Literature DB >> 33398476

Glycerophospholipid and detoxification pathways associated with small for gestation age pathophysiology: discovery metabolomics analysis in the SCOPE cohort.

Aude-Claire Morillon1,2, Debora F B Leite3,4, Shirish Yakkundi1,2, Lee A Gethings5,6, Gregoire Thomas7, Philip N Baker8, Louise C Kenny9, Jane A English1,10, Fergus P McCarthy11,12.   

Abstract

INTRODUCTION: Small for gestational age (SGA) may be associated with neonatal morbidity and mortality. Our understanding of the molecular pathways implicated is poor.
OBJECTIVES: Our aim was to determine the metabolic pathways involved in the pathophysiology of SGA and examine their variation between maternal biofluid samples.
METHODS: Plasma (Cork) and urine (Cork, Auckland) samples were collected at 20 weeks' gestation from nulliparous low-risk pregnant women participating in the SCOPE study. Women who delivered an SGA infant (birthweight < 10th percentile) were matched to controls (uncomplicated pregnancies). Metabolomics (urine) and lipidomics (plasma) analyses were performed using ultra performance liquid chromatography-mass spectrometry. Features were ranked based on FDR adjusted p-values from empirical Bayes analysis, and significant features putatively identified.
RESULTS: Lipidomics plasma analysis revealed that 22 out of the 33 significantly altered lipids annotated were glycerophospholipids; all were detected in higher levels in SGA. Metabolomic analysis identified reduced expression of metabolites associated with detoxification (D-Glucuronic acid, Estriol-16-glucuronide), nutrient absorption and transport (Sulfolithocholic acid) pathways.
CONCLUSIONS: This study suggests higher levels of glycerophospholipids, and lower levels of specific urine metabolites are implicated in the pathophysiology of SGA. Further research is needed to confirm these findings in independent samples.

Entities:  

Keywords:  Fetal growth restriction; Lipidomics; Metabolomics; Placental insufficiency; Pregnancy complication; Small for gestational age infant

Year:  2021        PMID: 33398476     DOI: 10.1007/s11306-020-01740-9

Source DB:  PubMed          Journal:  Metabolomics        ISSN: 1573-3882            Impact factor:   4.290


  27 in total

1.  A novel precursor ion discovery method on a hybrid quadrupole orthogonal acceleration time-of-flight (Q-TOF) mass spectrometer for studying protein phosphorylation.

Authors:  R H Bateman; R Carruthers; J B Hoyes; C Jones; J I Langridge; A Millar; J P C Vissers
Journal:  J Am Soc Mass Spectrom       Date:  2002-07       Impact factor: 3.109

Review 2.  Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy.

Authors:  Warwick B Dunn; David I Broadhurst; Helen J Atherton; Royston Goodacre; Julian L Griffin
Journal:  Chem Soc Rev       Date:  2010-08-17       Impact factor: 54.564

3.  Metabolic profiling uncovers a phenotypic signature of small for gestational age in early pregnancy.

Authors:  Richard P Horgan; David I Broadhurst; Sarah K Walsh; Warwick B Dunn; Marie Brown; Claire T Roberts; Robyn A North; Lesley M McCowan; Douglas B Kell; Philip N Baker; Louise C Kenny
Journal:  J Proteome Res       Date:  2011-06-29       Impact factor: 4.466

Review 4.  Metabolomics and the great obstetrical syndromes--GDM, PET, and IUGR.

Authors:  Angelica Dessì; Flamina Cesare Marincola; Vassilios Fanos
Journal:  Best Pract Res Clin Obstet Gynaecol       Date:  2014-08-21       Impact factor: 5.237

Review 5.  Small for gestational age, term babies, in the first six years of life.

Authors:  S M Grantham-McGregor
Journal:  Eur J Clin Nutr       Date:  1998-01       Impact factor: 4.016

6.  Lipidomic analysis of human placental syncytiotrophoblast microvesicles in adverse pregnancy outcomes.

Authors:  S Baig; J Y Lim; A Z Fernandis; M R Wenk; A Kale; L L Su; A Biswas; S Vasoo; G Shui; M Choolani
Journal:  Placenta       Date:  2013-03-05       Impact factor: 3.481

7.  Analysis of sequential hair segments reflects changes in the metabolome across the trimesters of pregnancy.

Authors:  Thibaut D J Delplancke; Jamie V de Seymour; Chao Tong; Karolina Sulek; Yinyin Xia; Hua Zhang; Ting-Li Han; Philip N Baker
Journal:  Sci Rep       Date:  2018-01-08       Impact factor: 4.379

Review 8.  Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies.

Authors:  David Broadhurst; Royston Goodacre; Stacey N Reinke; Julia Kuligowski; Ian D Wilson; Matthew R Lewis; Warwick B Dunn
Journal:  Metabolomics       Date:  2018-05-18       Impact factor: 4.290

9.  Artificial intelligence and the analysis of multi-platform metabolomics data for the detection of intrauterine growth restriction.

Authors:  Ray Oliver Bahado-Singh; Ali Yilmaz; Halil Bisgin; Onur Turkoglu; Praveen Kumar; Eric Sherman; Andrew Mrazik; Anthony Odibo; Stewart F Graham
Journal:  PLoS One       Date:  2019-04-18       Impact factor: 3.240

10.  LIPID MAPS online tools for lipid research.

Authors:  Eoin Fahy; Manish Sud; Dawn Cotter; Shankar Subramaniam
Journal:  Nucleic Acids Res       Date:  2007-06-21       Impact factor: 16.971

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  2 in total

Review 1.  Non-targeted metabolomics and associations with per- and polyfluoroalkyl substances (PFAS) exposure in humans: A scoping review.

Authors:  Pengfei Guo; Tristan Furnary; Vasilis Vasiliou; Qi Yan; Kate Nyhan; Dean P Jones; Caroline H Johnson; Zeyan Liew
Journal:  Environ Int       Date:  2022-02-26       Impact factor: 9.621

2.  Delivery prediction by quantitative analysis of four steroid metabolites with liquid chromatography tandem mass spectrometry in asymptomatic pregnant women.

Authors:  Lanlan Meng; Shaofei Su; Lin Li; Shengmin Liu; Youran Li; Ying Liu; Yifan Lu; Zhengwen Xu; Lin Liu; Qixin He; Yuanyuan Zheng; Xiaowei Liu; Yuting Cong; Yanhong Zhai; Zhen Zhao; Zheng Cao
Journal:  Ann Med       Date:  2022-12       Impact factor: 5.348

  2 in total

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