Tao Ma1, Tonghua Liu2, Peifeng Xie1, Sheng Jiang3, Wenming Yi1, Pei Dai1, Xiangyu Guo4. 1. Dongfang Hospital of Beijing University of Chinese Medicine, Beijing 100078, China. 2. Key Laboratory of Health Cultivation of the Ministry of Education, Beijing University of Chinese Medicine, Beijing 100029, China. 3. The First Teaching Hospital of Xinjiang Medical University, Urumuqi 830013, China. 4. Dongfang Hospital of Beijing University of Chinese Medicine, Beijing 100078, China. Electronic address: gxyc1003@163.com.
Abstract
AIMS: Diabetic kidney disease (DKD) is a major prevalent chronic microvascular complication of type 2 diabetes (T2D). However, the present diagnostic indicators have limitations in the early diagnosis of DKD. This study concentrated on the sensitive and specific biomarkers in early diagnosis of DKD by metabolomics. MATERIALS AND METHODS: In this cross-sectional study, we performed a UPLC-MS based nontargeted metabolomics assay to profile the urinary metabolites in patients with DKD. Principal Component Analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) were used for screening out the metabolomic variables. KEY FINDINGS: A total of 147 urinary metabolites were identified and 5 metabolic pathways were correlated with DKD pathophysiology. Pantothenate and coenzyme A biosynthesis pathway alteration was found the most prominent in DKD subjects. 4 metabolites, including dihydrouracil, ureidopropionic acid, pantothenic acid (PA), and adenosine 3',5'-diphosphate involved in pantothenate and CoA biosynthesis were significantly down-regulated. SIGNIFICANCE: Our finding indicates that PA would be served as a novel predictive biomarker associated with DKD development and progression. Furthermore, our results provide a promising prospect that PA and CoA biosynthesis pathway can be potential therapeutic targets for DKD treatment.
AIMS: Diabetic kidney disease (DKD) is a major prevalent chronic microvascular complication of type 2 diabetes (T2D). However, the present diagnostic indicators have limitations in the early diagnosis of DKD. This study concentrated on the sensitive and specific biomarkers in early diagnosis of DKD by metabolomics. MATERIALS AND METHODS: In this cross-sectional study, we performed a UPLC-MS based nontargeted metabolomics assay to profile the urinary metabolites in patients with DKD. Principal Component Analysis (PCA) and orthogonal partial least square discriminant analysis (OPLS-DA) were used for screening out the metabolomic variables. KEY FINDINGS: A total of 147 urinary metabolites were identified and 5 metabolic pathways were correlated with DKD pathophysiology. Pantothenate and coenzyme A biosynthesis pathway alteration was found the most prominent in DKD subjects. 4 metabolites, including dihydrouracil, ureidopropionic acid, pantothenic acid (PA), and adenosine 3',5'-diphosphate involved in pantothenate and CoA biosynthesis were significantly down-regulated. SIGNIFICANCE: Our finding indicates that PA would be served as a novel predictive biomarker associated with DKD development and progression. Furthermore, our results provide a promising prospect that PA and CoA biosynthesis pathway can be potential therapeutic targets for DKD treatment.