Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence
Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher r...
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doaj-581cb2e05c924ec4aa505cd603f8b0d12021-06-01T00:54:45ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-05-01225512551210.3390/ijms22115512Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the EvidenceSimon Alesi0Drishti Ghelani1Kate Rassie2Aya Mousa3Monash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, AustraliaMonash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, AustraliaMonash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, AustraliaMonash Centre for Health Research and Implementation (MCHRI), School of Public Health and Preventive Medicine, Monash University, Melbourne 3168, AustraliaGestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher rates of stillbirth, instrumental delivery, and birth trauma. Metabolomics, which is a platform used to analyse and characterise a large number of metabolites, is increasingly used to explore the pathophysiology of cardiometabolic conditions such as GDM. This review aims to summarise metabolomics studies in GDM (from inception to January 2021) in order to highlight prospective biomarkers for diagnosis, and to better understand the dysfunctional metabolic pathways underlying the condition. We found that the most commonly deranged pathways in GDM include amino acids (glutathione, alanine, valine, and serine), carbohydrates (2-hydroxybutyrate and 1,5-anhydroglucitol), and lipids (phosphatidylcholines and lysophosphatidylcholines). We also highlight the possibility of using certain metabolites as predictive markers for developing GDM, with the use of highly stratified modelling techniques. Limitations for metabolomic research are evaluated, and future directions for the field are suggested to aid in the integration of these findings into clinical practice.https://www.mdpi.com/1422-0067/22/11/5512gestational diabetes mellitusmetabolomicsbiomarkersmetabolitesmass spectrometrylipidomics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Simon Alesi Drishti Ghelani Kate Rassie Aya Mousa |
spellingShingle |
Simon Alesi Drishti Ghelani Kate Rassie Aya Mousa Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence International Journal of Molecular Sciences gestational diabetes mellitus metabolomics biomarkers metabolites mass spectrometry lipidomics |
author_facet |
Simon Alesi Drishti Ghelani Kate Rassie Aya Mousa |
author_sort |
Simon Alesi |
title |
Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence |
title_short |
Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence |
title_full |
Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence |
title_fullStr |
Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence |
title_full_unstemmed |
Metabolomic Biomarkers in Gestational Diabetes Mellitus: A Review of the Evidence |
title_sort |
metabolomic biomarkers in gestational diabetes mellitus: a review of the evidence |
publisher |
MDPI AG |
series |
International Journal of Molecular Sciences |
issn |
1661-6596 1422-0067 |
publishDate |
2021-05-01 |
description |
Gestational diabetes mellitus (GDM) is the fastest growing type of diabetes, affecting between 2 to 38% of pregnancies worldwide, varying considerably depending on diagnostic criteria used and sample population studied. Adverse obstetric outcomes include an increased risk of macrosomia, and higher rates of stillbirth, instrumental delivery, and birth trauma. Metabolomics, which is a platform used to analyse and characterise a large number of metabolites, is increasingly used to explore the pathophysiology of cardiometabolic conditions such as GDM. This review aims to summarise metabolomics studies in GDM (from inception to January 2021) in order to highlight prospective biomarkers for diagnosis, and to better understand the dysfunctional metabolic pathways underlying the condition. We found that the most commonly deranged pathways in GDM include amino acids (glutathione, alanine, valine, and serine), carbohydrates (2-hydroxybutyrate and 1,5-anhydroglucitol), and lipids (phosphatidylcholines and lysophosphatidylcholines). We also highlight the possibility of using certain metabolites as predictive markers for developing GDM, with the use of highly stratified modelling techniques. Limitations for metabolomic research are evaluated, and future directions for the field are suggested to aid in the integration of these findings into clinical practice. |
topic |
gestational diabetes mellitus metabolomics biomarkers metabolites mass spectrometry lipidomics |
url |
https://www.mdpi.com/1422-0067/22/11/5512 |
work_keys_str_mv |
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