SynthesisGenome medicine2017
Machine learning identifies a compact gene set for monitoring the circadian clock in human blood.
Synthesis in Genome medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.
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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
45 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for Genome-Scale Analysis of Biological Rhythms.Journal of biological rhythms · 2017Guideline
- Association between dim light melatonin onset predicted from gene expression profiles with sleep time and chronotype preference: A pilot study.Chronobiology international · 2025Trial
- Identification of a Preliminary Plasma Metabolome-based Biomarker for Circadian Phase in Humans.Journal of biological rhythms · 2021Trial
- Chrono-immunotherapy in genitourinary oncology: From emerging evidence to clinical translation (Review).Oncology letters · 2026Review
- Interpretable machine learning reveals hemispheric asymmetry of state switching in the suprachiasmatic nucleus.Patterns (New York, N.Y.) · 2026Article
- The circadian architecture of tumor immunity: mechanistic insights and treatment strategies.Biomarker research · 2026Review
- Review
- Circadian rhythm-guided cellular therapy in hematologic malignancies: mechanisms, clinical evidence, and optimization strategies.Biomarker research · 2026Review
- Transcriptional noise sets fundamental limits to decoding circadian clock phase from single-cell RNA snapshots.iScience · 2026Article
- Performance of Blood-Based Biomarkers for Human Circadian Pacemaker Phase: Training Sets Matter As Much As Feature-Selection Methods.Journal of biological rhythms · 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
- Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.PLoS biology · 2025Article
- Retrospective discrimination of PNES and epileptic seizure types using blood RNA signatures.Journal of neurology · 2025Article
- Circadian disruption, clock genes, and metabolic health.The Journal of clinical investigation · 2024Review
- Estimating dim light melatonin onset time in children using delta changes in melatonin.Sleep and biological rhythms · 2024Article
- Extensive dynamic changes in the human transcriptome and its circadian organization during prolonged bed rest.iScience · 2024Article
- Tumor circadian clock strength influences metastatic potential and predicts patient prognosis in luminal A breast cancer.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- TimeTeller: A tool to probe the circadian clock as a multigene dynamical system.PLoS computational biology · 2024Article
- Platform-independent estimation of human physiological time from single blood samples.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsHere 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.
resultsIn cross-validation on 498 samples from 60 individuals across three publicly available datasets, ZeitZeiger predicted CT in single samples with a median absolute error of 2.1 h. The predictor trained on all 498 samples used 15 genes, only two of which are part of the core circadian clock. By then applying ZeitZeiger to 475 additional samples from the same three datasets, we quantified how the circadian clock in the blood was affected by various perturbations to the sleep-wake and light-dark cycles. Finally, we extended ZeitZeiger (1) to handle intra-individual variation by making predictions based on multiple samples taken a known time apart, and (2) to handle inter-individual variation by personalizing predictions based on samples from the respective individual. Each of these strategies improved prediction of CT by ~20%.
conclusionsOur results are an important step towards precision circadian medicine. In addition, our generalizable extensions to ZeitZeiger may be applicable to the growing number of biological datasets that contain multiple observations per individual.
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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 Socratic graph.