AUTHOR=Wang Fayou , Yang Jialiang , Lin Huixin , Li Qian , Ye Zixuan , Lu Qingqing , Chen Luonan , Tu Zhidong , Tian Geng 

TITLE=Improved Human Age Prediction by Using Gene Expression Profiles From Multiple Tissues

JOURNAL=Frontiers in Genetics

VOLUME=Volume 11 - 2020

YEAR=2020

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2020.01025

DOI=10.3389/fgene.2020.01025

ISSN=1664-8021

ABSTRACT=Studying transcriptome chronological change from tissues across the whole body can provide valuable information for understanding aging and longevity. Although there are researches on the effect of single tissue transcriptome on human aging, or aging in mouse across multiple tissues, the study of human body-wide multi-tissue transcriptomes on aging is not yet available. In this study, we proposed a quantitative model to predict human age by using gene expression data from 46 tissues generated by the Genotype-Tissue Expression (GTEx) project. Specifically, the biological age of a person was first predicted via gene expression profile of single tissue. Then we combined the gene expression profiles from two tissues and compared the predictive accuracy between single and two tissues. The best performance as measured by the root-mean-square error (RMSE) is 3.92 years for single tissue (in Pituitary), which deceased to 3.6 years when we combined two tissues (Pituitary and Muscle) together. Different tissues have different potential in predicting chronological age. The prediction accuracy is improved by combining multiple tissues, supporting that aging is a systemic process involving multiple tissues across human body.