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Hair Follicles as a Critical Model for Monitoring the Circadian Clock

Journal

Publisher

MDPI
DOI: 10.3390/ijms24032407

Keywords

circadian rhythm; clock; hair follicle; sleep; aging; chronotherapy

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Clock genes in hair follicles are regulated by both the central circadian system and external factors such as light and thyroid hormones. They play a role in regulating physiological processes of hair follicles, including hair growth and pigmentation. Hair follicles can serve as a noninvasive method for monitoring circadian-rhythm-related conditions in humans, and combining hair follicle sampling with other assays can improve their applications. Hair follicles provide insights into potential mechanisms of circadian-rhythm-related conditions and can support personalized treatment scheduling.
Clock (circadian) genes are heterogeneously expressed in hair follicles (HFs). The genes can be modulated by both the central circadian system and some extrinsic factors, such as light and thyroid hormones. These circadian genes participate in the regulation of several physiological processes of HFs, including hair growth and pigmentation. On the other hand, because peripheral circadian genes are synchronized with the central clock, HFs could provide a noninvasive and practical method for monitoring and evaluating multiple circadian-rhythm-related conditions and disorders among humans, including day and night shifts, sleep-wake disorders, physical activities, energy metabolism, and aging. However, due to the complexity of circadian biology, understanding how intrinsic oscillation operates using peripheral tissues only may be insufficient. Combining HF sampling with multidimensional assays such as detection of body temperature, blood samples, or certain validated questionnaires may be helpful in improving HF applications. Thus, HFs can serve as a critical model for monitoring the circadian clock and can help provide an understanding of the potential mechanisms of circadian-rhythm-related conditions; furthermore, chronotherapy could support personalized treatment scheduling based on the gene expression profile expressed in HFs.

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