ArticleInternational urology and nephrology2024
Role of metabolomic profile as a potential marker to discriminate membranous nephropathy from IgA nephropathy.
Article in International urology and nephrology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Lactobacillus and Tryptophan Supplementation Improve Renal Function and are Associated with Metabolomic Alterations in a Mouse Model of Chronic Kidney Disease.Probiotics and antimicrobial proteins · 2026Article
- Metabolomic profiling in IgA nephropathy: urinary and salivary biomarker insights.BMC nephrology · 2026Article
- Urinary betaine/creatinine ratio enhances diagnostic accuracy of PLA2R-Ab in idiopathic membranous nephropathy.BMC nephrology · 2025Article
- Integrated Analysis of Proteomics and Metabolomics for Heat Stress in Chinese Holstein Cows.Animals : an open access journal from MDPI · 2025Article
- Discovery of non-invasive biomarkers for accurate detection of membranous nephropathy.Scientific reports · 2025Article
- Impact of immune cell metabolism on membranous nephropathy and prospective therapy.Communications biology · 2025Review
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
backgroundMembranous nephropathy (MN) and IgA nephropathy (IgAN) are the most common primary glomerulopathies worldwide. The systemic metabolic changes in the progression of MN and IgAN are not fully understood.
methodsA total of 87 and 70 patients with MN and IgAN, respectively, and 30 healthy controls were enrolled in this study. Untargeted metabolomics was performed to explore the differential metabolites and metabolic pathways in the early stage of MN and IgAN. To judge the diagnostic ability of biomarkers, receiver operating characteristic curve analysis (ROC) were performed.
resultsPrincipal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) suggested that patients with MN and IgAN showed an obvious separation trend from the healthy controls. In addition, 155 and 148 metabolites were identified to be significantly altered in the MN and IgAN groups, respectively. Of these, 70 metabolites were markedly altered in both disease groups; six metabolites, including L-tryptophan, L-kynurenine, gamma-aminobutyric acid (GABA), indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine, showed the opposite tendency. The most affected metabolic pathways included the amino acid metabolic pathways, citrate cycle, pantothenate and CoA biosynthesis, and hormone signaling pathways.
conclusionsSubstantial metabolic disorders occurred during the progression of MN and IgAN. L-tryptophan, L-kynurenine, GABA, indoleacetaldehyde, 5-hydroxyindoleacetylglycine, and N-alpha-acetyllysine may show potential as biomarkers for the identification of MN and IgAN.
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