Machine learning identifies a compact gene set for monitoring the circadian clock in human blood.

ABSTRACT:

Background

The circadian clock and the daily rhythms it produces are crucial for human health, but are often disrupted by the modern environment. At the same time, circadian rhythms may influence the efficacy and toxicity of therapeutics and the metabolic response to food intake. Developing treatments for circadian dysfunction, as well as optimizing the daily timing of treatments for other health conditions, will require a simple and accurate method to monitor the molecular state of the circadian clock.

Methods

Here we used a recently developed method called ZeitZeiger to predict circadian time (CT, time of day according to the circadian clock) from genome-wide gene expression in human blood.

Results

In cross-validation on 498 samples from 60 individuals across three

SUBMITTER: Hughey JJ 

PROVIDER: S-EPMC5329904 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature