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Branched-chain/aromatic amino acids as integrated biomarker of type 2 diabetes mellitus: a systematic review and meta-analysis

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摘要 Background:As type 2 diabetes mellitus(T2DM)biomarkers,branched-chain amino acids(BCAAs:valine,leucine and isoleucine)and aromatic amino acids(AAAs:phenylalanine,tryptophan and tyrosine)may be correlated with the occurrence and development of T2DM.However,there is still no consensus on the disperse and isolated biomarkers of T2DM.Purpose:To explore the correlation between amino acids and T2DM based on integrated biomarker approach revealed.Methods:PubMed,Web of Science and CNKI were selected to search the literature published until August 31,2019.The included studies described the association between BCAAs,AAAs and T2DM.Random effect model and fixed effect model were adopted in pooled analysis to determine mean difference and 95 percent confidence interval of metabolites.Integrated biomarker was constructed in form of concentration change ratios or risk ratio(RR),relative risk(HR)and odds ratio(OR)of BCAAs and AAAs to reflect the integrated change information of amino acids.Results:The selected 20 studies contained 14942 healthy individuals and 3615 T2DM patients.The levels of BCAAs,phenylalanine and tyrosine both in plasma and serum samples were increased among all T2DM patients compared with those of the healthy control subjects(P<0.00001).However,the mean difference of tryptophan concentration was not statistically significant(P=0.60).The concentration change ratios or HR/RR/OR of BCAAs and AAAs were connected to form integrated biomarker.Conclusion:The integrated biomarker including BCAAs and AAAs could reflect the basic characteristics of T2DM,which has the potential clinical value on comprehensive diagnosis of T2DM.
出处 《Medical Data Mining》 2020年第1期10-21,共12页 TMR医学数据挖掘
基金 supported by the National Natural Science Foundation of China(grant number 81773891) the National Great New Drugs Development Project of China(grant number 2017ZX09301-040) the Beijing Municipal Science and Technology Commission(grant number XMLX201704,2018-2-2242,7194280).
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