Evidence mapPaperPMID 30917176Full record

ArticlePloS one2019

First-trimester proteomic profiling identifies novel predictors of gestational diabetes mellitus.

Tina Ravnsborg, Sarah Svaneklink, Lise Lotte T Andersen, Martin R Larsen, Dorte M Jensen, Martin Overgaard

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 7% 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

29 citing papers in PubMed, 1 synthesis or guideline pooled it, 47 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

6 authors at 3 institutions in 1 country.

Tina RavnsborgDepartment of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark.
Sarah SvaneklinkDepartment of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark.
Lise Lotte T AndersenDepartment of Obstetrics and Gynaecology, Odense University Hospital, Odense, Denmark.
Martin R LarsenDepartment of Biochemistry and Molecular Biology, University of Southern Denmark, Odense, Denmark.
Dorte M JensenThe Danish Diabetes Academy, Odense University Hospital, Odense, Denmark.
Martin OvergaardDepartment of Clinical Biochemistry and Pharmacology, Odense University Hospital, Odense, Denmark.ORCID 0000-0003-2277-590X
Odense University Hospital · DKUniversity of Southern Denmark · DKSteno Diabetes Centers · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse outcomes including preeclampsia, caesarean section, macrosomia, neonatal morbidity and future development of type 2 diabetes in both mother and child. Current selective screening strategies rely on clinical risk factors such as age, family history of diabetes, macrosomia or GDM in a previous pregnancy, and they possess a relatively low specificity. Here we hypothesize that novel first trimester protein predictors of GDM can contribute to the current selective screening strategies for early and accurate prediction of GDM, thus allowing for timely interventions.

methodsA proteomics discovery approach was applied to first trimester sera from obese (BMI ≥27 kg/m2) women (n = 60) in a nested case-control study design, utilizing tandem mass tag labelling and tandem mass spectrometry. A subset of the identified protein markers was further validated in a second set of serum samples (n = 210) and evaluated for their contribution as predictors of GDM in relation to the maternal risk factors, by use of logistic regression and receiver operating characteristic analysis.

resultsSerum proteomic profiling identified 25 proteins with significantly different levels between cases and controls. Three proteins; afamin, serum amyloid P-component and vitronectin could be further confirmed as predictors of GDM in a validation set. Vitronectin was shown to contribute significantly to the predictive power of the maternal risk factors, indicating it as a novel independent predictor of GDM.

conclusionsCurrent selective screening strategies can potentially be improved by addition of protein predictors.

Indexed as

ProteomicsAdultBiomarkersDiabetes, GestationalFemaleHumansPregnancyPregnancy Trimester, FirstPrognosisReproducibility of ResultsBiomarkers

Identifiers

PMID30917176
PMCPMC6436752
OpenAlexW2922643263

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.