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Quantitative Mapping of Human Hair Graying and Reversal in Relation to Life Stress

Overview of attention for article published in bioRxiv, May 2020
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Article details
Title
Quantitative Mapping of Human Hair Graying and Reversal in Relation to Life Stress
Published in
bioRxiv, May 2020
DOI 10.1101/2020.05.18.101964
Authors
Abstract

Hair graying is a universal hallmark of aging believed to be linked to psychological stress. Here we develop a novel approach to quantitatively profile natural graying events along individual human hair shafts, resulting in a quantifiable physical timescale of hair pigmentation patterns (HPPs). Using this approach, we quantify rare events of white/gray hairs that naturally regain pigmentation within days to weeks, thereby quantitatively defining the reversibility of graying in healthy, unmedicated individuals. Proteomic analysis shows that graying is marked by the upregulation of proteins related to energy metabolism, mitochondria, and antioxidant defenses. Combining hair pigmentation profiling and proteomics at the single hair level, we also report hair graying and its reversal occurring in parallel with behavioral and psychological stressors. A computational simulation suggests a threshold-based mechanism for the temporary reversibility of graying. Quantitatively mapping HPPs in humans provides an opportunity to longitudinally examine the influence of life exposures on biological aging.

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X Demographics

The data shown below were collected from the profiles of 124 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 5 31%
Professor 1 6%
Student > Postgraduate 1 6%
Student > Master 1 6%
Unknown 8 50%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 19%
Environmental Science 1 6%
Agricultural and Biological Sciences 1 6%
Computer Science 1 6%
Medicine and Dentistry 1 6%
Other 0 0%
Unknown 9 56%