Evidence map›Paper›PMID 27815605›Full record

ArticleDiabetologia2017

Peptide serum markers in islet autoantibody-positive children.

Christine von Toerne, Michael Laimighofer, Peter Achenbach, Andreas Beyerlein, Tonia de Las Heras Gala, Jan Krumsiek, Fabian J Theis, Anette G Ziegler, Stefanie M Hauck

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Diabetologia, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 3 pooled it
3.0field-weighted citation impact, top 8% 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

23 citing papers in PubMed, 3 syntheses or guidelines pooled it, 35 citations in OpenAlex.

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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

9 authors at 4 institutions in 1 country.

Christine von ToerneResearch Unit Protein Science, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, D-85764, München, Germany.
Michael LaimighoferInstitute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Peter AchenbachInstitute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, D-85764, München, Germany.
Andreas BeyerleinInstitute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, D-85764, München, Germany.
Tonia de Las Heras GalaGerman Center for Diabetes Research (DZD), Neuherberg, Germany.
Jan KrumsiekInstitute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Fabian J TheisInstitute of Computational Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, Germany.
Anette G ZieglerInstitute of Diabetes Research, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, D-85764, München, Germany. anette-g.ziegler@helmholtz-muenchen.de.
Stefanie M HauckResearch Unit Protein Science, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, D-85764, München, Germany. hauck@helmholtz-muenchen.de.
Helmholtz Zentrum München · DEKlinikum rechts der Isar · DEHeinrich Heine University Düsseldorf · DETechnical University of Munich · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisWe sought to identify minimal sets of serum peptide signatures as markers for islet autoimmunity and predictors of progression rates to clinical type 1 diabetes in a case-control study.

methodsA double cross-validation approach was applied to first prioritise peptides from a shotgun proteomic approach in 45 islet autoantibody-positive and -negative children from the BABYDIAB/BABYDIET birth cohorts. Targeted proteomics for 82 discriminating peptides were then applied to samples from another 140 children from these cohorts.

resultsA total of 41 peptides (26 proteins) enriched for the functional category lipid metabolism were significantly different between islet autoantibody-positive and autoantibody-negative children. Two peptides (from apolipoprotein M and apolipoprotein C-IV) were sufficient to discriminate autoantibody-positive from autoantibody-negative children. Hepatocyte growth factor activator, complement factor H, ceruloplasmin and age predicted progression time to type 1 diabetes with a significant improvement compared with age alone. CONCLUSION/

interpretationDistinct peptide signatures indicate islet autoimmunity prior to the clinical manifestation of type 1 diabetes and enable refined staging of the presymptomatic disease period.

Indexed as

AdolescentAutoantibodiesAutoimmunityBiomarkersCase-Control StudiesChildChild, PreschoolChromatography, LiquidDiabetes Mellitus, Type 1FemaleGenetic Predisposition to DiseaseHumansInsulinLipid MetabolismMalePeptidesAutoantibodiesBiomarkersInsulinPeptidesAutoantibody-positiveAutoimmunityBABYDIAB/BABYDIETLC-MS/MSProgression timeRisk scoreSelected reaction monitoringTargeted proteomicType 1 diabetes

Identifiers

PMID27815605
OpenAlexW2547711205

What OpenQuestion holds

Textmetadata
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.