A Decline in Stemness in Many Human Stem Cell Populations with Aging

Like the accumulation of senescent cells, loss of stem cell function is a problematic feature of aging. Also like the accumulation of senescent cells, loss of stem cell function is likely downstream of a combination of forms of molecular damage and consequent changes in cell behavior and cell signaling that are presently incompletely understood in detail and harder to address. Senescent cells can be cleared more readily than prevented, and stem cells may be more readily coerced into activity or replaced entirely than is the case for prevention of their age-related functional decline.

Stemness is a property of stem cells. Tautologically it is what distinguishes stem cells from somatic cells, primarily meaning (a) continual self-renewal of the population and (b) the ability to differentiate into multiple other cell types. Stem cell activity declines with age, but that doesn't necessarily mean that stemness is in decline. In muscle stem cells, for example, there is evidence for aged muscle stem cells to perform just as well as young muscle stem cells once removed from the aged tissue environment, even given a presumably greater burden of many forms of age-related damage inherent to the cells themselves. One can argue that many types of stem cell are restrained by damage to their niches, or by changes in the aged signaling environment, not by any inherent damage that reduces the potential for stemness.

In today's open access paper, researchers generate a stemness score based on transcriptomic data, and see how it changes with age in many tissues in the human body. This may be a blurred measure of capacity for stemness coupled with the impact of the aged microenvironment in which cells find themselves. Another interesting addition to this data would be to take cell samples and put them in a youthful environment, then test again and see how their stemness score changes.

Evidence of a pan-tissue decline in stemness during human aging

Although the aging process is the leading cause of human mortality and morbidity, being associated with several diseases, scientists still debate its causes and mechanisms. Among the biological pathways associated with aging, we can highlight stem cell exhaustion, which argues that during normal aging, the decrease in the number or activity of these cells contributes to physiological dysfunction in aged tissues. This concept is supported by the observation that aging is associated with reduced tissue renewal and repair at advanced ages. Moreover, longevity manipulations in mice often affect growth and cell division, which has been hypothesized to relate to stem cells.

Despite their importance, in vivo detection and quantification of stem cells are challenging, which makes it difficult to study their association with aging, especially in humans. In this context, detecting stemness-associated expression signatures is a promising strategy for studying stem cell biology. Stemness refers to a distinctive attribute marked by a series of molecular processes that delineate the essential properties of stem cells, enabling the generation of daughter cells and self-renewal. While widely employed in oncology, the exploration of this concept in gerontology has been comparatively limited.

In this study, we applied a machine learning method to detect stemness signatures from transcriptome data of healthy human tissues. The methodology, developed by Malta et al., was trained on stem cell classes and their differentiated progenitors and went through rigorous validation steps including tests in several datasets from tumor and non-tumor samples. Although initially used to study oncogenic dedifferentiation, this approach has also been employed to study normal and pathological (non-tumorous) samples. Therefore, we first downloaded expression data of 17,382 samples, divided into 30 tissues aged between 20 and 79 years, from GTEx in transcripts per million (TPM). After that, we followed assigned a stemness score to all GTEx samples.

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.

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