Metabolomic Profiling of Amino Acids in Human Plasma Distinguishes Diabetic Kidney Disease From Type 2 Diabetes Mellitus

Chunyu Zhou; Qing Zhang; Liqian Lu; Jiao Wang; Dongwei Liu; Zhangsuo Liu

doi:10.3389/fmed.2021.765873

Metabolomic Profiling of Amino Acids in Human Plasma Distinguishes Diabetic Kidney Disease From Type 2 Diabetes Mellitus

Front Med (Lausanne). 2021 Nov 29:8:765873. doi: 10.3389/fmed.2021.765873. eCollection 2021.

Authors

Chunyu Zhou^{1

2}, Qing Zhang^{2

3}, Liqian Lu^{2

3}, Jiao Wang^{2

3}, Dongwei Liu^{2

3

4}, Zhangsuo Liu^{1

2

3

4}

Affiliations

¹ Blood Purification Center, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
² Research Institute of Nephrology, Zhengzhou University, Zhengzhou, China.
³ Department of Nephrology, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
⁴ Key Laboratory of Precision Diagnosis and Treatment for Chronic Kidney Disease in Henan Province, Zhengzhou, China.

Abstract

Background: Diabetic kidney disease (DKD) is a highly prevalent complication in patients with type 2 diabetes mellitus (T2DM). Patients with DKD exhibit changes in plasma levels of amino acids (AAs) due to insulin resistance, reduced protein intake, and impaired renal transport of AAs. The role of AAs in distinguishing DKD from T2DM and healthy controls has yet to be elucidated. This study aimed to investigate the metabolomic profiling of AAs in the plasma of patients with DKD. Methods: We established an ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method to detect the plasma levels of the 20 AAs in healthy controls (n = 112), patients with T2DM (n = 101), and patients with DKD (n = 101). The key AAs associated with DKD were identified by orthogonal partial least-squares discriminant analysis (OPLS-DA) models with loading plots, shared and unique structures (SUS) plots, and variable importance in projection (VIP) values. The discrimination accuracies of these key AAs were then determined by analyses of receiver-operating characteristic (ROC) curves. Results: Metabolomic profiling of plasma revealed significant alterations in levels of the 20 AAs in patients with DKD when compared to those in either patients with T2DM or healthy controls. Metabolomic profiling of the 20 AAs showed a visual separation of patients with DKD from patients with T2DM and healthy controls in OPLS-DA models. Based on loading plots, SUS plots, and VIP values in the OPLS-DA models, we identified valine and cysteine as potential contributors to the progression of DKD from patients with T2DM. Histidine was identified as a key mediator that could distinguish patients with DKD from healthy controls. Plasma levels of histidine and valine were decreased significantly in patients with DKD with a decline in kidney function, and had excellent performance in distinguishing patients with DKD from patients with T2DM and healthy controls according to ROC curves. Conclusion: Plasma levels of histidine and valine were identified as the main AAs that can distinguish patients with DKD. Our findings provide new options for the prevention, treatment, and management of DKD.

Keywords: UPLC-MS /MS; amino acid; diabetic kidney disease; metabolomics; type 2 diabetes mellitus.