Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis
To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes. We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review o...
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| Veröffentlicht in: | Diabetes care 2016-05, Vol.39 (5), p.833-846 |
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| creator | Guasch-Ferré, Marta Hruby, Adela Toledo, Estefanía Clish, Clary B Martínez-González, Miguel A Salas-Salvadó, Jordi Hu, Frank B |
| description | To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes.
We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite.
We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%).
In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes. |
| doi_str_mv | 10.2337/dc15-2251 |
| format | Article |
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We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite.
We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%).
In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.</description><identifier>ISSN: 0149-5992</identifier><identifier>EISSN: 1935-5548</identifier><identifier>DOI: 10.2337/dc15-2251</identifier><identifier>PMID: 27208380</identifier><identifier>CODEN: DICAD2</identifier><language>eng</language><publisher>United States: American Diabetes Association</publisher><subject>Amino acids ; Biomarkers ; Biomarkers - blood ; Biomarkers - metabolism ; Cross-Sectional Studies ; Diabetes ; Diabetes Mellitus, Type 2 - blood ; Diabetes Mellitus, Type 2 - diagnosis ; Diabetes Mellitus, Type 2 - metabolism ; Diabetes Mellitus, Type 2 - therapy ; Female ; Humans ; Incidence ; Meta-Analysis ; Metabolites ; Metabolomics - methods ; Middle Aged ; Prediabetic State - diagnosis ; Prediabetic State - metabolism ; Prediabetic State - therapy ; Prospective Studies ; Risk factors ; Systematic review</subject><ispartof>Diabetes care, 2016-05, Vol.39 (5), p.833-846</ispartof><rights>2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.</rights><rights>Copyright American Diabetes Association May 2016</rights><rights>2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c469t-2e4772edfffbe010f6eabddce2f5bb42d4e72a53fe20c04ff22c6cc40afe5653</citedby><cites>FETCH-LOGICAL-c469t-2e4772edfffbe010f6eabddce2f5bb42d4e72a53fe20c04ff22c6cc40afe5653</cites><orcidid>0000-0001-8525-1404 ; 0000-0003-2700-7459</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,777,781,882,27905,27906</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27208380$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Guasch-Ferré, Marta</creatorcontrib><creatorcontrib>Hruby, Adela</creatorcontrib><creatorcontrib>Toledo, Estefanía</creatorcontrib><creatorcontrib>Clish, Clary B</creatorcontrib><creatorcontrib>Martínez-González, Miguel A</creatorcontrib><creatorcontrib>Salas-Salvadó, Jordi</creatorcontrib><creatorcontrib>Hu, Frank B</creatorcontrib><title>Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis</title><title>Diabetes care</title><addtitle>Diabetes Care</addtitle><description>To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes.
We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite.
We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%).
In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.</description><subject>Amino acids</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Biomarkers - metabolism</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>Diabetes Mellitus, Type 2 - blood</subject><subject>Diabetes Mellitus, Type 2 - diagnosis</subject><subject>Diabetes Mellitus, Type 2 - metabolism</subject><subject>Diabetes Mellitus, Type 2 - therapy</subject><subject>Female</subject><subject>Humans</subject><subject>Incidence</subject><subject>Meta-Analysis</subject><subject>Metabolites</subject><subject>Metabolomics - methods</subject><subject>Middle Aged</subject><subject>Prediabetic State - diagnosis</subject><subject>Prediabetic State - metabolism</subject><subject>Prediabetic State - therapy</subject><subject>Prospective Studies</subject><subject>Risk factors</subject><subject>Systematic review</subject><issn>0149-5992</issn><issn>1935-5548</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkclKA0EQhhtRTIwefAEZ8KKH0V5n8SCEuEIkork3PT3V2mGW2D2J5O2dMTGop6Korz6q-BE6JviCMhZf5pqIkFJBdlCfpEyEQvBkF_Ux4Wko0pT20IH3M4wx50myj3o0pjhhCe6jyRM0KquLurTaB7YKnh3kVmXQgA9UlQc3m-YqGAavK99AqRqrgxdYWvj8JjpDqCpVrLz1h2jPqMLD0aYO0PTudjp6CMeT-8fRcBxqHqVNSIHHMYXcGJMBJthEoLI810CNyDJOcw4xVYIZoFhjbgylOtKaY2VARIIN0PVaO19kJbR7VeNUIefOlsqtZK2s_Dup7Lt8q5eSJywlMW0FZxuBqz8W4BtZWq-hKFQF9cJLEqeYRxGPOvT0HzqrF679t6OSFMdCYNJS52tKu9p7B2Z7DMGyS0l2KckupZY9-X39lvyJhX0Bc4eOXg</recordid><startdate>20160501</startdate><enddate>20160501</enddate><creator>Guasch-Ferré, Marta</creator><creator>Hruby, Adela</creator><creator>Toledo, Estefanía</creator><creator>Clish, Clary B</creator><creator>Martínez-González, Miguel A</creator><creator>Salas-Salvadó, Jordi</creator><creator>Hu, Frank B</creator><general>American Diabetes Association</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>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8525-1404</orcidid><orcidid>https://orcid.org/0000-0003-2700-7459</orcidid></search><sort><creationdate>20160501</creationdate><title>Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis</title><author>Guasch-Ferré, Marta ; Hruby, Adela ; Toledo, Estefanía ; Clish, Clary B ; Martínez-González, Miguel A ; Salas-Salvadó, Jordi ; Hu, Frank B</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c469t-2e4772edfffbe010f6eabddce2f5bb42d4e72a53fe20c04ff22c6cc40afe5653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Amino acids</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Biomarkers - metabolism</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>Diabetes Mellitus, Type 2 - blood</topic><topic>Diabetes Mellitus, Type 2 - diagnosis</topic><topic>Diabetes Mellitus, Type 2 - metabolism</topic><topic>Diabetes Mellitus, Type 2 - therapy</topic><topic>Female</topic><topic>Humans</topic><topic>Incidence</topic><topic>Meta-Analysis</topic><topic>Metabolites</topic><topic>Metabolomics - methods</topic><topic>Middle Aged</topic><topic>Prediabetic State - diagnosis</topic><topic>Prediabetic State - metabolism</topic><topic>Prediabetic State - therapy</topic><topic>Prospective Studies</topic><topic>Risk factors</topic><topic>Systematic review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guasch-Ferré, Marta</creatorcontrib><creatorcontrib>Hruby, Adela</creatorcontrib><creatorcontrib>Toledo, Estefanía</creatorcontrib><creatorcontrib>Clish, Clary B</creatorcontrib><creatorcontrib>Martínez-González, Miguel A</creatorcontrib><creatorcontrib>Salas-Salvadó, Jordi</creatorcontrib><creatorcontrib>Hu, Frank B</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Diabetes care</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guasch-Ferré, Marta</au><au>Hruby, Adela</au><au>Toledo, Estefanía</au><au>Clish, Clary B</au><au>Martínez-González, Miguel A</au><au>Salas-Salvadó, Jordi</au><au>Hu, Frank B</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis</atitle><jtitle>Diabetes care</jtitle><addtitle>Diabetes Care</addtitle><date>2016-05-01</date><risdate>2016</risdate><volume>39</volume><issue>5</issue><spage>833</spage><epage>846</epage><pages>833-846</pages><issn>0149-5992</issn><eissn>1935-5548</eissn><coden>DICAD2</coden><abstract>To conduct a systematic review of cross-sectional and prospective human studies evaluating metabolite markers identified using high-throughput metabolomics techniques on prediabetes and type 2 diabetes.
We searched MEDLINE and EMBASE databases through August 2015. We conducted a qualitative review of cross-sectional and prospective studies. Additionally, meta-analyses of metabolite markers, with data estimates from at least three prospective studies, and type 2 diabetes risk were conducted, and multivariable-adjusted relative risks of type 2 diabetes were calculated per study-specific SD difference in a given metabolite.
We identified 27 cross-sectional and 19 prospective publications reporting associations of metabolites and prediabetes and/or type 2 diabetes. Carbohydrate (glucose and fructose), lipid (phospholipids, sphingomyelins, and triglycerides), and amino acid (branched-chain amino acids, aromatic amino acids, glycine, and glutamine) metabolites were higher in individuals with type 2 diabetes compared with control subjects. Prospective studies provided evidence that blood concentrations of several metabolites, including hexoses, branched-chain amino acids, aromatic amino acids, phospholipids, and triglycerides, were associated with the incidence of prediabetes and type 2 diabetes. We meta-analyzed results from eight prospective studies that reported risk estimates for metabolites and type 2 diabetes, including 8,000 individuals of whom 1,940 had type 2 diabetes. We found 36% higher risk of type 2 diabetes per study-specific SD difference for isoleucine (pooled relative risk 1.36 [1.24-1.48]; I(2) = 9.5%), 36% for leucine (1.36 [1.17-1.58]; I(2) = 37.4%), 35% for valine (1.35 [1.19-1.53]; I(2) = 45.8%), 36% for tyrosine (1.36 [1.19-1.55]; I(2) = 51.6%), and 26% for phenylalanine (1.26 [1.10-1.44]; I(2) = 56%). Glycine and glutamine were inversely associated with type 2 diabetes risk (0.89 [0.81-0.96] and 0.85 [0.82-0.89], respectively; both I(2) = 0.0%).
In studies using high-throughput metabolomics, several blood amino acids appear to be consistently associated with the risk of developing type 2 diabetes.</abstract><cop>United States</cop><pub>American Diabetes Association</pub><pmid>27208380</pmid><doi>10.2337/dc15-2251</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-8525-1404</orcidid><orcidid>https://orcid.org/0000-0003-2700-7459</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Diabetes care, 2016-05, Vol.39 (5), p.833-846 |
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| subjects | Amino acids Biomarkers Biomarkers - blood Biomarkers - metabolism Cross-Sectional Studies Diabetes Diabetes Mellitus, Type 2 - blood Diabetes Mellitus, Type 2 - diagnosis Diabetes Mellitus, Type 2 - metabolism Diabetes Mellitus, Type 2 - therapy Female Humans Incidence Meta-Analysis Metabolites Metabolomics - methods Middle Aged Prediabetic State - diagnosis Prediabetic State - metabolism Prediabetic State - therapy Prospective Studies Risk factors Systematic review |
| title | Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis |
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