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

ABSTRACT: Studying transcriptome chronological change from tissues across the whole body can provide valuable information for understanding aging and longevity. Although there has been research on the effect of single-tissue transcriptomes on human aging or aging in mice across multiple tissues, the study of human body-wide multi-tissue transcriptomes on aging is not yet available. In this study, we propose 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 is first predicted via the gene expression profile of a single tissue. Then, we combine the gene expression profiles from two tissues and compare the predictive accuracy between single and two tissues. The

SUBMITTER: Wang F 

PROVIDER: S-EPMC7546819 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature