Evidence map›Paper›PMID 27703025›Full record

ArticleDiabetes care2016

An Unbiased Lipidomics Approach Identifies Early Second Trimester Lipids Predictive of Maternal Glycemic Traits and Gestational Diabetes Mellitus.

Liangjian Lu, Albert Koulman, Clive J Petry, Benjamin Jenkins, Lee Matthews, Ieuan A Hughes, Carlo L Acerini, Ken K Ong, David B Dunger

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Diabetes care, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed, 1 pooled it
6.4field-weighted citation impact, top 3% 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

52 citing papers in PubMed, 1 synthesis or guideline pooled it, 89 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 2 institutions in 1 country.

Liangjian LuDepartment of Paediatrics, University of Cambridge, Cambridge, U.K.
Albert KoulmanMedical Research Council Human Nutrition Research, Cambridge, U.K.ORCID 0000-0001-9998-051X
Clive J PetryDepartment of Paediatrics, University of Cambridge, Cambridge, U.K.ORCID 0000-0002-6642-9825
Benjamin JenkinsMedical Research Council Human Nutrition Research, Cambridge, U.K.
Lee MatthewsMedical Research Council Human Nutrition Research, Cambridge, U.K.ORCID 0000-0002-0916-6141
Ieuan A HughesDepartment of Paediatrics, University of Cambridge, Cambridge, U.K.ORCID 0000-0002-8787-1575
Carlo L AceriniDepartment of Paediatrics, University of Cambridge, Cambridge, U.K.ORCID 0000-0003-2121-5871
Ken K OngDepartment of Paediatrics, University of Cambridge, Cambridge, U.K.ORCID 0000-0003-4689-7530
David B DungerDepartment of Paediatrics, University of Cambridge, Cambridge, U.K. dbd25@cam.ac.uk.
University of Cambridge · GBMRC Human Nutrition Research · GB

Funding

Diabetes UK 11/0004241Medical Research Council G0600717Medical Research Council MC_EX_G0800783Wellcome Trust
6 · The paper itself

Abstract

objectiveTo investigate the relationship between early second trimester serum lipidomic variation and maternal glycemic traits at 28 weeks and to identify predictive lipid biomarkers for gestational diabetes mellitus (GDM). RESEARCH DESIGN AND

methodsProspective study of 817 pregnant women (discovery cohort, n = 200; validation cohort, n = 617) who provided an early second trimester serum sample and underwent an oral glucose tolerance test (OGTT) at 28 weeks. In the discovery cohort, lipids were measured using direct infusion mass spectrometry and correlated with OGTT results. Variable importance in projection (VIP) scores were used to identify candidate lipid biomarkers. Candidate biomarkers were measured in the validation cohort using liquid chromatography-mass spectrometry and tested for associations with OGTT results and GDM status.

resultsEarly second trimester lipidomic variation was associated with 1-h postload glucose levels but not with fasting plasma glucose levels. Of the 13 lipid species identified by VIP scores, 10 had nominally significant associations with postload glucose levels. In the validation cohort, 5 of these 10 lipids had significant associations with postload glucose levels that were independent of maternal age and BMI, i.e., TG(51.1), TG(48:1), PC(32:1), PCae(40:3), and PCae(40:4). All except the last were also associated with maternal GDM status. Together, these four lipid biomarkers had moderate ability to predict GDM (area under curve [AUC] = 0.71 ± 0.04, P = 4.85 × 10

conclusionsSpecific early second trimester lipid biomarkers can predict maternal GDM status independent of maternal age and BMI, potentially enhancing risk factor-based screening.

Indexed as

Lipid MetabolismAdultArea Under CurveBlood GlucoseDiabetes, GestationalFemaleGlucose Tolerance TestHumansLipidsMaternal AgeMetabolomicsPregnancyPregnancy Trimester, SecondProspective StudiesRisk FactorsBlood GlucoseLipids

Identifiers

PMID27703025
PMCPMC5123716
OpenAlexW2527682611

What OpenQuestion holds

Textmetadata
LicenceTDM
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.