2021
DOI: 10.1021/acs.analchem.0c04686
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A Metabolite Array Technology for Precision Medicine

Abstract: The application of metabolomics in translational research suffers from several technological bottlenecks, such as data reproducibility issues and the lack of standardization of sample profiling procedures. Here, we report an automated high-throughput metabolite array technology that can rapidly and quantitatively determine 324 metabolites including fatty acids, amino acids, organic acids, carbohydrates, and bile acids. Metabolite identification and quantification is achieved using the Targeted Metabolome Batch… Show more

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Cited by 152 publications
(108 citation statements)
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“…The clinical diagnosis and enrolment criteria were detailed in our recently published report. 22 Test sets. A total of 48, 106, and 137 participants were enrolled independently from corresponding hospitals of the earlier studies (from January to September 2020).…”
Section: Discovery Setsmentioning
confidence: 99%
“…The clinical diagnosis and enrolment criteria were detailed in our recently published report. 22 Test sets. A total of 48, 106, and 137 participants were enrolled independently from corresponding hospitals of the earlier studies (from January to September 2020).…”
Section: Discovery Setsmentioning
confidence: 99%
“…An ultra-performance liquid chromatography coupled to tandem mass spectrometry (UPLC-MS/MS) system (ACQUITY UPLC-Xevo TQ-S, Waters Corp., Milford, MA, United States) was used to quantitatively determine 324 metabolites, including carbohydrates, amino acids, fatty acids, organic acids, and bile acids (Xie et al, 2021).…”
Section: Metabolomic Analysismentioning
confidence: 99%
“…Metabolomics provides detailed information on molecular structure and can detect a wide range of metabolites simultaneously ( 27 ). The metabolomics kit used in this investigation was also used in our previous study ( 28 ), and provided quantitative data on 52 metabolites, which were mainly fatty acids and amino acids. An unsupervised dimensionality reduction method, namely principal component analysis, was used to investigate the internal characteristics of the dataset and eliminate singularities.…”
Section: Methodsmentioning
confidence: 99%