Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases
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Kellis_Synchronized age-related.pdf
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Author(s)
Ward, Lucas D.
Kheradpour, Pouya
Iriarte, Benjamin
Kellis, Manolis
Date Issued
October 2015
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Yang, Jialiang, Tao Huang, Francesca Petralia, Quan Long, Bin Zhang, Carmen Argmann, Yong Zhao, et al. “Synchronized Age-Related Gene Expression Changes Across Multiple Tissues in Human and the Link to Complex Diseases.” Scientific Reports 5 (October 19, 2015): 15145.
Version
Final published version
Abstract
Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred individuals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed, and some essential tissues (e.g., heart and lung) show much stronger “co-aging” than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues; it also presents a tissue-specific view of the link between aging and age-related diseases.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1038/srep15145
