Metabolomics in gestational diabetes
Gestational diabetes mellitus (GDM) is a form of diabetes that is first diagnosed during pregnancy in the absence of existing type 1 or type 2 diabetes. Early screening tools for GDM are currently unavailable, but metabolomics is a promising approach for detecting biomarkers of GDM. This review eval...
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Veröffentlicht in: | Clinica chimica acta 2017-12, Vol.475, p.116-127 |
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description | Gestational diabetes mellitus (GDM) is a form of diabetes that is first diagnosed during pregnancy in the absence of existing type 1 or type 2 diabetes. Early screening tools for GDM are currently unavailable, but metabolomics is a promising approach for detecting biomarkers of GDM. This review evaluates recent GDM studies employing metabolomic techniques, highlighting the challenges in those studies and envisions the future directions for metabolomic study of GDM. A diverse range of predictive markers and dysregulated metabolic pathways have been associated with the pathogenesis of GDM, but these findings have lacked reproducibility among studies. The case-control study design has been most frequently employed in the studies of GDM, and most of them used specimens acquired in mid-pregnancy. However, this approach might not be adequate to recognise the complexity of the condition. The sample size in some of the studies is limited, and this may result in findings from a participant set that is not representative of the general population. Therefore, we propose that future metabolomic studies pertaining to GDM use a cross-platform approach employing unified diagnostic criteria, a longitudinal cohort, and innovative data processing methods to allow for full-scale identification and comprehensive coverage of the metabolome. In addition, the relationship between the exposure to environmental chemicals such as endocrine disruptors and the development of GDM should be further investigated in future studies.
•This review evaluates the impact of metabolomics in the studies of GDM.•Attention is paid to the study design, methodology and predictive biomarkers proposed.•Biomarker candidates proposed have been highly diverse even when the same instrument and study protocol are used.•A proposal of our vision for the future metabolomic studies of GDM is given. |
doi_str_mv | 10.1016/j.cca.2017.10.019 |
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•This review evaluates the impact of metabolomics in the studies of GDM.•Attention is paid to the study design, methodology and predictive biomarkers proposed.•Biomarker candidates proposed have been highly diverse even when the same instrument and study protocol are used.•A proposal of our vision for the future metabolomic studies of GDM is given.</description><identifier>ISSN: 0009-8981</identifier><identifier>EISSN: 1873-3492</identifier><identifier>DOI: 10.1016/j.cca.2017.10.019</identifier><identifier>PMID: 29066210</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Adult ; Biomarkers ; Biomarkers - blood ; Biomarkers - urine ; Case-Control Studies ; Chromatography, High Pressure Liquid - instrumentation ; Chromatography, High Pressure Liquid - methods ; Diabetes, Gestational - blood ; Diabetes, Gestational - diagnosis ; Diabetes, Gestational - physiopathology ; Diabetes, Gestational - urine ; Female ; Gestational diabetes mellitus ; Humans ; Magnetic Resonance Spectroscopy - instrumentation ; Magnetic Resonance Spectroscopy - methods ; Metabolic Networks and Pathways - physiology ; Metabolic pathways ; Metabolome ; Metabolomics ; Metabolomics - instrumentation ; Metabolomics - methods ; Pregnancy ; Pregnancy complications ; Reproducibility of Results ; Sample Size ; Tandem Mass Spectrometry - instrumentation ; Tandem Mass Spectrometry - methods</subject><ispartof>Clinica chimica acta, 2017-12, Vol.475, p.116-127</ispartof><rights>2017 Elsevier B.V.</rights><rights>Copyright © 2017 Elsevier B.V. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c353t-1fcaf439d906d92cee06df11e2f465eb61a06a7835469a790f68dfc21b7ddeeb3</citedby><cites>FETCH-LOGICAL-c353t-1fcaf439d906d92cee06df11e2f465eb61a06a7835469a790f68dfc21b7ddeeb3</cites><orcidid>0000-0003-0107-2885</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.cca.2017.10.019$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29066210$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mao, Xun</creatorcontrib><creatorcontrib>Chen, Xuyang</creatorcontrib><creatorcontrib>Chen, Chang</creatorcontrib><creatorcontrib>Zhang, Hua</creatorcontrib><creatorcontrib>Law, Kai P.</creatorcontrib><title>Metabolomics in gestational diabetes</title><title>Clinica chimica acta</title><addtitle>Clin Chim Acta</addtitle><description>Gestational diabetes mellitus (GDM) is a form of diabetes that is first diagnosed during pregnancy in the absence of existing type 1 or type 2 diabetes. Early screening tools for GDM are currently unavailable, but metabolomics is a promising approach for detecting biomarkers of GDM. This review evaluates recent GDM studies employing metabolomic techniques, highlighting the challenges in those studies and envisions the future directions for metabolomic study of GDM. A diverse range of predictive markers and dysregulated metabolic pathways have been associated with the pathogenesis of GDM, but these findings have lacked reproducibility among studies. The case-control study design has been most frequently employed in the studies of GDM, and most of them used specimens acquired in mid-pregnancy. However, this approach might not be adequate to recognise the complexity of the condition. The sample size in some of the studies is limited, and this may result in findings from a participant set that is not representative of the general population. Therefore, we propose that future metabolomic studies pertaining to GDM use a cross-platform approach employing unified diagnostic criteria, a longitudinal cohort, and innovative data processing methods to allow for full-scale identification and comprehensive coverage of the metabolome. In addition, the relationship between the exposure to environmental chemicals such as endocrine disruptors and the development of GDM should be further investigated in future studies.
