Three-dimensional facial-image analysis to predict heterogeneity of the human ageing rate and the impact of lifestyle

doi:10.1038/s42255-020-00270-x

	Three-dimensional facial-image analysis to predict heterogeneity of the human ageing rate and the impact of lifestyle
	Xia, Xian 1,2,3; Chen, Xingwei 1,2,3; Wu, Gang 1; Li, Fang 1; Wang, Yiyang 1,2,3; Chen, Yang 1,2,3; Chen, Mingxu 1,2,3; Wang, Xinyu1,2,4 ; Chen, Weiyang 1; Xian, Bo 1; Chen, Weizhong 1; Cao, Yaqiang 1; Xu, Chi 1; Gong, Wenxuan 1,2,3; Chen, Guoyu 1,2,3; Cai, Donghong 1,2,3; Wei, Wenxin 5; Yan, Yizhen 1,2,3; Liu, Kangping 2; Qiao, Nan 6; Zhao, Xiaohui 6; Jia, Jin 6; Wang, Wei 7; Kennedy, Brian K.8,9,10,11,12; Zhang, Kang 13; Cannistraci, Carlo, V 14,15,16; Zhou, Yong 17; Han, Jing-Dong J.1,2
	2020-09
发表期刊	NATURE METABOLISM (IF:18.9[JCR-2023],21.0[5-Year])
ISSN	11111
卷号	2 期号:9 页码:946-+
发表状态	已发表
DOI	10.1038/s42255-020-00270-x
摘要	Not all individuals age at the same rate. Methods such as the 'methylation clock' are invasive, rely on expensive assays of tissue samples and infer the ageing rate by training on chronological age, which is used as a reference for prediction errors. Here, we develop models based on convoluted neural networks through training on non-invasive three-dimensional (3D) facial images of approximately 5,000 Han Chinese individuals that achieve an average difference between chronological or perceived age and predicted age of +/- 2.8 and 2.9 yr, respectively. We further profile blood transcriptomes from 280 individuals and infer the molecular regulators mediating the impact of lifestyle on the facial-ageing rate through a causal-inference model. These relationships have been deposited and visualized in the Human Blood Gene Expression-3D Facial Image (HuB-Fi) database. Overall, we find that humans age at different rates both in the blood and in the face, but do so coherently and with heterogeneity peaking at middle age. Our study provides an example of how artificial intelligence can be leveraged to determine the perceived age of humans as a marker of biological age, while no longer relying on prediction errors of chronological age, and to estimate the heterogeneity of ageing rates within a population.
收录类别	SCIE ; ESCI
语种	英语
资助项目	National Natural Science Foundation of China[91749205] ; China Ministry of Science and Technology[2016YFE0108700] ; Shanghai Municipal Science and Technology Major Project[2017SHZDZX01]
WOS研究方向	Endocrinology & Metabolism
WOS类目	Endocrinology & Metabolism
WOS记录号	WOS:000571444300018
出版者	NATURE RESEARCH
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/123601
专题	生命科学与技术学院_博士生
通讯作者	Zhou, Yong; Han, Jing-Dong J.
作者单位	1.Chinese Acad Sci, CAS MPG Partner Inst Computat Biol, Shanghai Inst Biol Sci,Shanghai Inst Nutr & Hlth, Ctr Excellence Mol Cell Sci,Collaborat Innovat Ct, Shanghai, Peoples R China; 2.Peking Univ, Acad Adv Interdisciplinary Studies, Peking Tsinghua Ctr Life Sci, Ctr Quantitat Biol CQB, Beijing, Peoples R China; 3.Univ Chinese Acad Sci, Beijing, Peoples R China; 4.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai, Peoples R China; 5.Second Mil Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Hepat Surg, Shanghai, Peoples R China; 6.Accenture China Artificial Intelligence Lab, Shenzhen, Peoples R China; 7.Edith Cowan Univ, Sch Med & Hlth Sci, Perth, WA, Australia; 8.Natl Univ Singapore, Dept Biochem, Singapore, Singapore; 9.Natl Univ Singapore, Dept Physiol, Singapore, Singapore; 10.Natl Univ Hlth Syst, Ctr Hlth Ageing, Singapore, Singapore; 11.ASTAR, Singapore Inst Clin Sci, Singapore, Singapore; 12.Buck Inst Res Aging, Novato, CA USA; 13.Macau Univ Sci & Technol, Fac Med, Macau, Peoples R China; 14.Tech Univ Dresden, Cluster Excellence Phys Life PoL, Dept Phys,Ctr Syst Biol Dresden CSBD, Biomed Cybernet Grp,Biotechnol Ctr BIOTEC,Ctr Mol, Dresden, Germany; 15.Tsinghua Univ, Tsinghua Lab Brain & Intelligence THBI, Ctr Complex Network Intelligence CCNI, Beijing, Peoples R China; 16.Tsinghua Univ, Dept Bioengn, Beijing, Peoples R China; 17.Shanghai Jiao Tong Univ, Shanghai Gen Hosp, Clin Res Inst, Sch Med, Shanghai, Peoples R China
推荐引用方式 GB/T 7714	Xia, Xian,Chen, Xingwei,Wu, Gang,et al. Three-dimensional facial-image analysis to predict heterogeneity of the human ageing rate and the impact of lifestyle[J]. NATURE METABOLISM,2020,2(9):946-+.
APA	Xia, Xian.,Chen, Xingwei.,Wu, Gang.,Li, Fang.,Wang, Yiyang.,...&Han, Jing-Dong J..(2020).Three-dimensional facial-image analysis to predict heterogeneity of the human ageing rate and the impact of lifestyle.NATURE METABOLISM,2(9),946-+.
MLA	Xia, Xian,et al."Three-dimensional facial-image analysis to predict heterogeneity of the human ageing rate and the impact of lifestyle".NATURE METABOLISM 2.9(2020):946-+.