Evidence map›Paper›PMID 33674279›Full record

ArticleBMJ open diabetes research & care2021

Plasma lipidomics profile in pregnancy and gestational diabetes risk: a prospective study in a multiracial/ethnic cohort.

Mohammad L Rahman, Yen-Chen A Feng, Oliver Fiehn, Paul S Albert, Michael Y Tsai, Yeyi Zhu, Xiaobin Wang, Fasil Tekola-Ayele, Liming Liang, Cuilin Zhang

Open access · goldAbstract read
In one paragraph

Article in BMJ open diabetes research & care, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
7.7field-weighted citation impact, top 2% 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

33 citing papers in PubMed, 59 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

10 authors at 8 institutions in 1 country.

Mohammad L Rahman *Department of Population Medicine and Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-8322-0495
Yen-Chen A Feng *Massachusetts General Hospital Center for Genomic Medicine, Boston, Massachusetts, USA.
Oliver FiehnWest Coast Metabolomics Center, University of California Davis, Davis, California, USA.
Paul S AlbertDivision of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA.
Michael Y TsaiLaboratory Medicine and Pathology, University of Minnesota System, Minneapolis, Minnesota, USA.
Yeyi ZhuDivision of Research, Kaiser Permanente Northern California, Oakland, California, USA.
Xiaobin WangDepartment of Population, Family, and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA.
Fasil Tekola-AyeleEpidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA.
Liming LiangDepartment of Biostatistics, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA zhangcu@mail.nih.gov lliang@hsph.harvard.edu.
Cuilin ZhangEpidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland, USA zhangcu@mail.nih.gov lliang@hsph.harvard.edu.
Eunice Kennedy Shriver National Institute of Child Health and Human Development · USHarvard University · USBroad Institute · USJohns Hopkins University · USKaiser Permanente · USNational Cancer Institute · USUniversity of California, Davis · USUniversity of Minnesota System · US

Funding

The National Standard for Normal Fetal GrowthZIAHD008852 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI GRANTZ, KATHERINE · 2009 to 2025
$5.6M
West Coast Metabolomics Center for Compound IdentificationU2CES030158 · NIEHS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI FIEHN, OLIVER · 2018 to 2021
$4.1M
Pathogenesis of Gestational DiabetesZIAHD008887 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI YEUNG, EDWINA · 2009 to 2022
$2.3M
Pregnancy and perinatal complications and mortality: Collaborative Perinatal Project mortality linkage studyZIAHD008938 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI YEUNG, EDWINA · 2014 to 2025
$1.5M
Risk Factors of Gestational DiabetesZIAHD008889 · NICHD · EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT · PI YEUNG, EDWINA · 2009 to 2022
$1.4M
Fetal Programming of Growth and Obesity: A Metabolomics ApproachK01DK120807 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI ZHU, YEYI · 2019 to 2022
$699k
NICHD NIH HHS HHSN275200800002CNICHD NIH HHS HHSN275200800002INICHD NIH HHS HHSN275200800003CNICHD NIH HHS HHSN275200800003INICHD NIH HHS HHSN275200800012CNICHD NIH HHS HHSN275200800013CNICHD NIH HHS HHSN275200800014CNICHD NIH HHS HHSN275200800021CNICHD NIH HHS HHSN275200800028CNICHD NIH HHS HHSN275201000001GNICHD NIH HHS HHSN275201000001ZNICHD NIH HHS HHSN275201000009CNIDDK NIH HHS K01 DK120807NIEHS NIH HHS U2C ES030158
6 · The paper itself

Abstract

introductionDisruption of lipid metabolism is implicated in gestational diabetes (GDM). However, prospective studies on lipidomics and GDM risk in race/ethnically diverse populations are sparse. Here, we aimed to (1) identify lipid networks in early pregnancy to mid-pregnancy that are associated with subsequent GDM risk and (2) examine the associations of lipid networks with glycemic biomarkers to understand the underlying mechanisms. RESEARCH DESIGN AND

methodsThis study included 107 GDM cases confirmed using the Carpenter and Coustan criteria and 214 non-GDM matched controls from the National Institute of Child Health and Human Development Fetal Growth Studies-Singleton cohort, untargeted lipidomics data of 420 metabolites (328 annotated and 92 unannotated), and information on glycemic biomarkers in maternal plasma at visit 0 (10-14 weeks) and visit 1 (15-26 weeks). We constructed lipid networks using weighted correlation network analysis technique. We examined prospective associations of lipid networks and individual lipids with GDM risk using linear mixed effect models. Furthermore, we calculated Pearson's partial correlation for GDM-related lipid networks and individual lipids with plasma glucose, insulin, C-peptide and glycated hemoglobin at both study visits.

resultsLipid networks primarily characterized by elevated plasma diglycerides and short, saturated/low unsaturated triglycerides and lower plasma cholesteryl esters, sphingomyelins and phosphatidylcholines were associated with higher risk of developing GDM (false discovery rate (FDR) <0.05). Among individual lipids, 58 metabolites at visit 0 and 96 metabolites at visit 1 (40 metabolites at both time points) significantly differed between women who developed GDM and who did not (FDR <0.05). Furthermore, GDM-related lipid networks and individual lipids showed consistent correlations with maternal glycemic markers particularly in early pregnancy at visit 0.

conclusionsPlasma lipid metabolites in early pregnancy both individually and interactively in distinct networks were associated with subsequent GDM risk in race/ethnically diverse US women. Future research is warranted to assess lipid metabolites as etiologic markers of GDM.

Indexed as

Diabetes, GestationalBlood GlucoseChildFemaleHumansLipidomicsPregnancyProspective StudiesRisk FactorsBlood Glucosediabetesgestationallipidsmetabolismpregnancy

Identifiers

PMID33674279
PMCPMC7939004
OpenAlexW3133950152

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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 OpenQuestion graph.