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Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis

Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children bor...

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Autores principales: Sriboonvorakul, Natthida, Hu, Jiamiao, Boriboonhirunsarn, Dittakarn, Ng, Leong Loke, Tan, Bee Kang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143836/
https://www.ncbi.nlm.nih.gov/pubmed/35628864
http://dx.doi.org/10.3390/jcm11102737
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author Sriboonvorakul, Natthida
Hu, Jiamiao
Boriboonhirunsarn, Dittakarn
Ng, Leong Loke
Tan, Bee Kang
author_facet Sriboonvorakul, Natthida
Hu, Jiamiao
Boriboonhirunsarn, Dittakarn
Ng, Leong Loke
Tan, Bee Kang
author_sort Sriboonvorakul, Natthida
collection PubMed
description Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM.
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spelling pubmed-91438362022-05-29 Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis Sriboonvorakul, Natthida Hu, Jiamiao Boriboonhirunsarn, Dittakarn Ng, Leong Loke Tan, Bee Kang J Clin Med Article Gestational Diabetes Mellitus (GDM) is the most common metabolic complication during pregnancy and is associated with serious maternal and fetal complications such as pre-eclampsia and stillbirth. Further, women with GDM have approximately 10 times higher risk of diabetes later in life. Children born to mothers with GDM also face a higher risk of childhood obesity and diabetes later in life. Early prediction/diagnosis of GDM leads to early interventions such as diet and lifestyle, which could mitigate the maternal and fetal complications associated with GDM. However, no biomarkers identified to date have been proven to be effective in the prediction/diagnosis of GDM. Proteomic approaches based on mass spectrometry have been applied in various fields of biomedical research to identify novel biomarkers. Although a number of proteomic studies in GDM now exist, a lack of a comprehensive and up-to-date meta-analysis makes it difficult for researchers to interpret the data in the existing literature. Thus, we undertook a systematic review and meta-analysis on proteomic studies and GDM. We searched MEDLINE, EMBASE, Web of Science and Scopus from inception to January 2022. We searched Medline, Embase, CINHAL and the Cochrane Library, which were searched from inception to February 2021. We included cohort, case-control and observational studies reporting original data investigating the development of GDM compared to a control group. Two independent reviewers selected eligible studies for meta-analysis. Data collection and analyses were performed by two independent reviewers. The PROSPERO registration number is CRD42020185951. Of 120 articles retrieved, 24 studies met the eligibility criteria, comparing a total of 1779 pregnant women (904 GDM and 875 controls). A total of 262 GDM candidate biomarkers (CBs) were identified, with 49 CBs reported in at least two studies. We found 22 highly replicable CBs that were significantly different (nine CBs were upregulated and 12 CBs downregulated) between women with GDM and controls across various proteomic platforms, sample types, blood fractions and time of blood collection and continents. We performed further analyses on blood (plasma/serum) CBs in early pregnancy (first and/or early second trimester) and included studies with more than nine samples (nine studies in total). We found that 11 CBs were significantly upregulated, and 13 CBs significantly downregulated in women with GDM compared to controls. Subsequent pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) bioinformatics resources found that these CBs were most strongly linked to pathways related to complement and coagulation cascades. Our findings provide important insights and form a strong foundation for future validation studies to establish reliable biomarkers for GDM. MDPI 2022-05-12 /pmc/articles/PMC9143836/ /pubmed/35628864 http://dx.doi.org/10.3390/jcm11102737 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Sriboonvorakul, Natthida
Hu, Jiamiao
Boriboonhirunsarn, Dittakarn
Ng, Leong Loke
Tan, Bee Kang
Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
title Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
title_full Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
title_fullStr Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
title_full_unstemmed Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
title_short Proteomics Studies in Gestational Diabetes Mellitus: A Systematic Review and Meta-Analysis
title_sort proteomics studies in gestational diabetes mellitus: a systematic review and meta-analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9143836/
https://www.ncbi.nlm.nih.gov/pubmed/35628864
http://dx.doi.org/10.3390/jcm11102737
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