High-accuracy determination of internal circadian time from a single blood sample
Nicole Wittenbrink, … , Dieter Kunz, Achim Kramer
Nicole Wittenbrink, … , Dieter Kunz, Achim Kramer
Published August 6, 2018
Citation Information: J Clin Invest. 2018. https://doi.org/10.1172/JCI120874.
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Categories: Clinical Medicine Genetics

High-accuracy determination of internal circadian time from a single blood sample

Abstract

BACKGROUND. The circadian clock is a fundamental and pervasive biological program that coordinates 24-hour rhythms in physiology, metabolism, and behavior, and it is essential to health. Whereas therapy adapted to time of day is increasingly reported to be highly successful, it needs to be personalized, since internal circadian time is different for each individual. In addition, internal time is not a stable trait, but is influenced by many factors, including genetic predisposition, age, sex, environmental light levels, and season. An easy and convenient diagnostic tool is currently missing. METHODS. To establish a validated test, we followed a 3-stage biomarker development strategy: (a) using circadian transcriptomics of blood monocytes from 12 individuals in a constant routine protocol combined with machine learning approaches, we identified biomarkers for internal time; and these biomarkers (b) were migrated to a clinically relevant gene expression profiling platform (NanoString) and (c) were externally validated using an independent study with 28 early or late chronotypes. RESULTS. We developed a highly accurate and simple assay (BodyTime) to estimate the internal circadian time in humans from a single blood sample. Our assay needs only a small set of blood-based transcript biomarkers and is as accurate as the current gold standard method, dim-light melatonin onset, at smaller monetary, time, and sample-number cost. CONCLUSION. The BodyTime assay provides a new diagnostic tool for personalization of health care according to the patient’s circadian clock. FUNDING. This study was supported by the Bundesministerium für Bildung und Forschung, Germany (FKZ: 13N13160 and 13N13162) and Intellux GmbH, Germany.

Authors

Nicole Wittenbrink, Bharath Ananthasubramaniam, Mirjam Münch, Barbara Koller, Bert Maier, Charlotte Weschke, Frederik Bes, Jan de Zeeuw, Claudia Nowozin, Amely Wahnschaffe, Sophia Wisniewski, Mandy Zaleska, Osnat Bartok, Reut Ashwal-Fluss, Hedwig Lammert, Hanspeter Herzel, Michael Hummel, Sebastian Kadener, Dieter Kunz, Achim Kramer

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Figure 1

Biomarker discovery strategy, sampling schemes, and study cohorts.

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Biomarker discovery strategy, sampling schemes, and study cohorts. (A) B...
(A) Biomarker discovery pipeline. (B) Sampling scheme and composition of the BOTI study cohort (n = 12 subjects) by sex, age, and DLMO. Blood samples were drawn at regular 3-hour intervals over a period of 40 hours (M = 14 samples per subject). Each sample was assigned an external time (Central European Time) and an internal time (hours past DLMO, derived from saliva melatonin profiles). The displayed sampling scheme is representative of the subject highlighted by a circle in the study cohort plot (green lines indicate sampling times on the second day). (C) Sampling scheme and composition of the VALI study cohort (n = 28 subjects) by sex, age, and DLMO. The spread of the BOTI study cohort (B) in the same coordinate system is shaded in gray. In contrast to the BOTI study, the VALI study includes extreme and moderately extreme chronotypes. For each subject 2 blood samples were obtained, drawn 6 hours apart (M1, morning sample; M2, afternoon sample). Each sample was assigned an external time (Central European Time) and an internal time (hours past DLMO derived from saliva melatonin secretion profiles).