Evidence map›Paper›PMID 23043162›Full record

ArticleDiabetes2013

Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach.

Anna Floegel, Norbert Stefan, Zhonghao Yu, Kristin Mühlenbruch, Dagmar Drogan, Hans-Georg Joost, Andreas Fritsche, Hans-Ulrich Häring, Martin Hrabě de Angelis, Annette Peters and 8 more

Registry-linked trialOpen access · bronzeAbstract read
In one paragraph

Article in Diabetes, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04886973 (Effect of Insulin Resistance on Branched Chain Amino Acid Metabolism.), which is not on this map. Cited by 551 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
551citing papers in PubMed, 3 pooled it
20.4field-weighted citation impact, top 1% 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.

NCT04886973 nacompletednot on this mapstarted 2022, after this paper: background citation

Effect of Insulin Resistance on Branched Chain Amino Acid Metabolism.

TypeinterventionalSponsorInstituto Nacional de Ciencias Medicas y Nutricion Salvador ZubiranRan2022 to 2022Enrolled40ConditionsObesity, Insulin ResistanceArmsAdministration of an 8% crystalline L-amino acid solution with high concentrations of branched chain amino acids.
3 · Its place in the literature

Who cites it

551 citing papers in PubMed, 3 syntheses or guidelines pooled it, 1,010 citations in OpenAlex.

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491 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 5 institutions in 1 country.

Anna FloegelDepartment of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany. anna.floegel@dife.de
Norbert Stefan
Zhonghao Yu
Kristin Mühlenbruch
Dagmar Drogan
Hans-Georg Joost
Andreas Fritsche
Hans-Ulrich Häring
Martin Hrabě de Angelis
Annette Peters
Michael Roden
Cornelia Prehn
Rui Wang-Sattler
Thomas Illig
Matthias B Schulze
Jerzy Adamski
Heiner Boeing
Tobias Pischon
Helmholtz Zentrum München · DEGerman Institute of Human Nutrition · DEUniversity of Tübingen · DEHeinrich Heine University Düsseldorf · DEMax Delbrück Center · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Metabolomic discovery of biomarkers of type 2 diabetes (T2D) risk may reveal etiological pathways and help to identify individuals at risk for disease. We prospectively investigated the association between serum metabolites measured by targeted metabolomics and risk of T2D in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) among all incident cases of T2D (n = 800, mean follow-up 7 years) and a randomly drawn subcohort (n = 2,282). Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of T2D and serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 with decreased risk. Variance of the metabolites was largely explained by two metabolite factors with opposing risk associations (factor 1 relative risk in extreme quintiles 0.31 [95% CI 0.21-0.44], factor 2 3.82 [2.64-5.52]). The metabolites significantly improved T2D prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in the Tübingen Family study and were partly replicated in the independent KORA (Cooperative Health Research in the Region of Augsburg) cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of T2D.

Indexed as

MetabolomicsAdultBiomarkersDiabetes Mellitus, Type 2FemaleGlycineHexosesHumansInsulinInsulin ResistanceInsulin SecretionMaleMiddle AgedPhenylalaninePhosphatidylcholinesRiskBiomarkersGlycineHexosesInsulinPhenylalaninePhosphatidylcholinesSphingomyelins

Identifiers

PMID23043162
PMCPMC3554384
OpenAlexW2158958532

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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.