Evidence map›Paper›PMID 34402867›Full record

ArticleBioscience reports2021

Metabolic profiling of maternal serum of women at high-risk of spontaneous preterm birth using NMR and MGWAS approach.

Juhi K Gupta, Angharad Care, Laura Goodfellow, Zarko Alfirevic, Lu-Yun Lian, Bertram Müller-Myhsok, Ana Alfirevic, Marie M Phelan

Open access · goldAbstract read
In one paragraph

Article in Bioscience reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Systematic review of preterm birth multi-omic biomarker studies.Expert reviews in molecular medicine · 2022
    Review
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

8 authors at 1 institution in 2 countries.

Juhi K GuptaWolfson Centre for Personalised Medicine, Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 3GL, UK.ORCID 0000-0002-8292-9846
Angharad CareHarris-Wellbeing Research Centre, University Department, Liverpool Women's Hospital, Liverpool, L8 7SS, UK.
Laura GoodfellowHarris-Wellbeing Research Centre, University Department, Liverpool Women's Hospital, Liverpool, L8 7SS, UK.
Zarko AlfirevicHarris-Wellbeing Research Centre, University Department, Liverpool Women's Hospital, Liverpool, L8 7SS, UK.
Lu-Yun LianNMR Centre for Structural Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.
Bertram Müller-MyhsokWolfson Centre for Personalised Medicine, Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 3GL, UK.
Ana AlfirevicWolfson Centre for Personalised Medicine, Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 3GL, UK.
Marie M PhelanNMR Centre for Structural Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.
University of Liverpool · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

Preterm birth (PTB) is a leading global cause of infant mortality. Risk factors include genetics, lifestyle choices and infection. Understanding the mechanism of PTB could aid the development of novel approaches to prevent PTB. This study aimed to investigate the metabolic biomarkers of PTB in early pregnancy and the association of significant metabolites with participant genotypes. Maternal sera collected at 16 and 20 weeks of gestation, from women who previously experienced PTB (high-risk) and women who did not (low-risk controls), were analysed using 1H nuclear magnetic resonance (NMR) metabolomics and genome-wide screening microarray. ANOVA and probabilistic neural network (PNN) modelling were performed on the spectral bins. Metabolomics genome-wide association (MGWAS) of the spectral bins and genotype data from the same participants was applied to determine potential metabolite-gene pathways. Phenylalanine, acetate and lactate metabolite differences between PTB cases and controls were obtained by ANOVA and PNN showed strong prediction at week 20 (AUC = 0.89). MGWAS identified several metabolite bins with strong genetic associations. Cis-eQTL analysis highlighted TRAF1 (involved in the inflammatory pathway) local to a non-coding SNP associated with lactate at week 20 of gestation. MGWAS of a well-defined cohort of participants highlighted a lactate-TRAF1 relationship that could potentially contribute to PTB.

Indexed as

Magnetic Resonance SpectroscopyMetabolomeMetabolomicsOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideAdultBiomarkersCase-Control StudiesFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyGestational AgeHumansLactic AcidNeural Networks, ComputerPhenotypeBiomarkersLactic AcidTNF Receptor-Associated Factor 1biomarker discoverymetabolomicsmGWASmultiple omicsNMRPreterm birth

Identifiers

PMID34402867
PMCPMC8415214
OpenAlexW3195422608

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.