Impaired Amino Acid Metabolism and Its Correlation with Diabetic Kidney Disease Progression in Type 2 Diabetes Mellitus

• Published in: Nutrients Vol. 14; no. 16; p. 3345
• Main Authors: Zhu, Huanhuan, Bai, Mengqiu, Xie, Xishao, Wang, Junni, Weng, Chunhua, Dai, Huifen, Chen, Jianghua, Han, Fei, Lin, Weiqiang
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 15.08.2022; MDPI
• Subjects: Amino acid metabolism; Amino acids; asparagine; betaine; Biomarkers; Chromatography; Comparative analysis; Complications and side effects; Creatinine; cross-sectional studies; Development and progression; Diabetes; Diabetic nephropathies; Diabetic nephropathy; Discriminant analysis; disease progression; Health aspects; Independent sample; isoleucine; Kidney diseases; Medical research; Medicine, Experimental; Metabolism; Metabolites; metabolomics; noninsulin-dependent diabetes mellitus; Normal distribution; Physiological aspects; prospective studies; regression analysis; risk; Risk factors; Software; Type 2 diabetes; valine; China; United States > US
• ISSN: 2072-6643; 2072-6643
• DOI: 10.3390/nu14163345

Background: Metabolomics is useful in elucidating the progression of diabetes; however, the follow-up changes in metabolomics among health, diabetes mellitus, and diabetic kidney disease (DKD) have not been reported. This study was aimed to reveal metabolomic signatures in diabetes development and progression. Methods: In this cross-sectional study, we compared healthy (n = 30), type 2 diabetes mellitus (T2DM) (n = 30), and DKD (n = 30) subjects with the goal of identifying gradual altering metabolites. Then, a prospective study was performed in T2DM patients to evaluate these altered metabolites in the onset of DKD. Logistic regression was conducted to predict rapid eGFR decline in T2DM subjects using altered metabolites. The prospective association of metabolites with the risk of developing DKD was examined using logistic regression and restricted cubic spline regression models. Results: In this cross-sectional study, impaired amino acid metabolism was the main metabolic signature in the onset and development of diabetes, which was characterized by increased N-acetylaspartic acid, L-valine, isoleucine, asparagine, betaine, and L-methionine levels in both the T2DM and DKD groups. These candidate metabolites could distinguish the DKD group from the T2DM group. In the follow-up study, higher baseline levels of L-valine and isoleucine were significantly associated with an increased risk of rapid eGFR decline in T2DM patients. Of these, L-valine and isoleucine were independent risk factors for the development of DKD. Notably, nonlinear associations were also observed for higher baseline levels of L-valine and isoleucine, with an increased risk of DKD among patients with T2DM. Conclusion: Amino acid metabolism was disturbed in diabetes, and N-acetylaspartic acid, L-valine, isoleucine, asparagine, betaine, and L-methionine could be biomarkers for the onset and progression of diabetes. Furthermore, high levels of L-valine and isoleucine may be risk factors for DKD development.