Chronic Kidney Disease (CKD) is considered as a major public health problem as it can lead to end-stage kidney failure, which requires replacement therapy. A prompt and accurate diagnosis, along with the appropriate treatment, can delay CKD’s progression, significantly. Herein, we sought to determine whether CKD etiology can be reflected in urine metabolomics during its early stage. This is achieved through the analysis of the urine metabolic fingerprint from 108 CKD patients by means of Nuclear Magnetic Resonance (NMR) spectroscopy metabolomic analysis. We report the first NMR—metabolomics data regarding the three most common etiologies of CKD: Chronic Glomerulonephritis (IgA and Membranous Nephropathy), Diabetic Nephropathy (DN) and Hypertensive Nephrosclerosis (HN). Analysis aided a moderate glomerulonephritis clustering, providing characterization of the metabolic fluctuations between the CKD subtypes and control disease. The urine metabolome of IgA Nephropathy reveals a specific metabolism, reflecting its different etiology or origin and is useful for determining the origin of the disease. In contrast, urine metabolomes from DN and HN patients did not reveal any indicative metabolic pattern, which is consistent with their fused clinical phenotype. These findings may contribute to improving diagnostics and prognostic approaches for CKD, as well as improving our understanding of its pathology.

Metabolomics is one of the most attractive whilst still developing field of omics sciences, studying metabolites and the alterations of their levels. As an approach, metabolomics has the potential to identify using high‐throughput analytical precision statistically significant alterations, covering a broad spectrum of metabolic processes. What metabolomics can offer are qualitative and quantitative information, incorporating the consideration of more variables in analytical procedures. Measuring of metabolites and metabolic profiling provide an instant ‘snapshot’ which permits the follow up of the dynamics of complex biological systems and their mechanisms under physiological or abnormal conditions. Nuclear magnetic resonance (NMR) provides an excellent technique for profiling the biological fluids and is especially adept at characterising complex solutions. Advances in biochemical data obtained from NMR spectra allow us to observe the metabolome in a very accurate manner and thus estimate the complex index of biochemical processes, determining the health status of an organism. To date, metabolomics profiling is a powerful approach for examining disease‐related metabolic changes and is highly effective in the identification of new biomarkers. Key Concepts NMR is a novel, noninvasive, fast, accurate and reproducible bioanalytical method for metabolites identification and quantification in biological samples. Simple 1 H 1D NMR spectra are exploited for the definition of the physiological healthy status of organism's metabolism, based on a specific spectral pattern. NMR experiments selection depends on the biological fluid of interest. Metabolites identification and quantification and their role in a metabolomic experiment. The advantages of metabolic profiling and its utility in a potential diagnostic model. Monitoring of an individual's metabolic responses through the examination of its spectral fingerprint along specific time points. Significant alterations in metabolites concentrations are meaningful to exact interactions of pathways, perturbations and metabolite–metabolite correlations. Computational tools and global repositories in service of metabolomic data. Multivariate analysis techniques and their implementation in the field of NMR metabolomics. NMR metabolomics in clinical research, the intervention of the field and the impact in accessing unknown biological phenomena.