Medical researchers at Northwestern University have developed a new blood test that can determine the precise time of your body’s internal clock. Circadian clocks play a key role in regulating a vast array of biological processes, with significant implications for human health. Accurate assessment of physiological time using transcriptional biomarkers found in human blood can significantly improve the diagnosis of circadian disorders and optimize the delivery time of therapeutic treatments.
The new blood test will help doctors and hospital workers make sure that medications are delivered according to your body’s schedule, not the clock on the wall. Details on the patent-pending medical technology are described in the Sept. 10 issue of the journal PNAS
The test measures 40 different gene expression markers in the blood and can be taken any time of day. This is a much more precise and sophisticated measurement than identifying whether you are a morning lark or a night owl. Researchers have introduced TimeSignature, an algorithm that robustly infers circadian time from gene expression. They have demonstrated its application in data from three independent studies using distinct microarrays and further validate it against a new set of samples profiled by RNA-sequencing. Our results show that TimeSignature is more accurate and efficient than competing methods, estimating circadian time to within 2 hours for the majority of samples.
Determining the state of an individual’s internal physiological clock has important implications for precision medicine, from diagnosing neurological disorders to optimizing drug delivery. To be useful, such a test must be accurate, minimally burdensome to the patient, and robust to differences in patient protocols, sample collection, and assay technologies. TimeSignature is a machine-learning approach to predict physiological time based on gene expression in human blood. A powerful feature is TimeSignature’s generalizability, enabling it to be applied to samples from disparate studies and yield highly accurate results despite systematic differences between the studies. This quality is unique among expression-based predictors and addresses a major challenge in the development of reliable and clinically useful biomarker tests.
Circadian timing is a modifiable risk factor for improving cognitive health, but if we can’t measure it, it’s difficult to know if we’ve made the right diagnosis. Now we can measure it just like a lipid level.
The software and algorithm will be made available to other researchers for further development, and will also enable them to easily examine the impact of misaligned circadian clocks in a range of maladies, including diabetes and Alzheimer’s disease.
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