Evidence map›Paper›PMID 29215023›Full record

ArticleScientific reports2017

A Pilot Characterization of the Human Chronobiome.

Carsten Skarke, Nicholas F Lahens, Seth D Rhoades, Amy Campbell, Kyle Bittinger, Aubrey Bailey, Christian Hoffmann, Randal S Olson, Lihong Chen, Guangrui Yang and 7 more

5 registry-linked trialsAbstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 5 registered trials, which are not on this map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

NCT02249793 completednot on this map

Exploratory Study in Healthy Volunteers to Define Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics

TypeobservationalSponsorUniversity of PennsylvaniaRan2014 to 2017Enrolled6ConditionsHealthy
NCT03590821 early_phase1not yet recruitingnot on this mapstarted 2027, after this paper: background citation

Modulating Celecoxib Induced Blood Pressure Changes by Timed Administration of Aspirin and the Human Chronobiome

TypeinterventionalSponsorUniversity of PennsylvaniaRan2027 to 2028Enrolled60ConditionsHealthyArmsAspirin 81 mg, Celecoxib 200mg capsule
NCT03598894 active not recruitingnot on this mapstarted 2018, after this paper: background citation

Non-dipping Hypertension and the Human Chronobiome

TypeobservationalSponsorUniversity of PennsylvaniaRan2018 to 2028Enrolled150ConditionsHypertensionArmsAmbulatory blood pressure measurements
NCT03601728 nasuspendednot on this mapstarted 2019, after this paper: background citation

A Personalized Medicine Prehabilitation Intervention Delivered Using Wearable Mobile Devices to Improve Cognitive Function in Elective Joint Replacement Surgery

TypeinterventionalSponsorUniversity of PennsylvaniaRan2019 to 2029Enrolled28ConditionsArthropathy of Knee Joint, Arthropathy of Hip JointArmspersonalized prehabilitation
NCT04225442 naactive not recruitingnot on this mapstarted 2020, after this paper: background citation

The Physiological Chronobiome Modified by Age, Sex and Under Evoked Conditions

TypeinterventionalSponsorUniversity of PennsylvaniaRan2020 to 2028Enrolled48ConditionsHealthy, Healthy AgingArmsFatty meal to challenge the physiological chronobiome in healthy young and old
3 · Its place in the literature

Who cites it

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Age and the Diurnal Oscillatory Features of the Human Chronobiome.medRxiv : the preprint server for health sciences · 2026
    Article
  7. Quantifying Sleep-Wake Rhythms in the Hospital Environment with Digital Technologies.medRxiv : the preprint server for health sciences · 2025
    Article
  8. Article
  9. Review
  10. Article
  11. Review
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  16. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Carsten SkarkeDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA. cskarke@pennmedicine.upenn.edu.ORCID 0000-0001-5145-3681
Nicholas F LahensDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Seth D RhoadesDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Amy CampbellDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Kyle BittingerDepartment of Microbiology, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Aubrey BaileyDepartment of Microbiology, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.ORCID 0000-0002-0712-217X
Christian HoffmannDepartment of Microbiology, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.ORCID 0000-0003-1736-8007
Randal S OlsonInstitute for Biomedical Informatics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Lihong ChenDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Guangrui YangDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Thomas S PriceDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Jason H MooreInstitute for Biomedical Informatics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Frederic D BushmanDepartment of Microbiology, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.ORCID 0000-0003-4740-4056
Casey S GreeneDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.ORCID 0000-0001-8713-9213
Gregory R GrantInstitute for Translational Medicine and Therapeutics (ITMAT), at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Aalim M WeljieDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
Garret A FitzGeraldDepartment of Systems Pharmacology and Translational Therapeutics, at the University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA. garret@upenn.edu.

Funding

INSTITUTIONAL CLINICAL AND TRANSLATIONAL SCIENCE AWARDUL1RR024134 · NCRR · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2006 to 2011
$70.4M
Institutional Clinical and Translational Science AwardUL1TR000003 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2012 to 2015
$38.9M
Translational Research Support CoreP30ES013508 · NIEHS · UNIVERSITY OF PENNSYLVANIA · PI Rebecca A Simmons · 2006 to 2026
$35.3M
NCATS NIH HHS UL1 TR000003NCRR NIH HHS UL1 RR024134
6 · The paper itself

Abstract

Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome - despite the "noise" attributable to the behavioral differences of free-living human volunteers. The majority (62%) of sensor readouts showed time-specific variability including the expected variation in blood pressure, heart rate, and cortisol. While variance in the multi-omics is dominated by inter-individual differences, temporal patterns are evident in the metabolome (5.4% in plasma, 5.6% in saliva) and in several genera of the oral microbiome. This demonstrates, despite a small sample size and limited sampling, the feasibility of characterizing at scale the human chronobiome "in the wild". Such reference data at scale are a prerequisite to detect and mechanistically interpret discordant data derived from patients with temporal patterns of disease expression, to develop time-specific therapeutic strategies and to refine existing treatments.

Indexed as

Circadian RhythmMetabolomeMicrobiotaProteomeTranscriptomeAdultBlood PressureBlood ProteinsHeart RateHumansHydrocortisoneMaleMouthPilot ProjectsSalivaTime FactorsBlood ProteinsHydrocortisoneProteome

Identifiers

PMID29215023
PMCPMC5719427

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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.