Serum metabolic profiling in diabetic kidney disease patients using ultra-high performance liquid chromatography-tandem mass spectrometry - PubMed (original) (raw)

Serum metabolic profiling in diabetic kidney disease patients using ultra-high performance liquid chromatography-tandem mass spectrometry

Bin Zhang et al. Diabetol Metab Syndr. 2025.

Abstract

Background: Diabetic kidney disease (DKD) remains one of the leading causes of end-stage renal failure. The currently available diagnostic and classification markers, such as the urinary albumin-to-creatinine ratio and estimated glomerular filtration rate, demonstrate inadequate precision in forecasting the onset and progression of DKD. This study aims to investigate the serum metabolic profile of patients with DKD, with the objective of identifying reliable biomarkers that can enhance the prediction of the transition from diabetes mellitus (DM) to DKD and distinguishing DKD from nondiabetic kidney disease (NDKD).

Methods: Untargeted metabolomic analysis was performed on serum samples obtained from 53 DKD patients, 54 NDKD patients, 59 individuals diagnosed with simple diabetes mellitus (SDM), and 56 healthy controls utilizing ultra-high performance liquid chromatography-tandem mass spectrometry. Differential metabolites among the groups were identified, metabolic pathways were investigated, and the diagnostic efficacy of selected metabolites was evaluated.

Results: The metabolic enrichment pathways shared between DKD and NDKD encompassed glycerophospholipid metabolism, glycerolipid metabolism, and tryptophan metabolism. In contrast, pyrimidine metabolism and arginine biosynthesis were uniquely enriched in DKD. Compared to the NDKD group, significantly elevated levels of phosphatidylglycerol (PG, 14:0) and D-Maltose were observed in DKD patients. Additionally, in comparison to the SDM group, the DKD group exhibited significant increases in lysophosphatidic acid (LPA, 16:3), LPA (18:5), LPA (22:5), phosphatidic acid (PA, 18:3), PG (26:4), L-Glutamine, Uridine, Cytidine, Formyl-N-acetyl-5-methoxykynurenamine, 2-Oxoadipate, Thymidine, L-Citrulline, and 5-Hydroxy-L-tryptophan, while PG (28:4) levels were markedly reduced. Among these, Uridine, Cytidine, Thymidine, and L-Citrulline were associated with pyrimidine metabolism, whereas L-Glutamine and L-Citrulline participated in the arginine biosynthesis pathway. Furthermore, the differential metabolites exhibited varying degrees of correlation with renal function indicators in DKD patients.

Conclusions: PG (14:0) and D-Maltose may help distinguish DKD from NDKD, while L-Glutamine, Uridine, Cytidine, Thymidine, and L-Citrulline are linked to the progression from DM to DKD. Larger studies are needed to validate these findings and assess their diagnostic and causal significance.

Keywords: Candidate biomarkers; Diabetic kidney disease; Metabolic pathway analysis; Ultra-high performance liquid chromatography-tandem mass spectrometry; Untargeted metabolomics.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: All research procedures were conducted with approval of the Ethics Committee of Mianyang Central Hospital (P2020030). All patients and/or legal guardians signed the informed consent documentation prior to experiments. Consent for publication: All authors contributed to the article and approved the submitted version. Non-use of artificial intelligence: The authors affirm that no artificial intelligence (AI) tools or technologies were employed at any stage of this research or during the preparation of the manuscript. Competing interests: The authors declare no competing interests.

Figures

Fig. 1

Fig. 1

Quality analysis of QC samples. Total ion current (A) and base peak intensity (C) in ESI + patterns of QC samples. Total ion current (B) and base peak intensity (D) in ESI- patterns of QC samples. QC, group of quality control. TIC, total ion current; BPI, base peak intensity

Fig. 2

Fig. 2

RSD and PCA analysis of serum samples and QC samples. RSD of QC samples in ESI+ (A) and ESI- (B) patterns. PCA score plots in ESI+ (C) and ESI- (D) patterns among DKD, NDKD, SDM, HC, and QC groups. The QC specific PCA score plots in ESI+(E) and ESI-(F) patterns for visualizing the controls and QC replicates. DKD, group of diabetic kidney disease; NDKD, group of nondiabetic kidney disease; SDM, group of diabetes mellitus; HC, group of healthy control; QC, group of quality control; RSD, relative standard deviation

Fig. 3

Fig. 3

OPLS-DA analysis of serum samples. OPLS-DA analysis was performed between DKD and NDKD (A), between DKD and HC (B), between DKD and SDM (C), between NDKD and HC (D), between NDKD and SDM (E), between SDM and HC (F) in ESI + patterns. OPLS-DA analysis was performed between DKD and NDKD (G), between DKD and HC (H), between DKD and SDM (I), between NDKD and HC (J), between NDKD and SDM (K), between SDM and HC (L) in ESI- patterns. DKD, group of diabetic kidney disease; NDKD, group of nondiabetic kidney disease; SDM, group of diabetes mellitus; HC, group of healthy control

Fig. 4

Fig. 4

Volcano plot of metabolites. Volcano plot of metabolites between DKD and NDKD (A), between DKD and SDM (B), between NDKD and SDM (C), between SDM and HC (D). DKD, group of diabetic kidney disease; NDKD, group of nondiabetic kidney disease; SDM, group of diabetes mellitus; HC, group of healthy control; FC, fold change; P-value: the significance value of T-test and corrected as false discovery rate (FDR)-adjusted P values using Benjamini–Hochberg procedure; n, the number of upregulated or down-regulated metabolites. The abscissa is equal to log2(FC), and the abscissa is equal to -log10(p). The two lines parallel to the Y-axis are x = 0.58 and x=-0.58, the point to the left of x=-0.58 is more than 1.5 times down-regulated metabolites, and the point to the right of x = 0.58 is more than 1.5 times up-regulated metabolites. A line parallel to the X-axis is Y = 1.30, and points above the line represent metabolites with a significant p < 0.05

Fig. 5

Fig. 5

Pathway analysis of differential metabolites. Pathway analysis of differential metabolites between DKD and NDKD (A), between DKD and SDM (B), between NDKD and SDM (C), between SDM and HC (D). DKD, group of diabetic kidney disease; NDKD, group of nondiabetic kidney disease; SDM, group of diabetes mellitus; HC, group of healthy control

Fig. 6

Fig. 6

Venn diagrams of different metabolic pathways and metabolites in the subjects. Venn diagram for differential pathways (A) and venn diagram for metabolites on differential metabolic pathways (B). Figure 6A shows the number of metabolic pathways in the region, while Fig. 6B displays the number of metabolites in that area. DKD, group of diabetic kidney disease; NDKD, group of nondiabetic kidney disease; SDM, group of diabetes mellitus; HC, group of healthy control

Fig. 7

Fig. 7

Venn diagram illustrating differential metabolites with an AUC greater than 0.7 among the subjects. PG(14:0) and D-Maltose exist only in DKD vs. NDKD; PG(28:4), L-Glutamine, Uridine, Cytidine, Formyl-N-acetyl-5-methoxykynurenamine, Thymidine and L-Citrulline exist only in DKD vs. SDM; LPA(16:3), LPA(18:5), LPA(22:5), PA(18:3), PG(26:4), 5-Hydroxy-L-tryptophan and 2-Oxoadipate coexist in DKD vs. SDM and NDKD vs. SDM. The numeral “0” indicates no common differential metabolites in this region. DKD, group of diabetic kidney disease; NDKD, group of nondiabetic kidney disease; SDM, group of diabetes mellitus; HC, group of healthy control

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