•This review evaluates the impact of metabolomics in the studies of GDM.•Attention is paid to the study design, methodology and predictive biomarkers proposed.•Biomarker candidates proposed have been highly diverse even when the same instrument and study protocol are used.•A proposal of our vision for the future metabolomic studies of GDM is given.</description><subject>Adult</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Biomarkers - urine</subject><subject>Case-Control Studies</subject><subject>Chromatography, High Pressure Liquid - instrumentation</subject><subject>Chromatography, High Pressure Liquid - methods</subject><subject>Diabetes, Gestational - blood</subject><subject>Diabetes, Gestational - diagnosis</subject><subject>Diabetes, Gestational - physiopathology</subject><subject>Diabetes, Gestational - urine</subject><subject>Female</subject><subject>Gestational diabetes mellitus</subject><subject>Humans</subject><subject>Magnetic Resonance Spectroscopy - instrumentation</subject><subject>Magnetic Resonance Spectroscopy - methods</subject><subject>Metabolic Networks and Pathways - physiology</subject><subject>Metabolic pathways</subject><subject>Metabolome</subject><subject>Metabolomics</subject><subject>Metabolomics - instrumentation</subject><subject>Metabolomics - methods</subject><subject>Pregnancy</subject><subject>Pregnancy complications</subject><subject>Reproducibility of Results</subject><subject>Sample Size</subject><subject>Tandem Mass Spectrometry - instrumentation</subject><subject>Tandem Mass Spectrometry - methods</subject><issn>0009-8981</issn><issn>1873-3492</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kM1LAzEQxYMotlb_AC_Sgwcvu2aS3ewGT1L8gooXPYdsMpGU_ajJVvC_b0qrR0_DG957zPwIuQSaAwVxu8qN0TmjUCWdU5BHZAp1xTNeSHZMppRSmdWyhgk5i3GVZEEFnJIJk1QIBnRKrl9x1M3QDp03ce77-SfGUY9-6HU7t143OGI8JydOtxEvDnNGPh4f3hfP2fLt6WVxv8wML_mYgTPaFVza1G4lM4hpOgBkrhAlNgI0FbqqeVkIqStJnaitMwyaylrEhs_Izb53HYavTTpEdT4abFvd47CJCmRZCpAVFMkKe6sJQ4wBnVoH3-nwo4CqHRy1UgmO2sHZrRKclLk61G-aDu1f4pdGMtztDZie_PYYVDQee4PWBzSjsoP_p34LU9lzsw</recordid><startdate>201712</startdate><enddate>201712</enddate><creator>Mao, Xun</creator><creator>Chen, Xuyang</creator><creator>Chen, Chang</creator><creator>Zhang, Hua</creator><creator>Law, Kai P.</creator><general>Elsevier B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0003-0107-2885</orcidid></search><sort><creationdate>201712</creationdate><title>Metabolomics in gestational diabetes</title><author>Mao, Xun ; Chen, Xuyang ; Chen, Chang ; Zhang, Hua ; Law, Kai P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c353t-1fcaf439d906d92cee06df11e2f465eb61a06a7835469a790f68dfc21b7ddeeb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Adult</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Biomarkers - urine</topic><topic>Case-Control Studies</topic><topic>Chromatography, High Pressure Liquid - instrumentation</topic><topic>Chromatography, High Pressure Liquid - methods</topic><topic>Diabetes, Gestational - blood</topic><topic>Diabetes, Gestational - diagnosis</topic><topic>Diabetes, Gestational - physiopathology</topic><topic>Diabetes, Gestational - urine</topic><topic>Female</topic><topic>Gestational diabetes mellitus</topic><topic>Humans</topic><topic>Magnetic Resonance Spectroscopy - instrumentation</topic><topic>Magnetic Resonance Spectroscopy - methods</topic><topic>Metabolic Networks and Pathways - physiology</topic><topic>Metabolic pathways</topic><topic>Metabolome</topic><topic>Metabolomics</topic><topic>Metabolomics - instrumentation</topic><topic>Metabolomics - methods</topic><topic>Pregnancy</topic><topic>Pregnancy complications</topic><topic>Reproducibility of Results</topic><topic>Sample Size</topic><topic>Tandem Mass Spectrometry - instrumentation</topic><topic>Tandem Mass Spectrometry - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mao, Xun</creatorcontrib><creatorcontrib>Chen, Xuyang</creatorcontrib><creatorcontrib>Chen, Chang</creatorcontrib><creatorcontrib>Zhang, Hua</creatorcontrib><creatorcontrib>Law, Kai P.