Evidence map›Paper›PMID 31179513›Full record

ArticleMetabolomics : Official journal of the Metabolomic Society2019

NMR metabolomics identifies over 60 biomarkers associated with Type II Diabetes impairment in db/db mice.

Marina Mora-Ortiz, Patricia Nuñez Ramos, Alain Oregioni, Sandrine P Claus

Open access · hybridAbstract read
In one paragraph

Article in Metabolomics : Official journal of the Metabolomic Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

31 citing papers in PubMed, 53 citations in OpenAlex.

  1. The prairie vole gut-brain-microbiota-axis: a narrative review.Gut microbiome (Cambridge, England) · 2026
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  12. Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment.Diabetes, metabolic syndrome and obesity : targets and therapy · 2023
    Review
  13. Metabolites · 2022
    Article
  14. Article
  15. Review
  16. Frontiers in microbiology · 2022
    Article
  17. Article
  18. Metabolomics Based onFoods (Basel, Switzerland) · 2021
    Article
  19. Article
  20. 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

4 authors at 4 institutions in 2 countries.

Marina Mora-OrtizDepartment of Food and Nutritional Sciences, The University of Reading, Whiteknights Campus, P.O. Box 226, Reading, RG6 6AP, UK. marina.mora_ortiz@kcl.ac.uk.ORCID 0000-0002-6662-2932
Patricia Nuñez RamosFacultad de Medicina, Universidad de Extremadura, Campus de Badajoz, C.P. 06006, Badajoz, Spain.
Alain OregioniMRC Biomedical NMR Centre, The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK.
Sandrine P ClausDepartment of Food and Nutritional Sciences, The University of Reading, Whiteknights Campus, P.O. Box 226, Reading, RG6 6AP, UK. s.p.claus@reading.ac.uk.
St Thomas' Hospital · GBThe Francis Crick Institute · GBUniversidad de Extremadura · ESUniversity of Reading · GB

Funding

Medical Research Council M004945/1Wellcome Trust FC001029
6 · The paper itself

Abstract

introductionThe rapid expansion of Type 2 Diabetes (T2D), that currently affects 90% of people suffering from diabetes, urges us to develop a better understanding of the metabolic processes involved in the disease process in order to develop better therapies. The most commonly used model for T2D research is the db/db (BKS.Cg-Dock7 < m > +/+ Lepr < db >/J) mouse model. Yet, a systematic

objectivesThe aim of this study was to characterise the metabolic modulations associated with T2D in db/db mice in 18 relevant biological matrices.

methodsHigh-resolution

results61 metabolites associated with T2D were identified. Kidney, spleen, eye and plasma were the biological matrices carrying the largest metabolomics modulations observed in established T2D, based on the total number of metabolites that showed a statistical difference between the diabetic and control group in each tissue (16 in each case) and the strength of the O-PLS DA model for each tissue. Glucose and glutamate were the most commonly associated metabolites found significantly increased in nine biological matrices. Investigated sections where no increase of glucose was associated with T2D include all intestinal segments (i.e. duodenum, jejunum, ileum and colon). Microbial co-metabolites such as acetate and butyrate, used as carbon sources by the host, were identified in excess in the colonic tissues of diabetic individuals.

conclusionsThe metabolic biomarkers identified using

Indexed as

MetabolomeAnimalsBiomarkersDiabetes Mellitus, Type 2Disease Models, AnimalEyeFemaleKidneyMagnetic Resonance SpectroscopyMaleMetabolic Networks and PathwaysMetabolomicsMiceSpleenBiomarkersdb/db mouseMetabolomeNuclear magnetic resonance (NMR) spectroscopyType II Diabetes

Identifiers

PMID31179513
PMCPMC6556514
OpenAlexW2948851550

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.