Detecting

HairTime: A noninvasive assay for estimating circadian phase from a single hair sample

Authors

Bert Maier, Luísa K. Pilz, Selin Özcakir, Ali Rahjouei, Ashraf N. Abdo, Jan de Zeeuw, Dieter Kunz, Achim Kramer

Journal

Proc Natl Acad Sci USA

Abstract

Circadian clocks govern daily physiological and behavioral processes and are crucial for health; disruptions can lead to various diseases. The circadian phase of entrainment—the phase of the internal circadian clock in relation to external environmental cycles—is influenced by both genetic and environmental factors, varies between individuals, and is reflected in daily behaviors such as sleep–wake patterns, cognitive performance, and physical activity. While circadian phase may also fluctuate within individuals, the dynamics and extent of such variation in daily life remain largely unexplored. The gold standard for circadian phase assessment, dim-light melatonin onset (DLMO), is impractical for large-scale studies, and blood-based molecular biomarkers, while promising, are limited in feasibility. To address these challenges, we developed HairTime, a noninvasive assay that estimates circadian phase from a single daytime hair sample. Developed and evaluated in two steps—a training and a validation study—HairTime demonstrated strong predictive power compared to DLMO. Suitable for large-scale studies, it was assessed using over 4,000 samples. Circadian phase estimations showed a normal distribution and were associated with age, sex, and notably, work schedules, with earlier timing on workdays, suggesting that societal factors can modulate internal rhythms. Together, these findings establish HairTime as a promising tool for assessing circadian phase in research and lay the foundation for future applications in personalized chronotherapy.

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Supporting media

Member authors

Research area

S01

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Scientific service project

This consortium relies on standardized methods, high-quality biospecimens, and computational tools to enable circadian medicine research. This service project provides molecular biomarker assays, standardized cohorts, multi-omics datasets, and bioinformatics support for the analysis of high-dimensional circadian data. Its resources and expertise are used across the consortium, supporting the discovery of circadian principles and facilitating personalized interventions.

Scientific service project

This consortium relies on standardized methods, high-quality biospecimens, and computational tools to enable circadian medicine research. This service project provides molecular biomarker assays, standardized cohorts, multi-omics datasets, and bioinformatics support for the analysis of high-dimensional circadian data. Its resources and expertise are used across the consortium, supporting the discovery of circadian principles and facilitating personalized interventions.