Evidence map›Paper›PMID 42449945›Full record

ArticleInternational journal of molecular sciences2026

Impact of Daily Rhythms and Postprandial Responses on the Plasma Metabolome.

Tulsi Suchak, Namrata R Chowdhury, Victoria L Revell, Cheryl Isherwood, Florence I Raynaud, Daan R van der Veen, Nophar Geifman, Debra J Skene, Matt Spick

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Tulsi SuchakSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK.
Namrata R ChowdhuryChronobiology Section, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7JG, UK.ORCID 0009-0008-9277-6223
Victoria L RevellChronobiology Section, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7JG, UK.
Cheryl IsherwoodChronobiology Section, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7JG, UK.
Florence I RaynaudCancer Research UK Cancer Therapeutics Unit, Division of Cancer Therapeutics, The Institute of Cancer Research, London SM2 5NG, UK.ORCID 0000-0003-0957-6279
Daan R van der VeenChronobiology Section, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7JG, UK.
Nophar GeifmanSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK.ORCID 0000-0003-2956-6676
Debra J SkeneChronobiology Section, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7JG, UK.ORCID 0000-0001-8202-6180
Matt SpickSchool of Health Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK.ORCID 0000-0002-9417-6511

Funding

Biotechnology and Biological Sciences Research Council BB/I019405/1Cancer Research UK C2739/A22897Cancer Research UK C309/A25144EUCLOCK 018741
6 · The paper itself

Abstract

Peripheral blood metabolite concentrations vary with food intake and time of day, risking confounding effects in metabolomics studies with non-standardised sampling conditions or incomplete metadata. Such effects are often overlooked during study design, limiting the clinical translation of biomarkers and wasting resources for researchers, funders and clinicians. In our random sample of 100 human metabolomics studies, 56% did not control for food intake, and 59% did not explicitly control for sampling time. To provide a study design resource, we analysed a liquid-chromatography-mass-spectrometry-targeted dataset from controlled laboratory studies of 24 young, healthy participants (12 male, 12 female) sampled every 2 h for 34 h, with fixed-macronutrient meals provided at set times. Acute postprandial responses were quantified by effect size using pre- and post-meal windows, while daily rhythmicity was assessed using a mixed-effects cosinor model. Analyses were sex-stratified, and metabolites were classified as meal-responsive, time-of-day-responsive, both, or neither. Amino acids and their derivatives showed strong postprandial increases, whereas lipid classes showed minimal changes. Rhythmicity varied across metabolites, enabling the identification of features sensitive to meal timing and/or time of day. These results aim to provide a comprehensive dictionary of metabolite effect sizes for study design and metadata collection to support reproducibility and the clinical translation of potential biomarkers.

Indexed as

Circadian RhythmMetabolomePostprandial PeriodAdultBiomarkersFemaleHumansMaleMetabolomicsYoung AdultBiomarkerschronobiologymetabolomicspostprandial responsesreproducibilitystudy designtranslation

Identifiers

PMID42449945
PMCPMC13361673

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Registered trials

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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.