qMAP enabled microanatomical mapping of human skin aging Article Swipe
Kyu Sang Han
,
Inbal Sander
,
Jacqueline Kumer
,
Eric Resnick
,
C. Booth
,
Guoqing Cheng
,
Yebin Im
,
Bartholomew Starich
,
Ashley Kiemen
,
Jude M. Phillip
,
Sashank Reddy
,
Corrine E. Joshu
,
Joel Sunshine
,
Jeremy Walston
,
Denis Wirtz
,
Pei-Hsun Wu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.04.03.588011
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.04.03.588011
Aging is a major driver of diseases in humans. Identifying features associated with aging is essential for designing robust intervention strategies and discovering novel biomarkers of aging. Extensive studies at both the molecular and organ/whole-body physiological scales have helped determined features associated with aging. However, the lack of meso-scale studies, particularly at the tissue level, limits the ability to translate findings made at molecular scale to impaired tissue functions associated with aging. In this work, we established a tissue image analysis workflow - quantitative micro-anatomical phenotyping (qMAP) - that leverages deep learning and machine vision to fully label tissue and cellular compartments in tissue sections. The fully mapped tissue images address the challenges of finding an interpretable feature set to quantitatively profile age-related microanatomic changes. We optimized qMAP for skin tissues and applied it to a cohort of 99 donors aged 14 to 92. We extracted 914 microanatomic features and found that a broad spectrum of these features, represented by 10 cores processes, are strongly associated with aging. Our analysis shows that microanatomical features of the skin can predict aging with a mean absolute error (MAE) of 7.7 years, comparable to state-of-the-art epigenetic clocks. Our study demonstrates that tissue-level architectural changes are strongly associated with aging and represent a novel category of aging biomarkers that complement molecular markers. Our results highlight the complex and underexplored multi-scale relationship between molecular and tissue microanatomic scales.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.04.03.588011
- https://www.biorxiv.org/content/biorxiv/early/2024/04/05/2024.04.03.588011.full.pdf
- OA Status
- green
- Cited By
- 6
- References
- 73
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394695558
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4394695558Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2024.04.03.588011Digital Object Identifier
- Title
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qMAP enabled microanatomical mapping of human skin agingWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-04-05Full publication date if available
- Authors
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Kyu Sang Han, Inbal Sander, Jacqueline Kumer, Eric Resnick, C. Booth, Guoqing Cheng, Yebin Im, Bartholomew Starich, Ashley Kiemen, Jude M. Phillip, Sashank Reddy, Corrine E. Joshu, Joel Sunshine, Jeremy Walston, Denis Wirtz, Pei-Hsun WuList of authors in order
- Landing page
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https://doi.org/10.1101/2024.04.03.588011Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2024/04/05/2024.04.03.588011.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
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-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2024/04/05/2024.04.03.588011.full.pdfDirect OA link when available
- Concepts
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Skin Aging, Business, Psychology, Neuroscience, Medicine, DermatologyTop concepts (fields/topics) attached by OpenAlex
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6Total citation count in OpenAlex
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2025: 1, 2024: 5Per-year citation counts (last 5 years)
- References (count)
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73Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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