ArticleProceedings of the National Academy of Sciences of the United States of America2024
Platform-independent estimation of human physiological time from single blood samples.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Association between dim light melatonin onset predicted from gene expression profiles with sleep time and chronotype preference: A pilot study.Chronobiology international · 2025Trial
- BMAL1 in cardiovascular diseases: Molecular mechanisms, circadian regulation and translational perspectives (Review).Molecular medicine reports · 2026Review
- Time vortex: the circadian-dopaminergic dialogue in Parkinson's disease.NPJ Parkinson's disease · 2026Review
- Multi-Omics Landscape of Circadian Clock Dysregulation Across the Chronic Liver Disease Spectrum.International journal of molecular sciences · 2026Review
- VIST: variational inference for single cell time series.Genome biology · 2026Article
- Variational inference of single cell time series.bioRxiv : the preprint server for biology · 2025Article
- Advancing clinical response against glioblastoma: Evaluating SHP1705 CRY2 activator efficacy in preclinical models and safety in phase I trials.Neuro-oncology · 2025Article
- Blood Clock Correlation Distance (BloodCCD) as a novel marker to detect circadian rhythm disruption in cancer survivors with insomnia.BJC reports · 2025Article
- Integrating Assessment of Circadian Rhythmicity to Improve Treatment Outcomes for Circadian Rhythm Sleep-Wake Disorders: Updates on New Treatments.Current sleep medicine reports · 2025Review
- Higher central circadian temperature amplitude is associated with greater metabolite rhythmicity in humans.Scientific reports · 2024Article
- tauFisher predicts circadian time from a single sample of bulk and single-cell pseudobulk transcriptomic data.Nature communications · 2024Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Abundant epidemiological evidence links circadian rhythms to human health, from heart disease to neurodegeneration. Accurate determination of an individual's circadian phase is critical for precision diagnostics and personalized timing of therapeutic interventions. To date, however, we still lack an assay for physiological time that is accurate, minimally burdensome to the patient, and readily generalizable to new data. Here, we present TimeMachine, an algorithm to predict the human circadian phase using gene expression in peripheral blood mononuclear cells from a single blood draw. Once trained on data from a single study, we validated the trained predictor against four independent datasets with distinct experimental protocols and assay platforms, demonstrating that it can be applied generalizably. Importantly, TimeMachine predicted circadian time with a median absolute error ranging from 1.65 to 2.7 h, regardless of systematic differences in experimental protocol and assay platform, without renormalizing the data or retraining the predictor. This feature enables it to be flexibly applied to both new samples and existing data without limitations on the transcriptomic profiling technology (microarray, RNAseq). We benchmark TimeMachine against competing approaches and identify the algorithmic features that contribute to its performance.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.