1. A population-based gene expression signature of molecular clock phase from a single epidermal sample
- Author
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Gang Wu, Marc D. Ruben, Lauren J. Francey, David F. Smith, Joseph D. Sherrill, John E. Oblong, Kevin J. Mills, and John B. Hogenesch
- Subjects
Skin ,Dermis ,Epidermis ,Circadian medicine ,Population rhythm ,Circadian biomarkers ,Medicine ,Genetics ,QH426-470 - Abstract
Abstract Background For circadian medicine to influence health, such as when to take a drug or undergo a procedure, a biomarker of molecular clock phase is required––one that is easily measured and generalizable across a broad population. It is not clear that any circadian biomarker yet satisfies these criteria. Methods We analyzed 24-h molecular rhythms in human dermis and epidermis at three distinct body sites, leveraging both longitudinal (n = 20) and population (n = 154) data. We applied cyclic ordering by periodic structure (CYCLOPS) to order the population samples where biopsy time was not recorded. With CYCLOPS-predicted phases, we used ZeitZeiger to discover potential biomarkers of clock phase. Results Circadian clock function was strongest in the epidermis, regardless of body site. We identified a 12-gene expression signature that reported molecular clock phase to within 3 h (mean error = 2.5 h) from a single sample of epidermis––the skin’s most superficial layer. This set performed well across body sites, ages, sexes, and detection platforms. Conclusions This research shows that the clock in epidermis is more robust than dermis regardless of body site. To encourage ongoing validation of this putative biomarker in diverse populations, diseases, and experimental designs, we developed SkinPhaser––a user-friendly app to test biomarker performance in datasets ( https://github.com/gangwug/SkinPhaser ).
- Published
- 2020
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