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Role of metabolomic profile as a potential marker to discriminate membranous nephropathy from IgA nephropathy. | LitMetric

AI Article Synopsis

  • - This study investigates membranous nephropathy (MN) and IgA nephropathy (IgAN), two common kidney diseases, by examining metabolic changes in patients compared to healthy controls using untargeted metabolomics.
  • - Researchers analyzed 87 MN patients, 70 IgAN patients, and 30 healthy individuals, leading to the discovery of 155 metabolites altered in MN and 148 in IgAN, with several metabolites showing opposite trends between the two diseases.
  • - The findings highlight significant metabolic disturbances linked to MN and IgAN, suggesting that specific metabolites like L-tryptophan and GABA could serve as potential biomarkers for diagnosing these conditions.

Article Abstract

Background: Membranous 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.

Methods: A 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.

Results: Principal 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.

Conclusions: Substantial 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10808257PMC
http://dx.doi.org/10.1007/s11255-023-03691-1DOI Listing

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