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Background : Over the years, it was noticed that patients with diabetes have reached an alarming number worldwide. Diabetes presents many complications, including diabetic kidney disease (DKD), which can be considered the leading cause of end-stage renal disease. Current biomarkers such as serum creatinine and albuminuria have limitations for early detection of DKD. Methods : In our study, we used UHPLC-QTOF-ESI+-MS techniques to quantify previously analyzed metabolites. Based on one-way ANOVA and Fisher's LSD, untargeted analysis allowed the discrimination of six metabolites between subgroups P1 versus P2 and P3: tryptophan, kynurenic acid, taurine, l-acetylcarnitine, glycine, and tiglylglycine. Results : Our results showed several metabolites that exhibited significant differences among the patient groups and can be considered putative biomarkers in early DKD, including glycine and kynurenic acid in serum ( p < 0.001) and tryptophan and tiglylglycine ( p < 0.001) in urine. Conclusions : Although we identified metabolites as potential biomarkers in the present study, additional studies are needed to validate these results.

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease; however, few biomarkers of its early identification are available. The aim of the study was to assess new biomarkers in the early stages of DKD in type 2 diabetes mellitus (DM) patients. This cross-sectional pilot study performed an integrated metabolomic profiling of blood and urine in 90 patients with type 2 DM, classified into three subgroups according to albuminuria stage from P1 to P3 (30 normo-, 30 micro-, and 30 macroalbuminuric) and 20 healthy controls using high-performance liquid chromatography and mass spectrometry (UPLC-QTOF-ESI* MS). From a large cohort of separated and identified molecules, 33 and 39 amino acids and derivatives from serum and urine, respectively, were selected for statistical analysis using Metaboanalyst 5.0. online software. The multivariate and univariate algorithms confirmed the relevance of some amino acids and derivatives as biomarkers that are responsible for the discrimination between healthy controls and DKD patients. Serum molecules such as tiglylglycine, methoxytryptophan, serotonin sulfate, 5-hydroxy lysine, taurine, kynurenic acid, and tyrosine were found to be more significant in the discrimination between group C and subgroups P1-P2-P3. In urine, o-phosphothreonine, aspartic acid, 5-hydroxy lysine, uric acid, methoxytryptophan, were among the most relevant metabolites in the discrimination between group C and DKD group, as well between subgroups P1-P2-P3. The identification of these potential biomarkers may indicate their involvement in the early DKD and 2DM progression, reflecting kidney injury at specific sites along the nephron, even in the early stages of DKD.

Chronic kidney disease (CKD) has emerged as one of the most progressive diseases with increased mortality and morbidity. Metabolomics offers new insights into CKD pathogenesis and the discovery of new biomarkers for the early diagnosis of CKD. The aim of this cross-sectional study was to assess metabolomic profiling of serum and urine samples obtained from CKD patients. Untargeted metabolomics followed by multivariate and univariate analysis of blood and urine samples from 88 patients with CKD, staged by estimated glomerular filtration rate (eGFR), and 20 healthy control subjects was performed using ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry. Serum levels of Oleoyl glycine, alpha-lipoic acid, Propylthiouracil, and L-cysteine correlated directly with eGFR. Negative correlations were observed between serum 5-Hydroxyindoleacetic acid, Phenylalanine, Pyridoxamine, Cysteinyl glycine, Propenoylcarnitine, Uridine, and All-trans retinoic acid levels and eGFR. In urine samples, the majority of molecules were increased in patients with advanced CKD as compared with early CKD patients and controls. Amino acids, antioxidants, uremic toxins, acylcarnitines, and tryptophane metabolites were found in all CKD stages. Their dual variations in serum and urine may explain their impact on both glomerular and tubular structures, even in the early stages of CKD. Patients with CKD display a specific metabolomic profile. Since this paper represents a pilot study, future research is needed to confirm our findings that metabolites can serve as indicators of early CKD.

Background: Endoscopic retrograde cholangiopancreatography (ERCP) represents a major pivotal point in gastrointestinal endoscopy. Little is known about acute kidney injury (AKI) post-ERCP. This study analyses the incidence, risk factors, and prognosis of post-ERCP AKI. Methods: A total of 396 patients were prospectively studied. AKI was defined by an increase in serum creatinine (SCr) ≥ 0.3 mg/dL or by an increase in SCr ≥ 50% in the first 48 h post-ERCP. Logistic regression analysis was used to identify the predictors of AKI and in-hospital mortality. A two-tailed p value < 0.05 was considered significant. Results: One hundred and three patients (26%) developed post-ERCP AKI. Estimated glomerular filtration rate (adjusted odds ratio (aOR) = 0.95, 95% confidence interval (CI): 0.94−0.96, p < 0.001), nonrenal Charlson Comorbidity Index (Aor = 1.19, 95% CI: 1.05−1.35, p = 0.006), choledocholithiasis (aOR = 4.05, 95% CI: 1.98−8.29, p < 0.001), and bilirubin (aOR = 1.1, 95% CI: 1.05−1.15, p < 0.001) were associated with post-ERCP AKI. Post-ERCP AKI was associated with longer hospital stay (p < 0.001) and with increased in-hospital mortality (7.76% versus 0.36%, p < 0.001). Moderate-to-severe (stage 2 and 3) AKI was independently associated with in-hospital mortality (aOR = 6.43, 95% CI: 1.48−27.88, p < 0.013). Conclusions: Post-ERCP AKI represented an important complication associated with longer hospital stay. Moderate-to-severe post-ERCP AKI was an independent risk factor for in-hospital mortality.