Feng Yong Wang Delong Zhao Xuefeng Sun Guangyan Cai Hongwei Jiang Xiangmei Chen Progress in biological age research Frontiers in Public Health aging biological age aging biomarkers chronological age deep learning age |
| title | Progress in biological age research |
| title_full | Progress in biological age research |
| title_fullStr | Progress in biological age research |
| title_full_unstemmed | Progress in biological age research |
| title_short | Progress in biological age research |
| title_sort | progress in biological age research |
| topic | aging biological age aging biomarkers chronological age deep learning age |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2023.1074274/full |
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