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Quantitative mapping of human hair greying and reversal in relation to life stress.

ABSTRACT: Hair greying is a hallmark of aging generally believed to be irreversible and linked to psychological stress. Here, we develop an approach to profile hair pigmentation patterns (HPPs) along individual human hair shafts, producing quantifiable physical timescales of rapid greying transitions. Using this method, we show white/grey hairs that naturally regain pigmentation across sex, ethnicities, ages, and body regions, thereby quantitatively defining the reversibility of greying in humans. Molecularly, grey hairs upregulate proteins related to energy metabolism, mitochondria, and antioxidant defenses. Combining HPP profiling and proteomics on single hairs, we also report hair greying and reversal that can occur in parallel with psychological stressors. To generalize these observations, we develop a computational simulation, which suggests a threshold-based mechanism for the temporary reversibility of greying. Overall, this new method to quantitatively map recent life history in HPPs provides an opportunity to longitudinally examine the influence of recent life exposures on human biology. This work was supported by the Wharton Fund and NIH grants GM119793, MH119336, and AG066828 (MP).

SUBMITTER: Rosenberg AM

PROVIDER: S-EPMC8219384 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Quantitative mapping of human hair greying and reversal in relation to life stress.

Rosenberg Ayelet M AM Rausser Shannon S Ren Junting J Mosharov Eugene V EV Sturm Gabriel G Ogden R Todd RT Patel Purvi P Kumar Soni Rajesh R Lacefield Clay C Tobin Desmond J DJ Paus Ralf R Picard Martin M

eLife 20210622

<h4>Background</h4>Hair greying is a hallmark of aging generally believed to be irreversible and linked to psychological stress.<h4>Methods</h4>Here, we develop an approach to profile hair pigmentation patterns (HPPs) along individual human hair shafts, producing quantifiable physical timescales of rapid greying transitions.<h4>Results</h4>Using this method, we show white/grey hairs that naturally regain pigmentation across sex, ethnicities, ages, and body regions, thereby quantitatively definin ...[more]

PMID: 34155974

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Project description:BackgroundGreying of the hair is an obvious sign of human aging. In addition to age, sex- and ancestry-specific patterns of hair greying are also observed and the progression of greying may be affected by environmental factors. However, little is known about the genetic control of this process. This study aimed to assess the potential of genetic data to predict hair greying in a population of nearly 1000 individuals from Poland.ResultsThe study involved whole-exome sequencing followed by targeted analysis of 378 exome-wide and literature-based selected SNPs. For the selection of predictors, the minimum redundancy maximum relevance (mRMRe) method was used, and then two prediction models were developed. The models included age, sex and 13 unique SNPs. Two SNPs of the highest mRMRe score included whole-exome identified KIF1A rs59733750 and previously linked with hair loss FGF5 rs7680591. The model for greying vs. no greying prediction achieved accuracy of cross-validated AUC = 0.873. In the 3-grade classification cross-validated AUC equalled 0.864 for no greying, 0.791 for mild greying and 0.875 for severe greying. Although these values present fairly accurate prediction, most of the prediction information was brought by age alone. Genetic variants explained < 10% of hair greying variation and the impact of particular SNPs on prediction accuracy was found to be small.ConclusionsThe rate of changes in human progressive traits shows inter-individual variation, therefore they are perceived as biomarkers of the biological age of the organism. The knowledge on the mechanisms underlying phenotypic aging can be of special interest to the medicine, cosmetics industry and forensics. Our study improves the knowledge on the genetics underlying hair greying processes, presents prototype models for prediction and proves hair greying being genetically a very complex trait. Finally, we propose a four-step approach based on genetic and epigenetic data analysis allowing for i) sex determination; ii) genetic ancestry inference; iii) greying-associated SNPs assignment and iv) epigenetic age estimation, all needed for a final prediction of greying.

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Dataset Information

Quantitative mapping of human hair greying and reversal in relation to life stress.

Publications

Quantitative mapping of human hair greying and reversal in relation to life stress.

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