Evidence map›Paper›PMID 40657665›Full record

ArticleJournal of sleep research2026

Exploring the Relationship Between Caffeine Consumption, Caffeine Metabolism, and Sleep Behaviours: A Mendelian Randomisation Study.

Nilabhra R Das, Benjamin Woolf, Stephanie Page, Rebecca C Richmond, Jasmine Khouja

Abstract read
In one paragraph

Article in Journal of sleep research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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

5 authors.

Nilabhra R DasPopulation Health Sciences, University of Bristol, Bristol, UK.ORCID 0000-0001-8187-0080
Benjamin WoolfSchool of Psychological Sciences, University of Bristol, Bristol, UK.ORCID 0000-0002-1505-2570
Stephanie PageSchool of Psychological Sciences, University of Bristol, Bristol, UK.
Rebecca C RichmondPopulation Health Sciences, University of Bristol, Bristol, UK.
Jasmine KhoujaSchool of Psychological Sciences, University of Bristol, Bristol, UK.

Funding

Cancer Research UK C18281/A29019Medical Research Council Biostatistics Unit MC_UU_00040/1Medical Research Council Integrative Epidemiology Unit MC_UU_00011/1Medical Research Council Integrative Epidemiology Unit MC_UU_00011/7National Institute of Health and Care Research Oxford Health Biomedical Research Centre NIHR203316
6 · The paper itself

Abstract

Higher consumption of caffeinated beverages is associated with disturbed sleep patterns. Using genetic variants as proxies for caffeine consumption, caffeine metabolism, and sleep traits, we investigated whether this association reflects a direct effect of caffeine. Genetic variants associated with caffeine consumption (n = 407,072), caffeine metabolism (n = 9876), chronotype (n = 449,734), daytime napping (n = 452,633), daytime sleepiness (n = 452,071), getting up in morning (n = 385,949), insomnia (n = 453,379), and sleep duration (n = 446,118) identified in individuals from several studies, including the UK Biobank, were used to explore bi-directional causal relationships between caffeine and sleep using a series of univariable Mendelian Randomisation analyses. We used multivariable Mendelian Randomisation to explore the direct effects of caffeine consumption on sleep behaviours while adjusting for metabolism and vice versa. Higher consumption decreased daytime sleepiness (β

Indexed as

CaffeineSleepFemaleHumansMaleMendelian Randomization AnalysisMiddle AgedSleep Initiation and Maintenance DisordersCaffeinecaffeinegeneticsMendelian randomisationmetabolitessleep

Identifiers

PMID40657665
PMCPMC12856127

What OpenQuestion holds

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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.