Selected Publications

BACKGROUND. The circadian clock is a fundamental and pervasive biological program that coordinates 24-hour rhythms in physiology, metabolism and behaviour, and it is essential to health. Whereas time-of-day adapted therapy 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, gender, environmental light levels and season. An easy and convenient diagnostic tool is currently missing. METHODS. To establish a validated test, we followed a three-stage biomarker development strategy: (i) 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; (ii) these biomarkers were migrated to a clinically relevant gene expression-profiling platform (NanoString), and (iii) 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 dim light melatonin onset method at smaller monetary, time and sample number cost. CONCLUSION. The BodyTime assay provides a new diagnostic tool for personalization of healthcare according to the patient’s circadian clock.
JCI, 2018

Recent Publications

More Publications

Morning and evening peaking rhythmic genes are regulated by distinct transcription factors in Neurospora crassa

Towards quantifying coupling in circadian tissues.

Recent & Upcoming Talks

More Talks

Morgens ist das Infarktrisiko größer
22 Jul 2018 12:00 AM
Morgenmensch per Bluttest
9 Jul 2018 4:00 PM
Highly accurate determination of internal circadian time in humans from a single blood sample
5 Jun 2018 12:00 PM
BodyTime: Highly Accurate Determination of Internal Circadian Time From a Single Blood Sample
16 May 2018 11:30 AM
Harmonics in Mammals and Fungi: A Comparative Study
16 Jul 2017 1:00 PM

Recent Posts

It is common to encounter situations, where one has data from the same assay from different labs or sources, or data from different assays all targeting a phenomenon. One then proceeds to test a desired hypothesis on the basis of these multiple datasets. The only challenge in doing this is the manner in which the different datasets can be combined in a statistically appropriate way. Since in the biological context, it is rather difficult to quantify the quality of different datasets.


I was recently comparing different likely models (each was a different time profile) for each gene in time-series RNA-seq data. Since I did not have simple nested models, I was forced to use (as the simplest option) the Akaike Information Criterion (AIC) (I could have used the Bayesian Information Criterion as well) to select the “best” model. In the analysis of genomic data, the next step is typically thresholding the corrected p-values (i.


In the coming weeks, I plan to write a series of posts on good analysis practices for the calculation of circadian characteristics from common assays in chronobiology.



I give lectures as part of the Molecular Medicine program at the Charité.


  • bharath(dot)
  • +49 30 2093 98410
  • Philippstr. 13, Haus 4, D-10115 Berlin, Germany
  • email for appointment