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 best performance as measured by the root-mean-square error is 3.92 years for single tissue (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 the human body.

研究整个组织中转录组的时间顺序变化可以为了解衰老和寿命提供有价值的信息。尽管已经进行了关于单组织转录组对人衰老的影响或跨多个组织的小鼠衰老的研究，但尚无关于人体全组织多转录组对衰老的研究。在这项研究中，我们提出了一个定量模型，通过使用基因型组织表达（GTEx）项目生成的46个组织的基因表达数据来预测人类年龄。具体而言，首先通过单个组织的基因表达谱预测人的生物学年龄。然后，我们结合了来自两个组织的基因表达谱，并比较了单个组织和两个组织之间的预测准确性。以均方根误差衡量的最佳性能是单个组织（垂体）为3.92年，而当我们将两个组织（垂体和肌肉）结合在一起时，其最佳性能为3.6年。不同的组织在预测年龄方面具有不同的潜力。通过组合多个组织来提高预测准确性，支持衰老是涉及人体中多个组织的系统性过程。