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Expert Rev Proteomics. 2018 Oct;15(10):809-816. doi: 10.1080/14789450.2018.1526678. Epub 2018 Oct 4.

Untargeted metabolomics: an overview of its usefulness and future potential in prenatal diagnosis.

Author information

1
a Clinical Research Centre , Medical University of Bialystok , Bialystok , Poland.
2
b Department of Reproduction and Gynaecological Endocrinology , Medical University of Bialystok , Bialystok , Poland.
3
c Department of Endocrinology, Diabetology and Internal Medicine , Medical University of Bialystok , Bialystok , Poland.
4
d Centre for Metabolomics and Bioanalysis (CEMBIO), Facultad de Farmacia , Universidad CEU San Pablo , Madrid , Spain.

Abstract

Metabolomics opens up new avenues for biomarker discovery in different branches of medicine, including perinatology. Chromosomal aberration, preterm delivery (PTD), congenital heart defects, spina bifida, chorioamnionitis, and low birth weight are the main perinatal pathologies. Investigations using untargeted metabolomics have found the candidate metabolites for diagnostic biomarkers. Areas covered: This review describes areas of prenatal diagnosis in which untargeted metabolomics has been used. Data on the disease, type of sample, techniques used, number of samples used in the study, and metabolites obtained including the sign of their regulation are summarized. Expert commentary: Untargeted metabolomics is a powerful tool which can shed a new light on prenatal diagnostics. It helps to discover affected metabolic pathways what may help to reveal disease pathogenesis and propose potential biomarkers. Among others, glycerol and 2- and 3-hydroxybutyrate were proposed as markers of chromosomal aberration. Serum metabolic signature of PTD was characterized by increased lipids and decreased levels of hypoxanthine, tryptophane, and pyroglutamic acid. Lower level lipids and vitamin D3 metabolites together with increased bilirubin level in maternal serum were associated with macrosomia. However, to give a real value to those assays and allow their clinical application multicenter, large cohort validation studies are necessary.

KEYWORDS:

Metabolomics; biomarkers; metabolic fingerprinting; prenatal diagnosis

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