Cell-type-specific aging clocks to quantify aging and rejuvenation in neurogenic regions of the brain
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Abstract
The diversity of cell types is a challenge for quantifying aging and its reversal. Here we develop ‘aging clocks’ based on single-cell transcriptomics to characterize cell-type-specific aging and rejuvenation. We generated single-cell transcriptomes from the subventricular zone neurogenic region of 28 mice, tiling ages from young to old. We trained single-cell-based regression models to predict chronological age and biological age (neural stem cell proliferation capacity). These aging clocks are generalizable to independent cohorts of mice, other regions of the brains, and other species. To determine if these aging clocks could quantify transcriptomic rejuvenation, we generated single-cell transcriptomic datasets of neurogenic regions for two interventions—heterochronic parabiosis and exercise. Aging clocks revealed that heterochronic parabiosis and exercise reverse transcriptomic aging in neurogenic regions, but in different ways. This study represents the first development of high-resolution aging clocks from single-cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.
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This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/5860860.
This study addresses an essential question of the contribution of different cell types and rejuvenation strategies to the process of aging. Since many of the models used in this field are based on bulk tissue input or purified cell populations, the contribution of specific cell types is difficult to discern. The authors use single-cell transcriptomic data to define 'aging clocks' to predict chronological and biological age using the subventricular zone (SVZ) neurogenic region of young and old mouse models (This region has many different cell populations). They also use these models to study the effect of different rejuvenation strategies (exercise and parabiosis) on the process of aging.
In…
This Zenodo record is a permanently preserved version of a PREreview. You can view the complete PREreview at https://prereview.org/reviews/5860860.
This study addresses an essential question of the contribution of different cell types and rejuvenation strategies to the process of aging. Since many of the models used in this field are based on bulk tissue input or purified cell populations, the contribution of specific cell types is difficult to discern. The authors use single-cell transcriptomic data to define 'aging clocks' to predict chronological and biological age using the subventricular zone (SVZ) neurogenic region of young and old mouse models (This region has many different cell populations). They also use these models to study the effect of different rejuvenation strategies (exercise and parabiosis) on the process of aging.
In my review of this article, I am limited by the lack of proficiency in machine learning models; however, I enjoyed the challenge of reading this article. The study is robust and well designed, and the article follows a pattern that makes the data easy to understand. The following comments are geared towards including points to help with the layout and discussion points to help with understanding.
Comments:
1. The introduction provides a clear and concise summary of the process of aging, the current state of the machine learning approaches to quantify aging, and the challenges associated with it. The authors highlight the current need for single cell-based systems and provide the proper introduction to help get acquainted with the subject matter. However, it would help the readers if the introduction had a summary paragraph of the study's aims, methods, and main findings.
2. In the experiments related to the heterochronic parabiosis experiments, there is a difference in the results obtained between the two cohorts. It would be helpful for the readers if the authors could explain why the cohort with the 21m difference between the young and old mice had a better rejuvenation effect than the cohort with the 15.5m difference?
3. Since the mice in this study are male, It would be helpful if the authors could include in their discussion their speculation on if they would anticipate sex-based differences in their observations.
4. The current version of the preprint does not have a complete discussion, and it appears to be missing a page (page 11 when converted to a pdf). Adding this information will help the readers better understand the points discussed.
5. There are two references, 1-94 and then again 1-11 after the methods section. It wasn't easy to find some of the references in the text due to this reason.
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