Serum Metabolomic Profiling Reveals Distinct Signatures and Candidate Biomarkers in Chronic Kidney Disease.

Abstract

Introduction: Chronic kidney disease (CKD) is accompanied by systemic metabolic dysregulation, and metabolomics provides a robust approach for identifying disease-specific metabolic signatures and potential biomarkers. Hypertension may be closely associated with metabolic disturbances in CKD. This study aimed to characterize serum metabolic alterations and dysregulated pathways in CKD, and screen candidate metabolite biomarkers for distinguishing CKD patients from healthy individuals.

Methods: A total of 65 participants (35 CKD patients and 30 healthy controls) were enrolled in this study. Serum metabolic profiling was performed using high-resolution mass spectrometry-based untargeted metabolomics, while targeted analysis of small molecule metabolites was conducted via liquid chromatography-mass spectrometry (LC-MS). Multivariate statistical analyses including principal component analysis (PCA) and orthogonal partial least squared-discriminant analysis (OPLS-DA) were applied to identify metabolic alterations between groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to annotate the functional roles of differentially expressed metabolites. Independent t-tests and Pearson correlation analyses were performed to validate the expression and correlation of key metabolites.

Results: A total of 1,426 metabolites were detected in all serum samples, with 1,246 successfully identified by secondary mass spectrometry. Differential analysis revealed 397 significantly altered metabolites (216 up-regulated and 181 down-regulated) between the CKD and control groups. KEGG enrichment analysis indicated that these differential metabolites were mainly involved in phenylalanine metabolism, arginine and proline metabolism, and glutathione metabolism, suggesting systemic metabolic dysfunction in CKD. Targeted analysis of catecholamines showed that serum concentrations of adrenaline and nicotinamide mononucleotide (NMN) were significantly altered in CKD patients compared with healthy controls (P < 0.05), though no significant linear correlation was observed between these two metabolites and CKD progression via Pearson correlation analysis.

Discussion: The identified metabolic pathway dysregulations (amino acid metabolism and redox-related pathways) are core metabolic characteristics of CKD, which are closely associated with renal function impairment, oxidative stress and hypertension in CKD. Adrenaline and NMN may serve as potential candidate biomarkers for CKD, and their abnormal expression may be linked to the activation of the renin-angiotensin system and dysregulation of renal energy metabolism. However, the specific mechanistic roles of these two metabolites in CKD pathophysiology remain to be elucidated.

Conclusion: This study comprehensively characterized serum metabolic alterations in CKD and identified key dysregulated metabolic pathways, as well as adrenaline and NMN as potential candidate biomarkers. These findings enhance the understanding of biochemical dysregulation underlying CKD and provide novel insights for future diagnostic biomarker development and targeted therapeutic exploration for CKD.