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Two different aging paths in human blood revealed by integrated analysis of gene Expression, mutation and alternative splicing

Authors :
Xin Tong
Wen-Xing Li
Jihao Liang
Yang Zheng
Shao-xing Dai
Source :
Gene. 829:146501
Publication Year :
2022
Publisher :
Elsevier BV, 2022.

Abstract

Aging is a complex life process that human organs and tissues steadily and continuously decline. Aging has huge heterogeneity, which shows different aging rates among different individuals and in different tissues of the same individual. Many studies of aging are often contradictory and show little common signature. The integrated analysis of these transcriptome datasets will provide an unbiased global view of the aging process. Here, we integrated 8 transcriptome datasets including 757 samples from healthy human blood to study aging from three aspects of gene expression, mutations, and alternative splicing. Surprisingly, we found that transcriptome changes in blood are relatively independent of the chronological age. Further pseudotime analysis revealed two different aging paths (AgingPath1 and AgingPath2) in human blood. The differentially expressed genes (DEGs) along the two paths showed a limited overlap and are enriched in different biological processes. The mutations of DEGs in AgingPath1 are significantly increased in the aging process, while the opposite trend was observed in AgingPath2. Expression quantitative trait loci (eQTL) and splicing quantitative trait loci (sQTL) analysis identified 304 important mutations that can affect both gene expression and alternative splicing during aging. Finally, by comparison between aging and Alzheimer's disease, we identified 37 common DEGs in AgingPath1, AgingPath2 and Alzheimer's disease. These genes may contribute to the shift from aging state to Alzheimer's disease. In summary, this study revealed the two aging paths and the related genes and mutations, which provides a new insight into aging and aging-related disease.

Details

ISSN :
03781119
Volume :
829
Database :
OpenAIRE
Journal :
Gene
Accession number :
edsair.doi.dedup.....f4a58f44ad6e6d1e3ce3ef3fcc7ccac8
Full Text :
https://doi.org/10.1016/j.gene.2022.146501