Evidence map›Paper›PMID 38054622›Full record

ArticleMolecular nutrition & food research2024

Plasma Metabolites Related to the Consumption of Different Types of Dairy Products and Their Association with New-Onset Type 2 Diabetes: Analyses in the Fenland and EPIC-Norfolk Studies, United Kingdom.

Eirini Trichia, Albert Koulman, Isobel D Stewart, Soren Brage, Simon J Griffin, Julian L Griffin, Kay-Tee Khaw, Claudia Langenberg, Nicholas J Wareham, Fumiaki Imamura and 1 more

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In one paragraph

Article in Molecular nutrition & food research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Recent advances in precision nutrition and cardiometabolic diseases.Revista espanola de cardiologia (English ed.) · 2025
    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

11 authors at 1 institution in 1 country.

Eirini TrichiaMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.ORCID 0000-0002-7655-5905
Albert KoulmanMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Isobel D StewartMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Soren BrageMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Simon J GriffinMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Julian L GriffinDepartment of Biochemistry, University of Cambridge, Cambridge, CB2 1QW, UK.
Kay-Tee KhawMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Claudia LangenbergMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Nicholas J WarehamMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Fumiaki ImamuraMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
Nita G ForouhiMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0SL, UK.
University of Cambridge · GB

Funding

Cancer Research UK C864/A14136Medical Research Council MC_UU_00006/1Medical Research Council MC_UU_00006/3Medical Research Council MC_UU_00006/4Medical Research Council MC_UU_00006/6Medical Research Council MC_UU_12015/3Medical Research Council MR/N003284/1Wellcome Trust
6 · The paper itself

Abstract

scopeTo identify metabolites associated with habitual dairy consumption and investigate their associations with type 2 diabetes (T2D) risk. METHODS AND

resultsMetabolomics assays were conducted in the Fenland (n = 10,281) and EPIC-Norfolk (n = 1,440) studies. Using 82 metabolites assessed in both studies, we developed metabolite scores to classify self-reported consumption of milk, yogurt, cheese, butter, and total dairy (Fenland Study-discovery set; n = 6035). Internal and external validity of the scores was evaluated (Fenland-validation set, n = 4246; EPIC-Norfolk, n = 1440). The study assessed associations between each metabolite score and T2D incidence in EPIC-Norfolk (n = 641 cases; 16,350 person-years). The scores classified low and high consumers for all dairy types with internal validity, and milk, butter, and total dairy with external validity. The scores were further associated with lower incident T2D: hazard ratios (95% confidence interval) per standard deviation: milk 0.71 (0.65, 0.77); butter 0.62 (0.57, 0.68); total dairy 0.66 (0.60, 0.72). These associations persisted after adjustment for known dairy-fat biomarkers.

conclusionMetabolite scores identified habitual consumers of milk, butter, and total dairy products, and were associated with lower T2D risk. These findings hold promise for identifying objective indicators of the physiological response to dairy consumption.

Indexed as

CheeseDiabetes Mellitus, Type 2AnimalsButterDairy ProductsDietHumansMilkRisk FactorsUnited KingdomButterbiomarkersdairydiabetesmetabolitesmetabolomics

Identifiers

PMID38054622
PMCPMC10909549
OpenAlexW4389373286

What Socratic holds

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LicenceCC BY
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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 Socratic graph.