Search

Background/Aims: The aim of this study is to investigate the utility of clinical [age, gender, mean arterial pressure (MAP)] and laboratory parameters [eGFR, hemoglobin (Hgb), serum levels of creatinine, uric acid, albumin, proteinuria, hematuria] and also histopathological lesions (Oxford classification parameters, crescents, intensity and pattern of staining for C3, C1Q, IgA, IgG, IgM) as progression markers in patients with IgA Nephropathy (IgAN). Methods: A total of 111 IgAN patients with a follow-up period >1 year or who reached kidney failure [GFR category G5 chronic kidney disease (CKD)] <1 year were investigated. Primary endpoint was the development of kidney failure or eGFR decline ≥50% from the baseline. Kaplan-Meier and Cox proportional hazards analyses were performed. Results: Mean follow-up period was 33±29 months. Thirty-seven (33.3%) patients progressed to kidney failure and 4 (3.6%) patients developed eGFR decline ≥50% from the baseline after a median of 23 and 65 months, respectively. In multivariate Cox regression analysis, baseline levels of Hgb (HR:0.782, 95% CI 0.559-0.973, p=0.037), serum uric acid (HR:1.293, 95% CI 1.023-1.621, p=0.046), eGFR (HR:0.966, 95% CI 0.947-0.984, p=0.004) and intensity of C3 staining (HR:1.550, 95% CI 1.198-1.976, p=0.049) predicted primary endpoint. Serum uric acid level was associated independently with T score (β=0.303, p=0.005) in patients with eGFR>30 ml/min/m2. Conclusions: Hyperuricemia and the deposition of C3 are independent risk factors for IgAN progression. [ABSTRACT FROM AUTHOR]

[Display omitted] • Metabolomics reveals potential diagnostic markers for diabetic nephropathy (DN). • Lipid metabolism in podocytes emerges as pivotal in DN. • Cinaciguat activation of NO/sGC/PKG pathway shows promise in DN. • Tryptophan levels serve as prognostic indicators for DN progression. • Integration of metabolomics enhances understanding and management of DN. Diabetic nephropathy (DN), a severe complication of diabetes, involves a range of renal abnormalities driven by metabolic derangements. Metabolomics, revealing dynamic metabolic shifts in diseases like DN and offering insights into personalized treatment strategies, emerges as a promising tool for improved diagnostics and therapies. We conducted an extensive literature review to examine how metabolomics contributes to the study of DN and the challenges associated with its implementation in clinical practice. We identified and assessed relevant studies that utilized metabolomics methods, including nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) to assess their efficacy in diagnosing DN. Metabolomics unveils key pathways in DN progression, highlighting glucose metabolism, dyslipidemia, and mitochondrial dysfunction. Biomarkers like glycated albumin and free fatty acids offer insights into DN nuances, guiding potential treatments. Metabolomics detects small-molecule metabolites, revealing disease-specific patterns for personalized care. Metabolomics offers valuable insights into the molecular mechanisms underlying DN progression and holds promise for personalized medicine approaches. Further research in this field is warranted to elucidate additional metabolic pathways and identify novel biomarkers for early detection and targeted therapeutic interventions in DN. [ABSTRACT FROM AUTHOR]