Evidence mapPaperPMID 39349772Full record

ArticleDiabetologia2024

Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study.

Sapna Sharma, Qiuling Dong, Mark Haid, Jonathan Adam, Roberto Bizzotto, Juan J Fernandez-Tajes, Angus G Jones, Andrea Tura, Anna Artati, Cornelia Prehn and 22 more

Abstract read
In one paragraph

Article in Diabetologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Lifestyles, metabolome and diabetic kidney disease: a cohort study.QJM : monthly journal of the Association of Physicians · 2026
    Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. N-Lactoyl Amino Acids: Emerging Biomarkers in Metabolism and Disease.Diabetes/metabolism research and reviews · 2025
    Review
  15. Review
  16. Article
  17. 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

32 authors.

Sapna Sharma *Research Unit of Molecular Epidemiology, Institute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany. sapna.sharma@helmholtz-munich.de.
Qiuling Dong *Research Unit of Molecular Epidemiology, Institute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Mark Haid *Metabolomics and Proteomics Core, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Jonathan AdamResearch Unit of Molecular Epidemiology, Institute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Roberto BizzottoInstitute of Neuroscience, National Research Council, Padova, Italy.
Juan J Fernandez-TajesWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
Angus G JonesDepartment of Clinical and Biomedical Sciences, University of Exeter College of Medicine & Health, Exeter, UK.
Andrea TuraInstitute of Neuroscience, National Research Council, Padova, Italy.
Anna ArtatiMetabolomics and Proteomics Core, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Cornelia PrehnMetabolomics and Proteomics Core, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany.
Gabi KastenmüllerInstitute of Computational Biology, Helmholtz Zentrum München, Munich, Germany.
Robert W KoivulaOxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK.
Paul W FranksDepartment of Clinical Science, Genetic and Molecular Epidemiology, Lund University Diabetes Centre, Malmö, Sweden.
Mark WalkerTranslational and Clinical Research Institute, Faculty of Medical Sciences, University of Newcastle, Newcastle upon Tyne, UK.
Ian M ForgiePopulation Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK.
Giuseppe GiordanoDepartment of Clinical Science, Genetic and Molecular Epidemiology, Lund University Diabetes Centre, Malmö, Sweden.
Imre PavoEli Lilly Regional Operations GmbH, Vienna, Austria.
Hartmut RuettenSanofi Partnering, Sanofi-Aventis Deutschland GmbH, Frankfurt am Main, Germany.
Manolis DermitzakisDepartment of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.
Mark I McCarthyWellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
Oluf PedersenCenter for Clinical Metabolic Research, Herlev and Gentofte University Hospital, Copenhagen, Denmark.
Jochen M SchwenkScience for Life Laboratory, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden.
Konstantinos D TsirigosDepartment of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.
Federico De MasiDepartment of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.
Soren BrunakNovo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Ana ViñuelaBiosciences Institute, Faculty of Medical Sciences, University of Newcastle, Newcastle upon Tyne, UK.
Andrea MariInstitute of Neuroscience, National Research Council, Padova, Italy.
Timothy J McDonaldBlood Sciences, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK.
Tarja KokkolaInternal Medicine, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland.
Jerzy AdamskiDepartment of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Ewan R PearsonPopulation Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK.
Harald GrallertResearch Unit of Molecular Epidemiology, Institute of Epidemiology, German Research Center for Environmental Health, Helmholtz Zentrum München, Neuherberg, Germany. harald.grallert@helmholtz-munich.de.

Funding

DIRECT FP7/2007-2013
6 · The paper itself

Abstract

aims/hypothesisType 2 diabetes is a chronic condition that is caused by hyperglycaemia. Our aim was to characterise the metabolomics to find their association with the glycaemic spectrum and find a causal relationship between metabolites and type 2 diabetes.

methodsAs part of the Innovative Medicines Initiative - Diabetes Research on Patient Stratification (IMI-DIRECT) consortium, 3000 plasma samples were measured with the Biocrates AbsoluteIDQ p150 Kit and Metabolon analytics. A total of 911 metabolites (132 targeted metabolomics, 779 untargeted metabolomics) passed the quality control. Multivariable linear and logistic regression analysis estimates were calculated from the concentration/peak areas of each metabolite as an explanatory variable and the glycaemic status as a dependent variable. This analysis was adjusted for age, sex, BMI, study centre in the basic model, and additionally for alcohol, smoking, BP, fasting HDL-cholesterol and fasting triacylglycerol in the full model. Statistical significance was Bonferroni corrected throughout. Beyond associations, we investigated the mediation effect and causal effects for which causal mediation test and two-sample Mendelian randomisation (2SMR) methods were used, respectively.

resultsIn the targeted metabolomics, we observed four (15), 34 (99) and 50 (108) metabolites (number of metabolites observed in untargeted metabolomics appear in parentheses) that were significantly different when comparing normal glucose regulation vs impaired glucose regulation/prediabetes, normal glucose regulation vs type 2 diabetes, and impaired glucose regulation vs type 2 diabetes, respectively. Significant metabolites were mainly branched-chain amino acids (BCAAs), with some derivatised BCAAs, lipids, xenobiotics and a few unknowns. Metabolites such as lysophosphatidylcholine a C17:0, sum of hexoses, amino acids from BCAA metabolism (including leucine, isoleucine, valine, N-lactoylvaline, N-lactoylleucine and formiminoglutamate) and lactate, as well as an unknown metabolite (X-24295), were associated with HbA CONCLUSIONS/

interpretationOur findings identify known BCAAs and lipids, along with novel N-lactoyl-amino acid metabolites, significantly associated with prediabetes and diabetes, that mediate the effect of diabetes from baseline to follow-up (18 and 48 months). Causal inference using genetic variants shows the role of lipid metabolism and n-3 fatty acids as being causal for metabolite-to-type 2 diabetes whereas the sum of hexoses is causal for type 2 diabetes-to-metabolite. Identified metabolite markers are useful for stratifying individuals based on their risk progression and should enable targeted interventions.

Indexed as

Diabetes Mellitus, Type 2MetabolomicsPrediabetic StateAdultAgedBlood GlucoseFemaleHumansMaleMendelian Randomization AnalysisMiddle AgedBlood GlucoseCausalityGlycaemic traitsHbA1cIMI-DIRECTMediationMetabolomicsN-lactoylaminoacidsPatient stratificationTargeted metabolomicsType 2 diabetesUntargeted metabolomics

Identifiers

PMID39349772
PMCPMC11604760

What Socratic holds

Textmetadata
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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.