Jianglan Long1,2, Liwei Liu3, Qingquan Jia3, Zhirui Yang2, Zhi Sun3, Can Yan4, Dan Yan2. 1. College of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, 611130, China. 2. Beijing Key Laboratory and Joint Laboratory for International Cooperation of Bio-characteristic Profiling for Evaluation of Rational Drug Use, Capital Medical University Affiliated Beijing Shijitan Hospital, Beijing, 100038, China. 3. Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University First Affiliated Hospital, Zhengzhou, Henan, 450052, China. 4. College of Basic Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510006, China.
Abstract
RATIONALE: The prevalence of type 2 diabetes mellitus (T2DM) is increasing but its early diagnosis in high risk populations remains challenging using only fasting blood glucose (FBG) or hemoglobin A1c measurements. It is, therefore, important to search for an integrated biomarker for early diagnosis by determining metabolites associated with the progression of the disease. METHODS: We recruited 149 participants (51 T2DM patients, 50 individuals with impaired fasting glucose (IFG) and 48 normal glucose tolerance subjects). Their serum samples were analyzed based on a metabolomics approach using ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS). The changes in metabolites were profiled and evaluated using univariate and multivariate analyses. Furthermore, a biomarker model was established and the potential biomarkers were evaluated using binary logistic regression analysis and receiver operating characteristic analysis with AUC (area under the curve). Pathway analysis of differential metabolites was performed to reveal the important biological information. RESULTS: Thirty-eight differential metabolites were identified as significantly associated with T2DM patients and 23 differential metabolites with IFG individuals, mainly amino acids, carnitines, and phospholipids. By evaluating 17 potential biomarkers, we defined a novel integrated biomarker consisting of 2-acetolactate, 2-hydroxy-2,4-pentadienoate, L-arabinose and L-glutamine. The AUCs of the integrated biomarker with IFG and T2DM patients were 0.874 and 0.994, respectively, which showed a superior diagnostic performance. The levels of 2-acetolactate and 2-hydroxy-2,4-pentadienoate were strongly positively correlated with FBG, while L-glutamine and L-arabinose were strongly negatively associated with FBG. After pathway analysis, it was suggested that the majority of the influenced metabolic pathways associated with diabetes referred to amino acid metabolism. CONCLUSIONS: The integrated biomarker could diagnose IFG and T2DM with a superior diagnostic performance. This finding provides support for novel biomarkers in the diagnosis and treatment of diabetes.
RATIONALE: The prevalence of type 2 diabetes mellitus (T2DM) is increasing but its early diagnosis in high risk populations remains challenging using only fasting blood glucose (FBG) or hemoglobin A1c measurements. It is, therefore, important to search for an integrated biomarker for early diagnosis by determining metabolites associated with the progression of the disease. METHODS: We recruited 149 participants (51 T2DMpatients, 50 individuals with impaired fasting glucose (IFG) and 48 normal glucose tolerance subjects). Their serum samples were analyzed based on a metabolomics approach using ultra-high-performance liquid chromatography quadrupole-Orbitrap high-resolution accurate mass spectrometry (UHPLC/Q-Orbitrap HRMS). The changes in metabolites were profiled and evaluated using univariate and multivariate analyses. Furthermore, a biomarker model was established and the potential biomarkers were evaluated using binary logistic regression analysis and receiver operating characteristic analysis with AUC (area under the curve). Pathway analysis of differential metabolites was performed to reveal the important biological information. RESULTS: Thirty-eight differential metabolites were identified as significantly associated with T2DMpatients and 23 differential metabolites with IFG individuals, mainly amino acids, carnitines, and phospholipids. By evaluating 17 potential biomarkers, we defined a novel integrated biomarker consisting of 2-acetolactate, 2-hydroxy-2,4-pentadienoate, L-arabinose and L-glutamine. The AUCs of the integrated biomarker with IFG and T2DMpatients were 0.874 and 0.994, respectively, which showed a superior diagnostic performance. The levels of 2-acetolactate and 2-hydroxy-2,4-pentadienoate were strongly positively correlated with FBG, while L-glutamine and L-arabinose were strongly negatively associated with FBG. After pathway analysis, it was suggested that the majority of the influenced metabolic pathways associated with diabetes referred to amino acid metabolism. CONCLUSIONS: The integrated biomarker could diagnose IFG and T2DM with a superior diagnostic performance. This finding provides support for novel biomarkers in the diagnosis and treatment of diabetes.
Authors: Margarita Ortiz-Martínez; Mirna González-González; Alexandro J Martagón; Victoria Hlavinka; Richard C Willson; Marco Rito-Palomares Journal: Curr Diab Rep Date: 2022-03-10 Impact factor: 5.430
Authors: Alma Delia Genis-Mendoza; Thelma Beatriz González-Castro; Gisselle Tovilla-Vidal; Isela Esther Juárez-Rojop; Rosa Giannina Castillo-Avila; María Lilia López-Narváez; Carlos Alfonso Tovilla-Zárate; Juan Pablo Sánchez-de la Cruz; Ana Fresán; Humberto Nicolini Journal: Biomedicines Date: 2022-08-08