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinica chimica acta</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mao, Xun</au><au>Chen, Xuyang</au><au>Chen, Chang</au><au>Zhang, Hua</au><au>Law, Kai P.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metabolomics in gestational diabetes</atitle><jtitle>Clinica chimica acta</jtitle><addtitle>Clin Chim Acta</addtitle><date>2017-12</date><risdate>2017</risdate><volume>475</volume><spage>116</spage><epage>127</epage><pages>116-127</pages><issn>0009-8981</issn><eissn>1873-3492</eissn><abstract>Gestational diabetes mellitus (GDM) is a form of diabetes that is first diagnosed during pregnancy in the absence of existing type 1 or type 2 diabetes. Early screening tools for GDM are currently unavailable, but metabolomics is a promising approach for detecting biomarkers of GDM. This review evaluates recent GDM studies employing metabolomic techniques, highlighting the challenges in those studies and envisions the future directions for metabolomic study of GDM. A diverse range of predictive markers and dysregulated metabolic pathways have been associated with the pathogenesis of GDM, but these findings have lacked reproducibility among studies. The case-control study design has been most frequently employed in the studies of GDM, and most of them used specimens acquired in mid-pregnancy. However, this approach might not be adequate to recognise the complexity of the condition. The sample size in some of the studies is limited, and this may result in findings from a participant set that is not representative of the general population. Therefore, we propose that future metabolomic studies pertaining to GDM use a cross-platform approach employing unified diagnostic criteria, a longitudinal cohort, and innovative data processing methods to allow for full-scale identification and comprehensive coverage of the metabolome. In addition, the relationship between the exposure to environmental chemicals such as endocrine disruptors and the development of GDM should be further investigated in future studies.
•This review evaluates the impact of metabolomics in the studies of GDM.•Attention is paid to the study design, methodology and predictive biomarkers proposed.•Biomarker candidates proposed have been highly diverse even when the same instrument and study protocol are used.•A proposal of our vision for the future metabolomic studies of GDM is given.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>29066210</pmid><doi>10.1016/j.cca.2017.10.019</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-0107-2885</orcidid></addata></record> |
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subjects | Adult Biomarkers Biomarkers - blood Biomarkers - urine Case-Control Studies Chromatography, High Pressure Liquid - instrumentation Chromatography, High Pressure Liquid - methods Diabetes, Gestational - blood Diabetes, Gestational - diagnosis Diabetes, Gestational - physiopathology Diabetes, Gestational - urine Female Gestational diabetes mellitus Humans Magnetic Resonance Spectroscopy - instrumentation Magnetic Resonance Spectroscopy - methods Metabolic Networks and Pathways - physiology Metabolic pathways Metabolome Metabolomics Metabolomics - instrumentation Metabolomics - methods Pregnancy Pregnancy complications Reproducibility of Results Sample Size Tandem Mass Spectrometry - instrumentation Tandem Mass Spectrometry - methods |
title | Metabolomics in gestational diabetes |
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