One of the challenges in human circadian studies is tracking an individual’s own internal clock, which traditionally requires hourly sampling of markers such as melatonin across the 24-hour day, which is expensive and invasive for the subject.
A new study published in the journal PNAS, has unveiled TimeSignature – a new software tool with the ability to estimate our biological time from just two blood draws, which can be flexibly spaced 8-12 hours apart. Rosemary Braun and colleagues measured the expression of thousands of genes in the blood from their own cohort of healthy volunteers, as well as from three other independent datasets already published. They then developed a machine-learning algorithm to sift through the data and make predictions of circadian time based on genes with the strongest cyclical patterns.
The best markers consist of a panel of ~40 genes, many of which have diverse roles, such as in metabolism or immune function. This efficient new test is accurate to within 2 hours of an individual’s circadian time and will be useful in determining when our internal clock is out of sync with the time of the external world. As the blood test becomes clinically available, more easily than ever before will researchers and physicians be able to optimize the timing of medical interventions and explore the links between circadian disruption and chronic disease.
http://www.pnas.org/content/115/39/E9247
A new study published in the journal PNAS, has unveiled TimeSignature – a new software tool with the ability to estimate our biological time from just two blood draws, which can be flexibly spaced 8-12 hours apart. Rosemary Braun and colleagues measured the expression of thousands of genes in the blood from their own cohort of healthy volunteers, as well as from three other independent datasets already published. They then developed a machine-learning algorithm to sift through the data and make predictions of circadian time based on genes with the strongest cyclical patterns.
The best markers consist of a panel of ~40 genes, many of which have diverse roles, such as in metabolism or immune function. This efficient new test is accurate to within 2 hours of an individual’s circadian time and will be useful in determining when our internal clock is out of sync with the time of the external world. As the blood test becomes clinically available, more easily than ever before will researchers and physicians be able to optimize the timing of medical interventions and explore the links between circadian disruption and chronic disease.
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.
http://www.pnas.org/content/115/39/E9247
