AUTHOR=Li Zhe , Zhang Weiguang , Duan Yuting , Niu Yue , Chen Yizhi , Liu Xiaomin , Dong Zheyi , Zheng Ying , Chen Xizhao , Feng Zhe , Wang Yong , Zhao Delong , Sun Xuefeng , Cai Guangyan , Jiang Hongwei , Chen Xiangmei 

TITLE=Progress in biological age research

JOURNAL=Frontiers in Public Health

VOLUME=11

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.1074274

DOI=10.3389/fpubh.2023.1074274

ISSN=2296-2565

ABSTRACT=<p>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.</p>