Projects per year
Abstract
Despite their biological importance, the role of stem cells in human aging remains to be elucidated. In this work, we applied a machine learning methodology to GTEx transcriptome data and assigned stemness scores to 17,382 healthy samples from 30 human tissues aged between 20 and 79 years. We found that ~60% of the studied tissues exhibit a significant negative correlation between the subject's age and stemness score. The only significant exception was the uterus, where we observed an increased stemness with age. Moreover, we observed that stemness is positively correlated with cell proliferation and negatively correlated with cellular senescence. Finally, we also observed a trend that hematopoietic stem cells derived from older individuals might have higher stemness scores. In conclusion, we assigned stemness scores to human samples and show evidence of a pan-tissue loss of stemness during human aging, which adds weight to the idea that stem cell deterioration may contribute to human aging.
Original language | English |
---|---|
Pages (from-to) | 5796-5810 |
Number of pages | 15 |
Journal | Aging |
Volume | 16 |
Issue number | 7 |
DOIs | |
Publication status | Published - 4 Apr 2024 |
Keywords
- Humans
- Aging/physiology
- Aged
- Middle Aged
- Adult
- Female
- Cellular Senescence/physiology
- Stem Cells/metabolism
- Male
- Cell Proliferation
- Young Adult
- Transcriptome
- Machine Learning
- Hematopoietic Stem Cells/metabolism
Fingerprint
Dive into the research topics of 'Evidence of a pan-tissue decline in stemness during human aging'. Together they form a unique fingerprint.-
Machine learning to unravel anti-ageing compounds
Lourenco Rocha De Magalhaes, J. P. (Principal Investigator)
Biotechnology & Biological Sciences Research Council, University Of Liverpool
1/03/23 → 19/06/26
Project: Research Councils
-
GeneFriends: A gene and transcript co-expression resource
Lourenco Rocha De Magalhaes, J. P. (Principal Investigator)
1/09/22 → 28/08/24
Project: Research