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Progress in biological age research

Authors :
Zhe Li
Weiguang Zhang
Yuting Duan
Yue Niu
Yizhi Chen
Xiaomin Liu
Zheyi Dong
Ying Zheng
Xizhao Chen
Zhe Feng
Yong Wang
Delong Zhao
Xuefeng Sun
Guangyan Cai
Hongwei Jiang
Xiangmei Chen
Source :
Frontiers in Public Health, Vol 11 (2023)
Publication Year :
2023
Publisher :
Frontiers Media S.A., 2023.

Abstract

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.

Details

Language :
English
ISSN :
22962565
Volume :
11
Database :
Directory of Open Access Journals
Journal :
Frontiers in Public Health
Publication Type :
Academic Journal
Accession number :
edsdoj.7b559b5bc9ad46ca80e566b9132d5076
Document Type :
article
Full Text :
https://doi.org/10.3389/fpubh.2023.1074274