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A random effect model and a fixed effect model were applied to the results of forest plot analyses to determine the standardized mean difference (SMD) and 95% confidence interval (95% CI) for each metabolite. The SMD for every metabolite was then converted into an odds ratio to create an metabolite biomarker profile.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Twenty-four independent studies reported data from 14,131 healthy individuals and 3499 patients with T2DM, and 14 included studies reported 4844 healthy controls and a total of 2139 pre-diabetes patients. In the serum and plasma of patients with T2DM, compared with the healthy participants, the concentrations of valine, leucine, isoleucine, proline, tyrosine, lysine and glutamate were higher and that of glycine was lower. The concentrations of isoleucine, alanine, proline, glutamate, palmitic acid, 2-aminoadipic acid and lysine were higher and those of glycine, serine, and citrulline were lower in prediabetic patients. Metabolite biomarkers of T2DM and pre-diabetes revealed that the levels of alanine, glutamate and palmitic acid (C16:0) were significantly different in T2DM and pre-diabetes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Quantified multiple metabolite biomarkers may reflect the different status of pre-diabetes and T2DM, and could provide an important reference for clinical diagnosis and treatment of pre-diabetes and T2DM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12902-020-00653-x","type":"journal-article","created":{"date-parts":[[2020,11,23]],"date-time":"2020-11-23T15:03:53Z","timestamp":1606143833000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":111,"title":["Metabolite biomarkers of type 2 diabetes mellitus and pre-diabetes: a systematic review and meta-analysis"],"prefix":"10.1186","volume":"20","author":[{"given":"Jianglan","family":"Long","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhirui","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Long","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yumei","family":"Han","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Can","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1288-4144","authenticated-orcid":false,"given":"Dan","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,11,23]]},"reference":[{"issue":"4","key":"653_CR1","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1093\/oxfordjournals.aje.a115892","volume":"133","author":"JN Kostraba","year":"1991","unstructured":"Kostraba JN, Klein R, Dorman JS, et al. 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